Purpose: We created a clinically applicable nomogram to predict locally advanced prostate cancer using preoperative parameters and performed external validation using an external independent validation cohort.
Patients and methods: From a retrospective multicenter cohort study of 3622 Japanese patients with prostate cancer who underwent robot-assisted radical prostatectomy at ten institutions, the patients were divided into two groups (MSUG cohort and validation cohort). Locally advanced prostate cancer was defined as pathological T stage ≥ 3a. A multivariable logistic regression model was used to identify factors strongly associated with locally advanced prostate cancer. Bootstrap area under the curve was calculated to assess the internal validity of the prediction model. A nomogram was created as a practical application of the prediction model, and a web application was released to predict the probability of locally advanced prostate cancer.
Results: A total of 2530 and 427 patients in the MSUG and validation cohorts, respectively, met the criteria for this study. On multivariable analysis, initial prostate-specific antigen, prostate volume, number of cancer-positive and cancer-negative biopsy cores, biopsy grade group, and clinical T stage were independent predictors of locally advanced prostate cancer. The nomogram predicting locally advanced prostate cancer was demonstrated (area under the curve 0.72). Using a nomogram cutoff of 0.26, 464 of 1162 patients (39.9%) could be correctly diagnosed with pT3, and 2311 of 2524 patients (91.6%) could avoid underdiagnosis.
Conclusions: We developed a clinically applicable nomogram with external validation to predict the probability of locally advanced prostate cancer in patients undergoing robot-assisted radical prostatectomy.
Keywords: Locally advanced prostate cancer; Nomogram; Prostate cancer; Robot-assisted radical prostatectomy.
© 2023. Society of Surgical Oncology.