Increased Dynamic SDCCH Trial Report

数据挖掘技术在药品不良反应监测中的应用【摘要】在临床药品使用中，经常会受到一些不良反应的影响，导致患者生命安全受到威胁，因此，应当合理使用现代化数据挖掘技术，对其进行全面监测，创新技术形式，将ADR监测工作作为重点内容，制定完善的呈报系统，在全面预测的情况下，融入电子医疗记录形式，提高监测工作可靠性与有效性。

【关键词】数据挖掘技术；药品不良反应；监测措施对于数据挖掘技术而言，主要就是在数据库中，提取一些隐藏与未知信息数据，明确信息的规则情况，创建多种类型的模式。

当前，我国已经将数据挖掘技术应用在ADR监测工作中，能够及时发现药物不良反应问题，采取有效措施对其进行处理，在深层次改革的情况下，做好各类管理工作。

一、数据挖掘技术在ADR自发呈报系统中的应用分析在ADR自发呈报系统实际运行的过程中，相关人员应当合理应用数据挖掘技术，为医师与药师等提供良好的报告形式，在数据库中开展信息收集工作，在自发呈现的情况下，对报告内容进行改善。

然而，在报告数量逐渐增加的情况下，数据库信息结果越发庞大，使用传统方式开展分析工作，会出现一些困难，不能保证工作效率，难以提高工作成效。

因此，相关部门应当合理使用数据挖掘技术，筛选最佳监测方式，利用比值失衡测量技术与关联规则技术等，提高工作成效。

（一）比值失衡测量技术的应用此类方式是基于传统测量方式改革的产物，能够对数据库中可疑药物ADR进行计算，获取相关药物比值，一旦计算结果超出阈值范围，就可以认为药物与ADR之间产生一定的联系。

在使用此类方式期间，应当明确目标药物的ADR数据信息，对其他药物ADR信息进行处理，在二者之间相互对比的情况下，建立专门的数量分析机制，以便于完成相关工作任务，达到预期的管理目的。

在实际研究中，可以利用PRR方式对其进行处理，主要使用的公式为：其中，a主要为目标药物的ADR数据，b为目标药物的其他ADR数据，c为其他药物的ADR数据，d为其他药物的其他ADR数据。

药品生产实验室数据完整性管理的研究作者：徐敏尹晨辉来源：《科技创新与应用》2016年第16期摘要：参考国内外有关药品生产数据完整性的文献，对实验室数据完整性管理进行了简单的研究，对欧盟进行数据完整性检查的背景进行了讨论。

作者认为数据完整性是药品质量管理的需要，是日益增加的监管意识的需要，是行业选择的需要。

认识到这一点才能保证生产出符合法律法规的药品。

关键词：药品生产；数据完整性；研究分析2016年2月22日，成都欧康Chengdu Okay Pharmaceutical Co.， Ltd，EU GMP现场检查未能通过，再一次将数据完整性这一概念推上风口浪尖。

为应对接二连三发生的数据完整性的缺陷，2015年1月Medicines and healthcare products regulatory agency（MHRA）特地推出了一份行业指南指导药品生产企业完善数据完整性——GMP数据完整性定义和行业指南（GMP Data Integrity Definitions and Guidance for Industry）并在2015年三月进行了修订[1]。

而实验室数据完整性是现阶段现场检查的重点，所以我们要完善实验室数据完整性。

1 数据完整性的要求MHRA认为数据完整性由 ALCOA系统构成。

A是可追溯性（attributable to the person generating the data），L是清晰的和可永久保存的（legible and perm-anent），C是同步的（contemporaneous），O是原始记录（或真实“复制”）original（o-r 'true copy'），A是准确的（accurate）[1]。

1.1 可追踪到产生数据的人为了追踪到产生数据的人，我们需要了解数据的产生，数据是从原始数据获得或者派生出的信息（例如：分析报告结果）[1]。

实验室里的数据一般分为人工观察到的纸质数据和计算机系统的电子数据。

随机对照研究报告质量评价工具随机对照研究报告质量评价工具引言：随机对照研究（Randomized Controlled Trial，简称RCT）作为一种重要的研究设计方法，被广泛应用于医学、心理学、社会科学等领域中。

