Cochrane Handbook for Systematic Reviews of Interventions

Julian P.T. Higgins is Professor of Evidence Synthesis at Bristol Medical School, University of Bristol, UK. He has worked in methods for systematic review and meta-analysis for over 25 years and acts as Senior Methods Advisor to Cochrane.

James Thomas is Professor of Social Research and Policy at the EPPI-Centre, UCL Institute of Education. He has broad interests in systematic review methodology and tools and is Director of the Systematic Reviews Facility for the Department of Health, England.

Preface

Part one: Core methods

Chapter 1: Starting a review

1.1 Why do a systematic review?

1.2 What is the review question?

1.3 Who should do a systematic review?

1.4 The importance of reliability

1.5 Protocol development

1.6 Data management and quality assurance

1.7 Chapter information

1.8 References

Chapter 2: Determining the scope of the review and the questions it will address

2.1 Rationale for well-formulated questions

2.2 Aims of reviews of interventions

2.3 Defining the scope of a review question

2.4 Ensuring the review addresses the right questions

2.5 Methods and tools for structuring the review

2.6 Chapter information

2.7 References

Chapter 3: Defining the criteria for including studies and how they will be grouped for the synthesis

3.1 Introduction

3.2 Articulating the review and comparison PICO

3.3 Determining which study designs to include

3.4 Eligibility based on publication status and language

3.5 Chapter information

3.6 References

Chapter 4: Searching for and selecting studies

4.1 Introduction

4.2 General issues

4.3 Sources to search

4.4 Designing search strategies

4.5 Documenting and reporting the search process

4.6 Selecting studies

4.7 Chapter information

4.8 References

Chapter 5: Collecting data

5.2 Introduction

5.3 Sources of data

5.4 What data to collect

5.5 Data collection tools

5.6 Extracting data from reports

5.7 Extracting study results and converting to the desired format

5.8 Managing and sharing data

5.9 Chapter information

5.10 References

Chapter 6: Choosing effect measures and computing estimates of effect

6.1 Types of data and effect measures

6.2 Study designs and identifying the unit of analysis

6.3 Extracting estimates of effect directly

6.4 Dichotomous outcome data

6.5 Continuous outcome data

6.6 Ordinal outcome data and measurement scales

6.7 Count and rate data

6.8 Time-to-event data

6.9 Conditional outcomes only available for subsets of participants

6.10 Chapter information

6.11 References

Chapter 7: Considering bias and conflicts of interest among the included studies

7.1 Introduction

7.2 Empirical evidence of bias

7.3 General procedures for risk-of-bias assessment

7.4 Presentation of assessment of risk of bias

7.5 Summary assessments of risk of bias

7.6 Incorporating assessment of risk of bias into analyses

7.7 Considering risk of bias due to missing results

7.8 Considering conflict of interest of authors of included studies

7.9 Chapter information

7.10 References

Chapter 8: Assessing risk of bias in a randomized trial

8.1 Introduction

8.2 Overview of RoB 2

8.3 Bias arising from the randomization process

8.4 Bias due to deviations from intended interventions

8.5 Bias due to missing outcome data

8.6 Bias in measurement of the outcome

8.7 Bias in selection of the reported result

8.8 Differences from the previous version of the tool

8.9 Chapter information

8.10 References

Chapter 9: Summarizing study characteristics and preparing for synthesis

9.1 Introduction

9.2 A general framework for synthesis

9.3 Preliminary steps of a synthesis

9.4 Checking data before synthesis

9.5 Types of synthesis

9.6 Chapter information

9.7 References

Chapter 10: Analysing data and undertaking meta-analyses

10.1 Do not start here!

10.2 Introduction to meta-analysis

10.3 A generic inverse-variance approach to meta-analysis

10.4 Meta-analysis of dichotomous outcomes

10.5 Meta-analysis of continuous outcomes

10.6 Combining dichotomous and continuous outcomes

10.7 Meta-analysis of ordinal outcomes and measurement scales

10.8 Meta-analysis of counts and rates

10.9 Meta-analysis of time-to-event outcomes

10.10 Heterogeneity

10.11 Investigating heterogeneity

10.12 Missing data

10.12.1 Types of missing data

10.12.2 General principles for dealing with missing data

10.12.3 Dealing with missing outcome data from individual participants

10.13 Bayesian approaches to meta-analysis

10.14 Sensitivity analyses

10.15 Chapter information

10.16 References

Chapter 11: Undertaking network meta-analyses

11.1 What is network meta-analysis?

11.2 Important concepts

11.3 Planning a Cochrane Review to compare multiple interventions

11.4 Synthesis of results

11.5 Evaluating confidence in the results of a network meta-analysis

11.6 Presenting network meta-analyses

11.7 Concluding remarks

11.8 Chapter information

11.9 References

Chapter 12: Synthesizing and presenting findings using other methods

12.1 Why a meta-analysis of effect estimates may not be possible

12.2 Statistical synthesis when meta-analysis of effect estimates is not possible

12.3 Visual display and presentation of the data

12.4 Worked example

12.5 Chapter information

12.6 References

Chapter 13: Assessing risk of bias due to missing results in a synthesis

13.1 Introduction

13.2 Minimizing risk of bias due to missing results

13.3 A framework for assessing risk of bias due to missing results in a synthesis

13.4 Summary

13.5 Chapter information

13.6 References

Chapter 14: Completing 'Summary of findings' tables and grading the certainty of the evidence

