Correlation of unfavourable and favourable histology at radical prostatectomy with Decipher scores and freedom from biochemical recurrence.

[INTRODUCTION] A recent study proposed a system of unfavourable and favourable histology categories to risk-stratify prostate cancer patients. We hypothesized that unfavourable histology would be associated with higher Decipher radical prostatectomy (RP) scores and would improve biochemical recurrence (BCR) prediction.

[MATERIALS AND METHODS] The RP slide with Decipher testing was classified as having either unfavourable or favourable histology, with unfavourable histology defined as the presence of Gleason pattern 5, large cribriform (diameter >0.25 mm), intraductal carcinoma, complex intraluminal papillary architecture, anastomosing cords of epithelium with or without cribriform spaces and/or grade 3 stromogenic carcinoma. Favourable histology was defined as the absence of unfavourable histology patterns. The association between favourable/unfavourable histology and Decipher RP score was evaluated using the Mann-Whitney test. Univariable and multivariable analyses to test for a statistically significant association between the predictors favourable/unfavourable histology, age, PSA at diagnosis, race, RP grade group, pT and pN stage and margin status and the risk of BCR were performed.

[RESULTS] Four hundred and eleven RP cases from 2014 to 2020 were classified as 306 (74.5%) unfavourable and 105 (25.5%) favourable. Median Decipher scores were 0.7 for unfavourable and 0.52 for favourable (P < 0.001), corresponding to Decipher assay high and intermediate risk categories, respectively. On univariate analysis, unfavourable histology compared to favourable histology was significantly associated with decreased time to BCR, which remained significant in a multivariable model (HR 1.65; 95% CI 1.04-2.64, P = 0.035).

[CONCLUSIONS] Unfavourable histology was associated with higher Decipher scores and increased BCR risk. The addition of the histology category improved BCR prediction in a multivariable model.