Prediction of indolent prostate cancer: validation and updating of a prognostic nomogram

Abstract

Purpose: Screening with serum prostate specific antigen testing leads to the detection of many prostate cancers early in their natural history. Statistical models have been proposed to predict indolent cancer. We validated and updated model predictions for a screening setting.

Materials and methods: We selected 247 patients with clinical stage T1C or T2A from the European Randomized Study on Screening for Prostate Cancer who were treated with radical prostatectomy. We validated a nomogram that had previously been developed in a clinical setting. Predictive characteristics were serum prostate specific antigen, ultrasound prostate volume, clinical stage, prostate biopsy Gleason grade, and total length of cancer and noncancer tissue in biopsy cores. Indolent cancer was defined as pathologically organ confined cancer 0.5 cc or less in volume without poorly differentiated elements. Logistic regression was used to update the previous model and examine the contribution of other potential predictors.

Results: Overall 121 of 247 patients (49%) had indolent cancer, while the average predicted probability was around 20% (p <0.001). Effects of individual variables were similar to those found before and discriminative ability was adequate (AUC 0.76). An updated model was constructed, which merely recalibrated the nomogram and did not apply additional predictors.

Conclusions: Prostate cancers identified in a screening setting have a substantially higher likelihood of being indolent than those predicted by a previously proposed nomogram. However, an updated model can support patients and clinicians when the various treatment options for prostate cancer are considered.