Sophisticated refinements in histopathology are evolving to improve meningioma outcome prediction. The aim of this study is to evaluate the stand-alone performance of Ki-67 and progesterone receptor (PR) algorithm scores in meningiomas and their power in predicting recurrence and disease-free survival of the patients. Whole slide images of Ki-67 and PR-stained slides from 404 meningioma cases were analyzed by a digital image viewer and analysis software Virapath-2.1, which analyzes the tumor cells by size, color, and shape. Ki-67 scores were calculated in the hotspot region that contains at least 1000 tumor cells, while PR was calculated on the whole slide. The results were compared with WHO grade, tumor recurrence and disease-free survival (DFS). Mean Ki-67 scores were 4.2 ± 3.5, 12.1 ± 10.6 and 22. ± 8.5 for grade 1, 2 and 3 tumors (p <
0.05), while PR scores were 49 ± 35, 43 ± 34 and 16 ± 30, respectively (p >
0.05). Median survival of patients based on Ki-67 values ≤13.2 % and >
13.2 % was 122 versus 60 months (p = 0.004). Prediction of recurrence based on Ki-67 score was found to have acceptable discrimination (AUC = 0.74). PR expression was not found to correlate with DFS, but recurrent tumors had lower PR scores than non-recurrent tumors (31.3 ± 33.8 vs. 49.0 ± 33.0
p = 0.03). Elevated Ki-67 levels identified by the algorithm may classify meningioma patients at high recurrence risk and inform clinical management. Although PR scores did not correlate with DFS, lower expression in recurrent tumors suggests a role in recurrence risk assessment. Larger prospective studies are needed for routine clinical practice.