In low-risk prostate cancer (PCa) males, researchers sought to construct and verify a prediction model to predict the likelihood of unfavorable pathology results in final pathology.

In the study, 426 men who underwent radical prostatectomy (RP) for low-risk PCa performed a monocentric retrospective analysis. A total of 103 males from another institution were included in the validation cohort. A non-organ confined disease (pathologic stage ≥pT3a) or an improvement in RP Gleason Score (GS) (from GS 3+3 to GS ≥3+4 with Gleason pattern 4≥10%) were both considered adverse pathology outcomes. Multivariable logistic regression analysis was used to create a nomogram for forecasting a poor pathology result. By measuring the area under the receiver operating characteristic curves (AUC) and comparing the probabilities predicted by the nomogram with the actual rates of bad pathological results in the external cohort, nomogram validation was carried out.

A negative pathological result on RP was present in 45.7% of the 426 males in the development cohort. Age, body mass index, prostate-specific antigen density, previous negative biopsy history, magnetic resonance imaging, prostate imaging reporting and data system score 4-5, and proportion of positive biopsies were all significant predictors in the multivariate analysis. A nomogram was created with an 87% area under the curve. The validation cohort’s rates of unfavorable pathology outcomes were consistent with predictions. The 5-year biochemical recurrence-free survival rates were 70% and 98% in patients with and without poor pathology outcomes.

The innovative nomogram might be useful in determining low-risk PCa males at risk of negative pathologic outcomes and guiding treatment choices.