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Concordance and Performance of 4Kscore and SelectMDx for Informing Decision to Perform Prostate Biopsy and Detection of Prostate Cancer

      Objectives

      To compare both the concordance between the 4Kscore and SelectMDx for informing decision to perform prostate biopsy (PB) and the performance of these tests for detecting clinically significant prostate cancer (csPCa). Several biomarkers were developed to inform decisions whether to perform a PB based on the probability of detecting csPCa. There is a paucity of studies directly comparing them

      Methods

      Between 11/2018 and 4/2019, all new referrals with the diagnosis of elevated PSA were advised to undergo 4Kscore and SelectMDx in order to guide the selection of candidates for PB. Men were advised to undergo PB if the reported biomarker risk for detecting csPCA was ≥7.5%, or if they presented a Prostate Image Reporting and Data System ≥1 MRI. Cohen's Kappa was used to assess the concordance between the binary 4Kscore and SelectMDx results using externally validated cutoffs of 7.5% and 12%. Receiver operating characteristics curve and area under the curve (AUC) assessed the performance of each biomarker for distinguishing csPCa.

      Results

      Of 128 consecutive patients referred, 114 (89.1%) underwent 4Kscore and SelectMDx. The kappa coefficient between the biomarkers using the 7.5% cutoff was 0.184 (poor concordance) and 0.22 using the 12% cutoff. The two biomarkers yielded discordant guidance whether to proceed with PB in 46% and 38% of cases, respectively. csPCa was found in 22 of the 50 patients who underwent PB (44%). The AUC for 4Kscore and SelectMDx was 0.830 (95% confidence interval [CI]: 0.710 - 0.949) and 0.672 (95%CI: 0.517 - 0.828; P = .036) for csPCa, respectively.

      Conclusion

      The discordance observed between the 4Kscore and SelectMDx is disconcerting. The 4Kscore when combined with magnetic resonance imaging was superior to the SelectMDx for detecting csPCa. Prospective comparative studies must be performed to optimize implementation of biomarkers for selecting candidates for PB.
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