External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular...

Recently developed algorithm for prediction of side-specific extracapsular extension (ECE) of prostate cancer required validation before being recommended to use. The algorithm assumed that ECE on a particular side was not likely with same side maximum tumor diameter (MTD) <15 mm AND cancerous tissue in ipsilateral biopsy <15% AND PSA <20 ng/mL (both sides condition). The aim of the study was to validate this predictive tool in patients from another department.

Data of 154 consecutive patients (308 prostatic lateral lobes) were used for validation. Predictive factors chosen in the development set of patients were assessed together with other preoperative parameters using logistic regression to check for their significance. Sensitivity, specificity, negative and positive predictive values were calculated for bootstrapped risk-stratified validation dataset.

Validation cohort did not differ significantly from development cohort regarding PSA, PSA density, Gleason score (GS), MTD, age, ECE and seminal vesicle invasion rate. In bootstrapped data set (n = 200 random sampling) algorithm revealed 70.2% sensitivity (95% confidence interval (CI) 58.8-83.0%), 49.9% specificity (95%CI: 42.0-57.7%), 83.9% negative predictive value (NPV; 95%CI: 76.1-91.4%) and 31.1% positive predictive value (PPV; 95%CI: 19.6-39.7%). When limiting analysis to high-risk patients (Gleason score >7) the algorithm improved its performance: sensitivity 91%, specificity 47%, PPV 53%, NPV 89%.

Analyzed algorithm is useful for identifying prostate lobes without ECE and deciding on ipsilateral nerve-sparing technique during radical prostatectomy, especially in patients with GS >7. Due to significant number of false positives in case of: MTD ≥15 mm OR cancer in biopsy ≥15% OR PSA ≥20 ng/mL additional evaluation is necessary to aid decision-making.