Meta-analysis of prognostic studies for a biomarker with a study-specific cutoff value

In prognostic studies, a summary statistic such as a hazard ratio is often reported between low-expression and high-expression groups of a biomarker with a study-specific cutoff value. Recently, several meta-analyses of prognostic studies have been reported, but these studies simply combined hazard ratios provided by the individual studies, overlooking the fact that the cutoff values are study-specific. We propose a method to summarize hazard ratios with study-specific cutoff values by estimating the hazard ratio for a 1-unit change of the biomarker in the underlying individual-level model. To this end, we introduce a model for a relationship between a reported log-hazard ratio for a 1-unit expected difference in the mean biomarker value between the low-expression and high-expression groups, which approximates the individual-level model, and propose to make an inference of the model by using the method for trend estimation based on grouped exposure data. Our combined estimator provides a valid interpretation if the biomarker distribution is correctly specified. We applied our proposed method to a dataset that examined the association between the biomarker Ki-67 and disease-free survival in breast cancer patients. We conducted simulation studies to examine the performance of our method. Copyright (c) 2016 John Wiley & Sons, Ltd.