随机对照研究的目标是通过随机分组将研究对象分为试验组和对照组，并对两组进行比较，以评估干预措施的疗效。

然而，为了确保研究结果的可靠性和可信度，随机对照研究报告的质量评价显得尤为重要。

本文将介绍一种常用的随机对照研究报告质量评价工具，以帮助研究人员更好地评价研究报告的质量。

一、随机对照研究报告质量评价工具的背景随机对照研究报告的质量评价是在原始研究文章的基础上进行的，主要目的是判断研究报告是否具备一定的科学性和方法学的可靠性。

随着随机对照研究的持续增加，研究人员也逐渐意识到对研究报告的质量评价至关重要。

因此，一种科学、全面、客观的评价工具应运而生。

二、随机对照研究报告质量评价工具的内容1. 研究设计首先，我们需要评价随机对照研究报告中的研究设计部分。

该部分主要包括研究的目的、研究设计类型（如平行设计、交叉设计等）、研究对象、样本量计算、随机化方法等内容。

评价时需要注意是否有清晰的研究问题和假设、研究对象的选择是否合理、样本量是否足够等。

2. 干预措施和对照组设计其次，我们需要评价随机对照研究报告中的干预措施和对照组设计部分。

干预措施的评价需要关注干预的性质、干预的剂量和强度等。

对照组设计的评价需要关注对照组的选择方式、对照组的特点和可比性等。

3. 数据收集和分析再次，我们需要评价随机对照研究报告中的数据收集和分析部分。

数据收集的评价需要关注数据来源和数据采集工具的可靠性和有效性。

数据分析的评价需要关注统计方法的选择是否合理、是否存在选择性报告等。

4. 结果呈现和讨论最后，我们需要评价随机对照研究报告中的结果呈现和讨论部分。

结果呈现的评价需要关注是否全面、客观地呈现了研究结果。

讨论的评价需要关注对结果的解释是否合理、是否考虑了研究的局限性等。

数据挖掘技术在药品不良反应监测中的应用进展摘要：药物是用于临床诊断、治疗和保健的物品，在治疗疾病方面起着双重作用，同时也可能导致不良反应，例如一系列化学疗法，可导致害虫防治、减少血液贫困和肝功能损害。

合理用药直接关系到病人的健康安全，因此对于加强药物管理至关重要。

反应不良的药物效果是一种有害的反应，在药物应用中不会发生，它通过收集关于药物有害影响的报告，然后进行进一步分析，以确定临床药物的潜在风险，从而有助于降低药物的易受伤害性，从而在提高医疗质量方面发挥重要作用。

现代数据挖掘技术在监测有害影响方面具有更好的应用，并使人们能够发现药物反应不规则的情况，找出问题并采取有效的干预措施。

本文主要讨论数据挖掘技术在药品有害影响监测中的应用。

关键词：数据挖掘；药品不良反应监测；自发呈报系统；主动监测引言数据挖掘(DM)是一个过程，在此过程中，潜在有用的知识会自动从大型、模糊且干扰性的随机数据中选择。

复杂，医学上广泛应用的算法很多。

在药物监测(ADR)中更常用。

ADR的监测技术近年来一直致力于提高监测报告的数量和质量，扩大监测网络，逐步将监测系统从被动监测发展为ADR的主动监测。

本文介绍了DM技术应用ADR监控的情况，为ADR监控提供了有意义的指导。

1、DM与ADR监测的概述自1960年前后在伊斯兰会议组织发生的事件以来，各国产生了许多不利影响，从建立监测报告制度到建立特别监测制度，再到药物概念，这些都表明ADR 监测日益成熟。

1980年前后，我国开始在北京、沥青、粥等地监测广告遵守情况(ADR)。

1999年至2019年，我们的国家ADR监测网络共收到150万报告员的1.519亿份报告，其中包括近480 000份新的严重ADR报告，占同期的31.5%。

在这些情况下，解决办法主要是应用独立的报告系统检测ADR信号。

该系统尽管存在缺陷，但却是目前普遍使用的、经济上可行的ADR信号传播工具。

近年来，各国发现ADR信号的方式已从被动监测演变为主动监测，并开发了一系列主动监测系统，为药物安全提供了新的思路。

药物临床试验期间安全性数据快速报告常见问答（版本号：1.0 ）药品审评中心2019年4月前言2018年1月25日原国家食品药品监督管理总局发布了《关于适用国际人用药品注册技术协调会二级指导原则的公告》，要求“自2018年5月1日起，药物临床研究期间报告严重且非预期的药品不良反应适用《E2A:临床安全数据的管理：快速报告的定义和标准》《Ml：监管活动医学词典(MedDRA)》和《E2B ( R3 ):临床安全数据的管理：个例安全报告传输的数据元素》”。

