Evidence in Medicine

Evidence in Medicine
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High-quality evidence is the foundation for effective treatment in medicine. As the vast amount of published medical evidence continues to grow, concerns about the quality of many studies are increasing.  Evidence in Medicine  is a much-needed resource that addresses the ‘medical misinformation mess’ by assessing the flaws in the research environment. This authoritative text identifies and summarises the many factors that have produced the current problems in medical research, including bias in randomised controlled trials, questionable research practices, falsified data, manipulated findings, and more.  This volume brings together the findings from meta-research studies and systematic reviews to explore the quality of clinical trials and other medical research, explaining the character and consequences of poor-quality medical evidence using clear language and a wealth of supporting references. The text suggests planning strategies to transform the research process and provides an extensive list of the actions that could be taken by researchers, regulators, and other key stakeholders to address defects in medical evidence. This timely volume:  Enables readers to select reliable studies and recognise misleading research Highlights the main types of biased and wasted studies Discusses how incentives in the research environment influence the quality of evidence Identifies the problems researchers need to guard against in their work Describes the scale of poor-quality research and explores why the problems are widespread Includes a summary of key findings on poor-quality research and a listing of proposed initiatives to improve research evidence Contains extensive citations to references, reviews, commentaries, and landmark studies  Evidence in Medicine  is required reading for all researchers who create evidence, funders and publishers of medical research, students who conduct their own research studies, and healthcare practitioners wanting to deliver high-quality, evidence-based care.

Оглавление

Iain K. Crombie. Evidence in Medicine

Table of Contents

List of Tables

Guide

Pages

Evidence in Medicine. The Common Flaws, Why They Occur and How to Prevent Them

Preface

Aims of this Book

REFERENCES

CHAPTER 1 The Rationale for Treatment: A Brief History

THEORY AS JUSTIFICATION FOR TREATMENT

TESTING ON A SERIES OF PATIENTS

COMPARING GROUPS

COMPARING SIMILAR GROUPS

CASTING LOTS AND TREATMENT ALLOCATION

RANDOM NUMBERS FOR TREATMENT ALLOCATION

THE NEED FOR BLINDING

CONCLUSION

REFERENCES

CHAPTER 2 Sources of Bias in Randomised Controlled Trials

METHOD OF TREATMENT ALLOCATION

Generation of the Random Assignment

Importance of Concealed Allocation

Evidence that the Randomisation Process Is Subverted

Does Integrity of Allocation Concealment Matter?

PROBLEMS IN MEASURING THE OUTCOME

Switching Primary Outcomes

Blinding of Outcome Assessment

Reporting of Adverse Events

FOLLOW‐UP AND MISSING OUTCOMES

Extent of Loss to Follow‐up

Characteristics of Patients Lost

Bias from Loss to Follow‐up

MISSING OUTCOME DATA AND INTENTION TO TREAT

Methods of Imputation

Modified Intention to Treat

OTHER METHODOLOGICAL CONCERNS. Unregistered Trials and Bias

Small Studies

Low Power

Industry‐Funded Trials

CONCLUSIONS

REFERENCES

CHAPTER 3 Wasted and Unhelpful Trials

WASTED STUDIES. Uncompleted Trials

Unpublished Trials

Unnecessary Trials

NEGLECTED AREAS OF RESEARCH. Less Favoured Clinical Areas

Less Popular Types of Interventions

UNHELPFUL OUTCOME MEASURES

Surrogate Outcomes

Composite Outcomes

Relevance to Patients and Clinicians

COMET: Core Outcome Measures in Effectiveness Trials

LACK OF GENERALISABILITY

Possible Reasons for Exclusions

Poor Reporting of Patient Characteristics

The Average and the Individual

WEAK AND MISLEADING EVIDENCE

Reversals in Medicine

Lack of Reproducibility

CONCLUSION

REFERENCES

CHAPTER 4 Can the Analysis Bias the Findings?

THE P‐VALUE PROBLEM

Definition of the P‐value

The Frequency of Reported P‐values

Calculating and Reporting P‐values

QUESTIONABLE RESEARCH PRACTICES

HARKing (Hypothesising After the Results are Known)

Excluding Data

Multiple Comparisons

Subgroup Analyses

Selection of Covariates

ENSURING HIGH QUALITY ANALYSIS: THE STATISTICAL ANALYSIS PLAN

CONCLUSIONS

REFERENCES

CHAPTER 5 Systematic Reviews and Meta‐Analysis. INTRODUCTION

Meta‐Analysis

Aims of the Chapter

IDENTIFYING RELEVANT TRIALS

Unpublished Studies

Bias from Unpublished Studies

Adequacy of the Sources Searched

Problems with the Search Strategies

Screening for Relevant Trials

EXTRACTING TRIAL DATA

Incorrect Data

Multiple Outcomes

Outcome Reporting Bias

Adverse Events

THE QUALITY OF PRIMARY TRIALS

Taking Quality into Account

POOLING EFFECT SIZES ACROSS TRIALS

Heterogeneity

Exploring Heterogeneity

OTHER METHODOLOGICAL ISSUES. Missing Outcome Data

The Sparse Data Problem

Conflicting Findings

Wasted and Redundant Systematic Reviews

CONCLUSIONS

REFERENCES

CHAPTER 6. Fabrication, Falsification and Spin

FABRICATION

Impact of Fabrication

Identifying and Managing Data Fabrication

Reluctance to Report

FALSIFICATION

QUESTIONABLE RESEARCH PRACTICES

SPIN

Focussing on Misleading Significance

Drawing Misleading Conclusions

Misleading Abstracts

Words to Mislead

RETRACTIONS

DISCUSSION

REFERENCES

CHAPTER 7 Why Do Researchers Falsify Data or Manipulate Study Findings?

