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A guide to systematic review and meta-analysis of prognostic factor studies
Open accessAbstract
Prognostic factors are associated with the risk of future health outcomes in individuals with a particular health condition or some clinical start point (eg, a particular diagnosis). Research to identify genuine prognostic factors is important because these factors can help improve risk stratification, treatment, and lifestyle decisions, and the design of randomised trials. Although thousands of prognostic factor studies are published each year, often they are of variable quality and the findings are inconsistent. Systematic reviews and meta-analyses are therefore needed that summarise the evidence about the prognostic value of particular factors. In this article, the key steps involved in this review process are described.
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Cited by
Calculating the sample size required for developing a clinical prediction model
Riley, R. D., Ensor, J., Snell, K. I. E., Harrell, F. E., Martin, G. P., Reitsma, J. B., Moons, K. G. M., Collins, G., & van Smeden, M. (2020) · BMJ · doi:10.1136/bmj.m441 · Cited by 2,917
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Metadata
- Authors
- Riley, R. D., Moons, K. G. M., Snell, K. I. E., Ensor, J., Hooft, L., Altman, D. G., Hayden, J., Collins, G. S., & Debray, T. P. A.
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2019-01-30
- Volume
- 364
- Pages
- k4597
- ISSN
- 1756-1833 (ISSN-L)
- 0959-8138
- OpenAlex
- W2914356810
- Cited by
- 742
- References
- 34
- FWCI
- 14.81
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.bmj.com/company/legal-information/terms-conditions/legal-information/tdm-licencepolicy (tdm)
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- Riley, R. D., Moons, K. G. M., Snell, K. I. E., Ensor, J., Hooft, L., Altman, D. G., Hayden, J., Collins, G. S., & Debray, T. P. A. (2019). A guide to systematic review and meta-analysis of prognostic factor studies. BMJ. https://doi.org/10.1136/bmj.k4597
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