Construction and Validation of a Clinical Predictive Nomogram for Improving the Cancer Detection of Prostate Naive Biopsy Based on Chinese Multicenter Clinical Data

作者：Tao Tao, Changming Wang, Weiyong Liu, Lei Yuan, Qingyu Ge, Lang Zhang, Biming He, Lei Wang, Ling Wang, Caiping Xiang, Haifeng Wang, Shuqiu Chen, Jun Xiao · 发表于：Frontiers in Oncology · 年份：2022 · DOI：10.3389/fonc.2021.811866 · 被引用次数：10 · 研究领域：Prostate Cancer Diagnosis and Treatment、Prostate Cancer Treatment and Research、AI in cancer detection

Objectives Prostate biopsy is a common approach for the diagnosis of prostate cancer (PCa) in patients with suspicious PCa. In order to increase the detection rate of prostate naive biopsy, we constructed two effective nomograms for predicting the diagnosis of PCa and clinically significant PCa (csPCa) prior to biopsy. Materials and Methods The data of 1,428 patients who underwent prostate biopsy in three Chinese medical centers from January 2018 to June 2021 were used to conduct this retrospective study. The KD cohort, which consisted of 701 patients, was used for model construction and internal validation; the DF cohort, which consisted of 385 patients, and the ZD cohort, which consisted of 342 patients, were used for external validation. Independent predictors were selected by univariate and multivariate binary logistic regression analysis and adopted for establishing the predictive nomogram. The apparent performance of the model was evaluated via internal validation and geographically external validation. For assessing the clinical utility of our model, decision curve analysis was also performed. Results The results of univariate and multivariate logistic regression analysis showed prostate-specific antigen density (PSAD) (P<0.001, OR:2.102, 95%CI:1.687-2.620) and prostate imaging-reporting and data system (PI-RADS) grade (P<0.001, OR:4.528, 95%CI:2.752-7.453) were independent predictors of PCa before biopsy. Therefore, a nomogram composed of PSAD and PI-RAD...