Validation of models predicting lymph node involvement probability in patients with prostate cancer

Abstract

Objectives: There are many models to predict lymph node involvement in patients with prostate cancer. We aimed to externally validate several models in a Japanese cohort.

Methods: We considered patients who were treated with robotic-assisted radical prostatectomy with extended pelvic lymph node dissection for prostate cancer. The risk of lymph node involvement was calculated for each patient in several models. Model performance was assessed by calculating the receiver operating characteristic curve and the area under the curve, calibration plots, and decision curve analyses.

Results: We identified lymph node involvement in 61 (18.4%) of the 331 considered patients. Patients with lymph node involvement had a higher prostate-specific antigen level, percentage of positive biopsy cores, primary Gleason grade, Gleason group grade, and clinical T-stage category. The Memorial Sloan Kettering Cancer Center web calculator presented the highest area under the curve (0.78) followed by the Yale formula area under the curve (0.77), the updated version of Briganti nomogram of 2017 area under the curve (0.76), and the updated version of the Partin table by Tosoian et al. had an area under the curve of 0.75. However, the 95% confidence interval for these models overlapped. The calibration plot showed that the Memorial Sloan Kettering Cancer Center web calculator and the updated version of the Briganti nomogram calibrated better. In the decision curve analyses, all models showed net benefit; however, it overlapped among them. However, the Memorial Sloan Kettering Cancer Center web calculator and the updated Briganti nomogram presented the highest net benefit for lymph node involvement risks <35%.

Conclusion: Models predicting lymph node involvement were externally validated in Japanese men. The Memorial Sloan Kettering Cancer Center web calculator and the updated Briganti nomogram of 2017 were the most accurate performing models.

Keywords: lymphadenectomy; nomograms; prognosis; prostate cancer; prostatectomy.