A segregation index combining phenotypic (clinical characteristics) and genotypic (gene expression) biomarkers from a urine sample to triage out patients presenting with hematuria who have a low probability of urothelial carcinoma

摘要: Hematuria can be symptomatic of urothelial carcinoma (UC) and ruling out patients with benign causes during primary evaluation is challenging. Patients hematuria undergoing urological work-ups place significant clinical financial burdens on healthcare systems. Current involves processes that individually lack the sensitivity for accurate determination UC. Algorithms nomograms combining genotypic phenotypic variables have largely focused cancer detection failed to improve performance. This study aimed develop validate a model incorporating both high negative predictive value (NPV) combined triage who low probability having UC may not require work-up. Expression IGFBP5, HOXA13, MDK, CDK1 CXCR2 genes in voided urine sample (genotypic) age, gender, frequency macrohematuria smoking history (phenotypic) data were collected from 587 macrohematuria. Logistic regression was used models A genotypic-phenotypic (G + P INDEX) compared (G (P models. Area under receiver operating characteristic curves (AUC) defined performance each INDEX: sensitivity, NPV >0.97 test-negative rate considered optimal triaging patients. The robustness G + P INDEX tested 40 microhematuria without offered bias-corrected AUC 0.86 0.61 0.83, P G INDEXs respectively. When 0.4, (sensitivity = 0.95; NPV = 0.98) improved (sensitivity = 0.86; NPV = 0.96). 80% did correctly triaged using INDEX, therefore requiring full adoption enables change utility. segregate degree confidence evaluation. Triaging low-probability early significantly reduces need expensive invasive work-ups, thereby lowering diagnosis-related adverse events costs.