{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 2. Research and experiments with data\n", "\n", "> Research is read more than it is written.\n", "\n", "It is a truth fundamental to research that new knowledge is advanced through the acquisition and interpretation of existing knowledge. \n", "\n", "There are numerous estimates of the number of research papers published every year, with one claim of [30,000 journals serving two million articles a year](https://www.universityworldnews.com/post.php?story=20180905095203579#:~:text=No%20one%20knows%20how%20many,million%20articles%20published%20each%20year). [SciHub](https://en.wikipedia.org/wiki/Sci-Hub), an open access research paper repository, lists over 83 million papers. Quacquarelli Symonds, a company specialising in higher education analysis, considered 5,500 research institutes for their 2021 [World University Rankings](https://www.topuniversities.com/university-rankings). Some scientists publish more than 70 papers a year; a frequency of about one every five days.\n", "\n", "Clearly, not all of these can be of equal quality, nor are all likely to stand much scrutiny. The challenge is how to quickly evaluate research claims and assess whether the results can inform your own work. \n", "\n", "How does a scientist read and evaluate research?\n", "\n", "Any scholarly work rests on the quality of the data informing the analysis. The objective of this lesson is to learn how to read and review a research paper, with specific focus on sample randomisation, and assessing a level of confidence using core statistical and logical techniques. \n", "\n", "
\n", "Research question:\n", "Published research may recommend new courses of treatment for disease, or seek to settle contested hypotheses. Specialised subjects require specialised knowledge but the techniques used to conduct any study are common to all branches of research. Using only core statistical techniques, evaluate two papers \\cite{budoff_effect_2020, packer_cardiovascular_2020} and assess whether the claims they make are reasonable in the context of the validity of patient randomisation. Which, if any, would you trust?\n", "
\n", "\n", "The two papers we will refer to are these:\n", "\n", "> _Budoff, Matthew J., Deepak L. Bhatt, April Kinninger, Suvasini Lakshmanan, Joseph B. Muhlestein, Viet T. Le, Heidi T. May, et al. 2020. “Effect of Icosapent Ethyl on Progression of Coronary Atherosclerosis in Patients with Elevated Triglycerides on Statin Therapy: Final Results of the EVAPORATE Trial.” European Heart Journal. [doi:10.1093/eurheartj/ehaa652](https://academic.oup.com/eurheartj/advance-article/doi/10.1093/eurheartj/ehaa652/5898836)._\n", "> \n", "> _Packer Milton, Anker Stefan D., Butler Javed et al., 2020. ``Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure'', New England Journal of Medicine, August 2020. [doi:10.1056/NEJMoa2022190](https://sci-hub.tw/10.1056/NEJMoa2022190)_\n", "\n", "Don't worry if you don't understand them on first read. Our objective is to learn how to evaluate research even when you are not immersed in the topic." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.1 Ethics: privacy, anonymity and permission\n", "\n", "
\n", "Recognise the importance and process for applying concepts of privacy and anonymity.\n", "
\n", "\n", "In late 2017, while on a cruise vacation which stopped at the French Caribbean island of Martinique, a British couple reported a burning rash on their buttocks. The medical team on the ship prescribed antibiotics and an antifungal agent, which did nothing to improve their symptoms. On return to the UK, their conditions had worsened and they went to a hospital in Cambridge for further treatment. There they were diagnosed as suffering from _cutaneous larva migrans_, a condition caused by nematode hookworms of the _Ancylostomatidae_ family.\n", "\n", "Their condition had worsened by then, and the hookworms had spread to their lungs, causing a persistent cough, shortness of breath and pain. They were prescribed _ivermectin_, and - since the diagnosis was relatively unusual - their doctors asked if they could write up the case as a study for the _British Medical Journal_. Approval was granted, and the paper appeared as _Cutaneous larva migrans with pulmonary involvement_ \\cite{maslin_cutaneous_2018}. The paper included a number of photographs of the couple's buttocks to facilitate diagnosis.\n", "\n", "Almost immediately, the study was picked up and presented by British tabloid newspapers, including the [Daily Mail](https://www.dailymail.co.uk/health/article-5278581/Couples-burning-red-rash-bottoms-worms.html#ixzz58NPOjYbK) (warning: graphic content). This, obviously, horrified the couple and they contacted the BMJ to ask that the paper be retracted.\n", "\n", "The BMJ considered the request, and [retracted the paper](https://casereports.bmj.com/content/2018/bcr-2017-223508wit.full):\n", "\n", "> With no admission of liability, BMJ has removed this article voluntarily at the request of the patient concerned.\n", "\n", "Given the legitimate medical interest in well-founded research that supports diagnosis of a risky condition, should a patient have the right to retract permission they have already granted? \n", "\n", "What are the limits and considerations for privacy and anonymity?\n", "\n", "### 2.1.1 The context of _negative_ and _positive_ rights\n", "\n", "Researchers, particularly those working with human subjects, have a duty of care towards their stakeholders that arises from rights they, or their stakeholders, may hold. \n", "\n", "__Negative rights__ are also called _rights of non-interference_; the right to act, think or speak without being interrupted or interfered with. These are rights which oblige others not to do things to the rights-possessor. Privacy, the right to deny others knowledge of certain information, falls within negative rights. \\cite{baggini_ethics_2007}\n", "\n", "Conversely, a __positive right__ imposes a duty upon others, such as protection from harm or - as in a medical environment - a duty of care. These are then _rights of obligation_.\n", "\n", "The intersection of these rights may be codified in research practice, but different countries have different legislative environments.\n", "\n", "As researchers, to who or what do we owe these rights? \n", "\n", "We may differentiate between __moral agents__ and __moral subjects__.\n", "\n", "A moral agent is one who is able to act morally or immorally, who can choose between these paths of action, and who can be judged to have acted well or badly on moral grounds. Computers are not, even if they are programmed to do good or evil things, because they have no control - no agency - over their choices. Similarly, a [2015 US court case](https://arstechnica.com/tech-policy/2015/08/chimps-dont-have-same-legal-rights-as-humans-must-remain-in-research-lab/) in response to whether animals can be subjected to medical experiments, judged that chimpanzees are property with no writ of [_habeas corpus_](https://en.wikipedia.org/wiki/Habeas_corpus_). That does not mean that nothing else has rights, just that they don't have agency.\n", "\n", "A moral subject is something, or someone, for which things can go well or badly, which has welfare interests, and whose interests a moral agent has a responsibility to consider.\n", "\n", "Is a geographical feature a moral subject? To the extent that a mountain, a valley, or a gorge has no point of view, no. However, that does not mean that destruction of such an object won't impact other moral agents or moral subjects.\n", "\n", "In most cases, moral agents and subjects are interchangeable. A moral agent is always also a moral subject, but not all moral subjects are moral agents. If a baby were to topple a vase which fell on a person's head and killed them, one wouldn't declare that the baby had made a conscious decision to do so. A baby has no conscious understanding of right or wrong so is not capable of moral agency, yet it is a moral subject. \n", "\n", "This consideration may be governed by statute with legal consequences for ignoring them, but ethics must go further than codified law - especially when researchers work at the outer boundary of knowledge and codified practice - and consider both the ethical and moral case for an action. \n", "\n", "> What is _legal may not be moral_ and _what is moral may not be legal_.\n", "\n", "In May 2020, Rio Tinto, a mining company, destroyed the Juukan Gorge, a 46,000-year-old Aboriginal heritage site, [to clear way for a mine](https://www.theguardian.com/australia-news/2020/may/26/rio-tinto-blasts-46000-year-old-aboriginal-site-to-expand-iron-ore-mine). \n", "\n", "They had full legal permission to do so. However, they [ignored the pleas of the traditional owners of gorge, the Puutu Kunti Kurrama and Pinikura people](https://www.theguardian.com/australia-news/2020/may/26/rio-tinto-blasts-46000-year-old-aboriginal-site-to-expand-iron-ore-mine), causing them quantifiable harm. Rio Tinto themselves conducted a [research survey in 2014 at the Juukan Gorge](https://www.theguardian.com/business/2020/jun/05/rio-tinto-blames-misunderstanding-for-destruction-of-46000-year-old-aboriginal-site) _\"that gathered more than 7,000 artefacts, including a plaited belt made from human hair that DNA testing revealed belonged to the direct ancestors of PKKP alive today, and tools and grinding stones which showed those tools had been in use far earlier than archeologists previously believed.\"_\n", "\n", "Rio Tinto had a legal right to destroy the heritage site, but did they have a moral one? And even if they had sympathy with the plea, they may believe that the value of the ore they extract from the site justifies its destruction.\n", "\n", "These are __means/ends trade-offs__ and it is essential that they be evaluated _together_ so as to arrive at a valid conclusion as to a course of action.\n", "\n", "
\n", "Research is performed by moral agents undertaking activities which may effect moral subjects such that their rights - both positive and negative - must be considered within the context of legal and moral means and ends.\n", "
\n", "\n", "### 2.1.2 Moral subjects and ethical review\n", "\n", "In 2012, Facebook conducted a week-long experiment on 689,000 of its users \\cite{kramer_experimental_2014}. People were randomly assigned to one of two groups which either received more positive stories or more negative stories in their news feed than they would regularly receive. People who received more positive stories tended to behave more positively, themselves posting more positively, while the converse occured for those exposed to more negative stories. The research suggests that social media creates a _social contagion_ acting to transfer emotions to others and reinforce those emotions.\n", "\n", "None of the participants in the study were aware of their involvement, and none had even been approached to request formal consent.\n", "\n", "Writing in [When and Why Is Research without Consent Permissible?](https://onlinelibrary.wiley.com/doi/abs/10.1002/hast.548), Gelinas et al declare two reasons when consent can be ignored:\n", "\n", "- if it stands to infringe no right of the participants and obtaining consent is impracticable, \n", "- or if the gravity of the rights infringement is minor and outweighed by the expected social value of the research and obtaining consent is impracticable.\n", "\n", "This is an express claim that the ends, the research outcomes, outweigh the means, the consent required of the participants. Clearly, though, you'd want to be extremely clear that whoever is considering the means/ends be completely impartial, or that each party has some representation.\n", "\n", "Follow-up questions are: who decides if no rights are harmed, or if the infringement is minor? What constitutes a minor harm, and who decides - and on what grounds - that the social value is greater than any harm caused?\n", "\n", "Any review would need to be conducted by impartial agents and consider all of the actions and potential consequences.\n", " \n", "The authors declared that Facebook's existing user terms gave this consent, and that the non-Facebook employees leading the study didn't have access to individual user information anyway.\n", "\n", "The researchers claimed what they did was ethical because data was anonymous. They addressed negative rights - that moral subjects have a right to privacy - but not positive rights - that moral subjects have a right not to be harmed. They ignored whether it was ethical to deliberately manipulate the emotional state of users without their consent \\cite{shaw_facebooks_2015}. \"The main result is that exposure to negative posts made people feel worse; if valid, this means that hundreds of thousands of people were made less happy by the study.\"\n", "\n", "Unnecessary involvement in a study can cause harm to healthy and unhealthy people. The least one would hope from any research is that participants - subjects - are informed and consent to their participation, and that they are not harmed as a result of their consent.\n", "\n", "Shaw's review highlights that the extreme number of participants in the Facebook study was far in excess of that required to produce a statistically meaningful result and implies that far more people, of unpredictable backgrounds, were effected than should have been. This sample would also include children under the age of 13 and people particularly susceptable to anxiety. Shaw describes that the research itself may be invalid since its design and methods resulted in a tiny effect size, meaning there's little statistical meaning from the results; a claim of a large risk of harm relative to a low return for social value.\n", "\n", "Perhaps this research really is of such pressing importance that harm to participants could be ignored, although this isn't supported by the quality of the results, but this was not considered during ethical review or by the researchers themselves.\n", "\n", "Which leads to the review of the BMJ decision. Clearly, the authors had received consent from their patients. However, the patients themselves expressed fear of harm after publication. It is easy to see how this fear could be realised. We know the date (late 2017), the location of the cruise ship (Martinique), the approximate age and ethnicity of the patients (from the photographs, even of their posteriors), the hospital where they were attended (Cambridge), and the names of the physicians who attended them. It wouldn't be particularly difficult for their friends and colleagues to figure out it was them, and at that point they are no longer anonymous.\n", "\n", "The potential for harm to their privacy and to their dignity is obvious. It could be argued that retracting the paper after international news coverage is a bit late, but the principle is important too.\n", "\n", "### 2.1.3 Bias, spurious correlations and non-representative sampling\n", "\n", "> _Protocols of randomized trials specify __inclusion and exclusion criteria__ to determine the population under study. Exclusion criteria typically focus on identifying subjects who might be harmed by the study intervention, those for whom benefit is doubtful and those who are unlikely to provide useful data. Inclusion criteria tend to focus on risk: all trials identify the population at risk for the study event, some trials additionally specify criteria to define a study population at high-risk._ \\cite{vickers_selecting_2006}\n", "\n", "People may give their permission to participate in a research study, but it isn't indefinite or all-encompasing. They may expect discomfort, but not active harm. A person's rights as a moral subject - both positive and negative - are critical to ensuring valid and repeatable research, but also as a marker to the overall approach of the researchers themselves.\n", "\n", "Researchers who ensure their subjects' rights are considered throughout the research process are also ensuring the validity of their study. Randomisation - of which more in _[2.2 Curation](#2.2-Curation:-data-acquisition-and-management)_ - relies on anonymity. If agents of the research process have any bias - any expectations of behaviour or effect from certain categories of patients - they may, consciously or not, steer their measurements towards an expected result.\n", "\n", "These biases can be measured in the results and may render research conclusions unverifiable and invalid. The risks of considering your sample population in isolation from other factors extant to your study may compromise your research. For example, an inclusion study of only smokers at high risk for developing lung cancer may – in a group of 100 – have a disproportionately high (or low) number of people who are simultaneously obese. If adverse events are concentrated in the obese study participants then your results may be biased upward or downward, depending on the sample bias.\n", "\n", "The tension between the difficulty of recruiting, and maintaining, study participants, and the need to ensure a representative sample often confounds results.\n", "\n", "### 2.1.4 Ensuring subject safety and confidentiality during recruitment and participation\n", "\n", "These seven criteria require consideration to ensure that patients’ interests are accounted for during recruitment into a study, and during and after their participation (\\cite{emanuel_what_2000} with text in this section via [the NIH](https://www.cc.nih.gov/recruit/ethics.html)). While this is focused on health research, the reality is that these concerns are true for any study involving moral subjects.\n", "\n", "#### Social and clinical value\n", "\n", "Answers to the research question should contribute to scientific understanding of health or improve our ways of preventing, treating, or caring for those with a given disease. Only if society will gain useful knowledge — which requires sharing results, negative, positive and neutral — can exposing moral subjects to the risk and burden of research be justified.\n", "\n", "#### Scientific validity\n", "\n", "A study should be designed in a way that will get an understandable answer to a valuable research question. This includes considering whether the question researchers are asking is answerable, whether the research methods are valid and feasible, and whether the study is designed with a clear scientific objective and using accepted principles, methods, and reliable practices. It is also important that statistical plans be of sufficient power to definitively test the objective and for data analysis. Invalid research is unethical because it is a waste of resources and exposes subjects to risk for no purpose\n", "\n", "#### Fair subject selection\n", "\n", "The primary basis for recruiting and enrolling groups and individuals should be the scientific goals of the study — not vulnerability, privilege, or other factors unrelated to the purposes of the study. Consistent with the scientific purpose, people should be chosen in a way that minimizes risks and enhances benefits to individuals and society. Groups and individuals who accept the risks and burdens of research should be in a position to enjoy its benefits, and those who may benefit should share some of the risks and burdens. Specific groups or individuals (for example, women or children) should not be excluded from the opportunity to participate in research without a good scientific reason or a particular susceptibility to risk.\n", "\n", "#### Favourable risk-benefit ratio\n", "\n", "Uncertainty about the degree of risks and benefits associated with a drug, device, or procedure being tested is inherent in clinical research — otherwise there would be little point to doing the research. And by definition, there is more uncertainty about risks and benefits in early-phase research than in later research. Depending on the particulars of a study, research risks might be trivial or serious, might cause transient discomfort or long-term changes. Risks can be physical (death, disability, infection), psychological (depression, anxiety), economic (job loss), or social (for example, discrimination or stigma from participating in a certain trial). Has everything been done to minimize the risks and inconvenience to research subjects, to maximize the potential benefits, and to determine that the potential benefits to individuals and society are proportionate to, or outweigh, the risks? Research volunteers often receive some health services and benefits in the course of participating, yet the purpose of clinical research is not to provide health services.