Developing a prediction model in a large case-control study for the early detection of bladder cancer

在一项大型病例对照研究中建立膀胱癌早期检测的预测模型

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Abstract

BACKGROUND: Bladder cancer (BCa) is a lethal cancer, but early-detection offers an opportunity to improve prognosis. Our objective was to develop a urine-based multi-marker panel for BCa detection across multiple longitudinal cohort studies in a nested case-control study. METHODS: Longitudinal cohorts included healthy participants enrolled in the Southern Community Cohort Study (SCCS), Singapore Chinese Health Study (SCHS), Shanghai Women/Men Health Study (SWMHS), and Multiethnic Cohort (MEC). We measured the levels of 10 protein biomarkers (A1AT, ANG, APOE, CA9, IL8, MMP9, MMP10, PAI1, SDC1, and VEGF) in spot-voided urine samples using the multiplex immunoassay Oncuria. Single urine specimens collected from 274 participants who would go on to develop BCa in the ensuing 3‒60 months (i.e., cases) were age/sex-matched to 274 cancer-free controls. We used generalized estimating equation models, logistic regression analysis, and random forest algorithms to analyze the data. RESULTS: Differences in the individual biomarker levels between cases and controls were noted for ANG at 12 months (p = 0.046), APOE at 12 months (p < 0.001), MMP10 at 12 months (p = 0.009), PAI1 at 12 months (p = 0.005), SDC1 at 12 months (p = 0.003), 48 months (p = 0.029) and 60 months (p = 0.002), and VEGF at 12 months (p < 0.001). Lastly, the best preliminary model to predict subsequent BCa was IL8, CA9, PAI1, APOE and clinical features which had an AUC of 0.98, accuracy of 0.94 with a sensitivity of 0.88 and specificity of 1.00. CONCLUSIONS: Additional testing is needed; however preliminary results demonstrate that a multiplex immunoassay may be able to facilitate the early detection of BCa in at-risk patients. Identification of BCa at an early stage may lead to improved patient outcomes. PREVENTION RELEVANCE: Using large multinational patient populations, we tested the performance of the Oncuria multiplex assay to accurately predict the risk of developing bladder cancer by simultaneously analyzing the concentrations of 10 protein biomarkers in urine samples. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-025-07511-1.

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