VALIDATION OF AN MRI-BASED PROSTATE CANCER GLEASON SCORE PREDICTIVE NOMOGRAM
The Journal of Urology(2020)
Abstract
INTRODUCTION AND OBJECTIVE: Gleason score grading is a cornerstone of risk stratification and management of patients with prostate cancer (PCa). In this work, we derive and validate a nomogram that uses Multiparametric Prostate (MP)-MRI and clinical patient characteristics to predict biopsy Gleason scores (bGS). METHODS: A predictive nomogram was derived from 143 men who underwent MP-MRI prior to any prostate biopsy and then validated on an independent cohort of 235 men from a different institution who underwent MP-MRI for PCa workup. Screen positive lesions (SPLs) were defined as lesions positive on T2W and DWI sequences on MP-MRI. PSA density (PSAD), number of SPLs, and MRI suspicion were associated with PCa Gleason score on biopsy and were used to generate a predictive nomogram. The validation cohort was tested on the nomogram and the most likely bGS was noted. RESULTS: The mean PSA in the validation cohort was 9.25ng/ml vs 6.8ng/ml in the original cohort (p=0.001). In the original group, 41% of men had no cancer on biopsy, whereas 20%, 17%, and 22% had Gleason 6, 7, and ≥8 disease as compared to a distribution of 52%, 19%, 19%, and 10% in the validation group (p=0.7). In the original cohort of men, the most probable nomogram generated Gleason score agreed with actual pathologic bGS findings in 61% of the men. In the validation cohort, the most likely nomogram predicted bGS agreed with actual pathologic bGS 51% of the time. The nomogram correctly identified any PCa vs no PCa 63% of the time and clinically significant (Gleason score ≥ 7) PCa 69% of the time. CONCLUSIONS: A pre-intervention nomogram based on PSA and MRI findings can help narrow down the likely pathologic finding on biopsy. Validation of the nomogram demonstrated a significant ability to correctly identify the most likely bGS. This feasibility study demonstrates the potential of a pre-biopsy prediction of biopsy Gleason score which could have impact on future risk stratification for prostate cancer.Source of Funding: None
MoreTranslated text
Key words
prostate cancer,mri-based
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined