Prostate Health Index density improves detection of clinically significant prostate cancer.

OBJECTIVES: To explore the utility of Prostate Health Index (PHI) density for the detection of clinically significant prostate cancer (PCa) in a contemporary cohort of men presenting for diagnostic evaluation of PCa. PATIENTS AND METHODS: The study cohort included patients with elevated prostate-specific antigen (PSA; >2 ng/mL) and negative digital rectal examination who underwent PHI testing and prostate biopsy at our institution in 2015. Serum markers were prospectively measured per standard clinical pathway. PHI was calculated as ([{-2}proPSA/free PSA] × [PSA]½ ), and density calculations were performed using prostate volume as determined by transrectal ultrasonography. Logistic regression was used to assess the ability of serum markers to predict clinically significant PCa, defined as any Gleason score ≥7 cancer or Gleason score 6 cancer in >2 cores or >50% of any positive core. RESULTS: Of 118 men with PHI testing who underwent biopsy, 47 (39.8%) were found to have clinically significant PCa on biopsy. The median (interquartile range [IQR]) PHI density was 0.70 (0.43-1.21), and was 0.53 (0.36-0.75) in men with negative biopsy or clinically insignificant PCa and 1.21 (0.74-1.88) in men with clinically significant PCa (P < 0.001). Clinically significant PCa was detected in 3.6% of men in the first quartile of PHI density (<0.43), 36.7% of men in the IQR of PHI density (0.43-1.21), and 80.0% of men with PHI density >1.21 (P < 0.001). Using a threshold of 0.43, PHI density was 97.9% sensitive and 38.0% specific for clinically significant PCa, and 100% sensitive for Gleason score ≥7 disease. Compared with PSA (area under the curve [AUC] 0.52), PSA density (AUC 0.70), %free PSA (AUC 0.75), the product of %free PSA and prostate volume (AUC 0.79), and PHI (AUC 0.76), PHI density had the highest discriminative ability for clinically significant PCa (AUC 0.84). CONCLUSIONS: Based on the present prospective single-centre experience, PHI density could be used to avoid 38% of unnecessary biopsies, while failing to detect only 2% of clinically significant cancers.

Modeling grade progression in an active surveillance study.

Prostate cancer grade, assessed with the Gleason score, describes how abnormal the tumor tissue and cells appear, and it is an important prognostic indicator of disease progression. Whether prostate tumors change grade is a question that has implications for screening and treatment. Empirical data on tumor grade over time have become available from men biopsied regularly as part of active surveillance (AS). However, biopsy (BX) grade is subject to misclassification. In this article, we develop a model that allows for estimation of the time of grade change while accounting for the misclassification error from BX grade. We use misclassification rates from studies of prostate cancer BXs followed by radical prostatectomy. Estimation of the transition times from true low-grade to high-grade disease is conducted within a Bayesian framework. We apply our model to serial observations on BX grade among 627 cases enrolled in a cohort of AS patients at Johns Hopkins University who were biopsied annually and referred to treatment if there was any evidence of disease progression on BX. We consider different prior distributions for the time to true grade progression. The estimated likelihood of grade progression within 10 years of study entry ranges from 12% to 24% depending on the prior. We conclude that knowledge of rates of grade misclassification allows for determination of true grade progression rates among men with serial BXs on AS. Although our results are sensitive to prior specifications, they indicate that in a nontrivial fraction of the patient population, tumor grade can progress.