2018年4月27日药品审评中心发布了《药物临床试验期间安全性数据快速报告的标准和程序》，进一步明确了我国药物临床试验期间非预期严重不良反应（SUSAR）快速报告的重点内容和报告途径。

本问答文件是在上述基础上，对于我国药物临床试验期间安全性数据快速报告实施以来部分共性问题的统一解释和澄清，供申请人/ CRO 参考和遵循。

随着快速报告工作的逐步完善，本问答文件后续也将不断进行增补和更新，在使用过程中，需注意采用最新的版本。

目录█快速报告的范围 (3)█快速报告的时限 (6)█提交方式 (7)█关于购买第三方服务 (8)█Gateway账户申请及测试 (8)█申请人之窗与XML格式文件 (9)█E2B数据元素相关要求 (11)█破盲与阳性对照药、安慰剂报告问题 (11)█受理号填写 (13)█MedDRA词典 (14)█其它潜在严重安全性风险信息 (14)█咨询途径和方法 (15)快速报告的范围Q1. 《药物临床试验期间安全性数据快速报告的标准和程序》（以下简称《标准和程序》）中第一条“申请人获准开展药物(包括中药、化药及生物制品)临床试验后，对于临床试验期间发生的所有与试验药物肯定相关或可疑的非预期且严重的不良反应都应向国家药品审评机构进行快速报告”。

此处的药物包含范围是什么？疫苗是否包含在内？A1. 此处的药物包含与注册申请有关的中药、化药、生物制品。

中国循证医学杂志2021年2月第21卷第2期多臂平行对照随机临床试验报告规范：CONSORT2010声明扩展版魏旭煦\刘岩\胡嘉元\蒋寅\商洪才\张弛\段玉婷2’3，卞兆祥2,3，译1.北京中医药大学东直门医院（北京100700)2.香港浸会大学中医药学院（中国香港999077)3.中国E Q U A T O R中心（中国香港999077)•方法学•• 231 •【摘要】背景随机对照临床试验的报告质量欠佳。

当今，提高研究透明度至关重要，不充分的报告影响了对试验结果的可靠性和有效性的评估。

临床试验报告的统一标准（Consolidated Standards of Reporting Trials, CONSORT)2010声明是为提升随机对照临床试验的报告质量而制定的，但其最初关注的是两组平行对照试验。

