ArticlemedRxiv : the preprint server for health sciences2026
The urinary-metabolite-based lung cancer index (uLCI): an interpretable machine-learning risk model for early-stage disease.
Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Five-year survival from lung cancer exceeds 60% at stage I-II but falls below 10% once metastasis occurs. Low-dose CT (LDCT) screening reduces mortality in heavy smokers but carries a false-positive rate of approximately 29% and is restricted to smoking-based eligibility, leaving most cases undetected. We aimed to develop and independently validate an interpretable machine-learning urinary metabolite risk index (uLCI) for non-invasive lung cancer detection. Methods: Four urinary metabolites-creatine riboside (CR), N-acetylneuraminic acid (NANA), 27-nor-5β-cholestane-3α,7α,12α,24 Findings: uLCI achieved an area under the curve (AUC) of 0·906 (95% CI 0·887-0·926) in NCI-MD and 0·748 (0·701-0·793) in the independent Colorado cohort. Scores rose monotonically across stages in both cohorts (Spearman ρ=0·69 and 0·45; both p<0·0001). Stage-specific discrimination was preserved from stage I to IV (NCI-MD 0·900-0·927; Colorado 0·722-0·843). Net reclassification improvement over clinical variables was 1·24 (1·14-1·36) and 0·74 (0·56-0·90). uLCI tertiles stratified post-resection survival in stage I-II disease (adjusted hazard ratio 2·03, 1·26-3·27). Interpretation: uLCI is an independently validated, interpretable urinary risk index that detects lung cancer across all stages, with monotonic stage progression and post-resection prognostic value. Its false-positive rate compares favourably with published estimates for LDCT and cell-free-DNA assays, supporting prospective head-to-head evaluation as a non-invasive triage tool, including in screening-ineligible populations. Funding: Intramural Research Program, Center for Cancer Research, National Cancer Institute, US National Institutes of Health.
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