As of June 2007, 657 high-risk men were accrued to PRAP. This analysis includes 646 of these men with complete data for race, baseline PSA, and AIM genotypes. The demographics of this cohort by self-reported race are shown in . No differences exist in mean baseline age, PSA, percent free PSA, DRE findings, or biopsy history. In addition, the median age at entry was identical for self-reported AA and EA men at 49.0 years. Age-adjusted baseline PSA values were not significantly different between self-reported AA and EA men when testing for “race-specific PSA” effect (1.60 ng/mL vs. 1.67 ng/mL respectively, p=0.69).
Demographics and Prostate Cancer Characteristics by Self-reported Race of 646 PRAP Participants
To further explore the concept of “race-specific PSA”, we investigated if the baseline PSA was higher for PRAP men with higher genetic West African (WA) ancestry. The distribution of WA ancestry by IA estimates grouped by self-reported race is shown in and the demographics of this cohort of 646 men is the same as in .
Distribution of Individual Ancestry Estimates by Self-Reported Race in 646 PRAP Participants
As can be seen from , genetic WA ancestry was significantly higher in self-reported AA men compared to EA men. The distribution of WA ancestry varied widely in self-reported AA men compared to EA men. We found no significant correlation between IA estimates of WA ancestry and baseline PSA in self-reported EA men, however for AA men there appeared to be a nominal yet non-significant correlation (Pearson Correlations: ; EA men 0.071, p=0.30; AA men −0.024, p=0.06).
We next explored if the PSA prediction for PCA differed between AA and EA men by self-reported race using Cox models. This cohort included 411 out of the total 646 men; the remaining 235 men who were excluded were: 46 men who were not yet scheduled to return for their follow-up visit, and 189 men who did not return for any follow-up visits. Compared to the men included in the analysis, men lost to follow-up tended to be younger (mean age 46.9 year vs 50.9 years, t-test p-value <0.0001) and have lower baseline PSA values (mean PSA 1.25 ng/ml vs 1.86 ng/ml, t-test p-value = 0.001). AA men were more likely to be lost to follow-up than EA men (40% vs 19%, Chi-square test p-value <0.0001). shows the demographics and PCA characteristics of this group of 411 PRAP participants. For the Cox model analysis, an additional six PRAP men with a baseline PSA over 10 ng/mL were removed to reduce the possibility that they would be influential points (PSA levels of excluded men were 13, 15, 15, 22, 23, and 27 ng/mL). Therefore the final Cox model analyses were performed on 405 PRAP men and the results in this paper are hence only generalizable to men with PSA<=10 ng/mL. shows the plots of the Cox models of the PSA prediction for PCA at 3-years with age in the model. This 3-year time frame was chosen for study as the mean duration of follow-up in PRAP has been approximately 40–48 months. As can be seen from , the PSA had a noticeably higher prediction for PCA in the range of ~1.5–4.0 ng/mL in self-reported AA men compared to self-reported EA men. A statistically significant difference was seen by race in the association of baseline PSA to PCA development based on the Cox model when testing for interactions for race-PSA and race-age (p=0.025). When testing the model for the race-PSA interaction only, the interaction was still statistically significant (p=0.04).
Demographics and Prostate Cancer Characteristics by Self-reported Race in 411 PRAP Participants with At-Least One Follow-up Visit
Three-year Predicted Probability for Prostate Cancer of Baseline PSA by Self-Reported Race with Age in the Model
We next investigated if the higher prediction for PCA in self-reported AA men was due to the influence of genetic WA ancestry. We divided 219 self-reported AA men from into tertiles of lowest to highest IA estimates for WA ancestry. Each tertile included 73 AA men and the mean and range of WA ancestry were as follows: 0.561 (0.045–0.684) for Tertile 1, 0.785 (0.686–0.865) for Tertile 2, and 0.921 (0.866–0.995) for Tertile 3. shows the Cox model plots of 3-year prediction for PCA by baseline PSA in these tertiles of AA men with point estimates included on each figure. There is a trend for higher prediction for PCA at any given PSA in the range of 1.5–4.0 ng/mL with increasing genetic WA ancestry by IA estimates, although this was not statistically significant. Hazard ratios of PSA for PCA were significantly higher in self-reported AA men compared to self-reported EA men (1.59 [95% CI 1.38–1.84] vs. 1.30 [95% CI 1.12–1.51], p=0.04, respectively). By tertiles of WA ancestry, hazard ratios of PSA for PCA were as follows: tertile 1 = 2.19 (95% CI 1.49–3.22), tertile 2 = 1.46 (95% CI 1.19–1.79), and tertile 3 = 1.45 (95% CI 1.04–2.01). The joint test of equality of interaction terms in an interaction model was not statistically significant (p=0.150). The hazards estimated from the interaction models did not substantially differ from those reported above.
Predicted Probability for Prostate Cancer at 3-Years of the Baseline PSA with Increasing Genetic WA Ancestry in 219 AA Men in PRAP with Age in the Model