多臂试验常采用多个平行组设计方案，将试验者以相同概率随机分配至其中一个治疗组，比较多种干预措施的效 应，但以三组或者更多的组别为常见。

多臂试验的报告质量差异很大，使得对结果的判断和解释变得困难。

尽管 CONSORT2010声明的大部分内容同样适用于多臂试验，但其中一些要素需要修改，并且在某些情况下还有额外的问题需要澄清。

目的推出CONSORT2010声明的多臂试验报告扩展版，以便于此类试验的报告。

设计2014年CONSORT工作组会议后，成立了一个包括所有作者的指南撰写工作组。

工作组在2014年至2018年间，每两个月进行会面或电话会议，并通过电子邮件进行交流，讨论并制定了修订清单及其相关文本。

草稿随后发给了包含36人的CONSORT工作组及另外5名在临床试验领域的知名专家，以供他们审阅。

14人提供了详细的反馈意 见，工作组经过详细考虑，形成了扩展版的最终修订版。

结果 C O N SO R T声明多臂试验扩展版，扩展了 CONSORT2010清单中的10个条目，并提供了良好的报告示例及对每个扩展条目重要性的详尽解释。

Strengthening the Reporting of Observational Studies in Epidemiology(STROBE):Explanation and ElaborationJan P.Vandenbroucke1,Erik von Elm2,3,Douglas G.Altman4,Peter C.Gøtzsche5,Cynthia D.Mulrow6,Stuart J.Pocock7, Charles Poole8,James J.Schlesselman9,Matthias Egger2,10*for the STROBE Initiative1Department of Clinical Epidemiology,Leiden University Medical Center,Leiden,The Netherlands,2Institute of Social&Preventive Medicine(ISPM),University of Bern,Bern, Switzerland,3Department of Medical Biometry and Medical Informatics,University Medical Centre,Freiburg,Germany,4Cancer Research UK/NHS Centre for Statistics in Medicine,Oxford,United Kingdom,5Nordic Cochrane Centre,Rigshospitalet,Copenhagen,Denmark,6University of Texas Health Science Center,San Antonio,United States of America,7Medical Statistics Unit,London School of Hygiene and Tropical Medicine,London,United Kingdom,8Department of Epidemiology,University of North Carolina School of Public Health,Chapel Hill,United States of America,9Department of Biostatistics,University of Pittsburgh Graduate School of Public Health,and University of Pittsburgh Cancer Institute,Pittsburgh,United States of America,10Department of Social Medicine,University of Bristol,Bristol,United KingdomFunding:The initial STROBEworkshop was funded by theEuropean Science Foundation(ESF).Additional funding was received from the Medical Research Council Health Services Research Collaboration and the National Health Services Research& Development Methodology Programme.The funders had no role in study design,data collection and analysis,decision to publish,or preparation of the manuscript. Competing Interests:The authors have declared that no competing interests exist.Citation:Vandenbroucke JP,von Elm E,Altman DG,Gøtzsche PC,Mulrow CD,et al.(2007)Strengthening the Reporting of Observational Studies in Epidemiology(STROBE):Explanation and Elaboration.PLoS Med4(10):e297.doi:10.1371/journal.pmed. 0040297Received:July20,2007 Accepted:August30,2007 Published:October16,2007 Copyright:Ó2007Vandenbroucke et al.This is an open-access article distributed under the terms of the Creative Commons Attribution License,which permits unrestricted use,distribution,and reproduction in any medium,provided the original author and source are credited.In order to encourage dissemination of the STROBE Statement,this article is freely available on the Web site of PLoS Medicine,and will also be published and made freely available by Epidemiology and Annals of Internal Medicine.The authors jointly hold the copyright of this article.For details on further use,see STROBE Web site(http://www./). Abbreviations:CI,confidence interval;RERI,Relative Excess Risk from Interaction;RR,relative risk; STROBE,Strengthening the Reporting of Observational Studies in Epidemiology*To whom correspondence should be addressed.E-mail:strobe@ispm. unibe.chMuch medical research is observational.The reporting of observational studies is often of insufficient quality.Poor reporting hampers the assessment of the strengths and weaknesses of a study and the generalisability of its results.Taking into account empirical evidence and theoretical considerations,a group of methodologists,researchers,and editors developed the Strengthening the Reporting of Observational Studies in Epidemiology(STROBE)recommen-dations to improve the quality of reporting of observational studies.The STROBE Statement consists of a checklist of22items,which relate to the title,abstract,introduction,methods, results and discussion sections of articles.Eighteen items are common to cohort studies,case-control studies and cross-sectional studies and four are specific to each of the three study designs.The STROBE Statement provides guidance to authors about how to improve the reporting of observational studies and facilitates critical appraisal and interpretation of studies by reviewers,journal editors and readers.This explanatory and elaboration document is intended to enhance the use,understanding,and dissemination of the STROBE Statement.The meaning and rationale for each checklist item are presented.For each item,one or several published examples and,where possible,references to relevant empirical studies and methodological literature are provided.Examples of useful flow diagrams are also included. The STROBE Statement,this document,and the associated Web site(http://www. /)should be helpful resources to improve reporting of observational research.P L o S MEDICINEIntroductionRational health care practices require knowledge about the aetiology and pathogenesis,diagnosis,prognosis and treat-ment of diseases.Randomised trials provide valuable evi-dence about treatments and other interventions.However, much of clinical or public health knowledge comes from observational research[1].About nine of ten research papers published in clinical speciality journals describe observatio-nal research[2,3].The STROBE StatementReporting of observational research is often not detailed and clear enough to assess the strengths and weaknesses of the investigation[4,5].To improve the reporting of obser-vational research,we developed a checklist of items that should be addressed:the Strengthening the Reporting of Observational Studies in Epidemiology(STROBE)Statement (Table1).Items relate to title,abstract,introduction, methods,results and discussion sections of articles.The STROBE Statement has recently been published in several journals[6].Our