THE RESEARCH ENVIRONMENT

Impact Factors

Perverse Incentives

Gaming the System

RESEARCH OVERSIGHT

Peer Review

Predatory Journals and Conferences

CONFLICT OF INTEREST

Financial Conflicts

Non‐Financial Conflicts

INDIVIDUAL LEVEL EXPLANATIONS FOR RESEARCH MISCONDUCT

Data Fabrication and the Dark Triad

The Fraud Triangle, Data Falsification and Questionable Research Practices

HOW HONEST PEOPLE RATIONALISE MISCONDUCT

Societal Factors

Cognitive Biases

Blind Spot Bias

Confirmation Bias

Optimism Bias

Hindsight Bias

Moral Licensing

Motivation for Research

DISCUSSION

REFERENCES

CHAPTER 8 Developing a Strategy to Prevent Poor Quality and Misleading Research

RESEARCH ENVIRONMENT

Research Assessment

Research Training

RESEARCH TRANSPARENCY

Trial Registration

Quality of Reporting of Trial Methods

Data Sharing

RESEARCH OVERSIGHT

Strengthen Peer Review

Monitor Selective Outcome Reporting

RESEARCH INTEGRITY

Reduce the Use of Spin

Reporting Conflict of Interest

Integrity Training

ESSENTIAL ELEMENTS OF A TRANSFORMATIONAL STRATEGY

Commitment from Key Stakeholders

Monitoring the Research Process

Sanctions and Incentives

Availability of Expertise

Coordinated Approaches

Financial Support

The Cost of Inaction

Who Should Pay?

IMPLEMENTING A PROGRAMME FOR ACTION

REFERENCES

Appendix 1: Summary of the Key Findings on Poor Quality Research

PROBLEMS IN THE DESIGN, CONDUCT, ANALYSIS AND REPORTING OF STUDIES. Trials

Statistical Analysis

Systematic Reviews

FREQUENCY OF DATA FABRICATION AND FALSIFICATION

THE CAUSES OF POOR QUALITY AND MISLEADINGRESEARCH

THE FINDINGS IN PERSPECTIVE

REFERENCES

Appendix 2: Initiatives to Improve the Quality of Research

CHANGE THE RESEARCH ENVIRONMENT

Value Negative Findings

Change Research Assessment

Improve Training

Certificates of Research Competence

Trial Forge

PRECIS‐2

INCREASE RESEARCH TRANSPARENCY

Data Sharing

Open Science

The RIAT Initiative

QUALITY OF TRIAL METHODOLOGY. The CONSORT Statement for Trials

The SPIRIT 2013 Statement for Study Protocols

Reporting the Statistical Analysis: The SAMPL Guidelines

Reporting Harms

Reporting Trial Findings

TRIAL REGISTRATION

Enforcement of Trial Registration

REPORTING OF THE METHODS OF SYSTEMATIC REVIEWS

Registration of Protocols of Systematic Reviews

INCREASING ACCESS TO AND USE OF REPORTING GUIDELINES. EQUATOR and Reporting Guidelines

Interventions to Promote Guideline Use

IMPLEMENT VIGOROUS RESEARCH OVERSIGHT. Strengthen Peer Review

Alternative Forms of Peer Review

Reward Peer Reviewers

Audit Trial Publication

Monitor for Selective Outcome Reporting

Preprints and Pre‐Publication Review

Post‐Publication Review

PROMOTE RESEARCH INTEGRITY. National Level Initiatives

Training in Research Integrity

Monitor Data Quality

Promote Reporting of Fraud and Misconduct

Reduce the Use of Spin

Promote Honesty about Conflict of Interest

Research Institutions and Research Integrity

Criminalise Research Fraud

EXAMPLES OF COORDINATED INITIATIVES. The AllTrials Campaign

The QUEST Initiative

The Lancet REWARD Campaign

The UK Reproducibility Network

REFERENCES

Index. A

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Iain K Crombie

University of Dundee

.....

Obtaining evidence on treatment effectiveness is a challenging business. As Passamani remarked in 1991, ‘The history of medicine is richly endowed with therapies that were widely used and then shown to be ineffective or frankly toxic’ [53]. A similar view was expressed by the celebrated American physician, Oliver Wendell Holmes in 1860, ‘if the whole materia medica, as now used, could be sunk to the bottom of the sea, it would be all the better for mankind – and all the worse for the fishes’ [54]. These may seem somewhat jaundiced views, but they reflect the large proportion of ineffective and possibly harmful treatments that were once used. Even in the early years of the twentieth century many ineffective treatments were widely used [55], and some treatments of little value continue to be used today [56]. Concern about this has led to a recent international campaign, ‘Choosing Wisely’, to reduce the use of ineffective or harmful treatments [57].

.....

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