关键词: 前列腺肿瘤, 前列腺特异性抗原, 影像学报告和数据系统第2版

Abstract:

Objective To explore the predictive value of prostate specific antigen mass ratio (PSAMR) combined with prostate imaging reporting and data system version 2 (PI-RADS v2) score for high-grade prostate cancer. Methods The clinical data and auxiliary examination data of 207 patients with prostate biopsy and definite pathological diagnosis in the Affiliated Hospital of Panzhihua University from June 2017 to June 2020 were retrospectively analyzed. All patients were taken blood for prostate specific antigen (PSA), and underwent multi parameter magnetic resonance imaging and prostate biopsy. According to the gold standard of pathological biopsy diagnosis, all patients were divided into two groups: high-grade prostate cancer group (n=95) and non-high-grade prostate cancer group (n=112) (including 26 cases of low-grade prostate cancer and 86 cases of benign prostate disease). The patient's age, prostate volume, PSA, prostate specific antigen density (PSAD), PSAMR and PI-RADS v2 score in the two groups were compared. The independent predictors of high-grade prostate cancer were selected by multivariate analysis. Logistic regression model with independent predictors was established for the prediction of high-grade prostate cancer. Receiver operating characteristic (ROC) curve was used to analyze the predictive value, and the area under the curve (AUC) was calculated. Results In the high-grade prostate cancer group and non-high-grade prostate cancer group, the ages of patients were (77.34±7.76) years and (67.96±7.02) years, and there was a statistically significant difference (t=4.02, P<0.001); the prostate volumes were (44.00±15.31) cm³ and (63.90±28.45) cm³, and there was a statistically significant difference (t=19.05, P<0.001); the PSA levels of patients were (35.42±12.90) μg/L and (18.85±8.69) μg/L, and there was a statistically significant difference (t=6.55, P<0.001); the PSAD of patients were (0.86±0.36) μg/(L·cm³) and (0.32±0.13) μg/(L·cm³), and there was a statistically significant difference (t=12.85, P<0.001); the PSAMR of patients were 4.71±0.30 and 1.79±0.13, and there was a statistically significant difference (t=9.23, P<0.001); the PI-RADS v2 scores were 4.31±0.88 and 2.73±0.87, and there was a statistically significant difference (t=6.12, P=0.001). Logistic regression analysis showed that there were statistically differences in age, PSA, prostate volume, PSAMR, PSAD and PI-RADS v2 scores (all P<0.05). The AUC value of PSAMR in predicting high-grade prostate cancer was 0.834 (threshold value was 2.480, P<0.001), the sensitivity was 0.804, and the specificity was 0.726. The AUC value of PI-RADS v2 score was 0.874 (threshold value was 3.500, P<0.001), the sensitivity was 0.800, and the specificity was 0.821. The AUC value of PSAMR combined with PI-RADS v2 score was 0.922 (threshold value was 0.690, P<0.001), the sensitivity was 0.995, and the specificity was 0.758. Conclusion PSAMR combined with PI-RADS v2 score can improve the diagnostic efficiency for predicting high-grade prostate cancer.

Key words: Prostatic neoplasms, Prostate specific antigen, Prostate imaging reporting and data system version 2