A simple risk stratification model for prostate cancer using histopathologic findings of radical prostatectomy.

Autor: Semba, Remi, Uchida, Katsunori, Hirokawa, Yoshihumi, Shiraishi, Taizo, Onishi, Takehisa, Sasaki, Takeshi, Inoue, Takahiro, Watanabe, Masatoshi, Miyamoto, Hiroshi
Předmět:
Zdroj: American Journal of Clinical Pathology; Oct2024, Vol. 162 Issue 4, p420-425, 6p
Abstrakt: Objectives To develop a simple postoperative risk stratification based on histopathologic findings from radical prostatectomy specimens. Methods This study included 3 cohorts of patients with a preoperative diagnosis of clinically localized prostate cancer: 1 derivation cohort (n = 432) and 2 validation cohorts (n = 506 and n = 720). First, a postoperative risk stratification model was developed in the derivation cohort using the factors extraprostatic extension, surgical margin status, seminal vesicle invasion, and lymph node involvement. Each of the first 3 factors was assigned 0 or 1 point for negative or positive results, respectively, and the sum of the points, ranging from 0 to 3, was scored. pN1 was not scored but was analyzed separately. Validation cohorts were then used to evaluate the predictive accuracy of the model. Additionally, we compared the model with the Cancer of the Prostate Risk Assessment (CAPRA) score. Results Because the log-rank test showed no statistically significant differences between scores 1 vs 2 or score 3 vs pN1 in the derivation cohort, the following 3-level risk stratification was created: low risk (score 0), intermediate risk (score 1-2), and high risk (score 3 or pN1). There were statistically significant differences in recurrence-free survival between any of 2 groups of 3-level risk stratification. This model similarly worked in both validation cohorts. The C indexes for the model were higher than those for the CAPRA score. Conclusions This simple postoperative risk stratification model, based on radical prostatectomy findings, has a prognostic impact that has been validated in a multicenter population. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index