The impact of prognostic group classification on prostate cancer progression in intermediate-risk patients according to the European Association of Urology system: results in 479 patients treated with robot-assisted radical prostatectomy at a single tertiary referral center.

BACKGROUND

Treatment outcomes in intermediate-risk prostate cancer (PCa) may be impaired by adverse pathology misclassification including tumor upgrading and upstaging. Clinical predictors of disease progression need to be improved in this category of patients.

OBJECTIVES

To identify PCa prognostic factors to define prognostic groups in intermediate-risk patients treated with robot-assisted radical prostatectomy (RARP).

DESIGN

Data from 1143 patients undergoing RARP from January 2013 to October 2020 were collected: 901 subjects had available follow-up, of whom 479 were at intermediate risk.

METHODS

PCa progression was defined as biochemical recurrence and/or local recurrence and/or distant metastases. Study endpoints were evaluated by statistical methods including Cox's proportional hazards, Kaplan-Meyer survival curves, and binomial and multinomial logistic regression models.

RESULTS

After a median (interquartile range) of 35 months (15-57 months), 84 patients (17.5%) had disease progression, which was independently predicted by the percentage of biopsy-positive cores ⩾ 50% and the International Society of Urological Pathology (ISUP) grade group 3 for clinical factors and by ISUP > 2, positive surgical margins and pelvic lymph node invasion for pathological features. Patients were classified into clinical and pathological groups as favorable, unfavorable (one prognostic factor), and adverse (more than one prognostic factor). The risk of PCa progression increased with worsening prognosis through groups. A significant positive association was found between the two groups; consequently, as clinical prognosis worsened, the risk of detecting unfavorable and adverse pathological prognostic clusters increased in both unadjusted and adjusted models.

CONCLUSION

The study identified factors predicting disease progression that allowed the computation of highly correlated prognostic groups. As the prognosis worsened, the risk of PCa progression increased. Intermediate-risk PCa needs more prognostic stratification for appropriate management.