\n", "\n", "These benefits may often risk compromising informed consent in populations at risk to poor healthcare provision since their incentive to participate may be to secure healthcare, rather than to support the study.\n", "\n", "#### Independent review\n", "\n", "To minimize potential conflicts of interest and make sure a study is ethically acceptable before it even starts, an independent review panel with no vested interest in the particular study should review the proposal and ask important questions, including: Are those conducting the trial sufficiently free of bias? Is the study doing all it can to protect research volunteers? Has the trial been ethically designed and is the risk–benefit ratio favourable?\n", "\n", "#### Informed consent\n", "\n", "For research to be ethical, most agree that individuals should make their own decision about whether they want to participate or continue participating in research. This is done through a process of informed consent in which individuals:\n", "\n", "-\tare accurately informed of the purpose, methods, risks, benefits, and alternatives to the research, \n", "-\tunderstand this information and how it relates to their own clinical situation or interests, and \n", "-\tmake a voluntary decision about whether to participate.\n", "\n", "There are exceptions to the need for informed consent from the individual — for example, in the case of a child, of an adult with severe Alzheimer's, of an adult unconscious by head trauma, or of someone with limited mental capacity. Ensuring that the individual's research participation is consistent with his or her values and interests usually entails empowering a proxy decision maker to decide about participation, usually based on what research decision the subject would have made, if doing so were possible.\n", "\n", "#### Respect for potential and enrolled subjects\n", "\n", "Individuals should be treated with respect from the time they are approached for possible participation — even if they refuse enrollment in a study — throughout their participation and after their participation ends. This includes:\n", "\n", "1.\tRespecting their privacy and keeping their private information confidential.\n", "2.\tRespecting their right to change their mind, to decide that the research does not match their interests, and to withdraw without penalty.\n", "3.\tInforming them of new information that might emerge in the course of research, which might change their assessment of the risks and benefits of participating.\n", "4.\tMonitoring their welfare and, if they experience adverse reactions, untoward events, or changes in clinical status, ensuring appropriate treatment and, when necessary, removal from the study.\n", "5.\tInforming them about what was learned from the research. Most researchers do a good job of monitoring the volunteers’ welfare and making sure they are okay. They are not always so good about distributing the study results.\n", "\n", "Individuals participating in a study are often at their most vulnerable and exposing information about themselves they may find difficult to share even with those closest to them. A researcher who neglects to remember that moral subjects require ethical consideration is likely to neglect other critical aspects of their research.\n", "\n", "In lesson 1, we considered whether the research question itself could be considered ethical. To this we add a second:\n", "\n", "> When assessing whether research is valid, if a researcher ignores the rights of their study subjects, what other ethical considerations have they ignored?\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.2 Curation: data acquisition and management\n", "\n", "
\n", "Integrate methods for metadata and archival into data management.\n", "
\n", "\n", "The role of a data scientist is to support in producing _an_ answer to a research question that is robust, stands up to scrutiny, and is supported by ethical measurement data acquired during the study process.\n", "\n", "A published paper is a subset of the information curated and methods employed from a process. Any review - if it is thorough - will raise queries that may not have ready answers. Researchers may need to follow up on mundane requests for more details about assumptions in definitions or methods, or a regulatory audit triggered as a result of a notifiable event if a participant experiences harm. You may even be asked for individual consents from study participants.\n", "\n", "The strength and organisation of those answers will rely entirely on how data was acquired and curated throughout the project. Questions that are not asked at the outset of a study are very difficult to answer after the study has been completed and published. Memories fade, equipment degrades, callibration shifts, circumstances change.\n", "\n", "### 2.2.1 The data management lifecycle\n", "\n", "The data management lifecycle seeks not only to document what happened, but why and how decisions were made about what to capture.\n", "\n", "While the process for creating, maintaining and archiving new data are often presented as a cycle, it is more like a spiral. Each cycle spiralling upwards, and resulting in more information. However, the effectiveness of each step is defined by the needs of its users, and its relevance in terms of the process or events it reflects.\n", "\n", "![Data lifecycle](images/data-lifecycle-en.jpg)\n", "\n", "#### Collection and creation\n", "\n", "Before data can be collected, there are a range of things which must be known:\n", "\n", "- why are we collecting the data?\n", "- what purpose does it serve?\n", "- do we have consent and / or the legal authority to collect that data?\n", "- is there an existing data series which this data extends or compliments?\n", "- how will the data be collected?\n", "- who will be responsible for data quality, and how will quality be measured?\n", "- who will have access to the data, and how sensitive is this data (e.g. personally-identifying)?\n", "- are we using a standardised and agreed-upon classification or metadata format?\n", "\n", "#### Classification and processing\n", "\n", "The creator of the data would best know what the data are about and should assign keywords as descriptors. These data about data are called metadata. The term is ambiguous, as it is used for two fundamentally different concepts:\n", " \n", "- __Structural metadata__ correspond to internal metadata (i.e. metadata about the structure, or fields, of database objects such as tables, columns, keys and indexes);\n", "- __Descriptive metadata__ correspond to external metadata. (i.e. metadata typically used for discovery and identification, as information used to search and locate an object such as title, author, subjects, keywords, publisher);\n", " \n", "Descriptive metadata permits discovery of the object. Structural metadata permits the data to be applied, interpreted, analysed, restructured, and linked to other, similar, datasets. Metadata can permit interoperability between different systems. An agreed-upon structure for querying the _aboutness_ of a data series can permit unrelated software systems to find and use remote data.\n", " \n", "Beyond metadata, there are also mechanisms for the structuring of relationships between hierarchies of keywords. These are known as ontologies and, along with metadata, can be used to accurately define and permit discovery of data.\n", " \n", "Adding metadata to existing data resources can be a labour-intensive and expensive process. This may become a barrier to implementing a comprehensive knowledge management system.\n", "\n", "Generic and commonly-used metadata schemas include [Dublin Core](https://www.dublincore.org/specifications/dublin-core/dces/) and [DataScite](https://schema.datacite.org/). These generic types of descriptive metadata include:\n", "\n", "| REQUIRED | RECOMMENDED | OPTIONAL |\n", "|:----------------|:--------------|:----------------------|\n", "| Title | Tag(s) | Last update |\n", "| Description | Terms of use | Update frequency |\n", "| Theme(s) | Contact email | Geographical coverage |\n", "| Publishing body | | Temporal coverage |\n", "| | | Validity |\n", "| | | Related resources |\n", "| | | Regulations |\n", "\n", "Metadata standards differ from authority to authority (and from institution to institution) and need to be agreed as part of your protocol development. Some of the questions you will need to answer during protocol development include:\n", "\n", "- Which regulatory authorities will you need to account to? \n", "- What are their requirements and standards?\n", "- What software system will you use to capture and manage the data?\n", "\n", "The answers to these questions will define the data management mechanism, as well as requirements for collecting and collating data during the study.\n", "\n", "#### Manipulation, conversion or alteration\n", "\n", "This part of the process is where the data are transcribed, translated, checked, validated, cleaned and managed.\n", "\n", "This presents the greatest risk for data consistency. Any format change or manipulation, or even copying a file from one system to another, introduces the potential for data corruption. Similarly, it also increases the potential for data - whether erroneous or not - to be accidentally released to users or the public before it is ready.\n", "\n", "This is also known as __data wrangling__ or __Extract-Transform-Load (ETL)__.\n", "\n", "
\n", " Self-study: Complete the companion self-study course on Data Wrangling and Validation for Open Data to ensure you have the technical skills to work with the \"wild\" data we'll be using during this training series.\n", "
\n", "\n", "#### Analysis and presentation\n", "\n", "Analysis is the reason that data are collected and where data are interpreted, combined with other datasets to produce meta-analysis, and where analysis becomes the story you wish to tell derived from the data. Since the purpose of analysis is to inform collective or individual behaviour, influence policy, or support economic activity, amongst many others, it is essential for publication to include release of the evidence which informs.\n", "\n", "#### Preserving and storing\n", "\n", "Data needs to be preserved from corruption, as well as being available for later use once the initial analysis is complete. Long-term storage requires that the metadata be well-defined and exceptionally useful to ensure that understanding what the data describe is still possible long after its initial collection.\n", "\n", "Data may end up being stored in multiple formats or across multiple systems. \n", "\n", "It is essential that primacy is established (i.e. which dataset has priority over the others) and that the various formats are kept in alignment. It is critical that your software system maintain an audit trail. This will support and facilitate data quality management, any post-study surveillance requirements, as well as your regulatory application process.\n", "\n", "It is beyond the terms of any course to recommend a specific software suite to manage your data requirements, but there are a host of [software systems](https://www.bu.edu/data/share/selecting-a-data-repository/) and services which can support the archival process. \\cite{chait_technical_2014}. \n", "\n", "The class of software used in clinical research are known as Clinical Data Management Systems (CDMS). Most CDMS are commercial and proprietary, but a number are open source. If your institution already has such a system, your path is clear, learn it and use it. If you are in the position where you will need to secure and implement your own, then a combination of budget and technical requirements will need to be considered. Any of the main systems will support your needs, but you will be responsible for ensuring that it supports compliance with the protocols you have agreed.\n", "\n", "#### Release and access\n", "\n", "Even where data are only released within an institution - and not for the public - there will always be others who will want to use your data, or would benefit from it if they know it exists. The greatest inefficiency in data management arises when research is repeated because a different department needs the same data but did not know it already existed.\n", "\n", "Release is not simply about making data available to others, it is also about creating a predictable process for that release. Regularly collected data (such as inflation rates) need a predictable release cycle since many companies base their investment decisions on the availability of such information. Publishing a release calendar for your stakeholders (and sticking to it) permits them to plan their own analysis, or response to your analysis.\n", "\n", "Access implies that you need a centralised database which is accessible to your stakeholders. In the case of open data, how will data be moved from internal servers to a public repository?\n", "\n", "Responsibility for this process needs to be assigned and measured.\n", "\n", "#### Retention and reuse\n", "\n", "Once data are released, the question arises as to how long it will be available? Research data should, ordinarily, be available in perpetuity. Time-series data become more useful the longer it has been collected. Suddenly removing data can cause tremendous disruption. If appropriate systems and support have not been put in place then retention can become a very expensive problem.\n", "\n", "Importantly, in order to support reuse, clear copyright and licensing which permit data to be freely reused for any purpose is essential.\n", "\n", "#### Archival\n", "\n", "Datasets can become very large and may only be accessed infrequently. This can become problematic for long-term storage. A process of archival - where data can be stored more cheaply but still be accessible - may need to be considered.\n", "\n", "
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\n", " Actions:\n", "
\n", " \n", "
\n", "\n", "### 2.2.2 Data measurement and collection\n", "\n", "If a person told you that their mobile phone can handle 2.5 megawatts of power, or that a critical temperature sensor on a large industrial smelter reported an 80°C drop in a second, or that a patient had just lost 6 litres of blood and was in need of urgent care ... you should be skeptical.\n", "\n", "Small electronic circuits, like mobile phones, only handle a few watts, not megawatts. [Conservation of energy](https://en.wikipedia.org/wiki/Conservation_of_energy) means large blocks of metal, like a smelter, can't lose so much energy in seconds. The sensor is more likely to be faulty. And a human body only contains about 5 litres of blood, so anyone who loses 6 litres and is still alive is a miracle.\n", "\n", "The data management process is there to support data collection, but it is the responsibility of the data scientist to sanity check data going in. There are physical and technical limits to measurements and you need to have a comprehensive understanding of your research domain to ensure that measurements reflect reality.\n", "\n", "Sensors can need calibration. Software can contain \"fat finger\" errors, where significant digits are accidentally added to scaling factors or constants. Data can be recorded incorrectly at the point of collection.\n", "\n", "The least one expects from data management systems and analytical scripts is that they do not contribute to the likely sources of error. The best way to get a handle on what can go wrong in your software systems, and how best to catch these issues, is to test it with __synthetic data__. These are data which are similar to that which you will use in your study but which are produced deterministically by an algorithm.\n", "\n", "Our synthetic data could simply be a list of random numbers, but it is better to generate a simulacrum of the data we expect to collect. Natural data can naturally have weird outliers, but your controlled data - unless you deliberately introduce it - should not. This permits you to test your systems and see that they don't introduce anything unexpected.\n", "\n", "#### Populations and data collection \n", "\n", "The case study presented in the BMJ would not be considered a high-powered study since it relates the experiences of two people who are also married to each other. This is a single data point and considered anecdotal. The plural of _anecdote_ is not _evidence_ so, while such a single-point case study can strongly suggest a direction for future research, it doesn't of itself constitute evidence. This is another indication of why the BMJ were comfortable retracting it.\n", "\n", "Any studies based on a limited number of data points can suffer from any or all of the following \\cite{downey_think_2014}:\n", "\n", "- __Small numbers of observations__ can be distorted or dominated by outliers, giving emphasis to something that may be extremely rare;\n", "- __Selection bias__ occurs when observations or study participants are selected simply because they're convenient or present in an interesting way, but they may not be representative of a broader population;\n", "- __Confirmation bias__ occurs when researchers consciously or unconsciously select observations or participants that confirm their existing opinions;\n", "- __Innaccuracy__ is also a problem given that anecdotes are based on personal recollection rather than impartial measurement;\n", "\n", "For research conclusions to be meaningful, the study process must be repeatable by anyone who follows the same methodology. We need a formal and defined method for collecting data \\cite{vu_introductory_2020}.\n", "\n", "A __population__ is the entirety of a set of subjects which could be included in an area of study. For example, all people susceptible to diabetes, all buffalo on a migration route, or all plants pollinated by a single species of bees in a meadow. There may be practical or ethical reasons not to acquire information from each member of that population, and so we select a subset - a __sample__ - of that population.\n", "\n", "To be statistically meaningful, that subset needs to be __representative__ of the characteristics of the total population. There are an enormous number of ways that sampling can go wrong, and many assumptions that go into specifying the necessary sample size required to produce a representative result.\n", "\n", "__Randomisation__ of the sample selection process is critical to ensure representation and avoid accidentally introducing __bias__. Even with randomisation, it's easy to inadvertantly bias a sample:\n", "\n", "- __Convenience__ sampling for those members of the population which happen to be the easiest to collect rather than drawn from the entire population;\n", "- __Non-responsive__ members of a sample - where subjects are selected but then vanish for whatever reason from the study - can't simply be replaced without causing the original sample to become non-representative;\n", "- __Asymmetrical__ populations may also be difficult to sample. If individual members of the population are rare but not outliers and you wish to include them, a random sample may still leave them out.\n", "\n", "Similarly, through the research part of a study, it is critical to maintain a lack of bias. An expectation of particular results - confirmation bias - can lead to distortion of measurements.\n", "\n", "#### Observational and experimental studies\n", "\n", "Research begins with a __hypothesis__: a proposed explanation, on the basis of limited evidence, as to how something may occur. The limited evidence are grounds to define __explanatory__ and __response__ variables.\n", "\n", "Until the completion of the study, we have no idea if the explanatory variables have any connection with the response variables. For example, does a terrorist attack in a city centre cause businesses in other cities to move to the suburbs? Our explanatory variables will be a terrorist attack and our response variables will be commercial vacancy, but we have no idea if they're connected.\n", "\n", "__Observational studies__ are performed in a way that does not interfere with the behaviour of study subjects, permitting associations to naturally arise over time. These associations may strongly correlate with our explanatory and response variables, but they aren't necessarily causative.