14.1 'Summary of findings' tables

14.2 Assessing the certainty or quality of a body of evidence

14.3 Describing the assessment of the certainty of a body of evidence using the GRADE framework

14.4 Chapter information

14.5 References

Chapter 15: Interpreting results and drawing conclusions

15.1 Introduction

15.2 Issues of indirectness and applicability

15.3 Interpreting results of statistical analyses

15.4 Interpreting results from dichotomous outcomes (including numbers needed to treat)

15.5 Interpreting results from continuous outcomes (including standardized mean differences)

15.6 Drawing conclusions

15.7 Chapter information

15.8 References

Part two: Specific perspectives in reviews

Chapter 16: Equity and specific populations

16.1 Introduction to equity in systematic reviews

16.2 Formulation of the review

16.3 Identification of evidence

16.4 Appraisal of evidence

16.5 Synthesis of evidence

16.6 Interpretation of evidence

16.7 Concluding remarks

16.8 Chapter information

16.9 References

Chapter 17: Intervention complexity

17.1 Introduction

17.2 Formulation of the review

17.3 Identification of evidence

17.4 Appraisal of evidence

17.5 Synthesis of evidence

17.6 Interpretation of evidence

17.7 Chapter information

17.8 References

Chapter 18: Patient-reported outcomes

18.1 Introduction to patient-reported outcomes

18.2 Formulation of the review

18.3 Appraisal of evidence

18.4 Synthesis and interpretation of evidence

18.5 Chapter information

18.6 References

Chapter 19: Adverse effects

19.1 Introduction to issues in addressing adverse effects

19.2 Formulation of the review

19.3 Identification of evidence

19.4 Appraisal of evidence

19.5 Synthesis and interpretation of evidence

19.6 Chapter information

19.7 References

Chapter 20: Economics evidence

20.1 Introduction

20.2 Formulation of the review

20.3 Identification of evidence

20.4 Appraisal of evidence

20.5 Synthesis and interpretation of evidence

20.6 Chapter information

20.7 References

Chapter 21: Qualitative research and Cochrane Reviews

21.1 Introduction

21.2 Designs for synthesizing and integrating qualitative evidence with intervention reviews

21.3 Defining qualitative evidence and studies

21.4 Planning a qualitative evidence synthesis linked to an intervention review

21.5 Question development

21.6 Questions exploring intervention implementation

21.7 Searching for qualitative evidence

21.8 Assessing methodological strengths and limitations of qualitative studies

21.9 Selecting studies to synthesize

21.10 Selecting a qualitative evidence synthesis and data extraction method

21.11 Data extraction

21.12 Assessing the confidence in qualitative synthesized findings

21.13 Methods for integrating the qualitative evidence synthesis with an intervention review

21.14 Reporting the protocol and qualitative evidence synthesis

21.15 Chapter information

21.16 References

Part three: Further topics

Chapter 22: Prospective approaches to accumulating evidence

22.1 Introduction

22.2 Evidence surveillance: active monitoring of the accumulating evidence

22.3 Prospectively planned meta-analysis

22.4 Statistical analysis of accumulating evidence

22.5 Chapter information

22.6 References

Chapter 23: Including variants on randomized trials

23.1 Cluster-randomized trials

23.2 Crossover trials

23.3 Studies with more than two intervention groups

23.4 Chapter information

23.5 References

Chapter 24: Including non-randomized studies on intervention effects

24.1 Introduction

24.2 Developing criteria for including non-randomized studies of interventions

24.3 Searching for non-randomized studies of interventions

24.4 Selecting studies and collecting data

24.5 Assessing risk of bias in non-randomized studies

24.6 Synthesis of results from non-randomized studies

24.7 Interpretation and discussion

24.8 Chapter information

24.9 References

Chapter 25: Assessing risk of bias in a non-randomized study

25.1 Introduction

25.2 Biases in non-randomized studies

25.3 The ROBINS-I tool

25.4 Risk of bias in follow-up (cohort) studies

25.5 Risk of bias in uncontrolled before-after studies (including interrupted time series)

25.6 Risk of bias in controlled before-after studies

25.7 Chapter information

25.8 References

Chapter 26: Individual participant data

26.1 Introduction

26.2 Collecting IPD

26.3 Managing and checking IPD

26.4 Analysis of IPD

26.5 Reporting IPD reviews

26.6 Appraising the quality of IPD reviews

26.7 Chapter information

26.8 References

Index