攝護腺健康指數密度在臨床顯著攝護腺癌檢測中的表現優於攝護腺健康指數

蔣智宏^1,3、邱士庭¹、鄭詠庭²、蒲永孝¹、呂育全¹、洪健華¹、鐘旭東⁴、黃昭淵¹

¹臺大醫院泌尿部；²新竹臺大醫院泌尿部；³北榮員山分院泌尿外科；⁴亞東紀念醫院泌尿外科

Prostate Health Index Density Outperforms Prostate Health Index in Clinically Significant Prostate Cancer Detection

Chih-Hung Chiang^1,3, Shih-Ting Chiu¹, Yung-Ting Cheng², Yeong-Shiau Pu¹, Yu-Chuan Lu¹, Jian-Hua Hong¹, Shiu-Dong Chung^4,5, Chao-Yuan Huang¹*

¹Department of Urology, National Taiwan University Hospital, Taipei, Taiwan

²Department of Urology, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu City, Taiwan

³Department of Urology, Taipei Veterans General Hospital, Yuan-Shan/Su-Ao Branch, Yi-Lan, Taiwan

⁴Division of Urology, Department of Surgery, Far-Eastern Memorial Hospital, New Taipei, Taiwan.

Purpose: Prostate-specific antigen (PSA) is considered neither sensitive nor specific for prostate cancer (PCa). We aimed to compare total PSA (tPSA), percentage of free PSA (%fPSA), the PSA density (PSAD), Prostate Health Index (PHI), and the PHI density (PHID) to see which one could best predict clinically significant prostate cancer (csPCa): a potentially lethal disease.

Materials and Methods: A total of 412 men with PSA of 2–20 ng/mL were prospectively included. Serum biomarkers for PCa was collected before transrectal ultrasound guided prostate biopsy. PHI was calculated by the formula: (p2PSA/fPSA) x √tPSA. PHID was calculated as PHI divided by prostate volume measured by transrectal ultrasound.

Results: Of the 412 men, 134 (32.5%) and 94(22.8%) were diagnosed with PCa and csPCa, respectively. We used the area under the receiver operating characteristic curve (AUC) and decision curve analyses (DCA) to compare the performance of PSA related parameters, PHI and PHID in diagnosing csPCa. AUC for tPSA, %fPSA, %p2PSA, PSAD, PHI and PHID were 0.56、0.63、0.76、0.74、0.77 and 0.82 respectively for csPCa detection. In the univariate analysis, the prostate volume, tPSA, %fPSA, %p2PSA, PHI, PSAD, and PHID were all significantly associated with csPCa, and PHID was the most important predictor (OR 1.41, 95% CI 1.15–1.72). Besides, The AUC of PHID was significantly larger than PHI in csPCa diagnosis (p=0.004). At 90% sensitivity, PHID had the highest specificity (54.1%) for csPCa and could reduce the most unnecessary biopsies (43.7%) and miss the fewest csPCa (8.5%) when PHID ≥ 0.67. In addition to AUC, DCA re-confirmed the clinical benefit of PHID over all PSA-related parameters and PHI in csPCa diagnosis. The PHID cut-off value was positively correlated with the csPCa ratio in the PHID risk table, which is useful for evaluating csPCa risk in a clinical setting.

Conclusions: The PHID is an excellent predictor of csPCa. The PHID risk table may be used in standard clinical practice to pre-select men at the highest risk of harboring csPCa.