Methods for systematic review and meta-analysis of prognostic factors and prediction modelling studies

Lotty Hooft, Karel Moons

Prognostic information is essential to educate or inform management and decision making for patients. Systematic and transparent syntheses are necessary to evaluate a massive proliferation of prognostic factors and models available. This project will support the completion of prognostic exemplar reviews and develop new related training materials. The team will further develop necessary methods for this novel type of Cochrane Review. This will include testing the use of the QUIPS (Quality in Prognostic Studies) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) tools for critical appraisal of prognostic factors and modelling studies, respectively. They will test methods of prognostic factor systematic review literature searching, develop and illustrate meta-analysis methodsfor summarizing results of prognostic modelling studies.



Debray TPA, Damen JAA, Riley RD, Snell K, Reitsma JB, Hooft L, Collins GS, Moons KGM. A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes. Stat Methods Med Res 2018:0.

Debray TPA, Damen JAAG, Snell, KIE, Ensor J, Hooft L, Reitsma JB, Riley RD, Moons KGM. A guide to systematic review and meta-analysis of prediction model performance. BMJ 2017:356;i6460.

Damen JA, Hooft L, Schuit E, Debray TP, Collins GS, Tzoulaki I, et al. Prediction models for cardiovascular disease risk in the general population: systematic review. BMJ 2016:353;i2416.


Source of Funding

Our mission is to promote evidence-informed health decision-making by producing high-quality, relevant, accessible systematic reviews and other synthesized research evidence.

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  • Funder :Cochrane
  • Project Category : Cochrane Methods Innovation Funds (Round 2)
  • Project Reference : MTH001F
  • Funded Period : Mar 2015 - present
  • Funded Amount : GBP 50,000