ArticleIn vivo (Athens, Greece)
An Emergency-deployable Albumin-enhanced NLR Derived by Machine Learning Improves Risk Stratification in Lung Cancer: A Multicenter Cohort Study.
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Abstract
BACKGROUND/
aimSystemic inflammation is tightly linked to lung cancer prognosis, yet widely used blood-based indices show only modest discrimination. We aimed to develop a simple, albumin-enhanced inflammatory index to improve risk stratification. PATIENTS AND
methodsUsing the Investigation on Nutrition Status and Clinical Outcome of Common Cancer database, 1,576 patients with lung cancer with complete baseline data were randomly split into a training cohort (n=1,104) and an internal validation cohort (n=472). LASSO regression screened prognostically informative laboratory markers. Conventional inflammatory indices were compared by Harrell's C-index. A supervised machine-learning approach integrated serum albumin level with the neutrophil-to-lymphocyte ratio (NLR) to derive an albumin-enhanced NLR score (aNLR). Prognostic value was tested with Cox models (three prespecified adjustment levels), restricted cubic splines, Kaplan-Meier analysis, time-dependent area under the receiver operating characteristics curve, calibration, and decision curve analysis.
resultsLASSO highlighted lymphocyte count, albumin level, and neutrophil count as dominant factors in predicting prognosis. Among conventional indices, NLR showed the highest discrimination (C-index 0.600). The derived aNLR markedly improved performance (overall C-index 0.727; training 0.725; validation 0.731). Using an outcome-driven cutoff (0.56), high aNLR was consistently associated with worse survival (unadjusted hazard ratio=2.39, 95% confidence interval=2.21-2.58; fully adjusted hazard ratio=2.14, 95% confidence interval=1.97-2.32; both
conclusionAn albumin-enhanced NLR, created by machine-learning fusion of albumin and NLR, provides substantially better prognostic discrimination than conventional inflammatory indices and supports individualized survival assessment in lung cancer.
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