A nomogram prediction of postoperative pulmonary complications in patients undergoing lung cancer surgery

Abstract

Objective To analyze the risk factors for postoperative pulmonary complications (PPC) in patients undergoing lung cancer surgery to establish a nomogram model to predict the risk of PPC. Methods From January 2014 to October 2017, 316 patients undergoing lung cancer surgery at Shandong Provincial Hospital Affiliated to Shandong University were enrolled in this study. Their clinical data were analyzed and univariate analysis was used to determine the risk factors related to PPC. The significant variables were included in the multivariate logistic regression analysis to analyze the independent risk factors for PPC. Then the R software was used to establish a predictive nomogram model. Bootstrap method was used to validate the nomogram model and ROC curve was used to explore the predictive efficacy of the model in predicting the PPC. Results A total of 55 cases out of 316 patients undergoing lung cancer surgery had PPC. The prevalence rate was 17.4%. Age (OR=1.151, 95% CI 1.041-1.274), chronic obstructive pulmonary disease (COPD) (OR=3.659, 95%CI 1.498-8.939), smoking index (OR=1.171, 95% CI 1.055-1.300), pN stage (N1: OR=6.686, 95%CI 1.959-22.814; N2:OR=7.714,95%CI 2.390-24.900; N3: OR=15.943, 95%CI 4.318-58.869)and the poor compliance of breathing exercise (OR=1.298, 95%CI 1.031-1.635) were all independent risk factors for PPC. The nomogram model showed a conformance-index of 0.841, while ROC curve showed that the area under the curve for the nomogram model predicting pressure sores was 0.820 (95% CI: 0.760-0.881). Conclusions The nomogram built based on age, COPD, smoking index, pN stage, and the poor compliance of breathing exercises has good discrimination and accuracy which could be used for predicting individual PPC risk and screening the patients with high risk, with potentially high clinical application value. Key words: Lung neoplasms; Postoperative complications; Forecasting nomograms