Predicting Postoperative Complications in Patients With Lung Cancer and Idiopathic Pulmonary Fibrosis.

BACKGROUND AND

OBJECTIVE

Postoperative pulmonary complications are common and can be fatal in patients with IPF undergoing lung cancer surgery. This study aims to develop a novel scoring system for predicting postoperative pulmonary complications (PPCs) in patients with idiopathic pulmonary fibrosis (IPF) and non-small cell lung cancer (NSCLC) undergoing surgical resection and help establish optimal treatment strategies.

METHODS

We analysed data from 225 patients consisting of two cohorts who were diagnosed with IPF and who underwent curative resection for NSCLC. A scoring system was developed to predict postoperative pulmonary complications based on regression coefficients derived from a multivariable logistic regression model that included the following predictors: age, sex, diabetes, American Society of Anesthesiologists, diffusing capacity, and extent of surgery. Validation of the score was assessed through discrimination and calibration using a separate cohort of 51 patients.

RESULTS

Among the 276 patients analysed, 95 (34%) experienced postoperative pulmonary complications. The final model identified six predictors (with corresponding scores), resulting in a total score of 0-10 points: age ≥ 65 years (1 point), male (1 point), American Society of Anesthesiologists class ≥ 3 (1 point), diabetes (2 point), diffusing capacity ≤ 65% (2 point), and extent of surgery (3 points). The area under the curve for the scoring system was 0.75 (95% CI, 0.69-0.82) in the derivation cohort and 0.73 (95% CI, 0.57-0.88) in the validation cohort.

CONCLUSIONS

This novel scoring system consisting of six easily accessible clinical variables may help predict postoperative pulmonary complications and guide treatment decisions.