UCSF

Background

In the current study, the authors propose the quantitative Gleason score (qGS), a modification of the current Gleason grading system for prostate cancer, based on the weighted average of Gleason patterns present in the pathology specimen. They hypothesize that the qGS can improve prostate cancer risk stratification and help prevent the overtreatment of patients with clinically indolent tumors.

Methods

The qGS was applied to patients in the University of California San Francisco urologic oncology database with tumors determined to have a GS of 7 on prostate biopsy or final pathology after radical prostatectomy (RP). Using multivariable logistic regression, Cox proportional hazards regression, receiver operating characteristic (ROC), and decision curve analyses, the ability of qGS to predict pathological GS and the risk of disease recurrence after RP was assessed.

Results

A total of 225 men were included in the analysis of biopsy specimens and 618 men were included in the assessment of RP specimens. Compared with traditional Gleason scoring, the qGS improved concordance between biopsy and pathological GS on decision curve and ROC analyses (area under the curve ROC curve, 0.79 vs 0.71). On regression analysis, the qGS of biopsy specimens was found to be significantly associated with pathological grade after RP (hazard ratio [HR], 1.78; 95% confidence interval [95% CI], 1.49-2.12) and the qGS of RP specimens was significantly associated with the risk of biochemical disease recurrence after RP (HR, 1.13; 95% CI, 1.04-1.24).

Conclusions

The qGS, a simple modification of the current Gleason system, appears to improve the correlation between biopsy and pathological GS, as well as the prediction of biochemical disease recurrence after RP. This scoring system may allow more men to pursue active surveillance, thereby avoiding the morbidity of prostate cancer treatment modalities.