\n", "\n", "There are two types of observational studies:\n", "\n", "- __Prospective__ are those which identify a group and follow their behaviour over time without any specific endpoint or hypothesis in mind. Such studies can also be termed __cohort studies__ since the group may share a defining and common characteristic. Since cohort studies span a significant duration, they are a type of __longitudinal study__. The longest study is the [_MRC National Survey of Health and Development_](https://www.nshd.mrc.ac.uk/) which has been running continuously since 1946 with an initial cohort of 5,362 individuals.\n", "- __Retrospective__ studies are those conducted on existing research after the data has been collected. These can be anything from novel research, to meta-analysis of multiple existing studies.\n", "\n", "__Experimental studies__ are performed to find out if a variable causes a response, that is, whether it is __causative__. We divide our population sample into __experimental__ groups and __control__ groups. The control is treated almost as an observational study, while the experiment experiences an intervention in the explanatory variable.\n", "\n", "Our hypothesis becomes a set of tests:\n", "\n", "- If, at the end of the study, the experimental group matches our hypothetical response then our hypothesis is confirmed;\n", "- If, however, the experimental group is no different from the control, or contrary to our hypothesis, then our hypothesis has failed.\n", "\n", "Here it is critical that our experimental and control groups are randomly assigned and representative. Usually, we also want to ensure that none of the groups, those studying the groups, or applying interventions are aware of who is in which group. That all agents and subjects are __blinded__ so as to avoid any bias in measurement, experiment, or intervention.\n", "\n", "The conclusion of our study also requires that we have defined __endpoints__; that we have stated up-front what conditions must be met to conclude our measurements. If we change them during the study, we're changing the experiment in a non-deterministic way. We could decide arbitrarily and so bias our results.\n", "\n", "When we intervene in this way it should be clear that the potential for unethical or immoral actions are great. If we want to know whether terrorism causes office vacancy, there is no ethical way to intervene. You can't blow up a building just to see if people in a different city decide to move to a less congested location. If we want to test a new heart drug and state that the drug \"fails\" if the average treatment time exceeds 20 days, then change that to 40 days mid-way through the study, we can be accused of favouring our experimental hypothesis.\n", "\n", "The nature of an experiment will impose its own ethical requirements and necessity for impartial review. Documenting our plan, our methodology, and our results are critical to avoiding bias and producing a valid, repeatable result.\n", "\n", "### 2.2.3 Randomisation with synthetic data\n", "\n", "Any experimental research on a sampled population featuring different study groups, each experiencing different experimental effects, can be summarised like this:\n", "\n", "$$ \\text{About the same } \\to \\text{Different} $$\n", "\n", "- At the start of a study our various study groups - control, experimental - should be reasonably equivalent;\n", "- At the end of the study, these groups could be different, and we hope to have captured the causation of these differences.\n", "\n", "Randomisation of assignment to the groups ensures that statistical methods, including estimates and errors associated with those estimates, are reliable.\n", "\n", "Our research depends on our ability to identify appropriate randomisation techniques to sample from study populations.\n", "\n", "We can demonstrate this by generating a predictable set of data to work with.\n", "\n", "Synthetic data can be as simple as a list of random numbers produced according to some distribution pattern, or as complex as a procedurally-generated simulation using machine learning techniques \\cite{dahmen_synsys_2019}. As this course progresses, we will learn ever-more complex methods of producing synthetic data. For now, we will generate a profile for a patient at a hospital.\n", "\n", "Our research question for this lesson asks us to consider patients receiving care for long-term coronary-related diseases. These are a subset of all patients and we can define __inclusion__ and __exclusion__ criteria for acceptance of patients in our study sample.\n", "\n", "Defining our fields and metadata:\n", "\n", "- _age_: study participants must be normally distributed around 55 years old;\n", "- _weight_: participants are expected to be overweight, and normally distributed around a set weight, 85 kgs for women, and 100 kgs for men;\n", "- _gender_: participants should be normally distributed as male or female;\n", "- _smokes_: we need to know whether they smoke;\n", "- _family history_: we need to know whether there is a family history (i.e. a potential genetic predisposition) for the illness;\n", "- _disease_: we need to know whether they have already been diagnosed.\n", "- _color_: we assign the institution where participants are being treated a specified colour;\n", "\n", "Finally, we can include participants if they have at least one of the criteria (weight >10% of set weight, smokes, family history, disease) but exclude them if they have none or all. The exclusion of those with all the criteria may seem odd, but we also don't want patients who may die during the study purely as a consequence of being particularly frail. In a small sample size, such deaths may be __confounding variables__ in that they bias the result towards a particular hypothesis. We want to know if our intervention has an effect, and this effect must stand out clearly. Patients who are too ill may also be too ill for us to measure.\n", "\n", "We will use `numpy`, `matplotlib` and `pandas` during this lesson. If you haven't already, ensure they are installed (review Lesson 1 if you need) and let's begin to code." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Import the libraries we're going to use. If any of these are not installed, you can run\n", "# `pip install` to import them into your development environment\n", "from matplotlib import pyplot as plt\n", "%matplotlib inline\n", "\n", "import pandas as pd\n", "import numpy as np\n", "import random, uuid" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Before we get too much further, let's define what is meant by a __normal distribution__. This is a type of continuous probability distribution for a real-valued random variable. \n", "\n", "Consider, for example, a set of heights. We talk about someone being of \"average\" height and, while there are particularly short or tall people, most people are likely to be somewhere near the average height. That distribution is _normal_. If a group were particularly short or tall, it may be statistically interesting and tell you about that population.\n", "\n", "We can create and visualise a synthetic normal distribution using `numpy` [normal](https://numpy.org/doc/stable/reference/random/generated/numpy.random.normal.html):" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([2.000e+00, 1.000e+00, 1.000e+01, 2.100e+01, 5.400e+01, 1.440e+02,\n", " 2.400e+02, 4.130e+02, 6.710e+02, 8.760e+02, 1.185e+03, 1.328e+03,\n", " 1.378e+03, 1.159e+03, 8.920e+02, 6.920e+02, 4.630e+02, 2.450e+02,\n", " 1.220e+02, 5.400e+01, 3.400e+01, 1.400e+01, 2.000e+00]),\n", " array([148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160,\n", " 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171]),\n", " )" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Generate random normal distribution for an average height of 160 cm\n", "# https://numpy.org/doc/stable/reference/random/generated/numpy.random.normal.html\n", "heights = np.random.normal(loc=160, scale=3, size=10000).astype(int)\n", "# Plot\n", "axis = np.arange(start=min(heights), stop = max(heights) + 1)\n", "plt.hist(heights, bins = axis)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The chart is a __histogram__ and displays data density. The x-axis consists of bins for a height-range. We created that with the `axis` variable which produced a set of buckets (150 to 151, 151 to 152, etc). Where a value falls on the boundary of a bin (e.g. 151) it will be assigned to the lower bin. The y-axis is a count of the number of points falling within that bin range.\n", "\n", "A symmetrical distribution like this is _normal_, but they can also be _skewed_ in various ways that we will get to later.\n", "\n", "We're going to create a normally-distributed patient population. Age isn't usually normally distributed (in Western Europe it tends towards a greater number of older people, and in emerging market countries tends to be younger), but a hospital population does tend to be a subset of older people." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# Define a function to generate a random patient population\n", "# This returns a list of dictionaries, where each dictionary \n", "# is a set of fields defining a patient.\n", "\n", "def create_patient_population(**kwargs):\n", " \"\"\"\n", " Return a population for a group of patients defined by having:\n", " \n", " id: a unique anonymous string\n", " age: normal distribution\n", " gender: boolean\n", " weight: normal distribution, varies for male or female\n", " smokes: boolean\n", " family_history: boolean, has family history\n", " disease: boolean, has the disease\n", " color: group membership indicator\n", " included: meets inclusion criteria\n", " coordinates: random coordinates for plotting on a scatter plot, not meaningful\n", " \n", " Args:\n", " total: int, default 10000\n", " male_weight: int, default 100\n", " fmale_weight: int, default 85\n", " groups: int, default 4\n", " \n", " Returns:\n", " list of dicts\n", " \"\"\"\n", " patient_total = kwargs.get(\"total\", 10000)\n", " male_loc_weight = kwargs.get(\"male_weight\", 100)\n", " female_loc_weight = kwargs.get(\"fmale_weight\", 85)\n", " colour_list = [F\"C{n}\" for n in range(kwargs.get(\"groups\", 4))]\n", " # generate the colour coordinates to plot on a grid\n", " cc = int(len(colour_list)/2)\n", " # if the count is uneven\n", " if len(colour_list)%2: cc = int((len(colour_list)-1)/2)\n", " cc_coords = [i+1 for i in range(cc)]*2\n", " # And add in the extra group\n", " if len(colour_list)%2: cc_coords.append(cc+1)\n", " cc_coords.sort()\n", " colour_coordinates = {\n", " F\"C{n}\": ((20*c, 20) if n%2 else (20*c, 40)) for n, c in enumerate(cc_coords)\n", " }\n", " distance = 20\n", " # Create the patient population\n", " random_age = np.random.normal(loc=55, scale=3, size=patient_total).astype(int)\n", " patient_population = []\n", " for age in random_age:\n", " # Create patient fields\n", " gender = random.choice([\"Male\", \"Female\"])\n", " loc_weight = female_loc_weight\n", " if gender == \"Male\": loc_weight = male_loc_weight\n", " weight = int(np.random.normal(loc=loc_weight, scale=3))\n", " smokes = random.choice([True, False])\n", " family_history = random.choice([True, False])\n", " disease = random.choice([True, False])\n", " color = random.choice(colour_list)\n", " # Inclusion criteria\n", " included = any([smokes, family_history, disease, weight >= loc_weight * 1.1])\n", " # Exclusion criteria\n", " if all([smokes, family_history, disease, weight >= loc_weight * 1.1]):\n", " included = False\n", " patient_population.append({\n", " \"id\": str(uuid.uuid4()), # Generate a random unique string as a patient ID\n", " \"age\": age,\n", " \"weight\": weight,\n", " \"gender\": gender,\n", " \"smokes\": smokes,\n", " \"family_history\": family_history,\n", " \"disease\": disease,\n", " \"color\": color,\n", " \"coordinates\": (\n", " np.random.uniform(colour_coordinates[color][0], colour_coordinates[color][0] + distance),\n", " np.random.uniform(colour_coordinates[color][1], colour_coordinates[color][1] + distance)\n", " ),\n", " \"included\": included,\n", " \"selected\": False\n", " })\n", " # Shuffle the ordered list to create a random population\n", " random.shuffle(patient_population)\n", " return patient_population" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 123 ms\n" ] } ], "source": [ "%time patient_population = create_patient_population()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A __scatter plot__ uses Cartesian coordinates, usually for two variables (assumed to be dependent). A third variable can be shown by changing the colour or size of the point data on the chart. It's frequently a useful way to investigate any sort of correlation between the data. Correlation doesn't necessarily mean anything.\n", "\n", "When we created our random patient population, you'll note we created a random set of coordinates for them as well, including a `color` field so that we could draw them." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Draw our included patients as a scatter plot\n", "\n", "def get_coordinates(population_list):\n", " \"\"\"\n", " Restructure a population list into a set of coordinate lists for plotting in numpy.\n", " \n", " Returns:\n", " x, y, c lists of values\n", " \"\"\"\n", " x = [p[\"coordinates\"][0] for p in population_list if p.get(\"included\", True)]\n", " y = [p[\"coordinates\"][1] for p in population_list if p.get(\"included\", True)]\n", " c = [p[\"color\"] for p in population_list if p.get(\"included\", True)]\n", " return x, y, c\n", "\n", "plt.figure(figsize=(6,6))\n", "plt.axis(\"off\")\n", "# Plot them all by first converting the list of dicts to a list of values\n", "x, y, c = get_coordinates(patient_population)\n", "plt.scatter(x, y, s=50, facecolors=\"none\", edgecolors=c, alpha=0.3)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Our population is randomly distributed across the plain. If this were a hall, then we're looking down on people standing around. Each colour represents patients from a different hospital. Hospitals may have similar patients, they may focus on particularly difficult diseases, we don't know.\n", "\n", "We want to select a random - but representative - sample of this population to run our experiment.\n", "\n", "Let's assume we wanted to pick 80 people. There are four ways we could go.\n", "\n", "__Simple random sampling__ where we simply choose people from the whole population irrespective of any group they may belong to." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(6,6))\n", "plt.axis(\"off\")\n", "# Plot them all by first converting the list of dicts to a list of values\n", "x, y, c = get_coordinates(patient_population)\n", "plt.scatter(x, y, s=50, facecolors=\"none\", edgecolors=c, alpha=0.1)\n", "# Get a simple random selection of the total population using random.sample\n", "# https://docs.python.org/3/library/random.html#random.sample\n", "sample_patients = random.sample(patient_population, 80)\n", "x, y, c = get_coordinates(sample_patients)\n", "plt.scatter(x, y, s=50, facecolors=c, edgecolors=c)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Randomisation in this way means we haven't got much control over the distribution between groups. We may want to ensure that we have equal sample sizes in each group.\n", "\n", "__Stratified sampling__ overcomes this concern by randomly sampling from each group. In this case, we decide to have 20 samples from each for a total of 80." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(6,6))\n", "plt.axis(\"off\")\n", "# Plot them all by first converting the list of dicts to a list of values\n", "x, y, c = get_coordinates(patient_population)\n", "plt.scatter(x, y, s=50, facecolors=\"none\", edgecolors=c, alpha=0.1)\n", "# There are four groups, so let's randomly select 20 patients from each\n", "for i in range(4):\n", " sample_patient_group = list(filter(lambda d: d[\"color\"] == F\"C{i}\", patient_population))\n", " sample_patients = random.sample(sample_patient_group, 20)\n", " x, y, c = get_coordinates(sample_patients)\n", " plt.scatter(x, y, s=50, facecolors=c, edgecolors=c)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Hopefully you realise how difficult it is to tell these things by eye, and the density of the point data means that you could easily have points overlapping each other, making visual assessment even more challenging.\n", "\n", "Now, maybe we have problems with some of these hospitals. Maybe they're difficult to get to. Maybe you haven't received approval to work with them. Or maybe you want to go further and create subsets even within these groups. This is where clustering comes in.\n", "\n", "__Cluster sampling__ requires us to split the population into many groups. We then sample a fixed number of clusters and include all patients in each cluster. This could be as simple as all the patients attending a particular clinic during a specific week. __Multistage sampling__ goes further, first splitting into groups, then sampling from each group.\n", "\n", "Let's demonstrate that with multistage sampling from two hospitals." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(6,6))\n", "plt.axis(\"off\")\n", "# Plot them all by first converting the list of dicts to a list of values\n", "x, y, c = get_coordinates(patient_population)\n", "plt.scatter(x, y, s=50, facecolors=\"none\", edgecolors=c, alpha=0.1)\n", "# There are four groups, so let's randomly select 20 patients from each\n", "for i in range(4):\n", " if i in [0,3]:\n", " sample_patient_group = list(filter(lambda d: d[\"color\"] == F\"C{i}\", patient_population))\n", " sample_patients = random.sample(sample_patient_group, 40)\n", " x, y, c = get_coordinates(sample_patients)\n", " plt.scatter(x, y, s=50, facecolors=c, edgecolors=c)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.2.4 Randomisation and experimental design\n", "\n", "Randomised experiments are usually structured around five principles \\cite{dietz_openintro_2015}: \n", "\n", "1. __Controlling__: Any experiment is intended to reveal differences between groups as a result of an intervention. The starting differences between groups, and the behaviour and experiences of participants during the experiment, are controlled as much as possible to remove _confounding_ variables. For example, patients in a study should take their medication in the same way (i.e. not some intravenously and some with a pill, or some with a sip of water and a pill and some with a whole glass of water and a pill).\n", "2. __Randomisation__: We talked about randomising the patients included in the study, but we also randomise to which treatment group a patient is assigned to account for variables which can't be controlled. One hospital may only treat extremely vulnerable patients and it wouldn't help the experiment if all those patients were limited to a single group. The treatment and control arms of an experiment should start with a similar profile.\n", "3. __Replication__: We ensure that any effect measured is meaningful by ensuring a sufficiently large sample size. We need enough subjects in an experiment to validate explanatory variables. Individual patients are also individual replicated experiments. Additionally, entire studies may be replicated by entirely different researchers.\n", "4. __Blocking__: If researchers suspect that variables other than that being treated influence a response they may first group patients into blocks (similar to our clusters) and then randomly assign members of the blocks to treatment and control arms.\n", "5. __Blinding__: The [_placebo effect_](https://en.wikipedia.org/wiki/Placebo), where people receiving a fake medication respond as if they have received a real one, is real. The opposite, though, is [_nocebo_](https://en.wikipedia.org/wiki/Nocebo) where a study participant thinks that because they're in the control arm they will receive worse treatment. Similarly, stakeholders to the experiment (doctors, diagnosticians, researchers) may unconsciously bias treatment and measurements if they know whether subjects are in the treatment or control arms. _Blinding_ occurs when only the subjects are unsure as to which group they are in, and where the experimental design limits any capacity for them to find out (such as treating them with a placebo). _Double-blinding_ is when none of the stakeholders know who is in which arm until the end of the study.\n", "\n", "
\n", "
\n", " Patients in a placebo arm continue to receive the best alternative treatment. The objective of an experiment which includes a placebo is not to see what happens if a patient receives no treatment, but to see if the experimental procedure / medication / approach works better than the best existing alternative. Finding out whether it works isn't good enough. Finding out whether it works better than the best alternative is the experiment. Critically, this also means that the placebo and treatment need to, in all respects, be indistinguishable from each other.\n", "
