| Abstract: |
Using a population-based cohort, data from 50,598 patients treated with radical prostatectomy and pelvic lymph node dissection were used to externally validate our pathologic nodal staging score model. This model allows for quantification of the likelihood that a pathologically node-negative patient will not have lymph node metastasis after surgery. Background: We sought to externally validate our pathologic nodal staging score (pNSS) model, which allows for quantification of the likelihood that a pathologically node-negative patient will not have lymph node (LN) metastasis after radical prostatectomy for prostate cancer (PCa) in a population-based cohort. Patients and Methods: We analyzed data from 50,598 patients treated with radical prostatectomy and pelvic LN dissection using the Surveillance, Epidemiology, and End Results database. We estimated the sensitivity of pathologic nodal staging using a β-binomial model and developed a novel pNSS model, which represents the probability that a patient's PCa has been correctly staged as node negative as a function of the number of examined LNs. These findings were compared against those from the original cohort of 7135 patients. Results: The mean and median number of LNs removed was 6.5 and 5, respectively (range, 1-89; interquartile range, 2-8), and 96.9% of the patients (n = 49,020) had stage pN0. Similar to the original cohort, the probability of missing a positive LN decreased with the increasing number of LNs examined. In both the validation and the original cohort, the number of LNs needed to correctly stage a patient's disease as node negative increased with more advanced tumor stage, higher Gleason sum, positive surgical margins, and higher preoperative prostate-specific antigen levels. Conclusion: We have confirmed that the number of examined LNs needed for adequate nodal staging in PCa depends on the pathologic tumor stage, Gleason sum, surgical margins status, and preoperative prostate-specific antigen. We externally validated our pNSS in a population-based cohort, which could help to refine decision-making regarding the administration of adjuvant therapy. © 2017 Elsevier Inc. |
