TY - JOUR
T1 - Transparent reporting of multivariable prediction models for individual prognosis or diagnosis
T2 - checklist for systematic reviews and meta-analyses (TRIPOD-SRMA)
AU - Snell, Kym
AU - Levis, Brooke
AU - Damen, Johanna A. A.
AU - Dhiman, Paula
AU - Debray, Thomas P. A.
AU - Hooft, Lotty
AU - Reitsma, Johannes B.
AU - Moons, Karel G. M.
AU - Collins, Gary S
AU - Riley, Richard
PY - 2023/5/3
Y1 - 2023/5/3
N2 - Most clinical specialties have a plethora of studies that develop or validate one or more prediction models, for example, to inform diagnosis or prognosis. Having many prediction model studies in a particular clinical field motivates the need for systematic reviews and meta-analyses, to evaluate and summarise the overall evidence available from prediction model studies, in particular about the predictive performance of existing models. Such reviews are fast emerging, and should be reported completely, transparently, and accurately. To help ensure this type of reporting, this article describes a new reporting guideline for systematic reviews and meta-analyses of prediction model research.
AB - Most clinical specialties have a plethora of studies that develop or validate one or more prediction models, for example, to inform diagnosis or prognosis. Having many prediction model studies in a particular clinical field motivates the need for systematic reviews and meta-analyses, to evaluate and summarise the overall evidence available from prediction model studies, in particular about the predictive performance of existing models. Such reviews are fast emerging, and should be reported completely, transparently, and accurately. To help ensure this type of reporting, this article describes a new reporting guideline for systematic reviews and meta-analyses of prediction model research.
KW - Research Methods & Reporting
U2 - 10.1136/bmj-2022-073538
DO - 10.1136/bmj-2022-073538
M3 - Article
SN - 1756-1833
VL - 381
JO - BMJ
JF - BMJ
IS - 381
M1 - e073538
ER -