ArticleBMC medical informatics and decision making2026
Red blood cell distribution width-to-albumin ratio as a novel predictor for mortality in breast cancer patients admitted to ICU: a retrospective analysis using MIMIC-IV 3.1.
Article in BMC medical informatics and decision making, 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
backgroundThe red blood cell distribution width-to-albumin ratio (RAR), an emerging biomarker integrating inflammation and nutritional status, has not been systematically evaluated for its prognostic value in breast cancer patients admitted to intensive care units (ICU).
methodsWe conducted a retrospective cohort study using data from the MIMIC-IV 3.1 database, including 881 adult breast cancer patients admitted to the ICU. Patients were stratified into high- and low-RAR groups based on maximally selected rank statistics. Kaplan-Meier analysis, multivariable Cox proportional hazards models, restricted cubic splines, subgroup analysis, time-dependent concordance index (C-index) curves and Boruta feature selection (iterative random forest with shadow feature comparison) were applied to assess the association between RAR and 1-year all-cause mortality. Robustness was examined using E-value and propensity score weighting methods.
resultsPatients with high RAR (> 4.96) had significantly higher 1-year mortality compared to those with low RAR (log-rank P < 0.001). In adjusted models, high RAR independently predicted mortality (HR = 1.65, 95% CI: 1.33-2.06). Across the four models, E-values for the point estimates ranged from 2.18 (fully adjusted model, HR 1.65) to 2.82 (unadjusted model, HR 2.19); the E-value for the lower confidence limit of the primary model was 1.73. Each standard deviation increase in RAR was associated with a 17% higher mortality risk (HR = 1.17, 95% CI: 1.09-1.25). Restricted cubic spline analysis demonstrated a linear dose-response relationship (P for nonlinearity > 0.05). Incorporating RAR into SOFA and APS III scores improved prognostic performance (P < 0.001). Feature importance ranking further highlighted RAR as a major predictor. Sensitivity analyses using overlap-weighting (HR = 1.56, 95% CI: 1.25-1.96) and matching-weighting (HR = 1.53, 95% CI: 1.22-1.93) confirmed robustness.
conclusionRAR is an easily obtainable biomarker derived from routine laboratory testing that may enhance risk stratification for ICU-admitted breast cancer patients. Its integration into prognostic models may facilitate early decision support.
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