Creation and Validation of a Prebiopsy Nomogram for Predicting High-Risk Prostate Cancer in African American Men
Abstract
Objective and Rationale: African American men (AAM) have the highest rates of aggressive prostate cancer (PCa) on prostate biopsy; meanwhile, PSA (prostate specific antigen) screening results in detection of potentially lethal PCa along with benign enlargement and indolent PCa. Thus, an accurate means to detect potentially lethal PCa is sorely needed. Family history and PSA are the main reason that men are ultimately recommended to undergo prostate biopsy. But, family history is only present in 10%-20% of PCa patients and PSA has limited accuracy for predicting lethal PCa and also subjects many AAM without potentially lethal PCa to the pain, bleeding, and infection risk of biopsies. In order to improve the accuracy of PSA, several risk calculators (RCs) have been developed. Prominent RCs such as the Prostate Cancer Prevention Trial risk calculator 2.0 (PCPT RC) have been derived based on data from European American men (EAM). Recently, the PCPT RC has added a variable for African American (AA) race into their models for predicting overall PCa and aggressive PCa on biopsy. Genetic West African ancestry is associated with aggressive PCa risk and could be paired with the PCPT RC to potentially improve prediction accuracy in genetically admixed AAM. The results would provide objective data for decision-making to allow men to defer a biopsy or prompt an aggressive biopsy using magnetic resonance imaging (MRI)/ultrasound fusion prostate biopsies, thereby reducing overdiagnosis and enhancing detection of significant PCa. Unfortunately, no AA-tailored RC has ever been created, despite high rates of lethal PCa and high levels of medical mistrust. The overall goal of this project is to develop the best RC for predicting potentially lethal PCa in AAM undergoing prostate biopsy. Brief Description: This study will first compare the accuracy of the PCPT RC in 994 AAM versus 395 EAM using standard measures including discrimination (area under the curve) and net benefit (decision curve analysis) and by calculating the number of missed high-grade PCas and avoided biopsies in men who previously had enrolled in our observational study associating vitamin D deficiency with significant PCa. These men had at least a 12-core prostate biopsy in our institutions with available clinical and pathological data and provided DNA for future research. Of the 994 AAM, 249 will be analyzed later, leaving 745 men. We will divide the 745 men into 5 equal groups (n = 149) to create binary logistic regression models for each group that best predict potentially lethal Gleason >6 PCa from commonly available clinical variables. The top two best performing models from each of the five groups will then be tested (cross-validated) using area under the curve measurements in the other four groups. The model with the highest average area under the curve will then be tested in the 249 AAM, and the discrimination, net benefit, and number of missed Gleason >6 PCas will be calculated. We will analyze (genotype) patients’ germline DNA for determining their percentages of genetic West African ancestry. We will then add the percentage of African ancestry into the model and repeat the assessment of the discrimination, net benefit, and missed cancers. Lastly, we will prospectively recruit 395 AA men to test the accuracy of the PCPT RC and the AA-tailored model in men undergoing prostate biopsy in Chicago-area urology clinics. The accuracy will be compared using standard measures as above and the percentage of avoided biopsies. Our hypothesis is that we can create a superiorly performing RC for potentially lethal PCa tailored to AA men, which will be tested with the following specific aims: (1) Test the accuracy of the PCPT RC 2.0 for predicting the presence of significant Gleason >6 PCa in a retrospective cohort of AAM and EAM undergoing prostate biopsy. (2A) Develop and validate an AA-tailored pre-biopsy regression model for the prediction of potentia
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 29, 2018
- Source ID
- W81XWH1710608
Entities
People
- Adam B Murphy
Organizations
- Northwestern University
- United States Army