aim is to ensure clear presentation of what was planned,done,and found in an observational study.We stress that the recommendations are not prescriptions for setting up or conducting studies,nor do they dictate methodology or mandate a uniform presentation. STROBE provides general reporting recommendations for descriptive observational studies and studies that investigate associations between exposures and health outcomes. STROBE addresses the three main types of observational studies:cohort,case-control and cross-sectional studies. Authors use diverse terminology to describe these study designs.For instance,‘follow-up study’and‘longitudinal study’are used as synonyms for‘cohort study’,and ‘prevalence study’as synonymous with‘cross-sectional study’. We chose the present terminology because it is in common use.Unfortunately,terminology is often used incorrectly[7] or imprecisely[8].In Box1we describe the hallmarks of the three study designs.The Scope of Observational ResearchObservational studies serve a wide range of purposes:from reporting afirst hint of a potential cause of a disease,to verifying the magnitude of previously reported associations. Ideas for studies may arise from clinical observations or from biologic insight.Ideas may also arise from informal looks at data that lead to further explorations.Like a clinician who has seen thousands of patients,and notes one that strikes her attention,the researcher may note something special in the data.Adjusting for multiple looks at the data may not be possible or desirable[9],but further studies to confirm or refute initial observations are often needed[10].Existing data may be used to examine new ideas about potential causal factors,and may be sufficient for rejection or confirmation. In other instances,studies follow that are specifically designed to overcome potential problems with previous reports.The latter studies will gather new data and will be planned for that purpose,in contrast to analyses of existing data.This leads to diverse viewpoints,e.g.,on the merits of looking at subgroups or the importance of a predetermined sample size.STROBE tries to accommodate these diverse uses of observational research-from discovery to refutation or confirmation.Where necessary we will indicate in what circumstances specific recommendations apply.How to Use This PaperThis paper is linked to the shorter STROBE paper that introduced the items of the checklist in several journals[6], and forms an integral part of the STROBE Statement.Our intention is to explain how to report research well,not how research should be done.We offer a detailed explanation for each checklist item.Each explanation is preceded by an example of what we consider transparent reporting.This does not mean that the study from which the example was taken was uniformly well reported or well done;nor does it mean that itsfindings were reliable,in the sense that they were later confirmed by others:it only means that this particular item was well reported in that study.In addition to explanations and examples we included Boxes1–8with supplementary information.These are intended for readers who want to refresh their memories about some theoretical points,or be quickly informed about technical background details.A full understanding of these points may require studying the textbooks or methodological papers that are cited.STROBE recommendations do not specifically address topics such as genetic linkage studies,infectious disease modelling or case reports and case series[11,12].As many of the key elements in STROBE apply to these designs,authors who report such studies may neverthelessfind our recom-mendations useful.For authors of observational studies that specifically address diagnostic tests,tumour markers and genetic associations,STARD[13],REMARK[14],and STRE-GA[15]recommendations may be particularly useful.The Items in the STROBE ChecklistWe now discuss and explain the22items in the STROBE checklist(Table1),and give published examples for each item.Some examples have been edited by removing citations or spelling out abbreviations.Eighteen items apply to all three study designs whereas four are design-specific.Starred items(for example item8*)indicate that the information should be given separately for cases and controls in case-control studies,or exposed and unexposed groups in cohort and cross-sectional studies.We advise authors to address all items somewhere in their paper,but we do not prescribe a precise location or order.For instance,we discuss the reporting of results under a number of separate items,while recognizing that authors might address several items within a single section of text or in a table.The ItemsTITLE AND ABSTRACT1(a).Indicate the study’s design with a commonly used term in the title or the abstract.Example‘‘Leukaemia incidence among workers in the shoe and boot manufacturing industry:a case-control study’’[18]. ExplanationReaders should be able to easily identify the design that was used from the title or abstract.An explicit,commonly used term for the study design also helps ensure correct indexing of articles in electronic databases[19,20].Table1.The STROBE Statement—Checklist of Items That Should Be Addressed in Reports of Observational StudiesItemnumberRecommendationTITLE and ABSTRACT1(a)Indicate the study’s design with a commonly used term in the title or the abstract(b)Provide in the abstract an informative and balanced summary of what was done and what was foundINTRODUCTIONBackground/rationale2Explain the scientific background and rationale for the investigation being reportedObjectives3State specific objectives,including any prespecified hypothesesMETHODSStudy design4Present key elements of study design early in the paperSetting5Describe the setting,locations,and relevant dates,including periods of recruitment,exposure,follow-up,and data collection Participants6(a)Cohort study—Give