Meta-analysis of full ROC curves with flexible parametric distributions of diagnostic test values

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Abstract

Diagnostic accuracy studies often evaluate diagnostic tests at several threshold values, aiming to make recommendations on optimal thresholds for use in practice. Methods for meta-analysis of full receiver operating characteristic (ROC) curves have been proposed but still have deficiencies. We recently proposed a parametric approach that is based on bivariate time-to-event models for interval-censored data to this task. To increase the flexibility of that approach, to cover a wide range of distributions of diagnostic test values and to address the open point of model selection, we here suggest to use the generalized F family of distributions that includes previously used distributions for the bivariate time-to-event model as special cases. The results of a simulation study are given as well as an illustration by an example of population-based screening for type 2 diabetes mellitus.

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Hoyer, A., & Kuss, O. (2020). Meta-analysis of full ROC curves with flexible parametric distributions of diagnostic test values. Research Synthesis Methods, 11(2), 301–313. https://doi.org/10.1002/jrsm.1395

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