Clinical Validation of MyProstateScore 2.0 Testing Using First-Catch, Non-Digital Rectal Examination Urine

Abstract

Purpose: The 18-gene MyProstateScore 2.0 (MPS2) test was previously validated for detection of grade group (GG) ≥ 2 prostate cancer using post-digital rectal examination (DRE) urine. To improve ease of testing, we validated MPS2 using first-catch, non-DRE urine.

Materials and methods: Patients provided first-catch urine before biopsy. MPS2 values were calculated using previously validated models differing only by extent of clinical data included biomarkers alone (BA; no clinical data), biomarkers and clinical factors (BA + CF), and biomarkers, clinical factors, and prostate volume (BA + CF + PV). The primary outcome was GG ≥ 2 cancer on biopsy. MPS2 performance and clinical consequences of testing were compared with PSA and the Prostate Cancer Prevention Trial risk calculator (PCPTrc).

Results: The cohort included 266 men with median PSA 6.6 ng/mL (IQR, 4.9-9.1) of whom 103 (39%) had GG ≥ 2 cancer on biopsy. The AUC for GG ≥ 2 cancer was 57% for PSA, 62% for PCPTrc, and 71%, 74%, and 77% for MPS2 models. Under a testing approach detecting > 90% of GG ≥ 2 cancers, MPS2 testing would have avoided 36% to 42% of unnecessary biopsies, as compared with 13% using the PCPTrc. In patients with a prior negative biopsy, MPS2 testing would have avoided 44% to 53% of repeat biopsies, as compared with only 2.6% using PCPTrc.

Conclusions: Using first-catch urine, MPS2 meaningfully improved the proportion of biopsies avoided relative to PCPTrc while maintaining highly sensitive detection of GG ≥ 2 cancer. Non-DRE testing provides a convenient, objective, and highly accurate testing option to reduce the need for imaging and biopsy in men with elevated PSA.

Keywords: biomarkers; early detection of cancer; liquid biopsy; prostate cancer.

Figure 1.

Calibration curves for GG≥2 cancer for MPS2 models in the validation cohort. BA, Biomarkers Alone Model; BA+CF, Biomarkers plus Clinical Factors Model; BA+CF+PV, Biomarkers, Clinical Factors, and Prostate Volume Model.

Figure 2.

Decision curve analysis (DCA) plots for the outcome of GG≥2 cancer based on pre-biopsy testing with PSA, the PCPT risk calculator, and MPS2 models compared to baseline approaches of biopsying all patients and biopsying no patients. BA, Biomarkers Alone Model; BA+CF, Biomarkers plus Clinical Factors Model; BA+CF+PV, Biomarkers, Clinical Factors, and Prostate Volume Model. (A) Net clinical benefit, in which the unit of net benefit (y-axis) is true positives. A net benefit of 0.1 is equivalent to an approach in which an additional 10 patients per 100 are directed to biopsy, and all 10 patients are found to have GG≥2 cancer. (B) Net reduction in biopsies, in which the y-axis represents the net reduction in biopsies performed per 100 patients without missing a single diagnosis of GG≥2 cancer.