Planning of Prostate Cancer Biopsies and Interpretation of Biopsy Results Using Rules Based on Gland Volume and Number of Positive Cores

• Activity Number: 561
• Type: Contributed
• Date/Time: Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Gerald Ogola*+ and Robert Serfling
• Companies: Baylor Health Care System and University of Texas at Dallas
• Keywords: Prostate cancer biopsy ; Interpretation of Biopsy Results ; Specificity ; Sensitivity ; Bayesian posterior distributions

Abstract

A major dilemma in prostate cancer detection and diagnosis is how to avoid both overtreatment and undertreatment. When biopsy results are positive but only marginally so, it is challenging to decide between clinically insignificant and significant cases. It also is unclear how many more biopsy cores to take in larger prostates. To address this, we have developed probability modeling for the number of positive cores found in a biopsy, as a function of the total number of cores, the tumor nodule volumes, and prostate volume. This yields specificity and sensitivity values for any given criterion for deciding "insignificant" versus "significant" cancer based on the number of positive cores. We show how to utilize this modeling to obtain a guideline for increasing the number of cores with increasing prostate volume and to develop improved decision rules that take prostate volume into account and offer better trade-offs of specificity versus sensitivity than currently used procedures. Also, in conjunction with prior distributions on total tumor size, the probability modeling yields useful Bayesian posterior distributions on total tumor volume.