Prioritizing precision: detection of prostate cancer using mri guided fusion needle biopsy across the pennsylvania...

Targeted prostate biopsies are increasingly being performed by urologists in the United States including those in the Pennsylvania Urologic Regional Collaborative, a physician-led data-sharing and quality improvement collaborative. To evaluate the performance of MRI guided fusion needle prostate biopsies in the collaborative, we analyzed the variability by practice in rates of detection of clinically significant prostate cancer and patient characteristics associated with detection of clinically significant prostate cancer.

We analyzed 857 first-time MRI fusion biopsy procedures performed at five practices (minimum 20 procedures) between 2015 and 2019. We used chi-square analysis for baseline patient characteristics and Grade Group (GG) ≥ 3 tumor detection rates by practice. Multivariable logistic regression was used to estimate the odds of clinically significant cancer detection when adjusting for baseline patient characteristics.

Approximately 15% of men undergoing targeted MRI guided biopsy were ≤ 59 years old. Median prostate specific antigen (PSA) was 6.8 ng/ml. Detection rates for GG ≥ 3 tumors ranged from 14.3% to 28.3% (P = 0.02) across practices. However, the odds of GG ≥ 3 tumor detection did not differ significantly between practices after adjusting for clinical and radiographic factors. Overall, increased likelihood of detecting a GG ≥ 3 tumor was associated with increased age, DRE abnormalities, higher PSA, smaller gland volume and PI-RADS ≥ 4 MRI lesions. There was an 81% concordance rate between PI-RADS ≥ 4 and Gleason grade ≥ 3 prostate cancer.

We demonstrate the value of obtaining pre-biopsy MRI given high concordance between presence of suspicious lesions and MRI-targeted biopsy detection of clinically significant prostate cancer. Variability of baseline patient characteristics among practices may account for the observed differences in clinically significant cancer detection rates. These findings can aid standardization and quality improvement efforts within the collaborative.