ArticleAmerican journal of cancer research2026
Construction and validation of a prognostic prediction model for critically ill lung cancer patients based on respiratory functional reserve and systemic inflammatory characteristics.
Article in American journal of cancer research, 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
Critically ill lung cancer (LC) patients are often admitted to the Department of Respiratory and Critical Care Medicine (RCCM), the Intensive Care Unit (ICU), or the Emergency Intensive Care Unit (EICU), where early risk stratification is essential because of their high short-term mortality. Despite close monitoring, their short-term mortality remains high, and general scoring systems fail to account for tumor-specific pathology. A total of 541 patients with pathologically or cytologically confirmed LC hospitalized in the RCCM, ICU, or EICU were enrolled. They were randomly divided into a training set (n=379) and a validation set (n=162) at a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) Cox regression with 10-fold cross-validation was used for variable selection. Restricted cubic spline analysis examined nonlinearity, and the Schoenfeld residual test verified the proportional hazards assumption. Multivariable Cox regression identified five independent predictors of 28-day mortality: pulse oxygen saturation (SpO
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