Lifetime Data Anal - Estimating improvement in prediction with matched case-control designs.

Tópicos

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Resumo

When an existing risk prediction model is not sufficiently predictive, additional variables are sought for inclusion in the model. This paper addresses study designs to evaluate the improvement in prediction performance that is gained by adding a new predictor to a risk prediction model. We consider studies that measure the new predictor in a case-control subset of the study cohort, a practice that is common in biomarker research. We ask if matching controls to cases in regards to baseline predictors improves efficiency. A variety of measures of prediction performance are studied. We find through simulation studies that matching improves the efficiency with which most measures are estimated, but can reduce efficiency for some. Efficiency gains are less when more controls per case are included in the study. A method that models the distribution of the new predictor in controls appears to improve estimation efficiency considerably.

Resumo Limpo

exist risk predict model suffici predict addit variabl sought inclus model paper address studi design evalu improv predict perform gain ad new predictor risk predict model consid studi measur new predictor casecontrol subset studi cohort practic common biomark research ask match control case regard baselin predictor improv effici varieti measur predict perform studi find simul studi match improv effici measur estim can reduc effici effici gain less control per case includ studi method model distribut new predictor control appear improv estim effici consider

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