文献类型：期刊文献

英文题名：Artificial intelligence-aided detection for prostate cancer with multimodal routine health check-up data: an Asian multi-center study

作者：Song, Zijian[1,2];Zhang, Wei[1];Jiang, Qingchao[3,4];Deng, Longxin[1];Du, Le[3,4];Mou, Weiming[1,5];Lai, Yancheng[1];Zhang, Wenhui[1];Yang, Yang[6];Lim, Jasmine[7];Liu, Kang[8];Park, Jae Young[9];Ng, Chi-Fai[8];Ong, Teng Aik[7];Wei, Qiang[10];Li, Lei[11];Wei, Xuedong[12];Chen, Ming[13];Cao, Zhixing[3,4,18];Wang, Fubo[14,15,16,19];Chen, Rui[1,2,17]

机构：[1]Second Mil Med Univ, Shanghai Changhai Hosp, Dept Urol, Shanghai, Peoples R China;[2]Shanghai Jiao Tong Univ, Sch Med, Renji Hosp, Dept Urol, Shanghai, Peoples R China;[3]Minist Educ, Key Lab Smart Mfg Energy Chem Proc, Shanghai, Peoples R China;[4]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai, Peoples R China;[5]Shanghai Jiao Tong Univ, Sch Med, Shanghai Gen Hosp, Dept Urol, Shanghai, Peoples R China;[6]Nanjing Univ, Nanjing Jinling Hosp, Dept Clin Lab, Sch Med, Nanjing, Peoples R China;[7]Univ Malaya, Dept Urol, Med Ctr, Kuala Lumpur, Malaysia;[8]Chinese Univ Hong Kong, SH Ho Urol Ctr, Dept Surg, Hong Kong, Peoples R China;[9]Korea Univ, Ansan Hosp, Dept Urol, Soule, South Korea;[10]Sichuan Univ, West China Hosp, Inst Urol, Dept Urol, Chengdu, Sichuan, Peoples R China;[11]Xi An Jiao Tong Univ, Affiliated Hosp 1, Dept Urol, Xian, Shaanxi, Peoples R China;[12]Soochow Univ, Affiliated Hosp 1, Dept Urol, Suzhou, Peoples R China;[13]Southeast Univ, Zhongda Hosp, Dept Urol, Nanjing, Peoples R China;[14]Guangxi Med Univ, Sch Life Sci, Nanning, Guangxi, Peoples R China;[15]Guangxi Med Univ, Ctr Genom & Personalized Med, Guangxi Collaborat Innovat Ctr Genom & Personalize, Guangxi Key Lab Genom & Personalized Med, Nanning, Guangxi, Peoples R China;[16]Guangxi Med Univ, Affiliated Hosp 1, Dept Urol, Nanning, Guangxi, Peoples R China;[17]168 Changhai Rd, Shanghai, Peoples R China;[18]130 Meilong Rd, Shanghai 200237, Peoples R China;[19]22 Shuangyong Rd, Nanning, Guangxi Zhuang, Peoples R China

年份：2023

卷号：109

期号：12

起止页码：3848

外文期刊名：INTERNATIONAL JOURNAL OF SURGERY

收录：;EI(收录号：20230251733);WOS:【SCI-EXPANDED(收录号:WOS:001556237500003)】；

基金：This study is supported by the National Natural Science Foundation of China (82272905), the Rising-Star Program of the Science and Technology Commission of Shanghai Municipality (21QA1411500), and the Shanghai Action Plan for Technological Innovation Grant (No. 22ZR1478000, 22ZR1415300, 22511104000, 23S41900500).

语种：英文

外文关键词：artificial intelligence; diagnosis; prostate biopsy; Prostate cancer; risk prediction

摘要：Background:The early detection of high-grade prostate cancer (HGPCa) is of great importance. However, the current detection strategies result in a high rate of negative biopsies and high medical costs. In this study, the authors aimed to establish an Asian Prostate Cancer Artificial intelligence (APCA) score with no extra cost other than routine health check-ups to predict the risk of HGPCa.Patients and methods:A total of 7476 patients with routine health check-up data who underwent prostate biopsies from January 2008 to December 2021 in eight referral centres in Asia were screened. After data pre-processing and cleaning, 5037 patients and 117 features were analyzed. Seven AI-based algorithms were tested for feature selection and seven AI-based algorithms were tested for classification, with the best combination applied for model construction. The APAC score was established in the CH cohort and validated in a multi-centre cohort and in each validation cohort to evaluate its generalizability in different Asian regions. The performance of the models was evaluated using area under the receiver operating characteristic curve (ROC), calibration plot, and decision curve analyses.Results:Eighteen features were involved in the APCA score predicting HGPCa, with some of these markers not previously used in prostate cancer diagnosis. The area under the curve (AUC) was 0.76 (95% CI:0.74-0.78) in the multi-centre validation cohort and the increment of AUC (APCA vs. PSA) was 0.16 (95% CI:0.13-0.20). The calibration plots yielded a high degree of coherence and the decision curve analysis yielded a higher net clinical benefit. Applying the APCA score could reduce unnecessary biopsies by 20.2% and 38.4%, at the risk of missing 5.0% and 10.0% of HGPCa cases in the multi-centre validation cohort, respectively.Conclusions:The APCA score based on routine health check-ups could reduce unnecessary prostate biopsies without additional examinations in Asian populations. Further prospective population-based studies are warranted to confirm these results.