Abstract

BackgroundProstate cancer (PCa) patients with prostate-specific antigen (PSA) persistence after radical prostatectomy (RP) are at increased risk of mortality, although the natural history of these men is heterogeneous and the optimal management has not been established. ObjectiveTo develop a model to predict cancer-specific mortality (CSM) and to test the impact of radiotherapy (RT) on survival in this setting. Design, setting, and participantsWe identified 496 patients treated with RP and lymph node dissection at two referral centers between 1994 and 2014 who had PSA persistence, defined as a PSA level between 0.1 and 2 ng/ml at 6–8 wk after RP. Outcome measurements and statistical analysesA multivariable model predicting CSM was developed. We assessed whether the impact of postoperative PSA levels on survival differed according to baseline CSM risk. The nonparametric curve fitting method was then used to explore the relationship between baseline CSM risk and 10-yr CSM rates according to postoperative RT. Results and limitationsMedian follow-up for survivors was 110 mo. Overall, 49 patients experienced CSM. The 10-yr CSM-free survival was 88%. Pathologic grade group and pathologic stage were independent predictors of CSM (all p=0.01). The association between CSM-free survival and PSA at 6–8 wk differed by the baseline CSM risk, whereby the effect of increasing PSA was evident only in patients with a CSM risk of ≥10%. Postoperative RT was beneficial when the predicted risk of CSM was ≥30% (p=0.001 by an interaction test). Our study is limited by its retrospective design. ConclusionsIncreasing PSA levels should be considered as predictors of mortality exclusively in men with worse pathologic characteristics. Postoperative RT in this setting was associated with a survival benefit in patients with a CSM risk of ≥30%. Conversely, individuals with a CSM risk of <30% should be initially managed expectantly. Patient summaryNot all patients with prostate-specific antigen persistence have a poor prognosis. Pathologic characteristics should be used to estimate the risk of cancer-specific mortality in these individuals and to identify patients who could benefit from postoperative radiotherapy.

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