the eligibility criteria,and the sources and methods of selection of participants.Describe methods offollow-upCase-control study—Give the eligibility criteria,and the sources and methods of case ascertainment and control selection.Givethe rationale for the choice of cases and controlsCross-sectional study—Give the eligibility criteria,and the sources and methods of selection of participants(b)Cohort study—For matched studies,give matching criteria and number of exposed and unexposedCase-control study—For matched studies,give matching criteria and the number of controls per caseVariables7Clearly define all outcomes,exposures,predictors,potential confounders,and effect modifiers.Give diagnostic criteria,if applicableData sources/ measurement 8*For each variable of interest,give sources of data and details of methods of assessment(measurement).Describe comparability of assessment methods if there is more than one groupBias9Describe any efforts to address potential sources of biasStudy size10Explain how the study size was arrived atQuantitativevariables11Explain how quantitative variables were handled in the analyses.If applicable,describe which groupings were chosen,and whyStatistical methods 12(a)Describe all statistical methods,including those used to control for confounding(b)Describe any methods used to examine subgroups and interactions(c)Explain how missing data were addressed(d)Cohort study—If applicable,explain how loss to follow-up was addressedCase-control study—If applicable,explain how matching of cases and controls was addressedCross-sectional study—If applicable,describe analytical methods taking account of sampling strategy(e)Describe any sensitivity analysesRESULTSParticipants13*(a)Report the numbers of individuals at each stage of the study—e.g.,numbers potentially eligible,examined for eligibility,confirmed eligible,included in the study,completing follow-up,and analysed(b)Give reasons for non-participation at each stage(c)Consider use of a flow diagramDescriptive data 14*(a)Give characteristics of study participants(e.g.,demographic,clinical,social)and information on exposures and potential confounders(b)Indicate the number of participants with missing data for each variable of interest(c)Cohort study—Summarise follow-up time(e.g.,average and total amount)Outcome data15*Cohort study—Report numbers of outcome events or summary measures over timeCase-control study—Report numbers in each exposure category,or summary measures of exposureCross-sectional study—Report numbers of outcome events or summary measuresMain results16(a)Give unadjusted estimates and,if applicable,confounder-adjusted estimates and their precision(e.g.,95%confidence interval).Make clear which confounders were adjusted for and why they were included(b)Report category boundaries when continuous variables were categorized(c)If relevant,consider translating estimates of relative risk into absolute risk for a meaningful time periodOtheranalyses17Report other analyses done—e.g.,analyses of subgroups and interactions,and sensitivity analysesDISCUSSIONKey results18Summarise key results with reference to study objectivesLimitations19Discuss limitations of the study,taking into account sources of potential bias or imprecision.Discuss both direction and magnitude of any potential biasInterpretation20Give a cautious overall interpretation of results considering objectives,limitations,multiplicity of analyses,results from similar stu-dies,and other relevant evidenceGeneralisability21Discuss the generalisability(external validity)of the study resultsOTHER INFORMATIONFunding22Give the source of funding and the role of the funders for the present study and,if applicable,for the original study on which the present article is based*Give such information separately for cases and controls in case-control studies,and,if applicable,for exposed and unexposed groups in cohort and cross-sectional studies.Note:An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting.The STROBE checklist is best used in conjunction with this article(freely available on the Web sites of PLoS Medicine at /,Annals of Internal Medicine at /,and Epidemiology at /).Separate versions of the checklist for cohort,case-control,and cross-sectional studies are available on the STROBE Web site at http://www. /.doi:10.1371/journal.pmed.0040297.t0011(b).Provide in the abstract an informative and balanced summary of what was done and what was found. Example‘‘Background:The expected survival of HIV-infected patients is of major public health interest.Objective:To estimate survival time and age-specific mortal-ity rates of an HIV-infected population compared with that of the general population.Design:Population-based cohort study.Setting:All HIV-infected persons receiving care in Denmark from1995to2005.Patients:Each member of the nationwide Danish HIV Cohort Study was matched with as many as99persons from the general population according to sex,date of birth,and municipality of residence.Measurements:The authors computed Kaplan–Meier life tables with age as the time scale to estimate survival from age 25years.Patients with HIV infection and corresponding persons from the general population were observed from the date of the patient’s HIV diagnosis until death,emigration,or 1May2005.Results:3990HIV-infected patients and379872persons from the general population were included in the study, yielding22744(median,5.8y/person)and2689287(median, 8.4years/person)person-years of observation.Three percent of participants were lost to follow-up.From age25years,the median survival was19.9years(95%CI,18.5to21.3)among patients with HIV infection and51.1years(CI,50.9to51.5) among the general population.For HIV-infected patients, survival increased to32.5years(CI,29.4to34.7)during the 2000to2005period.In the subgroup that excluded persons with known hepatitis C coinfection(16%),median survival was38.9years(CI,35.4to40.1)during this same period.The relative mortality rates for patients with HIV infection compared with those for the general population decreased with increasing age,whereas the excess mortality rate increased with increasing age.Limitations:The observed mortality rates are assumed to apply beyond the current maximum observation time of10 years.Conclusions:The estimated median survival is more than35 years for a young person diagnosed with HIV infection in the late highly active antiretroviral therapy era.However,an ongoing effort is still needed to further reduce mortality rates for these persons compared with the general population’’[21].ExplanationThe abstract provides key information that enables readers to understand a study and decide whether to read the article.Typical components include a statement of the research question,a short description of methods and results,and a conclusion[22].Abstracts should summarize key details of studies and should only present information that is provided in the article.We advise presenting key results in a numerical form that includes numbers of participants,estimates of associations and appropriate measures of variability and uncertainty(e.g.,odds ratios with confidence intervals).We regard it insufficient to state only that an exposure is or is not significantly associated with an outcome.A series of headings pertaining to the background,design, conduct,and analysis of a study may help readers acquire the essential information rapidly[23].Many journals require such structured abstracts,which tend to be of higher quality and more readily informative than unstructured summaries [24,25].INTRODUCTIONThe Introduction section should describe why the study was done and what questions and hypotheses it addresses.It should allow others to understand the study’s context and judge its potential contribution to current knowledge.Box1.Main study designs covered by STROBECohort,case-control,and cross-sectional designs represent different approaches of investigating the occurrence of health-related events in a given population and time period.These studies may address many types of health-related events,including disease or disease remission, disability or complications,death or survival,and the occurrence of risk factors.In cohort studies,the investigators follow people over time.They obtain information about people and their exposures at baseline,let time pass, and then assess the occurrence of outcomes.Investigators commonly make contrasts between individuals who are exposed and not exposed or among groups of individuals with different categories of exposure. Investigators may assess several different outcomes,and examine exposure and outcome variables at multiple points during follow-up. Closed cohorts(for example birth cohorts)enrol a defined number of participants at study onset and follow them from that time forward, often at set intervals up to a fixed end date.In open cohorts the study population is dynamic:people enter and leave the population at different points in time(for example inhabitants of a town).Open cohorts change due to deaths,births,and migration,but the composition of the population with regard to variables such as age and gender may remain approximately constant,especially over a short period of time.In a closed cohort cumulative incidences(risks)and incidence rates can be estimated;when exposed and unexposed groups are compared,this leads to risk ratio or rate ratio estimates.Open cohorts estimate incidence rates and rate ratios.In case-control studies,investigators compare exposures between people with a particular disease outcome(cases)and people without that outcome(controls).Investigators aim to collect cases and controls that are representative of an underlying cohort or a cross-section of a population.That population can be defined geographically,but also more loosely as the catchment area of health care facilities.The case sample may be100%or a large fraction of available cases,while the control sample usually is only a small fraction of the people who do not have the pertinent outcome.Controls represent the cohort or population of people from which the cases arose.Investigators calculate the ratio of the odds of exposures to putative causes of the disease among cases and controls(see Box7).Depending on the sampling strategy for cases and controls and the nature of the population studied,the odds ratio obtained in a case-control study is interpreted as the risk ratio,rate ratio or(prevalence)odds ratio[16,17].The majority of published case-control studies sample open cohorts and so allow direct estimations of rate ratios.In cross-sectional studies,investigators assess all individuals in a sample at the same point in time,often to examine the prevalence of exposures, risk factors or disease.Some cross-sectional studies are analytical and aim to quantify potential causal associations between exposures and disease. Such studies may be analysed like a cohort study by comparing disease prevalence between exposure groups.They may also be analysed like a case-control study by comparing the odds of exposure between groups with and without disease.A difficulty that can occur in any design but is particularly clear in cross-sectional studies is to establish that an exposure preceded the disease,although the time order of exposure and outcome may sometimes be clear.In a study in which the exposure variable is congenital or genetic,for example,we can be confident that the exposure preceded the disease,even if we are measuring both at the same time.2.Background/rationale:Explain the scientific background and rationale for the investigation being reported. Example‘‘Concerns about the rising prevalence of obesity in children and adolescents have focused on the well docu-mented associations between childhood obesity and in-creased cardiovascular risk and mortality in adulthood. Childhood