How to Read a Paper - Paul Dijkstra

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Résumé :

Foreword to the first edition by Professor Sir David Weatherall xii

Preface to the seventh edition xiv

Preface to the first edition xvii

Acknowledgements xix

Chapter 1 Why read papers at all? 1

Does 'evidence- based medicine' simply mean 'reading papers in medical journals'? 1

Why do people sometimes groan when you mention evidence- based healthcare? 4

Before you start: formulate the problem 11

Exercises based on this chapter 13

References 14

Chapter 2 Searching the literature 15

The information jungle 15

What are you looking for? 16

Levels upon levels of evidence 17

Synthesised sources: systems, summaries and syntheses 18

Pre-appraised sources: synopses of systematic reviews and primary studies 21

Specialised resources 22

Primary studies: tackling the jungle 23

One-stop shopping: federated search engines 25

Using artificial intelligence to search the literature 25

Asking for help and asking around 26

Online tutorials for effective searching 26

Exercises based on this chapter 27

References 28

Chapter 3 Getting your bearings: what is this paper about? 30

The science of 'trashing' papers 30

Three preliminary questions to get your bearings 32

What are randomised controlled trials and why do they matter? 34

What are cohort studies? 38

What are case-control studies? 40

What are cross-sectional surveys? 40

What are case reports? 41

The traditional hierarchy of evidence 42

Exercises based on this chapter 43

References 43

Chapter 4 Assessing methodological quality 45

Was the study original? 45

Who is the study about? 46

Was the design of the study sensible? 47

Was bias avoided or minimised? 49

Was assessment 'blind'? 54

Were preliminary statistical questions addressed? 55

A note on ethical considerations 58

Summing up 59

Exercises based on this chapter 60

References 60

Chapter 5 Statistics for the non-statistician 63

How can non-statisticians evaluate statistical tests? 63

Have the authors set the scene correctly? 65

Paired data, tails and outliers 71

Correlation, regression and causation 72

Probability and confidence 74

The bottom line (quantifying the chance of benefit and harm) 77

Summary 79

Exercises based on this chapter 79

References 80

Chapter 6 Papers that report clinical trials of simple interventions 82

What is a clinical trial? 82

Drug trials: 'evidence' and marketing 83

Making decisions about therapy 86

Surrogate endpoints 87

What information to expect in a paper describing a randomised controlled trial: the CONSORT statement 91

Getting worthwhile evidence from pharmaceutical representatives 91

A note on vaccine trials 94

Exercises based on this chapter 95

References 95

Chapter 7 Papers that report trials of complex interventions 99

Complex interventions 99

Ten questions to ask about a paper describing a complex intervention 101

Exercises based on this chapter 106

References 107

Chapter 8 Papers that report diagnostic or screening tests 109

Ten suspects in the dock 109

Validating diagnostic tests against a gold standard 110

Ten questions to ask about a paper that claims to validate a diagnostic or screening test 115

Likelihood ratios 119

Clinical prediction models 122

Exercises based on this chapter 124

References 125

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