Biomarkers in previous histologically negative prostate biopsies can be helpful in repeat biopsy decision-making processes.

To evaluate whether the addition of biomarkers to traditional clinicopathological parameters may help to increase the accurate prediction of prostate re-biopsy outcome. A training cohort with 98 patients and a validation cohort with 72 patients were retrospectively recruited into our study. Immunohistochemical analysis was used to evaluate the immunoreactivity of a group of biomarkers in the initial negative biopsy normal-looking tissues of the training and validation cohorts. p-STAT3, Mcm2, and/or MSR1 were selected out of 10 biomarkers to construct a biomarker index for predicting cancer and high-grade prostate cancer (HGPCa) in the training cohort based on the stepwise logistic regression analysis; these biomarkers were then validated in the validation cohort. In the training cohort study, we found that the biomarker index was independently associated with the re-biopsy outcomes of cancer and HGPCa. Moreover supplementing the biomarker index with traditional clinical-pathological parameters can improve the area under the receiver operating characteristic curve of the model from 0.722 to 0.842 and from 0.735 to 0.842, respectively, for predicting cancer and HGPCa at re-biopsy. In the decision-making analysis, we found the model supplemented with the biomarker index can improve patients' net benefit. The application of the model to clinical practice, at a 10% risk threshold, would reduce the number of biopsies by 34.7% while delaying the diagnosis of 7.8% cancers and would reduce the number of biopsies by 73.5% while delaying the diagnosis of 17.8% HGPCas. Taken together, supplementing the biomarker index with clinicopathological parameters may help urologists in re-biopsy decision-making processes.