임상적으로 유의미한 전립선암의 예측 향상을 위한 Prostate Health Index와 PI-RADS Version 2 조합의 유용성

초록

Purpose: To evaluate the performance of combining prostate health index (PHI) and Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for detection of clinically significant prostate cancer (csPCa).Materials and Methods: We retrospectively reviewed patients who underwent prostate biopsy for elevated prostate-specific antigen (PSA) ≥2.5 ng/mL and/or abnormal digital rectal examination. Serum markers for PSA, free PSA (fPSA), and [-2] proPSA (p2PSA) were measured, and PHI was calculated as ([p2PSA/fPSA]×[PSA]1/2). Multiparametric magnetic resonance imaging was performed using a 3.0T scanner and scored using PI-RADSv2. csPCa was defined as either grade group (GG) ≥2 disease or GG1 cancer detected in >2 cores or >50% of positive on biopsy. Univariable and multivariable logistic regression modelling, along with receiver-operating characteristic (ROC) curve analysis was used to predict the probability of csPCa.Results: Of the total 358 patients, 159 (44.4%) were diagnosed with csPCa. On univariable analysis, age, PSA density (PSAD), PHI and PI-RADSv2 were associated with csPCa. The area under the ROC curve (AUC) of baseline model incorporating age and PSAD was 0.663. The AUC of combining PHI and PI-RADSv2 to baseline model was higher than that of PHI alone to baseline model (0.884 vs. 0.807, p<0.0001) and PI-RADSv2 alone to baseline model (0.884 vs. 0.846, p=0.0002), respectively. If biopsy was restricted to patients with PI-RADS 5 as well as PI-RADS 3 or 4 and PHI ≥27, 36.0% of unnecessary biopsy could be avoided at the cost of missing 4.7% of csPCa.Conclusions: The combination of PHI and PI-RADSv2 to baseline model incorporating age and PSAD had higher accuracy for detection of csPCa compared with PHI or PI-RADSv2 alone.

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