Clinical parameters affecting prediction accuracy of postoperative lung function in non-small cell lung cancer

Abstract

Despite significant development in chemotherapy and radiotherapy, surgery is still the cornerstone for curative lung cancer treatment. Accurate prediction of postoperative lung function is mandatory. The goal of this study was to identify important clinical factors affecting prediction accuracy of postoperative lung function for more careful patient selection. The medical records of non-small cell lung cancer patients undergoing pulmonary resection were reviewed. An accuracy index, apo/ppoFEV(1) was defined as the ratio of actual postoperative FEV(1) [apoFEV(1)] to predicted postoperative FEV(1) [ppoFEV(1)]. We used multivariate analysis to inspect the relationship between the accuracy index and seven tentative clinical factors: age, gender, preoperative FEV(1), time interval between operation and the first postoperative FEV(1), bronchodilator response (%), resected lung portion, and the number of resected lung segments. A total of 82 patients were analyzed. Accuracy index of quantitative perfusion lung scan-based prediction was better than that of simple calculation. Multivariate analysis identified the number of resected lung segments and preoperative FEV(1) as the significant clinical factors affecting the accuracy index (P=0.026 and 0.002, respectively). Preoperative FEV(1) and the number of resected lung segments are significant clinical factors affecting prediction accuracy of postoperative lung function.