The vast majority of systematic reviews are planned retrospectively, once most eligible trials have completed and reported, and are based on aggregate data that can be extracted from publications. Prior knowledge of trial results can introduce bias into both review and meta-analysis methods, and the omission of unpublished data can lead to reporting biases. The collaborative framework for prospective, adaptive meta-analysis (FAME) of aggregate data can reduce the potential for bias, and help produce more timely, thorough and reliable results.

Recognising that it might not be possible or desirable to apply all aspects of FAME to all Cochrane Reviews, this Methods Support Unit web clinic will demonstrate how the adoption of some of the key principles (FAME-lite) could improve the quality and efficiency of the vast majority.

Presenter Bios

Professor Jayne Tierney co-leads the Meta-analysis Programme of the MRC Clinical Trials Unit at UCL, and for more than 25 years, she has been responsible for designing and conducting international, collaborative, individual participant data (IPD) meta-analyses and systematic reviews of aggregate data both in cancer and a range of other health areas. Alongside, she has developed methods and guidance to improve how systematic reviews and meta-analyses are conducted and analysed, for example, improving the timeliness and reliability of aggregate data meta-analyses, and maximising the value of IPD. Jayne has been involved in the Cochrane Collaboration since its beginnings, providing peer review, contributions to the Cochrane Handbook, workshops at annual meetings and colloquia and as co-convenor of the IPD Meta-analysis Methods Group.

Sarah Burdett is a member of the Meta-analysis Group at the MRC Clinical Trials Unit at UCL, London, UK. For more than 20 years, she has been involved in designing and conducting systematic reviews and meta-analysis to rigorously re-evaluate the effectiveness of therapies. She has published international, collaborative, individual participant data (IPD) and aggregate data (AD) meta-analyses in bladder, lung, glioma, and prostate cancer. These projects have influenced practice guidelines and the treatment of patients worldwide. Sarah also provides advice and training on systematic review and meta-analysis methods, particularly in relation to IPD.

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Thursday, 9 March 2023, 10:00 UTC [Check the time in your time zone] SIGN UP HERE

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