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Background: Biopsy Gleason score (bGS) remains an important prognostic indicator for adverse outcomes in Prostate Cancer (PCA). In the light of recent studies purporting difference in prognostic outcomes for the subgroups of GS7 group (primary Gleason pattern 4 vs. 3), upgrading of a bGS of 6 to a GS≥7 has serious implications. We sought to identify pre-operative factors associated with upgrading in a cohort of GS6 patients who underwent prostatectomy., Design: We identified 281 cases of GS6 PCA on biopsy with subsequent prostatectomies. Using data on pre-operative variables (age, PSA, biopsy pathology parameters), logistic regression models (LRM) were developed to identify factors that could be used to predict upgrading to GS≥7 on subsequent prostatectomy. A decision tree (DT) was constructed., Results: 92 of 281 cases (32.7%) were upgraded on subsequent prostatectomy. LRM identified a model with two variables with statistically significant ability to predict upgrading, including pre-biopsy PSA (Odds Ratio 8.66; 2.03-37.49, 95% CI) and highest percentage of cancer at any single biopsy site (Odds Ratio 1.03, 1.01-1.05, 95% CI). This two-parameter model yielded an area under curve of 0.67. The decision tree was constructed using only 3 leave nodes; with a test set classification accuracy of 70%., Conclusions: A simplistic model using clinical and biopsy data is able to predict the likelihood of upgrading of GS with an acceptable level of certainty. External validation of these findings along with development of a nomogram will aid in better stratifying the cohort of low risk patients as based on the GS.

Purpose: Since clinically significant upgrading of the biopsy Gleason score has an adverse clinical impact, ancillary tools besides the visual determination of primary Gleason pattern are essential to aid in better risk stratification., Materials and Methods: A total of 61 prostate biopsies were selected in patients with a diagnosis of Gleason score 7 prostatic adenocarcinoma, including 41 with primary Gleason pattern 3 and 20 with primary Gleason pattern 4. Slides from these tissues were stained using Feulgen stain, a nuclear DNA stain. Areas of Gleason pattern in all cases were analyzed for 40 nuclear morphometric descriptors of size, shape and chromatin using a CAS-200 system (BD). The primary outcome analyzed was the ability of morphometric features to identify visually determined primary Gleason pattern 4 on the biopsy. Data were analyzed using logistic regression as well as a C4.5 decision tree with and without preselection., Results: Decision tree analysis yielded the best model. Automatic feature selection identified minimum nuclear diameter as the most discriminative feature in a 3-parameter model with 85% classification accuracy. Using a preselected 3-parameter model including minimum diameter, angularity and sum optical density the decision tree yielded a slightly lesser accuracy of around 79%. Bootstrap validation of logistic regression results revealed that there was no unique model that could significantly explain the variance in primary Gleason pattern status, although minimum nuclear diameter was the most frequently selected parameter., Conclusions: In this small cohort of patients with Gleason score 7 disease we report that Gleason pattern 4 nuclei from those with primary Gleason pattern 4 are generally larger with coarser chromatin compared with the Gleason pattern 4 in patients with primary Gleason pattern 3. These findings may aid in better risk stratification of the Gleason score 7 group by supplementing visual estimation of the percent of primary Gleason pattern 3 and 4 in the biopsy.