\n", "\n", "Continuing our example with our synthetic data, we can select two groups, divide them into blocks, and then randomly assign them to either the treatment or control arms of a study:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Let's assume the two colours we select each represent a specific group\n", "# perhaps one is low-risk and the other is high-risk\n", "\n", "low_risk_group = list(filter(lambda d: d[\"color\"] == F\"C0\", patient_population))\n", "low_risk_patients = random.sample(low_risk_group, 40)\n", "high_risk_group = list(filter(lambda d: d[\"color\"] == F\"C3\", patient_population))\n", "high_risk_patients = random.sample(high_risk_group, 40)\n", "\n", "# This all-risk patient sample represents our study participants\n", "all_risk_patients = low_risk_patients + high_risk_patients\n", "\n", "# Let's recreate the random coordinates and plot them:\n", "for p in all_risk_patients:\n", " p[\"coordinates\"] = (\n", " np.random.uniform(),\n", " np.random.uniform()\n", " )\n", "plt.figure(figsize=(4,4))\n", "plt.xticks(color=\"none\")\n", "plt.yticks(color=\"none\")\n", "plt.title(\"Sample Population\")\n", "# Plot them all by first converting the list of dicts to a list of values\n", "x, y, c = get_coordinates(all_risk_patients)\n", "plt.scatter(x, y, s=50, facecolors=\"none\", edgecolors=c)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create blocks (yes, I know they were in blocks when we started, but let's imagine they weren't)\n", "low_risk_group = list(filter(lambda d: d[\"color\"] == F\"C0\", all_risk_patients))\n", "high_risk_group = list(filter(lambda d: d[\"color\"] == F\"C3\", all_risk_patients))\n", "# Split each group in half and create new 'treatment' and 'control' groups\n", "# There are 40 members in each group, so ...\n", "control_group = low_risk_group[:20] + high_risk_group[:20]\n", "treatment_group = low_risk_group[20:] + high_risk_group[20:]\n", "\n", "plt.figure(figsize=(6,3))\n", "# Plot them all by first converting the list of dicts to a list of values\n", "plt.subplot(1, 2, 1)\n", "plt.xticks(color=\"none\")\n", "plt.yticks(color=\"none\")\n", "x, y, c = get_coordinates(control_group)\n", "plt.scatter(x, y, s=50, facecolors=\"none\", edgecolors=c)\n", "plt.title(\"Control Group\")\n", "# Plot them all by first converting the list of dicts to a list of values\n", "plt.subplot(1, 2, 2)\n", "plt.xticks(color=\"none\")\n", "plt.yticks(color=\"none\")\n", "x, y, c = get_coordinates(treatment_group)\n", "plt.scatter(x, y, s=50, facecolors=\"none\", edgecolors=c)\n", "plt.title(\"Treatment Group\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The distribution is presented below. Since it is a small sample size, you should expect a fair amount of variation between the two groups. How much would you think would be too much? How would you go about figuring that out?" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Control mean: 54.27\n", "Treatment mean: 54.88\n" ] } ], "source": [ "def get_age_distribution(population_list):\n", " \"\"\"\n", " Restructure a population list into a set of distribution lists for plotting in numpy.\n", " \n", " Returns:\n", " x, y, c lists of values\n", " \"\"\"\n", " x = [p[\"age\"] for p in population_list]\n", " bins = np.arange(start=min(x), stop = max(x) + 1)\n", " return x, bins\n", "\n", "plt.figure(figsize=(10,5))\n", "# Plot them all by first converting the list of dicts to a list of values\n", "plt.subplot(1, 2, 1)\n", "control_age, bins = get_age_distribution(control_group)\n", "plt.hist(control_age, bins = bins)\n", "plt.title(\"Control Group\")\n", "# Plot them all by first converting the list of dicts to a list of values\n", "plt.subplot(1, 2, 2)\n", "treatment_age, bins = get_age_distribution(treatment_group)\n", "plt.hist(treatment_age, bins = bins)\n", "plt.title(\"Treatment Group\")\n", "plt.show()\n", "print(F\"Control mean: {sum(cntrl_age)/len(cntrl_age):.2f}\")\n", "print(F\"Treatment mean: {sum(treat_age)/len(treat_age):.2f}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We allocated each patient a random id on selection and have known nothing about the patients, other than where they were sampled from, during the randomisation process. We sampled from each cluster, then mixed the clusters together to create a single random sample, then randomly allocated to our experimental groups. There is no information in the patient record which would indicate what arm of the experiment they're in.\n", "\n", "If the randomisation process has been done correctly, you should be able to flip a coin to pick which group becomes the _control_ and which the _treatment_ arm and it should have no consequence to the conduct or results of the experiment. Conversely, if results change depending on which group is assigned to which arm, you have some bias during the randomisation proces, or during the experiment itself, which nullifies the value of your experiment.\n", "\n", "Data curation must deliver statistically valid randomised study groups. Only then can the experiment be run and - once complete - can the data be presented for analysis.\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.3 Analysis: sampling methods with synthetic data\n", "\n", "
\n", "Investigate data distribution and confidence, using the principles of post-publication review.\n", "
\n", "\n", "### 2.3.1 Exploring data shape, distribution and variance\n", "\n", "We start any analysis by exploring our data to understand its shape, distribution and variance.\n", "\n", "The __mean__ (or _average_) is a measure of the centre of the __distribution__ of a data series. This is written as $\\bar{x}$ or $\\mu$ (mu) and is the sum of all of the observations divided by the number of observations:\n", "\n", "$$ \\bar{x} = \\frac{x_1 + x_2 + ... + x_n}{n} $$\n", "\n", "where $x_1, x_2 ... x_n$ represent the $n$ observed values.\n", "\n", "Earlier, we looked at __histograms__ which are used to visualise __data density__. Data can be divided into bins. Age, for example, is commonly divided by decile (0 to 10, 10 to 20, etc) where each observation increments the count of its appropriate bin (53 falls inside the 50 to 60 bin).\n", "\n", "These distributions can be __normal__ as shown earlier, where the observations are __symmetric__ about the central axis, or they can be __skewed__. Data which trail off in a particular direction are said to have __long tails__. If the tail falls on the left side of the chart it is __left skewed__ and if the tail is on the right it is __right skewed__.\n", "\n", "Viewing our data gives us an understanding of what our sample population, and our research observations, look like. If you want to run the next example, remember to install `scipy` (`pip install scipy`):" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# A demonstration of skewness, using skewnorm to randomly generate data\n", "# https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.skewnorm.html\n", "from scipy.stats import skewnorm\n", "\n", "fig, axs = plt.subplots(1, 3, figsize=(16,4))\n", "skewset = [[-6, \"Left skewed\"], [0, \"Symmetric\"], [6, \"Right skewed\"]]\n", "for n, [a, lbl] in enumerate(skewset):\n", " x = np.linspace(skewnorm.ppf(0.01, a),\n", " skewnorm.ppf(0.99, a), 100)\n", " rv = skewnorm(a)\n", " axs[n].plot(x, rv.pdf(x), \"k-\", lw=2, label=lbl)\n", " vals = skewnorm.ppf([0.001, 0.5, 0.999], a)\n", " r = skewnorm.rvs(a, size=1000)\n", " axs[n].hist(r, density=True, histtype=\"stepfilled\", alpha=0.2)\n", " axs[n].legend(loc=\"best\", frameon=False)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Histograms can also be used to identify __modes__, which are distinct peaks in the distribution. The above charts all have a single peak and are __unimodal__. Distributions can be __bimodal__ (two peaks) or __multimodal__ (> 2 peaks). This isn't rigourously defined, but is something you should be aware of when evaluating your data.\n", "\n", "The distance of an observation from its mean ($\\bar{x}$) is its __deviation__. The deviation of the $a^{th}$ observation from the mean is:\n", "\n", "$$ x_a - \\bar{x} = v_a $$\n", "\n", "Squaring the deviations, to get rid of negative signs, and averaging, gives an approximation of the sample variance ($s^2$):\n", "\n", "$$ s^2 = \\frac{v_1^2 + v_2^2 + ... + v_n^2}{n-1} $$\n", "\n", "The __standard deviation__ ($s$) is defined as the square root of the variance:\n", "\n", "$$ s = \\sqrt{s^2} $$\n", "\n", "This is useful when assessing how close the data are to the mean, where variance are the average squared distance from the mean, and standard deviation is the square root of this variance.\n", "\n", "These symbols are used to describe the sample of a population. For describing the population itself we use _sigma_ ($\\sigma$): $\\sigma^2$ for population variance, and $\\sigma$ for the population standard deviation. All going well during randomisation, your sample should be similar to the population, but that isn't always the case.\n", "\n", "The numbers themselves can be ambiguous since vastly different datasets can have the same means and standard deviations." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Draw a distribution chart shading the areas under the chart\n", "# for the first and second standard deviations\n", "# Derived from https://pythonforundergradengineers.com/plotting-normal-curve-with-python.html\n", "\n", "from scipy.stats import norm\n", "# Define constants\n", "mu = 1000 # mean\n", "sigma = 100 # first standard deviation\n", "# Calculate the distribution\n", "x1 = np.arange(-1, 1, 0.001) # first sd\n", "x2 = np.arange(-2, 2, 0.001) # second sd\n", "x_all = np.arange(-10, 10, 0.001) # all the data\n", "y1 = norm.pdf(x1,0,1)\n", "y2 = norm.pdf(x2,0,1)\n", "y_all = norm.pdf(x_all,0,1)\n", "# Draw the chart\n", "fig, ax = plt.subplots(figsize=(9,6))\n", "ax.plot(x_all,y_all, color=\"C0\")\n", "ax.fill_between(x1,y1,0, alpha=0.3, color=\"C0\")\n", "ax.fill_between(x2,y2,0, alpha=0.2, color=\"C0\")\n", "ax.fill_between(x_all,y_all,0, alpha=0.1, color=\"C0\")\n", "ax.set_xlim([-4,4])\n", "ax.set_yticklabels([])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "A useful rule-of-thumb for a symmetric distribution is that 70% of the data will be within one standard deviation of the mean, and about 95% will be within two standard deviations. Depending on skewness and modality, this won't always hold, but keep it in mind.\n", "
\n", "\n", "We now have enough theory to begin reading our research papers for this lesson and evaluate them for reliability.\n", "\n", "### 2.3.2 Principles of peer review\n", "\n", "Peer review is the process of subjecting scholarly research, work or ideas to the scrutiny of others who, ordinarily, are drawn from amongst the producer's peers.\n", "\n", "Historically, such a review takes place prior to publication, and approval acts as a gatekeeping function. This act of pre-publication review approval has created an unfortunate form of [moral hazard](https://en.wikipedia.org/wiki/Moral_hazard) in that simply being published in a prestigious journal is seen as sufficient for results to be taken seriously.\n", "\n", "A serious effort is being made by scholars for research to be reviewed _post-publication_. \n", "\n", "> Ending pre-publication review may remove the conferral of quality within the traditional system, thus eliminating the prestige associated with the simple act of publishing. Removal of this barrier may result in an increase of the quality of published work, as it eliminates the cachet of publishing for its own sake. Readers will also know that there is no filter, so they must interpret anything they read with a healthy dose of skepticism, thereby naturally restoring the culture of doubt to scientific practice. \\cite{crane_peer_2018, brembs_reliable_2019, stern_proposal_2019}\n", "\n", "This course will focus on public and transparent post-publication and informal research review. [PubPeer](https://pubpeer.com/) is an online application permitting community-based public post-publication peer review. They offer a useful guide on how to perform a review:\n", "\n", "- Base your observations and statements on __publicly verifiable information__. This will usually be the data published in the paper you are commenting on, but could also be another paper or some other source such as a book, newspaper or website. Include supporting information in your observation and you must cite your sources. This is to allow easy verification of the quality of your review.\n", "- If you are to post your statements publicly, assume that the authors may challenge you, potentially leading to a claim of defamation. When you write, __imagine having to defend the truth of your statement__ in court. If your comment only contains the obvious truth, that should discourage unhappy authors from initiating any legal attack.\n", "- Do not make allegations of misconduct, personal comments about authors, or speculation about researcher actions and motives. Focus exclusively on the work and publicly verifiable information.\n", "- If you are highlighting suspected __image irregularities__, provide marked-up images to prove your assertions. If you believe a particular transformation underlies an image irregularity, you should provide strong evidence, typically by performing the transformation yourself and including the result. If you believe image parts have been (inadvertently) duplicated, check first whether the experimental design offers an innocent explanation. \n", "- Criticism of specific __analysis and modelling methods__ should explain why they are unreasonable/erroneous and significant. This requires engagement with the purpose, design and methods of the article.\n", "\n", "In most cases you will __not__ have access to the researchers' underlying data. That does not mean you cannot test their results, but it does mean you cannot ordinarily attempt to correct any errors you find. You may know something does not make sense, or is incorrect, but not be able to assess the research data to recreate the results.\n", "\n", "This may seem daunting, but the best way to learn how to conduct your own research is to review the work of others. That way you also gain confidence as you realise how simple and inadvertant errors crop up regularly, and learn how to pre-emptively identify these issues throughout your own work. \n", "\n", "Even the most experienced researchers make mistakes and good-faith reviews will usually be met with gratitude and corrections. Everyone gains from public review.\n", "\n", "### 2.3.3 Case-studies in post-publication research review\n", "\n", "Research requires specialist domain knowledge, but it is built on fundamental skills and methods common to any scientist in any field. Just because you don't know the specific morphology of coronary atherosclerosis doesn't mean your skills in statistics or ethics are less valid. You may not be able to review everything, or even very much, in a paper but the little you can review could indicate underlying issues.\n", "\n", "It is critical, and an act of good faith towards your peers, that you stay within your area of competence. Validating arithmetic or statistics is one thing, declaring superior knowledge of, for example, organic chemistry when you've never studied the subject is reaching too far.\n", "\n", "We know sufficient to evaluate the quality of sample randomisation relied upon for experimental measurements. If the basics of patient randomisation are wrong, or bias has crept into measurements, you don't need to worry too much about the rest. If the fundamentals are correct, then you can hand the paper over to domain experts safe in the knowledge at least the foundations are solid.\n", "\n", "The analysis which follows is inspired by [Darrel Francis](https://www.imperial.ac.uk/people/d.francis), Professor of Cardiology at Imperial College London, who conducted a public review of both papers.\n", "\n", "#### Review: Effect of Icosapent Ethyl on Progression of Coronary Atherosclerosis\n", "\n", "Our first paper was produced by researchers at the [Lundquist Institute for Biomedical Innovation](https://lundquist.org/about) in the US.\n", "\n", "> _Budoff, Matthew J., Deepak L. Bhatt, April Kinninger, Suvasini Lakshmanan, Joseph B. Muhlestein, Viet T. Le, Heidi T. May, et al. 2020. “Effect of Icosapent Ethyl on Progression of Coronary Atherosclerosis in Patients with Elevated Triglycerides on Statin Therapy: Final Results of the EVAPORATE Trial.” European Heart Journal. [doi:10.1093/eurheartj/ehaa652](https://academic.oup.com/eurheartj/advance-article/doi/10.1093/eurheartj/ehaa652/5898836)._\n", "\n", "The paper __abstract__ summaries the research and lets us know what to expect from the body of the work:\n", "\n", "> __Aims:__ Despite the effects of statins in reducing cardiovascular events and slowing progression of coronary atherosclerosis, significant cardiovascular (CV) risk remains. Icosapent ethyl (IPE), a highly purified eicosapentaenoic acid ethyl ester, added to a statin was shown to reduce initial CV events by 25% and total CV events by 32% in the REDUCE-IT trial, with the mechanisms of benefit not yet fully explained. The EVAPORATE trial sought to determine whether IPE 4 g/day, as an adjunct to diet and statin therapy, would result in a greater change from baseline in plaque volume, measured by serial multidetector computed tomography (MDCT), than placebo in statin-treated patients.\n", "\n", "The researchers are looking at plaques - a deposit of some type - which forms in hearts, and assessing whether or not a specific treatment will reduce plaque volume in comparison to that of a placebo treatment. Note, patients continue to be \"statin-treated\". Placebo does not mean no treatment. Both arms of the trial will continue to receive the same care, except for one difference - whether or not they receive the active chemical molecule being assessed.\n", "\n", "We already, therefore, know to expect a treatment arm and a control arm in the methods. Adequate randomisation between these two arms, and an indistinguishable but inert placebo, are required.\n", "\n", "> __Methods and results:__ A total of 80 patients were enrolled in this randomized, double-blind, placebo-controlled trial. \n", "\n", "Is 80 patients a lot? It depends on the rareness of the condition and the scale of the difference between the treatment and control arms at the end of the trial. However, from the paper we know that - for two groups - we'd expect about 40 patients per group making up the 80-patient sample.\n", "\n", "> Patients had to have coronary atherosclerosis as documented by MDCT (one or more angiographic stenoses with ≥20% narrowing), be on statin therapy, and have persistently elevated triglyceride (TG) levels. \n", "\n", "These are the _inclusion_ criteria. This clarity will help domain experts assess whether these are the appropriate patients to include.\n", "\n", "> Patients underwent an interim scan at 9  months and a final scan at 18  months with coronary computed tomographic angiography. \n", "\n", "The endpoint of the study was treatment after 18 months with an interim scan at 9 months to evaluate if anything had happened. This is a long-term condition and the researchers hope the condition improves. The scan at 9 months is there, amongst other things, to test if the experiment caused the treatment arm to get worse - which may necessitate stopping the trial - or improve so much that the trial would be stopped so as to ensure those in the control arm also got the new treatment.\n", "\n", "In this case, the trial continued to its endpoint.\n", "\n", "> The pre-specified primary endpoint was changed in low-attenuation plaque (LAP) volume at 18  months between IPE and placebo groups. Baseline demographics, vitals, and laboratory results were not significantly different between the IPE and placebo groups; the median TG level was 259.1 ± 78.1 mg/dL. There was a significant reduction in the primary endpoint as IPE reduced LAP plaque volume by 17%, while in the placebo group LAP plaque volume more than doubled (+109%) (P = 0.0061). There were significant differences in rates of progression between IPE and placebo at study end involving other plaque volumes including fibrous, and fibrofatty (FF) plaque volumes which regressed in the IPE group and progressed in the placebo group (P < 0.01 for all). When further adjusted for age, sex, diabetes status, hypertension, and baseline TG, plaque volume changes between groups remained significantly different, P < 0.01. Only dense calcium did not show a significant difference between groups in multivariable modelling (P = 0.053).