Development and validation of the utLIFE-PC algorithm for noninvasive detection of prostate cancer in urine: A prospective, observational study

作者：Sujun Han, Mingshuai Wang, Yong Wang, Junlong Wu, Zhaoxia Guo, Huina Wang, Ranlu Liu, Xiaofu Qiu, Linjun Hu, Jianbin Bi, Weigang Yan, Hengqing An, Gejun Zhang, Yi Zhi, Zhiyuan Chen, Libin Chen, Lei Liu, Huanqing Cheng, Shuaipeng Zhu, Meng Wang, Yanrui Zhang, Xiao Liu, Feng Lou, Shanbo Cao, Dingwei Ye, Yuanjie Niu, Nianzeng Xing · 发表于：Cell Reports Medicine · 年份：2024 · DOI：10.1016/j.xcrm.2024.101870 · 被引用次数：4 · 研究领域：Prostate Cancer Diagnosis and Treatment、Advanced X-ray and CT Imaging、Radiomics and Machine Learning in Medical Imaging

Overbiopsy is a serious health issue in prostate cancer (PCa) diagnostics. We have developed a urine tumor DNA multidimensional bioinformatic algorithm, utLIFE, to avoid unnecessary biopsy. The objective is to recognize all or clinically significant PCa. Of the 801 participants recruited in our study, 630 are selected for subsequent analysis. In the training cohort ( n = 237), utLIFE-PC gets an area under the receiver operating characteristic curve (AUC) of 0.967 and a sensitivity of 85.57% at 95% specificity. In the independent prospective validation cohort ( n = 343), utLIFE-PC has an AUC of 0.929, sensitivity of 84.24%, and specificity of 93.26%. Notably, in patients with ≥grade group (GG)2 and ≥GG3, the assay’s sensitivity is still excellent (85.33% and 87.10%, respectively). The model shows better performance than prostate-specific antigen (PSA) ( p < 0.001) or the single-dimensional biomarkers (methylation, p < 0.001; copy-number variations [CNVs], p < 0.001; mutation, p < 0.001). The utLIFE-PC model can potentially optimize the PCa diagnostic process and avoid unnecessary biopsies. This study was registered at Chinese Clinical Trial Registry: ChiCTR2300071837. • Developed utLIFE-PC algorithm for noninvasive prostate cancer early detection • Achieved high accuracy in detecting all grades of prostate cancer • Reduced unnecessary biopsies by up to 55% in initial biopsy populations • Improved diagnostic process with high sensitivity and specificity Han et al. introduce a u...