obesity has considerable social and psychological consequences within childhood and adolescence,yet little is known about social,socioeconomic,and psychological con-sequences in adult life.A recent systematic review found no longitudinal studies on the outcomes of childhood obesity other than physical health outcomes and only two longitu-dinal studies of the socioeconomic effects of obesity in adolescence.Gortmaker et al.found that US women who had been obese in late adolescence in1981were less likely to be married and had lower incomes seven years later than women who had not been overweight,while men who had been overweight were less likely to be married.Sargent et al.found that UK women,but not men,who had been obese at16years in1974earned7.4%less than their non-obese peers at age23. (...)We used longitudinal data from the1970British birth cohort to examine the adult socioeconomic,educational, social,and psychological outcomes of childhood obesity’’[26]. ExplanationThe scientific background of the study provides important context for readers.It sets the stage for the study and describes its focus.It gives an overview of what is known on a topic and what gaps in current knowledge are addressed by the study.Background material should note recent pertinent studies and any systematic reviews of pertinent studies.3.Objectives:State specific objectives,including any prespecified hypotheses.Example‘‘Our primary objectives were to1)determine the prevalence of domestic violence among female patients presenting to four community-based,primary care,adult medicine practices that serve patients of diverse socio-economic background and2)identify demographic and clinical differences between currently abused patients and patients not currently being abused’’[27].ExplanationObjectives are the detailed aims of the study.Well crafted objectives specify populations,exposures and outcomes,and parameters that will be estimated.They may be formulated as specific hypotheses or as questions that the study was designed to address.In some situations objectives may be less specific,for example,in early discovery phases.Regard-less,the report should clearly reflect the investigators’intentions.For example,if important subgroups or addi-tional analyses were not the original aim of the study but arose during data analysis,they should be described accord-ingly(see also items4,17and20).METHODSThe Methods section should describe what was planned and what was done in sufficient detail to allow others to understand the essential aspects of the study,to judge whether the methods were adequate to provide reliable and valid answers,and to assess whether any deviations from the original plan were reasonable.4.Study design:Present key elements of study design early in the paper.Example‘‘We used a case-crossover design,a variation of a case-control design that is appropriate when a brief exposure (driver’s phone use)causes a transient rise in the risk of a rare outcome(a crash).We compared a driver’s use of a mobile phone at the estimated time of a crash with the same driver’s use during another suitable time period.Because drivers are their own controls,the design controls for characteristics of the driver that may affect the risk of a crash but do not change over a short period of time.As it is important that risks during control periods and crash trips are similar,we compared phone activity during the hazard interval(time immediately before the crash)with phone activity during control intervals(equivalent times during which participants were driving but did not crash)in the previous week’’[28]. ExplanationWe advise presenting key elements of study design early in the methods section(or at the end of the introduction)so that readers can understand the basics of the study.For example,authors should indicate that the study was a cohort study,which followed people over a particular time period, and describe the group of persons that comprised the cohort and their exposure status.Similarly,if the investigation used a case-control design,the cases and controls and their source population should be described.If the study was a cross-sectional survey,the population and the point in time at which the cross-section was taken should be mentioned. When a study is a variant of the three main study types,there is an additional need for clarity.For instance,for a case-crossover study,one of the variants of the case-control design, a succinct description of the principles was given in the example above[28].We recommend that authors refrain from simply calling a study‘prospective’or‘retrospective’because these terms are ill defined[29].One usage sees cohort and prospective as synonymous and reserves the word retrospective for case-control studies[30].A second usage distinguishes prospective and retrospective cohort studies according to the timing of data collection relative to when the idea for the study was developed[31].A third usage distinguishes prospective and retrospective case-control studies depending on whether the data about the exposure of interest existed when cases were selected[32].Some advise against using these terms[33],or adopting the alternatives‘concurrent’and‘historical’for describing cohort studies[34].In STROBE,we do not use the words prospective and retrospective,nor alternatives such as concurrent and historical.We recommend that,whenever authors use these words,they define what they mean.Most importantly,we recommend that authors describe exactly how and when data collection took place.Thefirst part of the methods section might also be the place to mention whether the report is one of several from a study.If a new report is in line with the original aims of the study,this is usually indicated by referring to an earlier publication and by briefly restating the salient features of the study.However,the aims of a study may also evolve over time.。