The percentage of high-grade prostatic adenocarcinoma in prostate biopsies significantly improves on Grade Groups in the prediction of prostate cancer death
Berney DM., Beltran L., Sandu H., Soosay G., Møller H., Scardino P., Murphy J., Ahmad A., Cuzick J.
Aims: It has been recommended that the percentage of high-grade (HG) Gleason patterns 4 and 5 should be quantified in prostate cancer. However, this has not been assessed in a cohort using prostate cancer death as an outcome, and there is debate as to whether the biopsy with the ‘worst’ percentage of HG disease or an ‘overall’ percentage of HG disease should be reported. Such data may assist in active surveillance decisions. Methods and results: Men with clinically localised prostate cancer diagnosed by needle biopsy from 1990 to 2003 were included. The endpoint was prostate cancer death. Clinical variables included Gleason score (GS), prostate-specific antigen level, age, clinical stage, and disease extent. Deaths were divided into those from prostate cancer and those from other causes, according to World Health Organization criteria. Nine hundred and eighty-eight biopsy cases were centrally reviewed according to criteria agreed at the Chicago International Society of Urological Pathology conference in 2014. Cores were given individual GSs and Grade Groups (GGs), and a percentage of each grade was given for each core. Both the worst percentage of HG disease seen in a biopsy series and overall percentage of HG disease were calculated. The overall percentage of HG disease was highly significant, with a hazard ratio of 4.45 for the interquartile range (95% confidence interval 3.30–6.01, P ' 2.2 × 10−16), and was similar to the percentage of HG disease seen in the worst core. In multivariate analysis, both were highly significant. GG2 cases with ≤5% Gleason pattern 4 showed similar survival to GG1 cases. Conclusions: These data validate the use of percentage of HG disease to predict prostate cancer death. As both worst and overall percentage of HG disease are powerful predictors of outcome, either could be chosen to provide prognostic information.