\n", "\n", "This is the core of the experimental results. We may not know what all of these terms are, but they're all numbers and we should expect tables of these data for each of the treatment and control arms. We can review these data and test whether it is as expected and supports the conclusions.\n", "\n", "> __Conclusions:__ Icosapent ethyl demonstrated significant regression of LAP volume on MDCT compared with placebo over 18 months. EVAPORATE provides important mechanistic data on plaque characteristics that may have relevance to the REDUCE-IT results and clinical use of IPE.\n", "\n", "The __Results__ section contains tables of interest. Of interest is that, of the 80 patients who joined the trial, only 68 completed, with 31 in the treatment arm, and 37 in the placebo. _Table 1_ profiles these patients, and that is the lowest resolution we will get to ensure and preserve participant anonymity. You should see that we could create synthetic data to mimic this profile as well.\n", "\n", "_Table 2_ is the core area of interest:\n", "\n", "![Plaque changes by treatment group](images/module-1-lesson-2-budoff-et-al-table-2.jpg)\n", "\n", "Look for the familiar terms:\n", "\n", "- __Baseline__ are the measurements taken at the start of the trial;\n", "- __Follow-up__ are measurements taken at the end;\n", "- __Difference__ are the calculated differences;\n", "- __Mean (SD)__ are the mean (average) of the measurements for that group, and the standard deviation from the mean.\n", "\n", "The placebo arm is called _Placebo_ and the treatment arm is called _IPE_. For now, we don't have the context to understand many of the other terms, but that doesn't mean we can't perform analysis.\n", "\n", "We can start with our expectations from these data. We know it is a randomised trial, so we expect the two groups to have a similar profile at the beginning and - given the claims in the conclusions - that the IPE group should be meaningfully better than the Placebo at the end.\n", "\n", "The authors encourage this view: \"Baseline demographics, vitals, and laboratory results were not significantly different between the IPE and placebo groups.\"\n", "\n", "$$ \\text{About the same } \\to \\text{Different} $$\n", "\n", "Except ... \n", "\n", "![Plaque changes extract of Total](images/module-1-lesson-2-budoff-et-al-table-2-extract.jpg)\n", "\n", "Can you see something weird? The two means at baseline are quite different. We can draw this to get an idea of how different." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Baseline variance between study arms\n", "# Placebo\n", "mu_p = 4.1\n", "sd_p = 1.8\n", "x_p = np.arange(-5, 15, 0.1)\n", "y_p = norm.pdf(x_p, mu_p, sd_p)\n", "# Treatment (IPE)\n", "mu_t = 5.0\n", "sd_t = 1.8\n", "x_t = np.arange(-5, 15, 0.1)\n", "y_t = norm.pdf(x_t, mu_t, sd_t)\n", "# Draw the chart\n", "fig, ax = plt.subplots(figsize=(9,6))\n", "ax.plot(x_p,y_p, color=\"C0\", label=\"Placebo\")\n", "ax.plot(x_t,y_t, color=\"C1\", label=\"IPE\")\n", "ax.legend(loc=\"best\", frameon=False)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We know - based on a symmetrical distribution - that 70% of a sample occurs within one standard deviation of the mean. How far apart are the means of the two groups?\n", "\n", "$$ 5.0 - 4.1 = 0.9 $$\n", "\n", "$$ \\frac{0.9}{1.8} = 0.5$$\n", "\n", "Half a standard deviation apart, meaning there is at least a __40%__ difference between the two groups. Given the groups are quite small, these differences increase the risk from outliers (confounding variables), mean they're not the same in terms of disease morphology and treatment, and may mean we can't read much into the results.\n", "\n", "Confirm for yourself that these variations are present in each of the plaque types as well (and notice that the _Calcification_ type is less different).\n", "\n", "It's hard to reconcile these differences with their claim that \"Baseline demographics, vitals, and laboratory results were not significantly different between the IPE and placebo groups.\"\n", "\n", "And how different are they on conclusion of the trial?" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Follow-up variance between study arms\n", "# Placebo\n", "mu_p = 4.6\n", "sd_p = 1.4\n", "x_p = np.arange(-5, 15, 0.1)\n", "y_p = norm.pdf(x_p, mu_p, sd_p)\n", "# Treatment (IPE)\n", "mu_t = 4.5\n", "sd_t = 1.8\n", "x_t = np.arange(-5, 15, 0.1)\n", "y_t = norm.pdf(x_t, mu_t, sd_t)\n", "# Draw the chart\n", "fig, ax = plt.subplots(figsize=(9,6))\n", "ax.plot(x_p,y_p, color=\"C0\", label=\"Placebo\")\n", "ax.plot(x_t,y_t, color=\"C1\", label=\"IPE\")\n", "ax.legend(loc=\"best\", frameon=False)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The conclusion seems to be that the placebo patients got slightly worse, and the treatment patients got slightly better, and now they're almost the same.\n", "\n", "But a trial is supposed to consider the best alternative to a new treatment. The patients in the placebo arm should not have gotten worse. There are questions here that need answers and which we cannot find in the paper.\n", "\n", "We shouldn't speculate, but we can ask, what do we think may have happened? We _know_ from the paper, that the patients were randomised: \"multi-centre, randomized, double‐blind, placebo‐controlled trial\". Either the randomisation didn't work, or the measurements were biased in some way. But biased measurements implies a lack of blinding.\n", "\n", "In the section on _Plaque quantification_ we are told that an automated imaging system quantified the plaque volume but that: \"Once automated software had completed the vessel trace, an expert reader manually corrected areas of misregistration.\" In other words, a human manually adjusted the values scored by the computer. Could this person have inadvertantly biased the plaque volumes in the two groups? We cannot know, but it is at least one potential source of error.\n", "\n", "Besides the meaningful difference between the two arms, we also note that the patients in the placebo group got worse. For _low-attenuation plaques_ we can spot the following:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "image/png": 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d3QNvjTBnzhzefPNNQAVY559/vsOx48ePp7Cw8GiezCuvvMKCBQsAtWrx5z//mfPOO4/IyEjq6uo4ePAgkyZNIjEx8Wgy7J133kl0dDTV1dXU1dXR2dl5Sufc3jyY9evXExwcTHBw8IDfT18GshIyE8jTdT0fQNO0N4HLgaNrWLquH3+WaDOQcFazEkJgt+tsK6wnItCbsdGuPYJ4OqYnh7G7tIltBfVcnB7b/wVCeMiNN97IZZddxvTp08nMzGT8+PEATJo0iV//+tcsWLAAo9FIVlYWL730Ek888QR33303GRkZWK1W5s+ff/TEzcyZM1m+fDnFxcX89re/JS4ujiuvvJJNmzYxZcoUNE3jj3/8IzExJ64QLlu2jGeeeYaMjAzGjRvH7Nmzjz53xx13kJGRwdSpU3nttdf6fT9PPPEEt912G4899hiRkZG8+OKLDsf6+Pjw4osvcs0112C1WpkxYwZ33nknALNmzaKqqor58+cDkJGRQVRU38f8zWYzDzzwALNmzSI1NfXon2Gv0NBQ5syZQ3NzMy+88EK/76E/Wn/LS5qmXQ0s03X9+z3f3wTM0nX9Hgfjfw6MP258AdAA6MDfdV0/eZWk97o7gDsAkpKSpvVGsEKMVIerWvh4dwXLM2IZGx3o0bl8m1vD9qIGbjkvhVB/L4/ORQjhGQsXLuTxxx9n+vTT39TQNG17X7shA1nf7WvDp8/IRdO0RcDtHMsPAZir6/pU1HbO3Zqmze/rWl3Xn9V1fbqu69MjIyMHMC0hzl26rrOloJ4wfy9GR3puFaTX1KRQTAaNbYX1np6KEOIcMpAgpBRIPO77BKD85EGapmUAzwOX67pe1/u4ruvlPb9WA++htneEEE7k17ZR29LJjJQwDAbXV0Y9Xf7eJibHB3OgooWmjoHvaQshzh1r1649o1UQZwYShGwDxmialqppmhdwHfDh8QM0TUsC3gVu0nX98HGP+2uaFtj7e+BC4OwOFQtxjtN1na0F9QT7mhkX49ltmONNSw5F02B7kayGCCFco98gRNd1K3AP8DlwAFil6/o+TdPu1DTtzp5hDwDhwF81TcvRNC275/FoYL2mabuArcDHuq5/5vJ3IcQ5pLi+ncomCzNSwjAOgVWQXoE+ZibFBbG3rJkWi6yGCCHO3oDqhOi6/gnwyUmPPXPc778PfL+P6/KBKWc5RyFGlO1FDQR4m5gQO3RWQXpNTw5jT1kTu0ubmDvaPdVbhRDnLukdI8QQ0tDWRVFdOxkJwZg8UBekP8F+ZtIiA9hT1iQ9ZYQQZ23o/ZQTYgTbVdqI0aAxOf7sCgANpsyEEDq6bByuavX0VMQIExCgTooVFhbi6+tLZmYmEydO5M4778Rut5/weO/Xyy+/POD7v/TSS5SXn3LuAoCVK1eSmpp6tP7If/3Xf7nkPfVau3Ytl156KQAffvghjz76aD9XnBukGYQQQ0SX1c6+8mbGRAUM6T4tiWG+hPl7sau0kYlxQZ6ejhihRo0aRU5ODlarlcWLF/P+++8zderUo4+fiZdeeonJkycTFxfX5/OPPfYYV199NRaLhYkTJ3LzzTeTmpp6Fu+ibytWrDilH825SlZChBgiDlY202W1MyUxxNNTcUrTNKYkhlDZZKGyyTU9MYQ4UyaTiTlz5hwtVz4QDz/8MDNmzGDy5Mnccccd6LrOO++8Q3Z2NjfeeCOZmZl0dHQ4vL63n4q/v7/D+4GqeDpx4kQyMjK47rrrANWF9rbbbmPGjBlkZWXxwQcfnHL/l156iXvuUfVAV65cyb333sucOXNIS0vjnXfeOTruscceY8aMGWRkZPDggw8O+P0PJUP345YQI4iu6+wqaSQqyJvYYB9PT6dfE2ID2ZBXS05JI8uCpbHdiJO7GlqrXHvPgGgYs/S0L2tvb+err77i4YcfBuDIkSNHO+0CPPnkk6d0i73nnnt44IEHANWd9qOPPuLqq6/mqaeecloR9Be/+AW///3vycvL49577yUqKsrh/S677DIeffRRCgoK8Pb2prGxEYBHHnmExYsX88ILL9DY2MjMmTNZutT5+66oqGD9+vUcPHiQFStWcPXVV/PFF1+Qm5vL1q1b0XWdFStWsG7duqOl2YcLWQkRYggobeigtrWLKQkhZ92V0h28TUYmxgZxuKqF9i6rp6cjRqDeYGPu3LksX76ciy++GDi2TdP71Ve7+jVr1jBr1izS09P5+uuv2bdv34Be87HHHiMnJ4fKykq++uorNm7c6PR+GRkZ3Hjjjbz66quYTOoz/xdffMGjjz5KZmbm0Q67xcXFTl/3iiuuwGAwMHHiRKqqqo7e54svviArK4upU6dy8OBBcnNzB/aHN4TISogQQ8Cu0kZ8zMYhVZysPxkJweSUNLK3rJmZqWGeno5wpzNYsXC1M839sFgs3HXXXWRnZ5OYmMhDDz10Srv6/gQEBLBw4ULWr1/P1KlTHd7v448/Zt26dXz44Yf87ne/Y9++fei6zr/+9S/GjRt3wj17g4u+eHt7H/1971aPruv88pe/5Ic//OFpzX2okZUQITysvcvKkeo2JsYFYR6Cx3IdCQ/wJjHMj33lTfTXCFOIoaI3QIiIiKC1tfWEHIvAwEBaWlr6vYfVamXLli2MGjXK4f3sdjslJSUsWrSIP/7xjzQ2NtLa2spFF13Ek08+efTvzM6dO8/ofVx00UW88MILtLaqU2plZWVUV1ef0b08SVZChPCwg5Ut2HWdScPwpMnE2CA+31dJWWMHCaF+np6OEKfkhNx2223ce++9R78PCQnhBz/4Aenp6aSkpDBjxoyjz61cuZI777wTX19fNm3ahK+v7wn37s0J6erqYsmSJXznO99B07Q+72ez2fje975HU5MK0n/6058SEhLCb3/7W+677z4yMjLQdZ2UlBQ++uij036fF154IQcOHOC8884D1OrMq6++ejRPZbjQhuInmOnTp+vZ2dn9DxTiHPDq5iIMmsYNs5I8PZXT1mW189y3+YyJCuDCSZKgKoTom6Zp23VdPyXjV1ZChPCg6mYLNS2dLB4/vD699PIyGRgfZqAmfyfdejdmWweEJkNYGvhHwjBIshVCeI4EIUJ40L6KZowGbVglpALQ0QA5b8D2l1hSe0g9tv2kMT7BMPlqmHE7RE9y+xSFEEOfBCFCeIjNrnOosoVRkQH4mI2ens7AtNbA1w/D7rfB2gEJM9EX/5a1NQFYg1O4YEoaNBZBfT6UbYedr0L2PyDpPFj8G0g539PvQAgxhEgQIoSHFNS20tFlGz6lz/d/CB/dB50tkHkDTL8dYjPQAL/8OjYeqWOmfyrBkWOPXbPsUch5DbY8Cy8th1k/gqUPgtnX0asIIUaQ4XMeUIhzzL7yZgK8TSSHDfFTJZYm+NcPYNVNEJwAP1wHl/0FYjOODpkQF4Smwf6K5hOv9QuDOT+GuzfDzDtgy9/gmXlqlUQIMeJJECKEB7R1WimsbWdCbBAGwxBO3myrhZcuhb3/goW/hO9/BVETThkW5GMmMdSP/RXNfdcM8fKHSx6Dmz8AqwVeXK5KfwshRjQJQoTwgNzqVuy6zvjYIZyQ2lwOL14MtblwwypYeD8YzQ6HT4gNormjmwpnTe3SFsIdayFiDLxxHew/tXmXEI4EBAQAUFhYiK+vL5mZmUycOJE777wTu91+wuO9Xy+//PKA7//SSy9RXl7e53MrV64kNTX16H2feOIJh/dZu3Ytl1566dF79jajE6eSnBAhPOBwZQsRAV5EBHj3P9gT6vPh5cuhvQFueheS5/R7yagof0wHNA5VtRAX4iTnwz8Cbvk3vH4tvL0SVjwFWTe6bu5iROgt2261Wlm8eDHvv/8+U6dOPeNy7qAChsmTJxMXF9fn84899hhXX331WcxanExWQoRws2ZLN2WNHYyNHqKrIG218PIVKgH1lg8HFICAamqXEuFPblULdns/RRB9Q1RwkzofPrgbDpx+xUghAEwmE3PmzCEvL2/A1zz88MPMmDGDyZMnc8cdd6DrOu+88w7Z2dnceOONZGZm0tHR0e99LBYLt956K+np6WRlZbFmzRqn44uKiliyZAkZGRksWbKE4uJibDYbaWlp6LpOY2MjBoOBdevWATBv3rw+31dKSgq1tbUAZGdns3DhQgAeeughbrrpJhYvXsyYMWN47rnnBvxn4imyEiKEm+VWqd4UQ7I2iLUT3voetFTCrZ9A/NTTunxcTCB51a2UNXaQ2F/CrZc/XP8mvHgJvHsH3PbZCcmuYgj79H6o3OPae8akw8WPnvZl7e3tfPXVVzz88MPAqWXbn3zyyVM66d5zzz088MADANx000189NFHXH311Tz11FM8/vjjTJ9+SmFP4FjZdoBXXnmFL774AoA9e/Zw8OBBLrzwQg4fPuxwrvfccw8333wzt9xyCy+88AL33nsv77//PmPHjmX//v0UFBQwbdo0vv32W2bNmkVpaSmjR48+rT+P3bt3s3nzZtra2sjKymL58uUOV3aGAlkJEcLNDlW2EhPsQ4ifl6enciJdh49+BsWb4Iq/QkLfP4idSY3wx8tk4FBl/03AAHVU9/o3VGGzN66HFsedRIU4Xm+wMXfuXJYvX87FF18MHNum6f06OQABWLNmDbNmzSI9PZ2vv/6affv2Deg1H3vssaP3TU9PZ/369dx0000AjB8/nuTkZKdByKZNm7jhhhsAFfysX78eUCse69atY926dfzyl79k/fr1bNu27YS+NgN1+eWX4+vrS0REBIsWLWLr1q2nfQ93kpUQIdyooa2LqmYL88dGenoqp9r0FOS8Cgv+H6Sf2b632WggLcKf3OpWFo2PwjiQkz+BMXDDm/DCMnjrRrjlIzD7nNHrCzc5gxULVzvT3A+LxcJdd91FdnY2iYmJPPTQQ0c74Z6us+29pvW0NZg3bx7PPPMM5eXlPPzwwzz22GOsXbuW+fPnA6pjblVVFdOnT+f555/HZDJht9uPvp++7uno+6FGVkKEcKPDPVsxY6MDPDyTkxRvgS8fgImXw4L7z+pW42ICsXTbKK5vH/hFsVPgyr9D6TZY/eBZvb4QzvT+ox0REUFrayvvvPPO0ecCAwNpaRngKh4wf/58XnvtNQAOHz5McXEx48aNczh+zpw5vPnmmwC89tprnH++qiA8a9YsNm7ciMFgwMfHh8zMTP7+978fXcX5/PPPycnJ4fnnnwdUTsj27arWzr/+9a8TXuODDz7AYrFQV1fH2rVrz2g1xZ0kCBHCjQ5XtRAf6kugj+Ojrm7X2Qrv3aEKka14Cgxn92MhOdwfb/NpbMn0mrgCZt0JW56BI1+f1RzEyNW7TePoKG1ISAg/+MEPSE9P54orrjjhH+mVK1dy5513Djgx9a677sJms5Gens61117LSy+9hLe34xNvTzzxBC+++CIZGRm88sor/OUvfwHA29ubxMREZs+eDaiVkZaWFtLT0/u8z4MPPshPfvIT5s2bh9F4YsuHmTNnsnz5cmbPns1vf/vbIZ0PAqCd7XLSYJg+fbqenZ3t6WkI4VK1rZ28sqmIxeOjmJIY4unpHPPhvbDjZZWIOsCTMP35cn8Vh6tauGN+GmbjaQQ13R3w9/nqZM6PNqqKq0KIAXnooYcICAjg5z//uaencgpN07brun5KopnkhAjhJoerWtA0GDOUtmIOfQo7/glz7zvtAKShrYsv9ldysLKF8sYOyhstdHTbiA32IcjXTENbF2OjA7kgzRdqD0N7nQouLE2ADt7B4B2oAo2IMeAbqhJVv/McPL8EPvk5XP3CoLxtIcTQICshQrjJK5sK8TEbuWZ6oqenorTVwl9nQ0AM/OBrMPV/Wsdm1/l4TwXv7yxj3eEarHYdfy8jcSG+xIb44mMyUNlsoaqhhaj2PMYbikkPaGV8tD+TkqPxDwpVwYemqWCksxm6exLrguIgepI6qrnxSfj6d3DVP844SVYIMXTISogQHlTf1kVtaxcLxw2hUzFfPggdjXDzhwMKQDYeqeXhf+/nYGULscE+3HZ+KiumxDEpLuhYBr6uQ81BOLKbffll5NR7cdA+hf87HIK1KJQfLx7NyqwUvE3H7WN3NEL1AajeB7lfQtFGGLVYrdJ8+v9g9FJV3EwIcc6RIEQINzhS0wrAqKghshVTslUdx517H0RPdDq0ssnCQx/u47N9lcSH+PL0DVO5eHLMqY33Wmvg8GfQVAoBUQTMvpnqI0a+Py2BW2w6//3JAf7704O8vrWY/1oxiYXjotR1viGQfJ76aiqFvK/g8Oeqz8z6/4M1j6jmd0KIc46cjhHCDfKqVYGyoKFwKsZug49/BkHxMP8XToduLajn0ifX883hGn5+4Vi++o8FLM+IPTUAqT4AO15SeR/jlsG0W4lPGY+X2UhedSujowL4x8oZ/PO2mZgMGitf3MafVx8+tbx7cAJMvRkmXKaCk7ipsO15qNjt0j8CIcTQIEGIEIOs2dJNZZOF0UNlFST7BVVy+6JHwLvvOem6zsubCrnhuc0E+pj48J653LN4DD7mE48DYrer47T73oeAaJhxO8RlgcGAyWggJdyfIzWtR4ONBWMj+fjeeXxnajx/Xp3LHa9k02zpPvGemgYxk2H67TDlBjD5wL++D7aTxgkhhj0JQoQYZEeq1VbM6MghEIS01sBXv1NbHROv6HOI3a7zm/f38sAH+1gwNpL3757LmL6a7dm6Ye87qtBZ/FTIvFGddjnO6KgA2jptVDQfq+roYzbyv9dM4b9WTGLtoRqueHoDFU191GTw8oPpt6rApvYQfHSf6m0jhDhnSBAixCDLrW4lItCbUP8h0Cvm699Bdztc/JhacTiJ3a7z6/f38tqWYn64II3nbp5OsG8fW0g2K+x9F+rzYexF6stgPGVYSoQfRoN2tGlfL03TuGVOCq99fxY1zZ1c/+xmKpv6KJ1tMMDSh9WJmb3vqnom1q4zfvtCiKFFghAhBlFbp5Xyxo6hsQpSmws7X4UZ34fIsac8res6D3y4lze2FnPXwlHcv2z8qbkfoAKQfT0ByLiLnXba9TYZSQ73I6+6tc8+G7PSwnnptpnUtHRyw3ObqW52EIhc+hcVPO3/APaskkBEiHOEBCFCDKL8mjZ0naGRD/LVw6oY2Lz/OOUpXdf5r3/v59XNxfxwfhq/uGhc342v7DbY9x7UHVEJqLFT+n3ZUZEBtFisVLf0vZUyLTmUl26bSWWzheue20xtax/jEqapZNWy7VBzGPa8LTkiQpwDJAgRYhAdqWkl2NdMRICHt2LKtsOBD2HOjyHg1FolL24o5KWNhdw2N5X7Lx7vuPNm3ldQlwdjL1QJqAMwKjIAg6aR15Mb05cZKWG8dOtMyhs7uPOV7XRabacOWvxbsFqgtRKaSlQdkSFYbFEIMXAShAgxSLqsdorr2xkVFeDZdtq6DqsfAr8IOO/uU55ed7iG33+8nwsnRvOb5RMcz7VshwpmkmZB/LQBv7yvl5G4EB/ya9ucjpuZGsbj10whu6iB376/99Ttm8hxKvl133vq91X7oGTLgOchhBh6JAgRYpAU17dhs+ukRfh7diL5a6BgnaoJctLplYLaNu55fQdjowP507WZfeeAADQWq2qm4aMgdeFpTyEt0p/alk6aOpxvoVyaEcePF49mVXYpL20sPHXAwvsBTRUzi5oA+WuhNu+05yOEGBokCBFikBypacPHrPqqeIyuq1yQkCR13PU4LZZuvv/PbRgNGs/dPB1/bwcFlDsa1ckU31CYsEIlip6mtAiVE5Nf43hLptdPl47lgonR/O6j/azPrT3xyeAEmHUH7HoTwkdDQBQc+ED1wRFCDDsShAgxCOx2nYLaNlJ7jqh6TN5qKN+pVkFM3ic89cAH+yisa+evN04jMcyv7+vtdpVLottUIzmzzxlNI9TfizB/L/JrnG/JABgMGn+6NpPRUQHc99bOUxNV5/5UJdhu+AtMvgoMJtj/vjq1I4QYViQIEWIQVDRb6OiykebJo7m6Dt/8EYITIeO6E576cFc57+0s455FozlvVLjjexRvhKYyGLsM/MLOajppkf6UNnRg6e4j6fQkAd4mnrg+i2aLlf/3zu4T80P8w2H6bapQWnsdjL9UFWErWHtW8xNCuJ8EIUIMgvyaVgyaRpKjFQZ3KPwWSrfC3J+c0CW3rLGDX7+3h6ykEH68eLTj65vKoHADRE9SX2cpLTIAu65TVNc+oPHjY4K4f9l4vjpYzWtbik98cs6PwWCG9X9SeSrxU6FkG9QXnPU8hRDuI0GIEIOgoLaNhFDfU3utuNO6x1Q/l6ybjj5ks+v87K0c7Hadv1ybhcno4EeAtQsO/Fslso650CXTiQ3ywdfLSEFt/3khvVbOSWHemAh+//H+E4/4BsaoRnc5b0BjCYxaDH7hcPAj6BpYkCOE8DwJQoRwsYa2Lupau0iL9OCpmOIt6kTMnB+fkMfxj/X5bCmo56EVk0gKd7JKc+QrsDTChEvPOA/kZAaDRmqEP/m16tTQQK/532um4Gs28tO3crDa7MeenPsTQIeNT4DRDBNXQHcH5H7ukvkKIQafBCFCuFhvPQyP5oN8+zj4hsG0YydiSurb+b8vD7N0QjRXT0twfG1jMZTnQMIMdarGhdIi/OnstlPe2EfDOgeignz4/RXp7ClrOvHYbkgiTLketv8TWqrU6kjyXKg+KMd2hRgmJAgRwsXya1TDuj4bv7lD5R7I/QJm3wXeKhDSddWYzqhpPHz5JMcFyWxWOPQZ+ARDyjyXTy0pXJ0W6q9w2ckuSY9h8fgo/u/Lw5QdH8Cc/1Owd8Pmv/a8wGzwj1CrIdJfRoghT4IQIVzI0m2jvNHi2QJlm/4KZj+Y+f2jD/17dwXrDtfw84vGOa9bUrJZnTgZe9EJyayu4m0ykhjmS8EA6oUcT+sJnnQdHji+mmr4KFW7ZPuL0NmqOvmOXQaWZihc5/L5CyFca0BBiKZpyzRNO6RpWp6maff38fyNmqbt7vnaqGnalIFeK8S5pLi+Hbuuk+KpIKS5QjV3y/qeKi4GNLV38/C/95OREMzN56U4vra9Hoo2qUqk4aMGbYop4f40tHfT2H56KxUJoX787IKxfHWwms/3VR574rx7wNIEOa+p70MSIS4TSrOhpbLPewkhhoZ+gxBN04zA08DFwETgek3TJp40rABYoOt6BvA74NnTuFaIc0ZhraqSGhvkmmTO07btObBbYfaPjj70P58fpKG9iz9cme64cJquw+HP1ErC6KWDOsXUngCtcIBHdY9369wUJsUF8eCH+2ix9JSAT5wBibPUloy9pwZJ2kK1GnToU1VwTQgxJA1kJWQmkKfrer6u613Am8Dlxw/QdX2jrusNPd9uBhIGeq0Q5wpd1ymsayM53M9xD5bB1NUG2S/A+OUQlgbAvvIm3thazC3npTA5PtjxtbWHoaEI0hYczSMZLCF+XoT4mSk8zbwQAJPRwB+uTKequZO/rj1y7Inz7oaGQjj0ifre7Aujl6iVkKo9rpm4EMLlBhKExAMlx31f2vOYI7cDn57utZqm3aFpWramadk1NTUDmJYQQ0tNSydtnTaSnR19HUw5r0NHg9qeQAVFv//oACG+Zn6ydIzj62xWOPK1SuiMzXLLVFMi/Cmpb6fbdvqrFFMSQ/jO1Hj+8W0BJfU9qynjL4WQZNj41LGBURMhOB7yvwFrZ983E0J41ECCkL4+0vV5yF/TtEWoIOT/ne61uq4/q+v6dF3Xp0dGRg5gWkIMLb3bCynhHsgHsdvVdkT8NHVCBPhyfxWb8uv46QVjnZ/UKctWTepGLzmj5nRnIjXcH6tdp6xh4Ed1j/efF43HaNB49NOD6gGDUZ0GKtmsckEANA1GLVErRMWbXDRzIYQrDeQnTimQeNz3CUD5yYM0TcsAngcu13W97nSuFeJcUFjbRnSQj+NutIPp8GdQn6+2JTSNLqudP3xygNFRAdww00mtj642KNqgElF7tnDcIT7UF5NBo6Du9LdkAGKCffjhgjQ+3lPBtsJ69WDWjeAdDJuePjYwOB6iJ6qS7h2NZz9xIYRLDSQI2QaM0TQtVdM0L+A64MPjB2ialgS8C9yk6/rh07lWiHOBpdtGeVMHKZ7aitn6LATFwwSVcvXypkIK69r59fIJjkuzAxR8q7ZjRi1200QVs9FAYpjfGeWF9LpjfhoxQT787qP92O26KjE/9SbV9be54tjAtIXq1/y1ZzVnIYTr9RuE6LpuBe4BPgcOAKt0Xd+nadqdmqbd2TPsASAc+KumaTmapmU7u3YQ3ocQHlVc346u45mjubW5kL9GVUc1mmhs7+KJr3KZPzaSReOiHF/XWgMVORCXpfJB3Cwlwp/G9m4a2s6sqJifl4n/XDaO3aVNfLCrTD0443Z1Qmb7S8cG+gRD4kyoPqCa8gkhhowBbQDruv6JrutjdV0fpev6Iz2PPaPr+jM9v/++ruuhuq5n9nxNd3atEOeagp6juTGeOJq77XnVUXbaLQA8800+LZ1Wfn3JBOfXFa5TPVdSznfDJE/Vu2pUeIZbMgBXZMYzOT6I//vyMF1Wu9pSGr1UBSG27mMDk84DLz+1GqIPrG+NEGLwScVUIc6SrusUeepobmerOhUz8XIIiKK62cJLGwu4fEoc42ICHV/XXA41hyFhpvrH2QNC/LwI9TOfVRBiMGj8x4XjKKnv4K3snoN4M38ArZWqC3AvkxckzVF9cRoKz27iQgiXkSBEiLPUezTXI6di9qyCzmb1Dy/w9Jo8rDad+5aOdX5dwTpVSyNxphsm6VhKhD+l9R1ndFS318KxkcxICeXJr3KxdNvUSkhIslohOl5cFvgEQcE3shoixBAhQYgQZ6mgJ7kyJcLNKwq6Dlufh+h0SJxFSX07r28t5prpic5zUxqKoL5AbVGYvN033z6k9BzVLT3Do7qg+sr8/MJxVLd08vKmQnVcd8bt6tRP1XEpaEaT6rLbXAF10mVXiKFAghAhzlJhnTqa6+fl5qO5xZugep9qVKdpPPFVLpqmce+S0Y6v0XW1CuIdAPFT3TdXBxJCfTEbtbM6JQMwKy2c+WMj+dvaI6qce9ZNYPI5dTUkJh38wmQ1RIghQoIQIc6CpdtGRZPF/asgoP6B9Q6G9GvIq27lXztKuWl2MrHBTrrk1udDUykkz1FJqR5m6jmqW1Dbdqwz7hn6+YVjaWjv5h/rC1SgMfkq2PWW6qjby2BUibitNVC9/yxnL4Q4WxKECHEWiurU0dxUdx/NbatTiZeZ14OXP099nYuP2ciPFjrpfqvrUPitOrIam+m2qfYnOdyfpo5uGtu7+x/sREZCCBdNiuYf6wtotnTD9Nuhu011FT5e1EQIiITCDdLcTggPkyBEiLNQUNuGr5eR6EA3H83d9QbYumDqLRTWtvHhrnK+NzuZiAAnOR4NBSofIvk8tSIwRKT2JPSeafXU4/148RhaLFZe3liotpui02HHP08cpGkqN6S9DmoPnfVrCiHOnAQhQpyho0dzw9x8NFfXVR2MxFkQPZG/rs3DbDTw/Xmpzq8r2qiqikanu2WaAxXsZybM34siFwQhk+ODWTw+in+sL6Cty6Zqp1TsgvKdJw6MGAd+4Sp5VXJDhPAYCUKEOEPVLZ20d9ncXyW1aCPU5cLUWyipb+fdHWVcPzOJKGerMQ1F0FiimtsZPdDbph/J4X5nfVS31z2LR9PQ3s2rm4sg47tg8j2xgiqoRn3J56nckNrcs35NIcSZkSBEiDNUUNumVvbd3S9mxz9VQuqkK/n7uiNomuqj4lTRRvDyh9gp7pnjaUqNUEd1S+rbz/peU5NCOX90BM99m4/FGACTvwN73lGF3Y4XNQl8Q2Q1RAgPkiBEiDNU5Imjue31sO99yLiGyg4Dq7aVcvW0ROJCnJyIaSpTVUITZw2JEzF9iQ9RR3WL6s4+CAG1GlLb2sUbW4th6i3Q1Qp7/3XiIINB1UppqVSnhoQQbidBiBBnoKOr52iuu6uk7l4Ftk6YtpJn1+Vj03XucnYiBtQqiNlXVQwdolx5VBdgdlo4M1PC+Ps3+XTGToPICacmqIKqG+ITpP6MhBBuJ0GIEGegqL7N/UdzexNS46fRGDSON7YWc/mUOBLDnGwHtVar6qAJ01X/lCEspeeobsNZHtXtddeiUVQ2W/hgVwVMWwll26Fyz4mDDEa1QtRUqnJmhBBuJUGIEGegsLZdHc0NcmPZ8/IdUHMAsm7i1c1FdHTbuGNBP7kgJVtUImqc56uj9qc3wfdsGtodb8HYSMbHBPLcunzs6d8FoxfsfO3UgTEZYPZRf1ZCCLeSIESI06TrOsX1bSSF+aFpbjyam/M6mHywjLuClzYWsnBcJONjghyPtzRD1X5VmMxDnXJPR7CvmVA/M8UuygvRNI0fLkgjt7qVNcXdMO4S1fDP2nXiQJMXxE9Tp2Ta6lzy2kKIgZEgRIjTVNvaRVunzb2nYrot6oTHhMt4d38Lta1d/HB+P7kgpdvUrwkzBn9+LpIc7k9pQztWFxzVBbg0I464YB/+vi4fMm9UBcpyvzh1YPw0MJhkNUQIN5MgRIjTVFyvtguSnOViuNrhT8HSiC3jBp77Np+MhGBmp4U5Ht9tUQW6osarY6jDRHK4H902nfJGi0vuZzYauH1eGlsL6tnplQUB0WpF6WRe/hCbAVV7obPFJa8thOifBCFCnKbC2nYiArwI9HHjcdec1yEoni8t4yiobeOH80c53woq3wm2bpV0OYwkhPphNGguywsBuG5GIsG+Zp5dXwwZ10Lu59BW28eLzwDdDqXZLnttIYRzEoQIcRq6bXbKGztIcufR3JZKyPsKPeNa/v5tIUlhfiybHON4vM2qtmJCUyDQybghyMtkIC7ElyIXFC3r5e9t4nuzk/hsXyWlyVeC3XpqUztQnXcjxqoAztrpstcXQjgmQYgQp6GsoQOrXSfFnfkgu1eBbmNf1HJ2Fjfy/XmpGJ31qqneD11tkDS8VkF6JYf7UdvSSWun1WX3XDknFbPBwLMHvVS9lJw+TsmAKmtv7YSK3S57bSGEYxKECHEaiurbMRk05xVKXUnX1VZMwkz+ttdAkI+Jq6YmOB9fug38IyC0n4Z2Q1Rvwq8rGtr1igz0ZkVmHG9nl9Ix8TpVL6SvQCMoDoLjoSwb7K5JjhVCOCZBiBCnoaiujfhQX8xGN/3VKd8JNQdoGHcNn+2t5PqZSfh7OykT31isCpQlTFct64ehyABv/L2NLjuq2+vWuSl0dNtY1TlD1QzZ9UbfAxNmQEejKvImhBhUEoQIMUAtlm7qWrvcezS3pzbIiw2ZANw8J8X5+NJtqkR79ORBn9pg0TSNpDA/iurbXVLCvdekOHWi6NltTdjHXgy73zq1ZghAxDhVyr33iLMQYtBIECLEAPU2V0sKc1NSqrUT9ryNdcwlvLSjgWWTY4h3tg3UXq8+vcdlDdlGdQOVHO5PR5eN6hbXJojefn4aZY0dbA9ZpmqG5H156iCDAeKnq1WllkqXvr4Q4kQShAgxQMX17QR4m4gIcFMPlkOqNshav6U0W6zcNrefHI+yHaAZIH7ol2jvT+9qU2Gt6/JCABaPjyI53I/HjiSAf1TfNUMAYqeoQE6O6woxqCQIEWIA7Hadorp2ksLdWKp91xvogbE8ejCGKYkhTE0KcTzW2gmVuyByPHgHumd+g8jPy0RUkLdLj+oCGA0aK+eksLW4herUy+HwZ33XDDH7qJ4y1fuhs9WlcxBCHCNBiBADUN3SiaXbjaXaW6og90uKE1aQV2fhtrkpzoOfit0qv2EYlWjvT3KYPxWNFjqtNpfe95rpiQR6m3ih9byemiHv9D0wYboqXla+06WvL4Q4RoIQIQagqK4NTXNjqfY9qjbIM00ziQz05uLJsY7H6rrqsBscD0FOxg0zyeF+2HWdkvoOl943wNvEVdMS+EeuL93RUxzXDPELg7A0qMgBu2sDISGEIkGIEANQVN9OVKAPfl5Ojse6Sk9tkM7oqbxZ4Mv1M5PwMjn5q9pQoJJS44Z/Lsjx4kJ88TIZjvbqcaWbzkum26azKfBCqNyt6ob0OYmpajum9rDL5yCEkCBEiH51Wm1UNFrctxVTkQPV+1njuxSDpnHDzCTn48t2gJefygc5hxgNGgmhvhTWujYvBGBUZABzR4fz38WT0A1myHFQMyQsDXyC1Z+xEMLlJAgRoh8l9R3Ydd19WzE5b6