Construction of a novel tool for predicting chronic obstructive pulmonary disease mortality in lung cancer patients.

Journal: Scientific reports

This study analyzed data from over 28,000 lung cancer patients to identify risk factors associated with COPD mortality and develop a predictive model for clinical use.

Using Cox regression analysis, the following factors were found to independently influence COPD mortality:

  • Age
  • Race
  • Sex
  • Tumor grade
  • Histological type
  • Cancer stage
  • Treatment modalities
  • Bone metastasis
  • Marital status

The predictive model demonstrated strong accuracy and reliability, with AUC values around 0.87–0.90 in both training and validation cohorts. Calibration and decision curve analyses confirmed the model’s robustness and clinical benefit.

This tool may support individualized risk assessment and guide treatment decisions for lung cancer patients with COPD.

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