AbvXmkaAIXTowmJtjH8VhLkzqWGzsFjG5YpXGz5HB/mjq6aWzvo57HWbppdgoHmr2ojl2kaobYuk8dZOg5bdRYDK01Lp+DECOdBCFC9KO4vu1oY7VBZ7PCvncpi5pPSYc3N52X7Hx8b9JkbOagT80TknsCv0IXV08FWDohirhgH96wnAfttZC/tu+BMRlgMKm8GyGES0kQIkQ/iuraSQj1dd40zlXy10JbDa+0zmR0VADnpYU7HmuzQsUuCB8NviGDPzcPCPEzE+xrdmkfmV4mo4EbZiXx17I0bN7BqlFgX7z8IGq8yhuR7rpCuJQEIUI40djeRWN7N8nhbqqSumcVVq8gXqwZy02zk50fy605CF3t50RxMkc0TSM53I/Shg5sdteVcO917YwkdKMXOYEL4eBHjmuCxE9T2zWVe10+ByFGMglChHCit1R7sjvyQbra4MBHZPvNx+zlw3emxjsfX75DHSMdpt1yByo53J8uq53yRtce1QWOHn9+sjYLutvh0Cd9DwyKg8AY9Wfuwn42Qox0EoQI4URRfTtBvmZC/NzQi+XQp9DdxtN1WVw5NZ5AHyev2VIFTWWqT8ww7ZY7UAmhvhg0jWIXV0/tdfN5yXxjGU2bT6xKUHUkfqqqrtpYPCjzEGIkkiBECAdsdp2S+naSw9xUqn3P27R6R7G+exw3zU5xPrZsuzoNE5M++PPyMB+zkdhgHwoHIS8EYFpyKONigvmIuehH1kBrdd8Doyaqcu5l2wdlHkKMRBKECOFAZbOFLqudlAg3bMW01aHnrebftvOYkRrBuBgn/V+6O6B6H0RNArMbTuwMAcnhflQ3d9LeZXX5vTVN4+bzUni+aSaaboO97/Y90GhWJ2Vqc8HS7PJ5CDESSRAihANFtW0YNI2EUDcEIfvfQ7NbeaVtFjf3dyy3cq86GXMOJ6SerDcxeLC2ZK7IiqPSO4VS71GqZL4jcVmArk4lCSHOmgQhQjhQVN9OTLA3Pmbj4L/Y7rcpMydT4z+WiybFOB53fJ+YQCfjzjFRgd74ehkHpXoqqK69V09L4NX22Wq7pe6Ig4HST0YIV5IgRIg+WLptVDVbSApzw9HchiIo2czrHbO4flYyZuPI6xPTH4NBIynMj+L6NvRBOp3yvdnJvNd9Hjqa45ohIP1khHAhCUKE6ENxfTu6jnv6xexVreT/bT9/xPaJGYjkcD/aOm3UtA5OwbBRkQGMGT2W7dpk9N1vOT6KK/1khHAZCUKE6ENRXTveZgMxQU76triCrmPfvYqdjGPSxMkD6xMTk3FO9onpT2/vnuJBKOHe66bzknmr6zy0hgLHp2CO7yfTVjtocxFiJJAgRIiT6LpOUV0bSWF+GAa7VHvVXgw1B/lX9xxunNVPQmrFbvXpPC5zcOc0RAX6mIkI8BqUPjK9loyPItv3fLoxO68ZEpMOBiOU5wzaXIQYCSQIEeIk9W1dtFisJLsjH2T3KqwY2RW0iDmjnPSJsdvViYywVPANHfx5DVHJ4f6UN3bQZbUPyv1NRgOXzhzPl7YsbHv+1XdnXQAvf4gYA1V71EklIcQZkSBEiJMU9RwDTRrsfBC7Hevut/nGlsHFsyY5X3Wpz4fOlnO2W+5AJYf7YbPrlA1CCfde352eyPv28zF21MGRNY4HxmZCt0X18BFCnJEBBSGapi3TNO2Qpml5mqbd38fz4zVN26RpWqemaT8/6blCTdP2aJqWo2latqsmLsRgKa5rJ8zfi2DfQS7VXrQBU2sF/9bncvW0BOdjK3KOffoeweJDfDEbtUGrngqQGOaHNW0pzQRgd7YlE5qiVqUqcgZtLkKc6/oNQjRNMwJPAxcDE4HrNU2beNKweuBe4HEHt1mk63qmruvTz2ayQgw2q81OaUP74K+CALbdq2jHB33sxUQFOktIbe5JSO3JQxjBTEYD8aG+g5qcCvDdWaP4t3UW+oGPHXfW1TSInQKNJdBWN6jzEeJcNZCVkJlAnq7r+bqudwFvApcfP0DX9Wpd17cBDjZQhRgeyhstdNv0we+aa+3Etvd9PrNN56rZ45yPrexJSI2dMrhzGiaSw/2pb+uiqWPwftwsmRDFWu+FGG0dcPBjxwNj0kEzQMXOQZuLEOeygQQh8UDJcd+X9jw2UDrwhaZp2zVNu+N0JieEuxXVt2E0uKFUe+6XeHU3s9F3IeePjnA8rjchNTRFVesURwPEwVwNMRsNjJ2xlFI9AsvONxwP9A5QW2S9pfSFEKdlIEFIX9lyp1OycK6u61NR2zl3a5o2v88X0bQ7NE3L1jQtu6am5jRuL4TrFNa1Exfii5dpcHO227LfoFYPIm32Zc4TUhsK1HbMCD2W25cwfy8CfUyDmhcCcO2MFD60zcGrcB20OvmZFJepmgrWHhrU+QhxLhrIT9pSIPG47xOA8oG+gK7r5T2/VgPvobZ3+hr3rK7r03Vdnx4ZGTnQ2wvhMq2dVmpbOkkZ7HwQSxPe+V/wiX02V09PcT62IkdVSI0YO7hzGkY0TSM53J+Shnbs9sEp4Q7qdFRJ/HIM2LDv/ZfjgaGp4BsiTe2EOAMDCUK2AWM0TUvVNM0LuA74cCA31zTNX9O0wN7fAxcCe890skIMpqKeT9aDnZRq3fshJr2L8qTLiHJWkbWzBWolIbUvyeF+dHbbqWy2DOrrzDt/AQfsSbRsc7Il05ug2lCk+voIIQas3yBE13UrcA/wOXAAWKXr+j5N0+7UNO1OAE3TYjRNKwV+BvxG07RSTdOCgGhgvaZpu4CtwMe6rn82WG9GiLNRVNeOv7eRyADvQX2dxi2vUWiPZva8i5wPrNwDun3E1wbpS1KYH5rGoG/JLJ0QzZem+QTX5ahaLY7EZPQkqOYM6nyEONcMaONb1/VPdF0fq+v6KF3XH+l57Bld15/p+X2lrusJuq4H6boe0vP75p4TNVN6vib1XivEUGO36xTVtZMc7o+mDWKp9pZKwmo2s8Y8n3ljoxyP03VVEjw0WRJS++BjNhIT5DPoR3W9TAaMGd8FoDX7TccDvQMgYrQqrS8JqkIMmFRMFQKoarFg6baREj64pdobtryBAR1z5rUY+01IbZJVECeSwv2obFb/3QbT8vOns8U+nu6dbzrurAs9FVQ7oC53UOcjxLlEghAhUFsxmnasU+tg6dz5JnvtqSydP8/5wPIcMPtKQqoTKeH+6DoU1w/uakhKhD97wi4itKMIe1mO44FhaeATLE3thDgNEoQIgUpKjQ7ywddr8BJAu6sOEdN2kP0RFxET7CwhtRVqc1VCqtE0aPMZ7mKCfPA2Gyga5C0ZgMTzr6NLN1K2/mXHg44mqBZKgqoQAyRBiBjxLN02KposJA/yqZiitS9h1zXi533P+cDehNS4rEGdz3BnMGgkhflRVNeG7mybxAUWZY5nozaVwNwPwO5k+ye2N0FVjusKMRAShIgRr6S+HV1X5cAHja4TmPse2w3pzJ4y2ek4KnIgJEkSUgcgOcyfFouV+rauQX0dL5OBhlGXE2Kro2H/V44HegdC+ChVat9ZsCKEACQIEYLCuna8zQZindXsOEtVBzYQba2gcfQV/SSkFkJHo1RIHaDkCLV6VeiGLZnMpdfRovtSuf4V5wPjsqCrXW2pCSGckiBEjGi6rlNU10ZSmJ/z8ulnqWzdP+nUzaRf0M9WTEVOT0JqP03tBABBPmbC/L0orh/ceiEAqbGR7PA7n8TK1di7OhwPDE0FnyCpGSLEAEgQIka0urYuWizWQT2a293dRXLl5+zxn01MVLTjgZ2tUHMYYiZLQuppSAr3o7S+g26bfdBfy2vqtQTQzsFv33E8yGBQCar1BdDRMOhzEmI4kyBEjGi9JysGs1T77nXvE04TXlnXOh9YtbenQqokpJ6OlHB/rHad8kYnqxMuMnXB5dQSTNcOJ4XLoKeCqiYJqkL0Q4IQMaIV1bURHuBFkI950F6jc8ebNOPPxPlXOx7UWyE1JBH8wwdtLuei+BBfjAbNLUd1vb28yI++iImtm6mtqXI80CcIwnsqqEqCqhAOSRAiRqxum52yho5BPRVTVl3LlNb1FEUvxeTt63hgY5FaupcKqafNy2QgPsT3aAPCwRY37xa8NCt7v+wnQTU2E7raoC7PLfMSYjiSIESMWGUNHVjtOsmDWCU1Z/Ub+GudxJx/s/OB5Tlg9oFISUg9E8nhftS2dtFi6R7010qYNJdyYzxBee9jtzupTxKWpo7slu8c9DkJMVxJECJGrMK6NkwGjfhQJysUZ8FqsxOU+x71xggiJy12PLCrDWoPQ/RkMA7ettC5rHc1yx1bMmgaTaOvINO2l+179zke15ug2lAoCapCOCBBiBixiuraSQjzxWwcnL8G63cfYrY9h+ZRK9Q/SI5U7lV5A7IVc8YiArzw9zYOeh+ZXmmLV2LQdErW9bclk6F+rdg9+JMSYhiSIESMSE0d3dS3dQ1qPkjxt69j1mwkLFjpeFBvhdTgBAiIHLS5nOs0TSMpzJ+iunbnWyQu4h09ljK/CYyv+ZTa1k7HA32CIUwqqArhiAQhYkQq7lm2H6x8kLLGDibWfkatbyqmuAzHAxuLVbMzqZB61lIi/LB026hucRIUuJBX1rVM1Ir4at065wPjMlUNmLojbpmXEMOJBCFiRCqsayPQx0SYv9eg3P+zb7cw3XAYU+a1ql6EIxU5YPKGyPGDMo+RJCnMD03DbadkImffgB0DXTvfct5AL2wUeAdIBVUh+iBBiBhxbHad4vp2ksP90ZwFCGfIarPTnfMWACEzr3c8sKsdag5BTLokpLqAn5eJqEAf9ySnAgRGUxM5mwWda9l8pM7xuKMVVPPB0uSeuQkxTEgQIkac8sYOuqx2UiMGZyvmm0PVLO7+hobwLAhNcTywqjchdcqgzGMkSgn3o7ypA0u3e/IvQmffSJKhhs3rPnU+MKY3QVUqqApxPAlCxIhTUNuG0aCROEj5IN+u/4axhjKCZt7geFBvhdTgeAiIGpR5jESpkf7outpucwevSSvo1ryIKviQ+rYuxwN9Q1TdkIrdYB/8HjdCDBcShIgRp7CujfgQX7xNRpffu7LJQmzxh9g0I8bJVzke2FQC7XVyLNfFogN98PUyUljrniAEnyA60i5imWET72UXOB8bmwmdLVAvCapC9JIgRIwoTe3d1LV2kRo5OEdzV20r4jLjRrqSFznvAVOeAyYvSUh1MYNBIyXcn0I3HdUFCJpxA+FaC3mb/+08QTV8FHj5q//2QghAghAxwhT0LNOnDkJ9EJtdJ3fLp8Rp9fhOc5KQ2t2hElKjJ6tARLhUaoQ/HV02Kpst7nnB0UvpMgcxq/UrthbUOx5nMKriZfVHJEFViB4ShIgRpaC2lVA/M6GDcDR3XW4N8zq+ptvkD+MucTywci/YrbIVM0iSw/0waBoF7tqSMXlhmHQlFxq386/NB52PjZ3SU6BOKqgKARKEiBGky2qntL6DlIjB2Yr516bDXGLaimHi5eDlIOm1t0JqUCwERg/KPEY6H7OR2BAf9wUhgCnzWvzoxHrgExrbnSWohkJYak8FVUlQFUKCEDFilDS0Y7XrpEUEuPzeVc0WjHmfEUAHxszrHA9sLoO2WlkFGWRpEf7UtHS6pasuAEnn0e0fx6Ws590dZc7HxmaCpRka+klkFWIEkCBEjBiFtW14mQyD0jX37ewSLte+xRoQCynzHA/sTUiNmujyOYhjele7CmvdVLjMYMCc+V0WGHfzyeY9zhNUI8b0JKjudM/chBjCJAgRI4Ku6xTUtpEU5ofR4NoqqXa7zmdb9rDAuBvTlGsdd8zt7oDqAxA1SRJSB1m4vxdBvmbya1vd96IZ38WInQkNX7G9qMHxOINRVcmtO6JWRIQYwSQIESNCbWsXLRYrqYOQD/JtXi0zWr/GiB2mONmKqdqvElKlWd2g0zSN1Ag/SurbsdrclHsRPQl75ASuMm3k9a3FzsfGTgHdDpV73DM3IYYoCULEiNCbpDgYSalvbCnmGvMG7DEZEDWh70G6DhU7ITBGfYlBlxoRQLdNp7Shw22vacj4LpnaYXbtzqGp3Uk+il+YKulfsUsSVMWIJkGIGBEKa9uICvImwNvk0vtWN1soOLCDieRjcLYK0lwOrTWyCuJGCaG+mI3a0dowbpF+NQDL9A28t7PU+di4TFUvRBJUxQgmQYg453V02Shv6hiUrZi3t5dymeFbdM0Ak692PLAiR3XKlYRUtzEbDSSG+VFQ0+Y8UdSVQpIgeS7X+2zgjS3F/SSojlVHuSty3DM3IYYgCULEOa+ovg1dx+VBiN2us2prEdd6b0JLW+S47ke3Bar3Q/QkMHm7dA7CuZRwf5o6umlwtjXialOuI8FWhl/NTnYUNzoe15ugWpunesoIMQJJECLOeQU1bfh5GYkJ8nHpfTceqSOmcSeRtmrnCanV+8AmFVI9obdHUIE7T8lMvALd5Mu1Xut5o98E1UxJUBUjmgQh4pxmt+sU1rWTHO6Pprn2aO4bW4u5znsDutkfxi/ve5Cuq9oggdGSkOoBQT5mIgK8KHBXvRAAnyC0CZdyuWkTX+wupNlZwTS/MAhNVgmq7toyEmIIkSBEnNMqmi1Yum2kubhrbk1LJ2v3FXOxcQvaxBWq+FRfWiqgtVp94nVxECQGJjUigLKGDizdNve96JTr8bW1cr4tmw92DqCCakejJKiKEUmCEHFOK6xtw6BpJIU56OVyht7ZXspCtuNja4OMax0PLM8Bo0nlgwiPSInww67rlNS7cTUkbSEExrHSfxOvDSRB1eyr/l8RYoSRIESc0/Jr24gL8cHHbHTZPW12nde3FnFb4BYIjIXU+X0P7LaofJAoSUj1pLhgX3zMRvLd2NAOgxEyvst06w5qK0vZUeykgqrR1JOgmisJqmLEkSBEnLOaLd3UtnS6fCtm3eEa2uqryOraDunXqH9w+lK5RyWkxk916euL02MwaCSH+1FY68ajugCZN2DQbVzrvYlXNhU5HxuXpRJUZTVEjDAShIhzVmFvldRw1wYhr24u4jq/bRh0q+NTMbquGpQFxUlC6hCQGuFPe5eNquZO971o5DiIm8pNfhv5ZE8lda1OXtsvDMLSVM0QuxtzV4TwMAlCxDkrv6aNYF8zYf6uaxZXUt/O14equcV3g1pCd5Tr0VgE7XWyCjJEpIT7o2mQX+PGo7oAmTcQ05HHaHs+q7L7qaAaPxU6W6Euzz1zE2IIkCBEnJO6rHZK6tsZFRXg0qO5r28tZoJWRHTbQci6yfHAsh0q2TDSQS8Z4Va+XkbiQnw54s68EIDJV4HBzD1h23htSxE2u5PtoLBR4BOk/t8RYoSQIESck4rq2rDaddJcWCW102rjrW0l/CxiGxi9VD5IXyzNKskwNkMlHYohYVRkALUtnc4by7maXxiMW8YS6zdUNrTwzeFqx2MNBpUb0lAIbXVum6IQniRBiDgnHalpw8dsJD7E12X3/HRPJS1t7SzoXAPjLlH/wPSlYhegS4XUIWZUT4LyEXdWTwWYcgPenfWs8N/ff4JqTIZKdC7f6Z65CeFhEoSIc47drlNQ20ZqhD8Gg+u2Yl7ZXMQNIfswdzZA1vccvLhNJReGpTkOUoRHhPh5ERHgxZFqNwchYy4AvwjuDNnK2sM1FNc5qVfiHaASWit3g7XLfXMUwkMkCBHnnLJGVR1zdJTrtmL2lzezvaiB2/03QGAcjFrc98DaXJVcGCcJqUPRqMgAyho76Ohy4wkUoxnSr2FM43pCtTZe29rfcd2pYO1UTQ+FOMdJECLOOUdqWjEZNJLCXBeEvLqliCRzI4n1GyHzese1Qcp3gE+wWgkRQ05aZAC6DgXuTlDNvB7N1sUv4vayaluJ8xLywQkQEKn+X5J+MuIcN6AgRNO0ZZqmHdI0LU/TtPv7eH68pmmbNE3r1DTt56dzrRCupOs6R2raSAr3w8vkmhi72dLN+zvLuD8uB023Q+aNfQ9sq4WGIpVcaJD4fiiKDvImwNvEEXcf1Y3JgKhJXKqvpaG9m0/2VDgeq2lqNaSlCprL3TdHITyg35+UmqYZgaeBi4GJwPWapk08aVg9cC/w+BlcK4TL1LZ20dzRzajIAJfd870dZbR3WVliWQ1JcyB8VN8Dy3eqFZLYDJe9tnAtTdMYFeVPcX07VpvdnS8MmdcTWLeLhWH1vLK5ny2Z6Elg8lKrIUKcwwbycW0mkKfrer6u613Am8Dlxw/Qdb1a1/VtwMln3/q9VghXOlLTiqapCpmuoOs6r2wu4trocryb8iHLwSqItUslE0aOc9xRVwwJaREBdFntFLuzoR2oRocGE/8RsYWdxY3sLWtyPNbkDdGTofogdLl5nkK40UCCkHig5LjvS3seG4gBX6tp2h2apmVrmpZdU1MzwNsLcaIjNa3EBvvg7+2a+hxbCurJq27lh0GbwOwPE6/oe2D1fhWISELqkJcYprbqjtS4OS8kIArGXcykmo8JNNt4bcsAElTtVtWDSIhz1ECCkL7OOA40W2rA1+q6/qyu69N1XZ8eGRk5wNsLcUxTezfVzZ0u3Yp5ZXMRMT5WUqu+gElXqiOUJ9N1KNuukgmDE1z22mJwGA0aqRH+HKlpxe6sgulgmLoSQ0c996cc4f2d5TR1OCmcFhAJIYmSoCrOaQMJQkqBxOO+TwAGmi11NtcKcVryalQb9DFRgS65X1Wzhc/3VvLr1MNoXa2Oa4M0l0Frtfrk6sIS8WLwjIkKoKPLRlljh3tfeNQiCE7kcvtqOrptvLO9n34ycVOhoxHq890yPSHcbSBByDZgjKZpqZqmeQHXAR8O8P5nc60QpyWvupXIQG+C/cwuud+rm4uw6ToXdK5WfT2SZvc9sDT72B6+GBaSw/0xGzXy3F24zGCErJsIKFvPJfEWXt5U6LyfTOQ4tfpWmu2+OQrhRv0GIbquW4F7gM+BA8AqXdf3aZp2p6ZpdwJomhajaVop8DPgN5qmlWqaFuTo2sF6M2Lkau20Ut5oYUyUa7ZiLN02XttSzPWjrfiUb1YJqX2tcliaoOYQxE5RpxnEsOBlMpAc7k9edSu6u7c6sr4HmoGfRmyhqK6drw866ydjVKsh9fnqCLgQ55gBFTPQdf0TXdfH6ro+Stf1R3oee0bX9Wd6fl+p63qCrutBuq6H9Py+2dG1Qrha7yfa0S4KQj7IKaO+rYu7greAZoAp1/c9sGwHoEP8NJe8rnCf0VEBtHZaqWiyuPeFg+Nh9AWMLvuAxCAzL6wvcD4+LhMMJlkNEeckqagkzgl51a2EB3gRHuB91vfSdZ0X1hcyKcaf+KL3YNQSCIo7daC1S/WJiRgLviFn/brCvVIj/DEaPLAlAzDtFrTWSn49toRN+XUcqGh2PNbLX9UNqdoD3W7OYRFikEkQIoa99i4rpQ3tjHbRqZhNR+o4VNXC/WNK0VrKHSekVu2FbgskzHDJ6wr38jEbSQrzI9cTWzJjLoKAGJa0f4qv2ciLG/pZDUmYATYrlOe4ZXpCuIsEIWLYy69pQ9dhdLRrgpAXNhQQ7u/FnMZ/g38kjLvk1EG6rpbHA2PkWO4wNjoqgOaObmpaOt37wkYTZN2IueArbk03835OObWtTuYQEAmhKeoouN2NzfeEGGQShIhhL7e6hWBfM5Eu2IopqG3jq4PV/DDLB2PeF2oVpK+E0/p8aK9Tn1DlWO6wNSoyAIOmkeuJLZmsm0C3c7v/Rrqsdl7fUux8fMIM6GxRidBCnCMkCBHDmqXbRkl9B2OiA9BcEAz8c2MhJoPGDeZvQLfD1Fv6Hliarfbqoyac9WsKz/H1MhIf6ktuVYv7t2TCUiFtIeGH32LR2DBe2VxEp9XJKkf4KPANhdJt7pujEINMghAxrOVVt2Kz6y4pUNZs6ebt7BIuz4giYN/rMGqx+ofiZG21aiUkfpo6QimGtbHRATS0d1PjbDtksEy9BZpK+GlaOTUtnXy8u5/uugkzVGfdpjL3zVGIQSRBiBjWerdiooPOfitm1bYS2rps/DixUFVBnbay74Gl2erIZFzmWb+m8LzRUT1bMlUe2JIZvxz8wkmvep/RUQG8sKHA+YpMTLoqjFcmx3XFuUGCEDFsdXTZKK7rYGx04FlvxdjsOi9tLGRmShjJhW9DQHTfCandHeqoZPRE6ZZ7jvDzMpEY5suhSg9syZi8Ycr1aIc+4UfTA9lb1kx2UYOT8V4Qm6G661qcHOsVYpiQIEQMW7nVLdh1nbExZ38q5sv9VZQ2dHDXVG/I7UlINfZR/r08Rx2VlGO555Sx0YE0dXRT1eyJLZmbwW5lhf4Nwb4DKF4WPw3QVWM7IYY5CULEsHW4qpUwfy+XnIp5YUMBCaG+zG/5WB2/nXrzqYPsNnVEMjRZtWUX54zRUQEYDRqHq1rc/+KR4yBpDuacf3LDzAQ+31dJSX274/G+oRAxBsp3gs1JF14hhgEJQsSw1NqpCpS5Yitmb1kTWwvquW12PIYdL8OYC1VNhpPVHlZHJGUV5JzjYzaSHO7HYU+ckgGYcTs0FPCDuAI0TePlTYXOxyfMUIXyqva6ZXpCDBYJQsSwpI5UqpMNZ+uFDQX4exm5LnAntFXDzB+cOkjXoWSr+hQaPvqsX1MMPWOjA2mxWCl3dy8ZgAkrwD+KsL3/5JL0WN7cVkJrp9Xx+OBECIxWSdKeCJqEcBEJQsSwlFvVSkSg91n3iqlo6uDDnHKumZ6I384XITRV9Yo5WVOpOhopxcnOWWmR/pg8tSVj8oJpt0DuF9w1xUiLxcqbW50UL9M0SJipjovXHXHfPIVwMQlCxLDTbOmmrLGDcdFnXxvkhfUF6MCPxrdDyWa1LG7o469FyRYw+6qTCeKc5G0ykhLhT25VC3a7B1YXpt0KmoEJpW8zOy2Mf6wvoNtmdzw+agL4BKn/b4UYpiQIEcPO4Ur1SfVst2KaOrp5fUsxl2XEEn3wFTD5QOaNpw5sq4XaXHUqoa8TM+KcMS4mkLZOG6UNHuhWGxyv6obsfIUfzY2nosnCv3eVOx5vMKrVkMYSKV4mhi0JQsSwc6CyhdhgH0L8+ujpchpe21JEW5eNO2dFwJ63If0a8As7dWDJFtVwLH7aWb2eGPpSI/zxMhk4UOmhGhwzfwAdDczvWse46ED+/k2+80TZ2Clg9pHVEDFsSRAihpWalk5qWzoZHxt0VvexdNt4cUMh88dGMr7y39Dd3ndCqqUZqvZBzBTw8jur1xRDn9loYExUAHnVrc63QgZLyjyIHI+27Xl+uCCNQ1UtrD1c43i8yQvipqqVuvZ6981TCBeRIEQMKwcqmjFo2lnng7y/s4yalk5+OC8Ftj6rlrVjp5w6sCxbNbJLlGO5I8WE2CC6rHbya9rc/+KaBjO+D+U7WRFeRmywD3//pp/E0/hpoBnVip0Qw4wEIWLYsNt1DlW2kBLhh6/XmTeOs9l1nv02n8nxQcyxbYOGApj9o1MHdltUQajI8eporhgREkJ9CfQxcaDCQ1syU64H72BMW//G7eensjm/npySRsfjvQNUT5nKPaqOjRDDiAQhYtgobeigtdPKhLPcivlsbyX5NW3cuWAU2ua/QVCCqtNwsvIdYO2CpNln9XpieNE0jfExQRTVtdPmrFbHYPEOgGk3w/4PuX6cgWBfM0+vyXN+TeJMtWJXus09cxTCRSQIEcPG/opmvEwG0iLOvHGcrus8tSaPtEh/Lo6ohcJvYdYdKvH0eNYuVZwsfBQExpzlzMVwMz42ELuue6ZmCMDMOwAd/10vsHJOCl/ur+Kgs2RZvzB1ZLdsh2qyKMQwIUGIGBa6rHaO1LQyNjoQk/HM/7ddc6iaAxXN/GjBKIxbnwGzX999Yip2qR/myXPOYtZiuIoI8CYy0JsDFR4KQkKS1Orc9pe4dUYE/l5G/rqmn9yQpDmql0xptnvmKIQLSBAihoUjNa10We2MjznzhFRd13nq6zziQ3y5YoxZHcvNvOHUfA+bVR15DEmC4ISznLkYribEBlHVbKG+rcszE5h9F1iaCDn8L743O5mPdpdTWOskWTYgUjW2K8sGqwe6AQtxBiQIEcPCgYpmAn1MJIT6nvE9NuXXsaO4kTsXpGHe+RLYumBWHwmpVXugs1VWQUa4cTGBaBqeS1BNnKmO3255htvPT8ZkNPC3tf2shiTPPZZQLcQwIEGIGPKaLd0U17czMS7orDrmPr0mj8hAb67JjIRtz8OYiyDipGZ0djsUb4ag2L476YoRI8DbRGqEP/vLmz1Txl3T1GpIXR5RFeu4bkYi7+4spbzRSc5HUCyEpap8Jlu3++YqxBmSIEQMefvLm9F1mBQbfMb32FHcwIa8On4wLxWffaugrQbOu/vUgdX7oKNRfaKURnUj3qS4IFo7rRTWeaBmCMCkK9TprY1P8MMFo9B1+q8bkjwHutpUXpMQQ5wEIWJI03WdfeXNJIX5Eex35n1b/rw6lzB/L26ckQAbn4S4LEidf+Igux2KNkJAFISP7vtGYkRJjQjAz8vIvnIPbckYzXDeXVC0gfiWvVw9LYE3tpVQ2WRxfE1Ikvoq3qTym4QYwiQIEUNaSX0HzR3dTIo/89og24saWHe4hjvmp+Ff8DnUH4G5Pzl1paN6nyp9nTJPVkEEAEaDxoTYIPJr2jxTMwTU6S2fYNj4F+5eNBq7Xeeva/upG5JyvsprqshxyxSFOFMShIghbW95Ez5mI6Mjz7xj7p9XHybc34ubZyfBhj+rXI+Ti5PZ7VC4AQKj1QkDIXpMigvCruvO63QMJu9AmPEDOPARifZyrpmewJtbS5znhoQmq9WQoo2SGyKGNAlCxJBl6bZxpLqV8TFnXhsku7Ceb3Nr+eGCNPwqtkLZdpjzY9UG/XhVe6GjQVZBxCnCA7yJC/FhX3mz8462g2nWD8HoBZue5O5Fo9EZ4GpIVxuU57hlikKcCQlCxJB1sLIFq10/q62YP6/OJSLAi+/NToYNfwG/CMi88cRBdhsU9ayCSC6I6MOkuGDqWruocJaLMZgColRNm5w3SDC1cM30RN7aNoDVkNDkntwQWQ0RQ5MEIWJI0nWdvWVNRAV5ExXoc0b32FZYz/q8Wu5cMAq/hkOQ+znMuhPMJ9UaqdqrTsTIKohwYEx0AF4mA3vLmjw3iTk/VrVttvyNuxepYLnfnjJHV0OkbogYmiQIEUNSZbOFmpZOJsed2bFcXdd57PNDRAR4c+OsZFj3OHgFwIzbTxxos/bkgsTIKohwyNtkZGx0IIerWrB02zwzifBR6sju1ueJ9+rg2hmJrMouobiu3fE1IUkqB6p4k1RRFUOSBCFiSNpV0oSXycD42DMr0/7N4Rq2FtRz75LR+DYdgX3vwYzvq0Zfx6vIAUsTpC2QVRDh1JSEYLptuucqqALM+zl0tcCWv/PjxWMwGjT+tPqw82tS50NXu3TYFUOSBCFiyOnospFb1cKE2EC8Tcb+LziJ3a7zx88OkRjmy3UzkuDb/wWTD5x3z4kDrZ0qFyQ0GUJTXTR7ca6KCvIhNtiH3aVNnktQjZkM45bDlr8R7dXFyjmpvJ9T5vzkTnA8RI6Fki0qGBFiCJEgRAw5+8qbsNp1MhJCzuj6j/dUsL+imZ9dMBav5kLVqG76barB1/FKt6kfyqmyCiIGJiMhhPq2LkobnCSEDrYFv1Crd1uf5UcLRhHgbeLxzw85vyZ1gUpOLd7knjkKMUAShIghxW7X2V3aREKoLxEB3qd9fbfNzv9+cYjxMYGsmBIP3/4fGEww994TB3a1q0+GEWPUJ0UhBmBsdAC+XkZySho9N4m4LBh9AWx6mmBjJ3cuGMXqA9VkF9Y7vsY/AqInQ9kOFcAIMURIECKGlKL6dpo6upmSGHJG17+dXUphXTu/uGgcxuYS2PWGqjgZGHPiwN5ji6kLzn7SYsQwGQ1Mjgsmv6aNFosHj70u+E/oqIfsF7h1bgoRAd788bNDzreJUs4HdJWILcQQIUGIGFJ2lzbi721k1BlUSG3vsvLn1YeZlhzK4vFRahUEDc6/78SBHY3qE2H05FO3aIToR3p8MDo6ezx5XDdxpgqgNz6BH53cu2Q0Wwvr+fpgteNrfEMgbipU7oa2WrdNVQhnJAgRQ0ZTezcFtW1Mjg/GaDj9HI2/f5NPdUsnv7pkPFpDIex8BabdAsEJJw4s+Eb9mjrv7CctRpxgPzOpEf7sLWvCZvdQgirAol+rbtBbn+W6GUmkRvjzh08O0G2zO74meY6qvHrka/fNUwgnJAgRQ8bOkgY0NNLjT782SFWzhWfX5bM8I5ZpyWHwzf+oXJB5Pz9xYHM5VO1XnyR9zqwGiRBTEkJo67RxqLLFc5NImgVjLoT1f8bL2sIvLx7PkZo23txa7PgaLz9Ingt1R6A+331zFcIBCULEkGDptrGvvJlxMQEE+phP+/rHPz+Eza5z/7LxUHMIdr8FM38AQbHHBuk65H0FXv6QNNuFsxcjTXK4H+EBXuwobvDccV2Axb8BSyNsepoLJkYzKzWMP63OpdlZvkr8NLU1c+Rr1bhRCA+SIEQMCXvLmuiy2pmaFHra1+4rb+KdHaWsnJtCYpgfrHkEzH4w96cnDqw5BE2lahvGdPonb4TopWkaU5NCqWnp9Oxx3dgpMPFy2PQ0Wns9v1k+kfq2Lv665ojja4wmSFsIrTUqP0QID5IgRHicza6TU9JIYpgfUUGn1ydG13X+8MkBQnzNqp9GxS7Y/wHMvgv8w48NtNsgf606qhgzxbVvQIxI42MC8fMysr2owbMTWfgr1R9mw59JTwjmO1nxvLChgJJ6J4XJIsero+kF68Da5b65CnESCUKEx+VWt9BisTI1KeS0r/1yfxUb8ur4yZIxBPua4evfg08IzDmpOmrpNuhogFGLwSD/24uzZzIamJIYQkFtG3WtHuzLEjUeMq6Frc9BcwU/v2gcBg0e/fSg42s0Tf1d6GqD4o3um6sQJ5GfxsKjdF1ne1EDYf5epEb4n9a1lm4bD3+0n3HRgXxvdjLkfwO5X8D5Pz0x6dTSDIXrVWGy8FEufgdiJMtICMZk0NhZ3OjZiSz6Jeg2WPMIcSG+3LVwNB/vqWBDnpOjuMEJqgx8yVZod1LoTIhBJEGI8KjShg6qmzuZmhSKdpql0/+29gilDR08tGISJg344jcQnASz7jxxYP4alZQ6arHrJi4E4OdlYmJcEAcqmmnvsnpuIqEpMPMO2PkqVO7ljvlpJIX58eCH+5wf2U1bCAYj5K1Wf0eEcLMBBSGapi3TNO2Qpml5mqbd38fzmqZpT/Q8v1vTtKnHPVeoadoeTdNyNE3LduXkxfCXXVSPr5fxtLvlFte187dvjnDZlDjOGxUOe1apJLulD4L5uLySxmJ1JDdp1qkddIVwgaykUGy67vnVkHn/oVYAv3wAH7ORBy6dSF51K//cWOj4Gu9ASJmnjuzW5bltqkL06jcI0TTNCDwNXAxMBK7XNG3iScMuBsb0fN0B/O2k5xfpup6p6/r0s5+yOFdUNVsorG1nWnIoZuPpLcr97uP9mAwav7pkPHR3wFcPq2qQk75zbJDdrrZnfIIg6TwXz14IJczfizFRgeSUNGLptnluIn5hqpz7ka8gbzVLJkSxaFwkf16dS3WzxfF18dNUwnbearB5cDVHjEgD+ck/E8jTdT1f1/Uu4E3g8pPGXA68rCubgRBN02JPvpEQx9tSUI+P2UhGwukVDVtzsJov91fx48VjiA32hc1/heYyuPD3Jyadlu9QxxBHLwXj6dceEWKgZqSG0mW1e7axHcCM76utmS8eQNPtPHjZJLqsdv7wyQHH1xiM6u9IR6N02RVuN5AgJB4oOe770p7HBjpGB77QNG27pml3OHoRTdPu0DQtW9O07JqamgFMSwxnNS2dHKluJTMxBG+TccDXtXdZ+c37exkV6c9t56dASxV8+ycYfymkzD020NKkjuSGpUHEWJfPX4jjRQX6kBbpz87iRjqtHlwNMXnD0oegeh/sfJWUCH/uXJDG+znlfJvr5OdqWCpETVBBSFud26YrxECCkL6yBU/OYHI2Zq6u61NRWzZ3a5o2v68X0XX9WV3Xp+u6Pj0yUpqKneu2FtTjZTKQdZrHcv+8Opeyxg7++zsZKnhZ/RBYLbD0v44N0nXI/RLQYeyF6jiiEINsVmo4lm4bu0s92NgOYOIVkDhbbVF2NHDXotGkRfjz6/f20tHlJEAavVS1Ojj8mSSpCrcZSBBSCiQe930CUD7QMbqu9/5aDbyH2t4RI1h9Wxe51S1kJobgYx74Ksjesib+sb6A62cmMjM1DIq3wK7XYc6PIWL0sYG1h6E2F1Lmg+/pV2AV4kzEBPuQHO7HjqIG5ydSBpumwSWPQUc9rPkDPmYjj1yZTnF9O098nev4Ou8AGLVIJXNLJVXhJgMJQrYBYzRNS9U0zQu4DvjwpDEfAjf3nJKZDTTpul6haZq/pmmBAJqm+QMXAntdOH8xDG0tqMdk0E5rFcRm1/nlu3sI9fPi/mUTVAXUT34OQfEw/7gmdd0WlYwaEAUJM1w/eSGcmJUWTnvXEFgNic2A6bfDtuehcg/njQrnu9MTeHZdPgcqmp1clwkhiaqvTGer26YrRq5+gxBd163APcDnwAFgla7r+zRNu1PTtN6CDJ8A+UAe8BxwV8/j0cB6TdN2AVuBj3Vd/8zF70EMI7WtnRysbCYjIQQ/L9OAr3txQwF7ypp4aMVEgv3MsP1F9Wntwt+rhnS98teqKpDjLpHKqMLt4kN8SQzzI7uw3rO5IQCLfqVWAj/5Beg6v7pkAiG+Zu5/dw82u4PtFk2DscvA1q1OywgxyAb0U1rX9U90XR+r6/ooXdcf6XnsGV3Xn+n5va7r+t09z6frup7d83i+rutTer4m9V4rRq6NR+owGw3MSBl4zY78mlYe/+IQS8ZHsTw9ViXOffU7SJ0Pk648NrC+AMp3QsL0E7vnCuFGc0er1RCP1w3xC4MlD6pk092rCPHz4sEVk9hV0shz3+Y7vs4/ApLnQPUB1fRRiEEkHxWF25Q3dnCkupXpyaH4eg0sF8Rm1/n527vwNhn5w3fSVVXVL38LXa1w8R+PJZ1aO+HQJ+AXDqkLBvFdCOFcbLAvo6MC2F7U4DwR1B2yblJ1QL74NbTXc1lGLBdPjuH/vjjMocoWx9clnQeB0SpJtavNffMVI44EIcItdF1nfV4t/t5GspIGniz63Lf57Chu5OHLJxEd5ANH1kDOazD3PnWksFfeV9DZAuOXS00Q4XFzRoXTbbOztdDDPVkMBrjsL6o3zBe/RdM0fn/FZAJ9TPzH2zmOE2gNRhh/mQruD38up2XEoJEgRLhFUV07ZQ0dzEwNx8s0sP/tDle18H9fHGbZpBhWTImDrnb4908gfDTM/8WxgXVHoGIXJM5S7cmF8LDwAG8mxgaxq6SRZku3ZycTkw5zfwI5r8KRNYQHePPIlZPZW9bMX9cccXxdQKQq6V5zCKr3u2++YkSRIEQMut5VkGBfM+nxA6uO2mW18x+rdhHgY+L3V05W2zBrHoHGIrjsiWP9Ybra1TaMf4T6gSnEEDF7VDgasOnIECj+teA/IWwUfHQfdLWzbHIsl2fG8eTXuexxdpIncRYExakTZ51Otm+EOEMShIhBt6+8mZqWTuaMDsdoGFjhsP/94hB7ypr4w5XpRAR4Q9kOVZ592q3HKqPqugpAujtgwmVgHPhpGyEGW5CPmSmJIRyoaHbeu8UdzL6w4gloKIS1fwDgv1ZMIiLAm3vf3Elbp4OeMQaD+rtlt8KBf6t+TEK4kAQhYlBZum1syKslLsSHcdED65S77nANf1+Xz42zklg2OUbV/vjgbvCPgguOq4xavkMVJUtbCIExg/MGhDgLM1PD8DUbWXuoBt3TeRUp58O0lbDpaSjZSoifF3++LpPCujYe/HCf4+v8wmDMhdBQBCWb3TZdMTJIECIG1daCejq6bSwcF6W2VPpR09LJz1btYmx0AL+9tKdZ85rfqz3py59SrcoBWqsh72sIHyVFycSQ5WM2Mnd0BGWNHRyqGgLbGRf8DoIT4L0fQmcrs9PC+fGi0byzvZQPcsocXxeToRLBC76FJifjhDhNEoSIQVPf1sXO4kYmxQWrky39sPccx22xdPPk9VNVSfeCb2HjU6r645gL1EBbN+z/QDXrGr9cesOIIW1SXBDRQT6sz62ly+rh7QyfILjiGVVT54vfAHDvkjFMSw7lN+/tpbiuve/reouYeQeqv3vdHt5eEucMCULEoNB1nW8OV2M2acwdHT6ga/72zRG+OVzDb5ZPYFxMoOqE+/6PVCfcC3/Xe2OVJNdWCxMuPbFaqhBDkKZpLBwXSYvFyjZPH9kFlVM158eq6vDhzzEZDfzlukw0De5+fQeWbge1Tcw+MHGFSlA99LEc2xUuIUGIGBRHatoorG1ndlr4gMqzf5tbw/9+cYjLpsTxvdnJ6sFP/x80l8N3nj0WbJTvhIrd6gdpWNogvgMhXCcuxJcJsUFsL2qgoa3L09OBxb+BqEnwwT3QVktCqB//991M9pQ18eAHTvJDghNUk7uaw1As+SHi7EkQIlzO0m1jzcFqIgK9mZIQ0u/40oZ27n1jJ2OiAvmfq3qqoua8AbveUM3pEqargU1lqp9F+Cg5jiuGnfPHRGAyaqw+UOX5JFWTtwruLU3w7h1gt7N0YjQ/Xjyat7JLeGNrseNrE2b05Id8o7Z1hDgLEoQIl9uQV0tbl5ULJkT3eyTX0m3jR6/uwGrTeeamaWrVpPogfPwzSD4f5v+nGtjVBvveU3vSEy6TPBAx7AR4m5g/JpLShg72ljnpZOsuMZNh2X/Dka9g/f8BcN/SscwfG8mDH+wjp6Sx7+s0TTWI9AtX+SEWD3cMFsOaBCHCpUrq29ld2sTUpFBigp0no+q6zq/e28Oesib+97tTSI3wV8HGqpvV9svV/1C1P+w2FYB0d6iGdWZfN70bIVxrUlwQiWF+rMutocXTlVQBpt8Gk69ShQAL12M0aPzl2kwiA7350avbHdc3MXnBpO+AboO974J1CGwxiWFJghDhMt02O6sPVBHsa+a8Uf0no/517RHe3VHGfUvHcOGkGJXo9tHPoPYwXPW8qv2h63DoU2gsgfGXSD0QMaxpmsbSCVHous7XB6s9vy2jaaq3TFgavHMbtFYT6u/FszdPo6mjm++/nO24CZ9/OEy4HFqr4OC/JVFVnBEJQoTLbM6vo7G9mwsmRmM2Ov9f6+PdFTz2+SEuz4zjJ0vGqAe3PQ+734SF96sCZKCS3yr3qEJL0ZMG9w0I4QYhfl6cNyqc/Jo2Dle1eno6aovzmn+qbZW3bwVrF5Pignniuiz2lDXx07dysNsdBBgRo2HUEpWomr/WrdMW5wYJQoRLlNS3s72ogYyEYBLD/JyOzSlp5GercpiWHMr/XJWhElHzv1GnYcYuO9acrvqg+sEWPVEFIUKcI7ISQ4kN9uGrg1U0dQyBbZmYybDiSShaD5/+J+g6SydG8+tLJvDZvkoe++KQ42sTpkNclvrAULHLfXMW5wQJQsRZ6+iy8dneSkL9vJg3JtLp2ILaNr7/z21EBXnz7E3TVEGy+nx4+xaIGAvfeU61EW8sVr0qguNhnBQkE+cWg0Hj4smx6Dp8vq/S8UqDO2V8F+bep+qHbHsegNvPT+WGWUn8be0RXtlc1Pd1mqYKCYalwqHPVFdrIQZIghBxVnRdZ/WBKjq6bVw8OQYvk+P/pSqbLHzv+S3YdXjp1pmEB3iDpRlev04NuP4NVdGxpQr2vKNKtE++WhrTiXNSsJ+ZReOiKGvoGBpFzACWPKBWIz/9f5D/DZqm8fCKSSydEMUDH+zl37vK+77OYFRJ4wGRsO9daCp177zFsCVBiDgre8uayatuZe7ocKKclGZvbO/i5he20NTRzT9vncmoyACVUb/qZqjLg+++rD5JtdfD7rdUHYMp14KX860dIYazCbGBjI8JZHN+PeWNHZ6ejgomvvOcWpVcdRNUH8BkNPDUDVOZkRzGz1bl8M3hmr6vNXlDxrXgHQS7V6n+TkL0Q4IQccaqmy2sPVRNcrgfU5NCHY5r7bRy60vbKKxr57mbp5OeEKxagn9wF+SvUS3GU+erVZHdb4Fuh4zrjjWrE+IcpWkai8ZHEeBj4pM9FbR3WT09JbUaeeMqMPnCK9+BxhJ8zEaeXzmd0VGB3PnKdrYXOVi58fJXgYjRS/1dbh8iKzxiyJIgRJyR9i4rH+4qx9fLyLLJMQ475LZYurnlha3sLm3iyeuz1NFdXVfNs/a8DUsehKzvqcz8nNehu13tTfsPrN+MEMOdj9nIpRmxdHTZ+Hh3BbahkB8SkgTf+5eq2/PqVdBeT5CPmZdvm0lMsA83/2Mr2Y62kHxDYMp1qr5PzusSiAinJAgRp81m1/l4dwUdXTYumxLnsDdMbwCyq6SRp67P4qJJPTU+NvwFNj8Ns34E5//0uACkTa2ABMW58d0I4XnRQT4smRBNaUMH3+Y62O5wt5jJKk+roRBe/y50thIZ6M0bP5hNdJAPt7yw1XEui38EZN4AdqsEIsIpCULEafs2t4bShg6WTIgm2kEeSPNxKyBP3ZDFxemx6olNT8PqB1XC6UV/gM7m41ZArlOnYYQYgSbGBZGVFMLO4kb2lw+Bsu6gGkVe/Q8o26ECka42YoJ9eOOOY4HI1gIHAUZA1HGByGsSiIg+SRAiTsvu0kZ2FjeSlRTCxLigPsdUt1i47u+bewKQqSybfFwA8vmvYOLlcOUz0FEPO15R5dinXC8BiBjx5o2JJCHUl68OVFHa0O7p6SgTLoOrnoPiTfCaCkSig3x4847ZamvmhS18daCq72sDoiDzRpXntfMVaK5w79zFkCdBiBiwvOoWvj5YTWqEP/Md1AMprG3j6r9torCujX+snMGyyT1bMJv+qgKQCSvgqn+oUs87X1E/nDJvlC0YIQCjQePSjDiCfM18uKuc2tZOT09JmXyVOjVTvBFevxa62ogK8uHtH57H2OhA7nhlO29nl/R9bUAkZN0EBrNaEZHOu+I4EoSIASlr7ODTPZXEBPlwSXoshj664+4pbeLqZzbS2mnl9R/MZsHYSJWEuvZ/4PNfqgDk6hegoQh2vaGy76feBIHRHnhHQgxNvl5GrsiKx2ww8P7OMpqHQqM7gPSrVSBStAFevgLa6wkP8Ob1H8xmzqhwfvHObv66Nq/vfjh+Yervum+ISkiv2u/u2YshSoIQ0a/a1k4+yCkjyNfM5ZnxfRYk+3h3Bdf8fSPeJiNv33kemYkhKjv+k5/D2j+o7ZarevaW974DfhE9P5QcH+0VYqQK9jVzRVY8XTY77+8sc9xEzt3Sr1Z9Zipy4IVl0FRKgLeJf9wyg8sz4/jjZ4f4xTu76bT2MV/vQMj8nlr13P8BFHwrTe+EBCHCuZqWTt7ZXorZYOCKrHh8vYwnPG+36/zpy8Pc/foOJsYG8f7dc3sKkXXCO7eq8s9z7oXLnoTcL+DI16oQUuaNqqaAEKJPkYHeXJYRR1N7N+/sKB0aNUQAJq6A770LLRXwjwuh+iBeJgN/+m4m9y4ZwzvbS7nhuS3UtPSxlWT2UQnoMelQuB72vaeKFooRS/N4K+k+TJ8+Xc/Ozvb0NEa86hYL7+4ow2TQuGpqAqH+Xic832Lp5j/f2c2neyu5eloCj1w5GW+TUZVdf+t7ULoVLvw9TL0F9r8PTWWqEV3K+dILRogBKqpr48OcckL8zFw1LcHhkXi3q9yjaoh0d6ht1jEXAGpV9D/eziHMz4tnbppGRkLIqdfqOpRsVcUKA6JUyXdZFT2naZq2Xdf16ac8LkGI6EtVswpAzEaNq6clEOJ3YgCyt6yJu1/fQWlDB7+8eDy3n5+qCpaV7YA3bwRLI1zxN/WJ58C/1TG98cshaoJn3pAQw1hJffvRLdHvTE0gwHuIBCKNxfDmDVC5Fy74L7XqqWnsLWvijpezqWnt5FeXTGDlnJS+CxrWHVFbM+iqUWXUeLe/BeEeEoSIASusbePjPRX4mI1cPS2BYF/z0ed0XeeVzUX8/qMDhAd48eT1WUxPCVNP5rwBH90H/lFw7atgaYCiTSo7fuKVUgVViLNQUt/Oh7vK8TEbuSIzTjWAHAq62uD9u9RqZ/o1cOmfwTuAxvYufv72LlYfqOaiSdH88aopBPuZT72+o1Fd21wB8dNg1GJpWnkOkiBEDMie0ia+PlhNeIAXl2fGEehz7IdGVbOF+/+1mzWHalg0LpL//W4mYf5e0NmqElB3vQHJ58Ol/wdFG6GlEuIyYfRSMPbxw0cIcVoqmyx8kFOGTde5LCOOxLAh0uBR1+Hbx+HrRyB8FFz9IsRmoOs6/1hfwKOfHiQiwJv/uTpDnZo7md2mtmZKtqlqqxMug8AY978PMWgkCBFO2e06G4/Usa2wnpQIPy5Jj1X5HajVj/dzynjwg3102ez8v2XjueW8FHVMt2IXvH0rNBTAvF9A2gIVgBjNqiW4LK8K4VJN7d18sKuMxvZulk6Idlg00CMK1sG7d0B7ncoHm3kHaBq7Sxv52apd5FW3cv3MRH69fGLfW0p1R+DQJ9DVDslz1JfBeOo4MexIECIcau+y8tneSorq2slICGbRuKijdUCK69p56N/7+PpgNVOTQnj8mimkRQaojPZv/1d9+UfCxf+jKqA2V0DEGBWAeAd4+J0JcW6ydNv4aHcFJfXtTEkMZv6YSEzGIXLYsa1Wbc/kfg5pC+Gyv0BoCpZuG3/68jDPfptPbJAPD66YxIUTo0/NFenugNwvoWqf2sodcxGEJHrkrQjXkSBE9KmssYNPdldg6baxaHwUk+KC0DSNTquNv3+Tz9Nr8jAZNH56wVhunZuK0aBB2Xb44B6o3q8qKY5bDnW5YPaD0UsgaqKcfhFikNnsOhvyatle1EB0kA/L02P7zrnwBF2H7H/Alw+q3y99EGb8AAwGthfV86t393KoqoXF46N46LJJJIX3sa1Uc1gd6+9sgdgMSFsEXkNk+0mcNglCxAlsdp2tBfVsLagnyNfE8oxYogJ9sNt1Pt5TwWOfH6K4vp3lGbH8dvlEYoJ9VAOqNY9A9gsQEA3n3QO6TX1yiZ8GKfNUHQAhhNvkVbfyxf5KABaMjWRibFDfJ1E8obFEJavnrVY/Iy7+IyRMp9tm558bC/nTl4fptuvcNjeVHy0cdUISPKBWXIvWq1wRoxmS56r7SOLqsCNBiDiqutnC5/urqG3pZEJsIAvHReFjNrLxSC2PfnqQ3aVNjI8J5NfLJzBvTCTYrCrwWPOI+lQy+UqImgxWC4QkqdUPSSITwmOa2rv5fF8lZY0dpEb4s2RC1AlJ5R6l67B7FXz5W9Uzasr1sPQhCIyhssnCHz87yHs5ZQT7mrln0Wi+NzsZH/NJeSBttarQYd0R8AmC1PkQNQkMQ2QLSvRLghBBp9XG1oJ6dhQ14udlZPGEKNIi/NmQV8cTX+eytaCeuGAffnbhOK7MiseIDvvehTV/gPojED8dRi0EzaQy2EcthrA02XoRYgjQdZ2ckkY25NWiaRpzR0eQER/cZ58nj+hsgXWPw+a/gsGkklbn/gT8wthX3sSjnx7k29xaogK9uWN+GjfOSj6lQjMNhSoYaakCv3BIPk+CkWFCgpARzG7X2V/RzMYjtbR12pgUF8ScUeF8m1vLs9/ms7O4kZggH364II3rZybhY0QVGPvmf1TeR1gapMxXWzD+EfIXX4ghrLG9i68OVFNc3054gBcLxkaSHD6EWiTU58Oa/1aN7LwC4Ly7YNad4BfGxrxanvg6l8359YT7e3Hr3BRumJWsSgH00nWoOaQa6bVWq6Z4iTMhOh1MXg5fVniWBCEjkK7rHKlpY3N+HTUtncSF+JCVFMqag9W8vKmIssYOEkJ9uXPBKK6ZnoC3vVO12t70lPrEERQPSXNUEBIYrY7LRYyT4EOIIa737/63uTU0tneTEuHH7LRwYoN9PT21Y6oPwNr/VhVTTb6Q9T0VkISlsa2wnie/zmPd4Rq8TQauyIznljkpJx5H1nWoy1PBSHMFmLwhdgrET5US8EOQBCEjiN2uc6SmlS0F9dS0dBLsa8LHbGTTkTo+319Fl9XO7LQwbp2bytIJ0RjrDsP2f8Ku16GjQQUdsZnqqG3EWEiYoXI/ZNtFiGHFarOTU9JIdlEDHV02ksP9mJUWTlywz9BJXq0+oD747F6l2juMuRCmrYTRF5Bb28GLGwt5d0cplm47UxKCuWZ6Iisy4wjqzXnRdWgug9JstUKi2yE0RZ2oiRgrhRKHCAlCRgBLt4195U3sKmmisb2Ljm4bda1dbMqvo6LJQrCvmSuz4rl2RiITQmyw/0NV5bR4kyoIFDEe4rIgcrz6CxybIZ8ohDgHdFnt7C49FoxEB/kwJTGYcdGBQ6e+SEslbH0Odr6iElgD4yDzBki/hsaANN7dUcaq7BIOVrbgbTKweHwUl2bEsXh81LHcEUszVO6Git1gaVKrIxFjVc+q0BQpfOZBEoSco+x2nZKGdg5UtHCospnCunZqWjrJq26lstmC2agxf0wkV2TFc0GqFz4FX6lk07zV6lOHX7jaS42fqkqsR0+G0FTZchHiHNRltXOgopldpY3UtXbh62VkfEwgE2KDiAr0HhqrI7ZuOPwZbH9JJaHqdvVzafJ30MctZ29nDO/sKOXjPZXUtnbi52Vk4bhIFo+PZuG4SCICvNXqSGOR6vRbe1gd9TX7Qvho9RWWqgIU4TYShJxD7HadssYODle1sD63ltzqViqaOihr7MDSbcfLZGDuqHAunhzNxZH1BJaug4P/VkXGdDt4B/asdkxR5+6jJqp+D7JsKcSIoOs6JfUd7C5rJL+mDZtdJzzAizFRgYyK9CdyqAQkLVWqud2ed6B0q3osLA3GXowtbTHb7GP58EATq/dXUd3SiaZBRnwws9PCmZUWxrTkMIK9NNVWovqAOuXXbVErIkHxqhJrSJL6vfz8G1QShAxzLZZuDlW2sDm/jm2FDRTWtVHRaKHLZgcgJdyPuWkhrIhpIMu2G6/i9VCyBTqb1Q38IyF8DCRMV0XFIsdCcKIsTwoxwlm6beRWtXKgopnypg50HQJ9TKRF+pMU5kdCqN+pdTs8oalMrZAc+hQKvgFbFxjMkDgLPWk2xb4T+awxntXFKg+m26Zj0GBCbBCzUlVQkpkQRJS9Bq3+iEq+b61WqyYGIwTGqqAkOFH9XqqzupQEIcOIzWbnUFUrW/Lr2FXayOGqVsobO2js6D46ZmyogSviGpjvW8Aoay6+DYehNg9snWqAVyCEJqu8juR5EDcFQpKln4sQwqG2TisFtW0cqWmltKGDLqsdTYPIQG/ign2JCfYhLtiXIF+TZ1dKutpVLlv+WvVVtVet8gKEJGGLnUqx30S2dabwRW0I60rtdFnV82H+XkyMDWJiXBCTo7yZHNBCsrEWY3OJWnnpvY93oCpLEBB17FffUEnQP0MShAwxNrtOVZOFg5XN7K9o4UhNK8V1bVQ0Waht66LLaseIjUStmuk+FUzzr2GSdw0JWjXBHSUY26qBnv92Rm+10hGS2LPFcr76NShWlhiFEGfEZtepbLZQXNdOaUM71S2dR/8h9zIZCPf3Iszfi/AAb8L9vQgP8CLA20PBSVeb6uhdtl19lW6HpuKjT+t+4bQGpFJhTuSwLZbtbZFsagiiyBpKBz6YjRqJoX6khpnJCGxjtF8bSV6txBibCKEFc+9bMphUXRLf0ON+7fnyDpKVZSfOKgjRNG0Z8BfACDyv6/qjJz2v9Tx/CdAOrNR1fcdAru3LcA1CrDY7jR3dNLR1UdfaRXWLheqWTiqbLFQ0WahstlDX3IG1owmvzjrCaSJeqyVWqydGqyfO1EyMsYVwQyshejO+1iY0jvvvoxnBJxiC4tS+aNREdZolJl0VEZNEKyHEILHbdWrbOqlq6qS2tZO6ti7qWjtp77IdHeNlMhDkYyLAx0Sgt5lAHxOBPupXf28TvmYj3iaDe6q4tlarwKT2cM9Xrvq1reaEYV3mYBrMUVRrERRbQ8m1BFNuDaBBD6ROD6IJfwK8TST46yT5WYj37iTG3EG4sQ0/E/iajfiYDepX/0DMvkFqFcUroOdXf9Xc0+zT8+v/b+9+Y+So6ziOvz8zs3u7d9CWQkm0LRYVUYJ/QAIowSdAgkhowiNI/BN8QEgE0WhEJPGRzzQqCUZDABMDgQeICTEoYvQpiIKIgJIGAxxgLKmU9nq7s7Pz9cHMtUdp6YK9/ZXe55VMZmd2ZvPd393ufO43v5nrN/dFWWX//+YdhxBJOfAscBEwDzwKXBkRTy/b5hLgOpoQcg5wc0ScM8m+B7ISIaSsanYPK8qq6ZYbjMYslhWD4ZDRcJFyNGQ0HDIqB1TlkHE1oCpLxlXJcLBIWZaMhkNitADlAlm1SFbtIR8vUowHFPWAbj1kRiV9SuYYMKcBx7DILENmNaSvkhlKMg7S5nm3+cXtrW1CxZqNzWVlx3+guUnY8R9s0rfTtpkdIRbLMa/uHrJjoWTHnpLdg4pdg4pdg9EbAsoSCXqdnF6R0e/m9Do53Tyjk2d0ioxOrn3LeUa3EJ08o8gzcoksg1wiz0SWiUx60/q37I3Zs6MJJK89Dzvnm3uM7Jxvxpy8Pt/cK+kAxuTs0rHsih476x4L9BhEl5KCipxRFIwRyjK6uehlQTerUV6QZQVZ0czzvCAvCrJOn+j2iGIWij7qzqJOj6wzQ9adJe/MUCzNOx06nQ5FUVAUBVn7mnnRQVlOXnTI8hxlRXN8yApQ1kxo32Mp2emkg4WQSaLY2cC2iHiufaF7gK3A8iCxFfhFNInmYUnrJL0H2DLBvlPxp7u/x5nbbmGWmoyajGjmh+vnkTVTALUKxtkMddEnOrNkMyeS948l660l661pQkZ/LfTXN9fCr9vcjNeY2+BLY83sXaXfzdm8fpbN6988kHM0rveGkj2jisVyzOJo3P4RWLM4GrNrUDEa1+0Ue0/5/D8yiUyQZWqOu2jvsVeAdAJiA9JZsAa0VnufK+pF+uVr9KrX6Jf/pTfaQW+0k5lyBzOj1+lUC6ytdrO+XCCvdlNUO5gZL9Ad76Eb7Zi8AMbtNHpzfZOKgBoR7bT/44o3Ph/sO6Dte7ysP11Lj5fPtXf7l/sf4hM3PPjOC34HJgkhG4EXly3P0/R2HGqbjRPuC4Ckq4GrAU466aQJynp7Nmw5nRe2fxKyglCB8jYt5h2UFSjvkOUdsqJDlnfbeUHe6TIz06PT7VLkXbJen7w7R94/FnWOgZm5ZhBo2/WmTq9J44f9HZiZvbt08ozj5rocNzf5/3SJCEbj2BtMyjacjKqaOoI6gnFNO483zOtoxrLUdTBulyOiOeAGBMFS539EkxWWno92o4geQXOTxmHAoN1nadu3orqiqBbIxwOyumymcUlel2T1aO86VQOiGlJXQ6hKNC5hPCLqcTtVUNdEXZHVI6grVFfNPMZkUaGoyajI6jFiTBZjFDUQKGoUQVt1u559zy9N7XtWu92wf+LEP6fDZZIQcqC+gv1/EgfbZpJ9m5URtwK3QnM6ZoK63pZTz78czr/8cL+smZkdRpLoFqJbuFd4NZgkhMwDm5ctbwJennCb7gT7mpmZ2So0SdR8FDhF0smSusAVwP37bXM/8EU1zgV2RsQrE+5rZmZmq9Ahe0IiopJ0LfAgzWW2d0TEU5KuaZ//GfAAzZUx22gu0b3qrfZdkXdiZmZm7yq+WZmZmZmtqINdouuRP2ZmZpaEQ4iZmZkl4RBiZmZmSTiEmJmZWRIOIWZmZpaEQ4iZmZkl4RBiZmZmSTiEmJmZWRIOIWZmZpbEEXnHVEnbgedT17FCTgBeTV3EEcDt0HA7uA2WuB0aboejsw3eFxEb9l95RIaQo5mkPx/o1rWrjduh4XZwGyxxOzTcDqurDXw6xszMzJJwCDEzM7MkHEKm79bUBRwh3A4Nt4PbYInboeF2WEVt4DEhZmZmloR7QszMzCwJh5CEJH1TUkg6IXUtKUj6vqR/SPqbpF9JWpe6pmmRdLGkf0raJunbqetJQdJmSX+U9IykpyRdn7qmVCTlkh6X9OvUtaQiaZ2ke9vvhGckfSp1TSlI+nr7efi7pLsl9VLXtJIcQhKRtBm4CHghdS0JPQScHhEfA54Fbkxcz1RIyoGfAJ8FTgOulHRa2qqSqIBvRMRHgHOBr6zSdgC4HngmdRGJ3Qz8NiI+DHycVdgekjYCXwXOiojTgRy4Im1VK8shJJ0fAd8CVu2gnIj4XURU7eLDwKaU9UzR2cC2iHguIkrgHmBr4pqmLiJeiYjH2se7aA46G9NWNX2SNgGfA25LXUsqktYAnwFuB4iIMiJeS1pUOgXQl1QAs8DLietZUQ4hCUi6DHgpIp5IXcsR5MvAb1IXMSUbgReXLc+zCg++y0naApwBPJK4lBR+TPMHSZ24jpTeD2wHft6elrpN0lzqoqYtIl4CfkDTQ/4KsDMifpe2qpXlELJCJP2+Pae3/7QVuAn4buoap+EQ7bC0zU00XfN3pat0qnSAdau2R0zSMcAvga9FxOup65kmSZcC/4mIv6SuJbECOBP4aUScASwAq26slKTjaHpFTwbeC8xJ+nzaqlZWkbqAo1VEXHig9ZI+SvML9oQkaE5BPCbp7Ij49xRLnIqDtcMSSV8CLgUuiNVzvfg8sHnZ8iaO8i7Xg5HUoQkgd0XEfanrSeA84DJJlwA9YI2kOyPiqD7wHMA8MB8RSz1h97IKQwhwIfCviNgOIOk+4NPAnUmrWkHuCZmyiHgyIk6MiC0RsYXmw3fm0RhADkXSxcANwGURsSd1PVP0KHCKpJMldWkGnt2fuKapU5PCbweeiYgfpq4nhYi4MSI2td8FVwB/WIUBhPb770VJp7arLgCeTlhSKi8A50qabT8fF3CUD9B1T4ildAswAzzU9go9HBHXpC1p5UVEJela4EGa0e93RMRTictK4TzgC8CTkv7arvtORDyQriRL6DrgrjaYPwdclbieqYuIRyTdCzxGc4r6cY7yu6f6jqlmZmaWhE/HmJmZWRIOIWZmZpaEQ4iZmZkl4RBiZmZmSTiEmJmZWRIOIWZmZpaEQ4iZmZkl4RBiZmZmSfwP+0LbLkueKmsAAAAASUVORK5CYII=\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Variance between baseline and follow-up for low-attenuation plaques\n", "data = {\n", " \"placebo\": {\n", " # Baseline\n", " \"mu_b\": 0.8,\n", " \"sd_b\": 1.5,\n", " \"lbl_b\": \"Placebo at Baseline\",\n", " # Follow-up\n", " \"mu_e\": 1.6,\n", " \"sd_e\": 1.8,\n", " \"lbl_e\": \"Placebo at Follow-up\",\n", " },\n", " \"treatment\": {\n", " # Baseline\n", " \"mu_b\": 1.9,\n", " \"sd_b\": 1.8,\n", " \"lbl_b\": \"IPE at Baseline\",\n", " # Follow-up\n", " \"mu_e\": 1.6,\n", " \"sd_e\": 1.7,\n", " \"lbl_e\": \"IPE at Follow-up\",\n", " },\n", "}\n", "fig, ax = plt.subplots(figsize=(9,6))\n", "for n, arm in enumerate(data.values()):\n", " x_base = np.arange(-5, 9, 0.1)\n", " y_base = norm.pdf(x_base, arm[\"mu_b\"], arm[\"sd_b\"])\n", " ax.plot(x_base,y_base, color=F\"C{n}\", alpha=0.5, label=arm[\"lbl_b\"])\n", " x_end = np.arange(-5, 9, 0.1)\n", " y_end = norm.pdf(x_base, arm[\"mu_e\"], arm[\"sd_e\"])\n", " ax.plot(x_end,y_end, color=F\"C{n}\", label=arm[\"lbl_e\"])\n", "ax.legend(loc=\"best\", frameon=False)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There is a clear and unambiguous worsening of the placebo group that _exceeds_ any improvement in the treatment arm. The placebo was chosen because its physical properties, as a mineral oil, made it indistiguishable from the treatment, but could it have inadvertantly made patients in that group worse-off?\n", "\n", "There are other concerns we could consider ([1](https://twitter.com/ProfDFrancis/status/1300678237857689601?s=20), [2](https://twitter.com/ProfDFrancis/status/1301516307163209730?s=20), [3](https://twitter.com/ProfDFrancis/status/1299988896470753281?s=20)), however, at this stage how confident do you feel that the study shows what it claims to show? That the new treatment is better than the current best alternative?\n", "\n", "You can have a look at how others are reviewing the paper at [PubPeer](https://pubpeer.com/publications/C08A4CC251DF18B8FB7C3DEECB0124#). There is also comment on [Medscape](https://www.medscape.com/viewarticle/936924):\n", "\n", "> In an interview, Steven Nissen, MD, who is chair of cardiovascular medicine at the Cleveland Clinic, Cleveland, Ohio, and has been among the critics of the mineral oil placebo, also questioned the plaque progression over the 18 months. \"I've published more than dozen regression/progression trials, and we have never seen anything like this in a placebo group, ever,\" he said. \"If this was a clean placebo, why would this happen in a short amount of time?\"\n", "\n", "Domain experts are expressing doubts, but you didn't need to be one to evaluate this paper.\n", "\n", "#### Review: Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure\n", "\n", "Our second paper is a collaboration between 36 researchers:\n", "\n", "> _Packer Milton, Anker Stefan D., Butler Javed et al., 2020. ``Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure'', New England Journal of Medicine, August 2020. [dop:10.1056/NEJMoa2022190](https://sci-hub.tw/10.1056/NEJMoa2022190)_\n", "\n", "As before, lets review the abstract before diving into the body of the paper:\n", "\n", "> __Background:__ Sodium–glucose cotransporter 2 (SGLT2) inhibitors reduce the risk of hospitalization for heart failure in patients regardless of the presence or absence of diabetes. More evidence is needed regarding the effects of these drugs in patients across the broad spectrum of heart failure, including those with a markedly reduced ejection fraction.\n", "> \n", "> __Methods:__ In this double-blind trial, we randomly assigned 3730 patients with class II, III, or IV heart failure and an ejection fraction of 40% or less to receive empagliflozin (10 mg once daily) or placebo, in addition to recommended therapy. The primary outcome was a composite of cardiovascular death or hospitalization for worsening heart failure.\n", "\n", "Here we have a double-blinded trial with a much larger sample population: 3,730 patients, and we would expect about 1,850 patients in each group. Once again, the treatment molecule - _empagliflozin_ - is the only factor differentiating the two groups which continue to receive the standard recommended therapy.\n", "\n", "Recording of a __primary outcome event__ - the main measurement data - is cardiovascular death _or_ hospitalisation as a result of a worsening of their heart condition. This is a heart-related study and is conditional on heart-related event data.\n", "\n", "> __Results:__ During a median of 16 months, a primary outcome event occurred in 361 of 1863 patients (19.4%) in the empagliflozin group and in 462 of 1867 patients (24.7%) in the placebo group (hazard ratio for cardiovascular death or hospitalization for heart failure, 0.75; 95% confidence interval [CI], 0.65 to 0.86; P<0.001). The effect of empagliflozin on the primary outcome was consistent in patients regardless of the presence or absence of diabetes. The total number of hospitalizations for heart failure was lower in the empagliflozin group than in the placebo group (hazard ratio, 0.70; 95% CI, 0.58 to 0.85; P<0.001). The annual rate of decline in the estimated glomerular filtration rate was slower in the empagliflozin group than in the placebo group (–0.55 vs. –2.28 ml per minute per 1.73 m2 of body-surface area per year, P<0.001), and empagliflozin-treated patients had a lower risk of serious renal outcomes. Uncomplicated genital tract infection was reported more frequently with empagliflozin.\n", "\n", "The time-frame of the trial was not fixed, so the authors report a median time-frame for a primary outcome event of 16 months. They report differences between treatment and control for a variety of different patient outcomes, all indicating that treatment improves patient outcomes.\n", "\n", "Treatment has a side-effect.\n", "\n", "> __Conclusions:__ Among patients receiving recommended therapy for heart failure, those in the empagliflozin group had a lower risk of cardiovascular death or hospitalization for heart failure than those in the placebo group, regardless of the presence or absence of diabetes.\n", "\n", "All in all, a good outcome for the hypothesis that empagliflozin should be prescribed to patients at risk of heart failure. Given your experience with the IPE paper, how reliable are these claims?\n", "\n", "The study endpoint is not stated in so many words, but we can derive it. Instead of fixing a time period for the study, as in the IPE paper, here the endpoint is either cardiovascular death or heart failure hospitalisation - i.e. a coronory-related event.\n", "\n", "The objective of any study is to __limit confounding variables__. If the purpose of a study is to measure the effectiveness of a new treatment on patient outcomes then the most important thing to measure is patient outcomes. Setting an arbitrary time-limit may mean that healthcare events fall outside the measurement period and aren't recorded. This will bias the results.\n", "\n", "Death is the hardest of endpoints, but not all patients will die. Most patients receiving treatment will get better (or, at least, be able to manage their conditions), although they are at high risk of hospitalisation given the nature of heart failure. So hospitalisation becomes a _soft_ endpoint. \n", "\n", "This ensures the study _will_ end (otherwise, waiting for all patients to die would make the study unhelpfully long). It also massively reduces the sample size we'd need to ensure a statistically valid result. The absolute number of people who die will be significantly less than the number who are hospitalised. From a patient's perspective, death is certainly the worst outcome, but frequent hospitalisation is life-altering. By including these two events in the study, the number of patients recruited can be reduced, and your chance of getting people to participate improves (imagine recruiting people with the promise the study ends only when they die).\n", "\n", "By removing confounding variables, the study authors improve their opportunity to record a meaningful result. From a research perspective, they increase the _statistical power_ of their result on a smaller sample.\n", "\n", "You could argue, why not include all-cause mortality? What happens if the treatment causes some catastrophic side-effect unrelated to heart failure? Such occurrances are _notifiable events_. They trigger a review regardless. The authors included the side-effect of genital tract infection, so it's not as if such things are being ignored, they are just not a primary outcome event.\n", "\n", "On page 3 of the report, _Statistical Analysis_, the authors state: \"We determined that a target number of 841 adjudicated primary outcome events would provide a power of 90% to detect a 20% lower relative risk of the primary outcome in the empagliflozin group than in the placebo group at a two-sided alpha level of 0.05. Assuming an annual incidence of the primary outcome of at least 15% per year in the placebo group and a recruitment period of 18 months, we established a planned enrollment of 2850 patients, with the option of increasing the enrollment to 4000 patients if the accumulation of primary outcome events was slower than expected.\" The entirety of this section is worth reading to see how they estimated results which may require early termination of the study as well.\n", "\n", "Next, what is the __event rate ratio__; the ratio of the number of events in the treatment group divided by that in the control group:\n", "\n", "$$ \\frac{n_t}{n_c} \\approx 0.8 $$\n", "\n", "This is sanity-checking rather that specific accuracy. Use the event-related percentages and mentally divide 19.4/24.7 (or 20/25). We're studying people sampled from a general population with all its variability. You're looking for a clear signal of efficacy. These approaches to quick 'n dirty mental arithmetic help you read the paper fluidly and test whether conclusions stated in the text are reasonable.\n", "\n", "Reading further, you see the __hazard ratio__ for a primary outcome event is 0.75 which is close to our sanity-check approximation of 0.8.\n", "\n", "Let's review the study groups:\n", "\n", "![Primary and secondary cardiovascular outcomes](images/module-1-lesson-2-packer-et-al-table-2.jpg)\n", "\n", "Unlike in the IPE paper, we are not presented specifically with a standard deviation. The hazard ratio is a mean (or average) ratio of the difference between the two groups and the range is at a 95% confidence interval.\n", "\n", "We can't chart a mean and standard deviation for the baseline and endpoint stages of the treatment and control groups because those data are not given. The endpoint for the IPE study was a time-period, with measurement of the change in volume of coronary plaques. You could then measure plaques in each of the groups at the beginning and end of the trial.\n", "\n", "In the empagliflozin study, the baseline is that none of the participants are either dead or in hospital. This is binary. Inclusion required them to be not one of these end-points. Therefore there's no value in assessing these groups separately. We must conduct our assessment on the variation between the groups on conclusion of the study.\n", "\n", "Similarly, these endpoints are far easier to quantify. There's no risk from measurement error in quantifying the volume of a plaque. A patient either is, or is not dead or in hospital at the end of their participation. Much less chance of ambiguity in that result.\n", "\n", "We know that 70% of patients (one standard deviation) experienced a hazard ratio of between 0.65 and 0.86, the indication of the ratio of how likely either group was to experience a primary outcome event.\n", "\n", "If there were no difference between the two groups then the hazard ratio would be 1. The ratio is treatment to placebo. As the ratio shifts towards zero, patients experience less and less risk than patients in the control group. If it were greater than 1, then those in the placebo group have more favourable outcomes.\n", "\n", "They draw this in the following figure:\n", "\n", "![Primary Outcome in Prespecified Subgroups](images/module-1-lesson-2-packer-et-al-figure-2.jpg)\n", "\n", "They've saved us some trouble on chart drawing. These are called box-plots and they summarise data showing the middle range of 50% of the data (the \"box\" part of the plot) and then an uppper and lower \"whisker\" which capture the rest of the data to give a visual idea of data distribution in a small space. In this chart, the size of the boxes have been scaled to represent the size of the groups represented by the ratio. That is clear in something like _age_ where most participants are above the age of 65.\n", "\n", "This figure also gives a clear view of variance along the hazard ratio continuum. Patient outcome improvement is unambiguous.\n", "\n", "Slightly beyond the theory covered in this lesson, but: how do you tell if the effect measured wasn't entirely due to chance?\n", "\n", "The $p$-value will be introduced in future lessons but it is a measure of the probability that the hypothesis is wrong (that the _null hypothesis_ is true). The smaller the p-value, the less likely such an event would be true. The authors state that $p < 0.001$ which is very low.\n", "\n", "However, we can ask questions about blinding and about whether the endpoint matters. Would changes to these criteria effect the outcome of the study?\n", "\n", "In _Effect of Study Design on the Reported Effect of Cardiac Resynchronization Therapy_ Jabbour, et al considered whether _observational_, _randomised but unblinded_ or _randomised and blinded_ trials influenced study findings \\cite{jabbou_effect_2015}.\n", "\n", "They summarise their findings as follows:\n", "\n", "![Meta‐analyses of effects on physiological variables](images/module-1-lesson-2-jabbour-et-al-table-2.jpg)\n", "\n", "This figure is similar to the empagliflozin study, presented with similar mean and distribution ranges. The charts used here are _violin plots_, a subtle variation on the box plot.\n", "\n", "It should be obvious that the key approach is not the choice of endpoint, but the study approach. Randomisation __with__ blinding is key. Observational studies are no better than unblinded studies (for the clinical trials anyway) ... The authors didn't test double-blinding, so only the patients weren't aware of their treatment status. It would have been interesting to see this study done with an included double-blind group.\n", "\n", "Our analysis - with the skills learned to this point - can only take us so far. As with the IPE study, we're not questioning the values themselves reported in the study, merely if they're internally consistent and if the textual analysis is aligned to the reported data.\n", "\n", "In the IPE study, the authors claimed that the groups were the same at baseline and changed over the duration of the study. This was not aligned with their own data.\n", "\n", "In the empagliflozin study, the data and analysis are aligned, and - from a review perspective - their assumptions, data and analysis are better presented.\n", "\n", "There's more we could consider. For instance, are the side-effects of treatment predictable? If you considered the way empagliflozin works (described in the paper) you may be able to work this out.\n", "\n", "There has been less online review of this paper (and less controversy), but you can keep an eye on [PubPeer](https://pubpeer.com/publications/EDCC039D6043B1F1D8EAF6613A3F7A) and read Prof Francis' [public review](https://twitter.com/ProfDFrancis/status/1299639170969862144?s=20).\n", "\n", "__Concluding__ our review of randomisation and blinding in the papers, how do you feel about each? Does either paper feel as if it has a solid foundation in reliance on randomisation and blinding into its two treatment groups? Which paper would you be more comfortable recommending, if any?\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.4 Presentation: charting measurement distribution to support analysis\n", "\n", "
\n", "Illustrate core analysis with histograms and box plots.\n", "
\n", "\n", "The objective of a published journal article is to support persuasion of the authors' peers of the validity of their work. The easier you make that, the more likely it is to be read, and the more persuasive it will be.\n", "\n", "Where a reader comes away confused or hesitant then the work has failed. A reason why authors may deliberately reduce the clarity of their presentation is precisely because they lack confidence in their conclusions.\n", "\n", "Well-designed charts and tables make any differences between data and conclusions obvious. They are not only an aid to understanding for the reader, but a meaningful part of the analytical process for the researchers. The IPE paper has no charts, while the empagliflozin does. The latter also includes a better description of methods and assumptions.\n", "\n", "Clarity is key to validation.\n", "\n", "Histograms and scatter charts are useful for analysis, but they are also bulky and presenting them in a way that aids comparisons is difficult. The charts we saw used in the empagliflozin and study design papers are a form of distribution chart. \n", "\n", "Here's how you can draw them. We'll use _Seaborn_, an extension to Matplotlib that offers shortcuts to standardised statistical charts, and a more modern design. If you haven't already installed it, `pip install seaborn` will do the job.\n", "\n", "Seaborn has a repository of [sample data](https://github.com/mwaskom/seaborn-data) which we will use for demonstrating the various functions. We're not going to analyse these data. They are useful only for demonstration. In future lessons, we'll use these charts along with case study data." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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HVVZWJo/Ho7feektZWVlJmg64cHy1IwAY4k4Xl6QNGzZo69atQ557/PHHNX/+fOMdAReGO10AMMQP0gDAENEFAENEFwAMEV0AMER0AcDQfwAeGWiZ2BR+8wAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Import Seaborn, and sample data to demonstrate a box plot\n", "# https://seaborn.pydata.org/generated/seaborn.boxplot.html#seaborn.boxplot\n", "\n", "import seaborn as sns\n", "sns.set(style=\"whitegrid\")\n", "# Load our sample data ... we're not going to analyse it\n", "tips = sns.load_dataset(\"tips\")\n", "ax = sns.boxplot(x=tips[\"total_bill\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A __box plot__ is a standardised way of displaying a statistical distribution based on a five-number summary:\n", "\n", "- __minimum__: the lowest data point _excluding any outliers_\n", "- __maxiumum__: the largest data point, excluding any outliers\n", "- __median ($Q_2$ / 50th percentile)__: the middle value of the dataset\n", "- __first quartile ($Q_1$ / 25th percentile)__: the _lower quartile $q_n(0.25)$_, or median of the lower half of the dataset\n", "- __third quartile ($Q_3$ / 75th percentile)__: the _lupper quartile $q_n(0.75)$_, or median of the upper half of the dataset\n", "- __interquartile range (IQR):__ the distance between the upper and lower quartiles\n", "\n", "$$ IQR = Q_3 - Q_1 = q_n(0.75) - q_n(0.25)$$\n", "\n", "The box plot itself is constructed of two parts, the box spanning the IQR, and a set of whiskers indicating the minimum and maximum. There are variations here:\n", "\n", "- whiskers can represent 1.5 x the IQR range (i.e. not the 'real' maximum/minimum)\n", "- one standard deviation above and below the mean\n", "\n", "Any data observations which fall outside this maximum and minimum range are presented as points. These are the __outliers__. These extreme measurements offer a range of insight:\n", "\n", "- identifying the extent of skewness in the distribution\n", "- identifying data collection or entry errors\n", "- providing insight into unusual or interesting properties of the data\n", "\n", "Box plots are extremely concise ways of presenting data and permit comparisons between quite complex observations." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax = sns.boxplot(x=\"total_bill\", y=\"day\", hue=\"smoker\",\n", " data=tips, palette=\"Set3\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you want to go further and show the observation distribution on the box plots, you can combine a _swarm plot_ with a box plot. The _swarm_ points will have jitter associated so their values on the chart are not directly meaningful, but it does give a sense of how the measurements were distributed amongst the bins in the histogram, as well as the relative positioning of the outliers." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax = sns.boxplot(x=\"day\", y=\"total_bill\", data=tips)\n", "ax = sns.swarmplot(x=\"day\", y=\"total_bill\", data=tips, color=\".25\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "__Violin plots__ are similar to the box plot. Unlike a box plot, in which all of the plot components correspond to actual datapoints, the violin plot features a kernel density estimation of the underlying distribution.\n", "\n", "As before, we'll use sample data from Seaborn to demonstrate how to draw them." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Import Seaborn, and sample data to demonstrate a violin plot\n", "# https://seaborn.pydata.org/generated/seaborn.violinplot.html#seaborn.violinplot\n", "\n", "import seaborn as sns\n", "sns.set(style=\"whitegrid\")\n", "# We're using the same dataset\n", "tips = sns.load_dataset(\"tips\")\n", "ax = sns.violinplot(x=tips[\"total_bill\"])" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Comparison of nested groupings by two categorical variables\n", "ax = sns.violinplot(x=\"total_bill\", y=\"day\", hue=\"smoker\",\n", " data=tips, palette=\"muted\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These approaches to presenting data distributions encourage engagement and support review of the means, standard deviations and variances presented in your tables. Not everyone finds it easy to read a table of numbers and instantly tell how they relate to each other. \n", "\n", "If you have a strong point to make, reinforce it with these and learn how to read them. If you want to make a claim that two randomised sample distributions are the same and can physically see they look different on a chart, then you really need to review your analysis or assumptions.\n", "\n", "Ultimately, it is for journal authors to make their case to others, not for everyone else to simply agree. The case-studies here took years of research and measurement to produce. It takes seconds to create a set of easy-to-read pleasant-looking charts that vastly improve understanding of what can be a complex and data-intensive study.\n", "\n", "If you have a strong set of research results to present, reinforce it with good presentation, don't undermine it by burying detail in the text.\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.5 Lesson summary\n", "\n", "[Ethics](#2.1-Ethics:-privacy,-anonymity-and-permission): Research is performed by moral agents undertaking activities which may effect moral subjects such that their rights - both positive and negative - must be considered within the context of legal and moral means and ends. \n", "\n", "Researchers, particularly those working with human subjects, have a duty of care towards their stakeholders that arises from rights they, or their stakeholders, may hold. There are seven criteria against which we may assess moral subject participation in research:\n", "\n", "- Social and clinical value\n", "- Scientific validity\n", "- Fair subject selection\n", "- Favourable risk-benefit ratio\n", "- Independent review\n", "- Informed consent\n", "- Respect for potential and enrolled subjects\n", "\n", "[Curation](#2.2-Curation:-data-acquisition-and-management): The data management process is there to support data collection, but it is the responsibility of the data scientist to sanity check data going in. There are physical and technical limits to measurements and you need to have a comprehensive understanding of your research domain to ensure that measurements reflect reality.\n", "\n", "- Ensure there is a data owner who is responsible for the data lifecycle, including publication and responding to feedback or queries;\n", "- Prepare a data-collection plan, ensuring that definitions and data structure conform to international standards;\n", "- Ensure metadata are agreed with stakeholders and are useful and standardised;\n", "- Ensure that data are appropriately licensed to ensure release and reuse;\n", "- Test all systems using structured and controlled synthetic data to ensure everything works predictably;\n", "\n", "Randomisation of the sample selection process is critical to ensure representation and avoid accidentally introducing bias. There are five factors to consider:\n", "\n", "- Controlling\n", "- Randomisation\n", "- Replication\n", "- Blocking\n", "- Blinding\n", "\n", "[Analysis](#2.3-Analysis:-sampling-methods-with-synthetic-data): We start any analysis by exploring our data to understand its shape, distribution and variance. The mean is a measure of the centre of the distribution of a data series. This is written as $\\bar{x}$ or $\\mu$ (mu) and is the sum of all of the observations divided by the number of observations. These distributions can be normal, where the observations are symmetric about the central axis, or they can be skewed. The distance of an observation from its mean is its deviation. The standard deviation is defined as the square root of the variance.\n", "\n", "Peer review is the process of subjecting scholarly research, work or ideas to the scrutiny of others who, ordinarily, are drawn from amongst the producer's peers.\n", "\n", "[Presentation](#2.4-Presentation:-charting-measurement-distribution-to-support-analysis): A box plot is a standardised way of displaying a statistical distribution based on a five-number summary. If you have a strong set of research results to present, reinforce it with good presentation, don't undermine it by burying detail in the text.\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.6 Exercises\n", "\n", "Conduct your own peer review on any of the publications listed here:\n", "\n", "- _Eghbal MJ, Haeri A, Shahravan A, et al. Postendodontic Pain after Pulpotomy or Root Canal Treatment in Mature Teeth with Carious Pulp Exposure: A Multicenter Randomized Controlled Trial. Pain Res Manag. 2020;2020:5853412. Published 2020 Jun 30. [doi:10.1155/2020/5853412](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7345601/)_\n", "- _Kjærgaard J, Stensballe LG, Birk NM, et al. Lack of a Negative Effect of BCG-Vaccination on Child Psychomotor Development: Results from the Danish Calmette Study - A Randomised Clinical Trial. PLoS One. 2016;11(4):e0154541. Published 2016 Apr 28. [doi:10.1371/journal.pone.0154541](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4849633/)_\n", "\n", "As your skills develop, you will gain confidence in ever-deeper review but, for now, focus on randomisation and distribution.\n", "\n", "You are also welcome to conduct your own review. There are a host of publication repositories which support redistribution of published research. Here are a few and you can explore them to run your own reviews:\n", "\n", "- [Pubmed](https://www.ncbi.nlm.nih.gov/pmc/) US National Library of Medicine National Institutes of Health\n", "- [PubPeer](https://pubpeer.com/) for post-publication peer review\n", "- [SciHub](https://en.wikipedia.org/wiki/Sci-Hub) for open access research publication\n", "\n", "If you're searching, remember to use the American spelling for _randomization_.\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# References\n", "\n", "(Budoff, Bhatt et al., 2020) Budoff Matthew J., Bhatt Deepak L., Kinninger April et al., ``_Effect of icosapent ethyl on progression of coronary atherosclerosis in patients with elevated triglycerides on statin therapy: final results of the EVAPORATE trial_'', European Heart Journal, vol. , number , pp. , August 2020. [online](https://academic.oup.com/eurheartj/advance-article/doi/10.1093/eurheartj/ehaa652/5898836)\n", "\n", "(Packer, Anker et al., 2020) Packer Milton, Anker Stefan D., Butler Javed et al., ``_Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure_'', New England Journal of Medicine, vol. 0, number 0, pp. null, August 2020. [online](https://sci-hub.tw/10.1056/NEJMoa2022190)\n", "\n", "(Maslin and Wallace, 2018) Maslin Douglas and Wallace Marc, ``_Cutaneous larva migrans with pulmonary involvement_'', Case Reports, vol. 2018, number , pp. bcr, February 2018. [online](https://casereports.bmj.com/content/2018/bcr-2017-223508)\n", "\n", "(Baggini and Fosl, 2007) Julian Baggini and Peter Fosl, ``_The Ethics Toolkit_'', 2007. [online](http://www.blackwellpublishing.com/)\n", "\n", "(Kramer, Guillory et al., 2014) Kramer Adam D. I., Guillory Jamie E. and Hancock Jeffrey T., ``_Experimental evidence of massive-scale emotional contagion through social networks_'', Proceedings of the National Academy of Sciences, vol. 111, number 24, pp. 8788--8790, June 2014. [online](https://www.pnas.org/content/111/24/8788)\n", "\n", "(Shaw, 2015) Shaw David, ``_Facebook’s flawed emotion experiment: Antisocial research on social network users:_'', Research Ethics, vol. , number , pp. , May 2015. [online](https://journals.sagepub.com/doi/10.1177/1747016115579535)\n", "\n", "(Vickers, Kramer et al., 2006) Vickers Andrew J., Kramer Barry S. and Baker Stuart G., ``_Selecting patients for randomized trials: a systematic approach based on risk group_'', Trials, vol. 7, number 1, pp. 30, October 2006. [online](https://doi.org/10.1186/1745-6215-7-30)\n", "\n", "(Emanuel, Wendler et al., 2000) Emanuel Ezekiel J., Wendler David and Grady Christine, ``_What Makes Clinical Research Ethical?_'', JAMA, vol. 283, number 20, pp. 2701--2711, May 2000. [online](https://jamanetwork.com/journals/jama/fullarticle/192740)\n", "\n", "(Chait, 2014) Gavin Chait, ``Technical assessment of open data platforms for national statistical organisations'', World Bank Group, number: , December 2014. [online](https://openknowledge.worldbank.org/handle/10986/21111)\n", "\n", "(Downey, 2014) Allen B. Downey, ``_Think Stats 2 - Exploratory Data Analysis in Python_'', 2014. [online](https://greenteapress.com/wp/think-stats-2e/)\n", "\n", "(Vu and Harrington, 2020) Julie Vu and David Harrington, ``_Introductory Statistics for the Life and Biomedical Sciences_'', July 2020. [online](https://www.openintro.org/book/biostat/)\n", "\n", "(Dahmen and Cook, 2019) Dahmen Jessamyn and Cook Diane, ``_SynSys: A Synthetic Data Generation System for Healthcare Applications_'', Sensors (Basel, Switzerland), vol. 19, number 5, pp. , March 2019. [online](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427177/)\n", "\n", "(Dietz, Barr et al., 2015) David M Dietz, Christopher D Barr and Mine Çetinkaya-Rundel, ``_OpenIntro Statistics_'', 2015. [online](https://www.openintro.org/)\n", "\n", "(Crane and Martin, 2018) Crane Harry and Martin Ryan, ``_In peer review we (don't) trust: How peer review's filtering poses a systemic risk to science_'', Researchers.One, vol. , number , pp. , September 2018. [online](https://www.researchers.one/article/2018-09-17)\n", "\n", "(Brembs, 2019) Brembs Björn, ``_Reliable novelty: New should not trump true_'', PLoS Biology, vol. 17, number 2, pp. , February 2019. [online](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372144/)\n", "\n", "(Stern and O’Shea, 2019) Stern Bodo M. and O’Shea Erin K., ``_A proposal for the future of scientific publishing in the life sciences_'', PLoS Biology, vol. 17, number 2, pp. , February 2019. [online](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372143/)\n", "\n", "(Jabbou, Shun‐Shin et al., 2015) Jabbou Richard J., Shun‐Shin Matthew J., Finegold Judith A. et al., ``_Effect of Study Design on the Reported Effect of Cardiac Resynchronization Therapy (CRT) on Quantitative Physiological Measures: Stratified Meta‐Analysis in Narrow‐QRS Heart Failure and Implications for Planning Future Studies_'', Journal of the American Heart Association, vol. 4, number 1, pp. e000896, May 2015. [online](https://www.ahajournals.org/doi/10.1161/JAHA.114.000896)\n", "\n" ] } ], "metadata": { "cite2c": { "citations": { "8093550/388QBQUZ": { "URL": "http://www.blackwellpublishing.com/", "author": [ { "family": "Baggini", "given": "Julian" }, { "family": "Fosl", "given": "Peter" } ], "issued": { "date-parts": [ [ 2007 ] ] }, "publisher": "Blackwell Publishing", "title": "The Ethics Toolkit", "type": "book" }, "8093550/9MWH8GTX": { "DOI": "10.1136/bcr-2017-223508", "URL": "https://casereports.bmj.com/content/2018/bcr-2017-223508", "abstract": "Douglas Maslin, Marc Wallace. 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