Applicability of logistic regression (LR) risk modelling to decision making in lung cancer resection.

摘要: The objective of this study was to evaluate the performance a locally derived risk-adjusted model predict cardiorespiratory morbidity after major lung resection for bronchogenic carcinoma. A logistic regression risk has been developed using database 515 patients undergoing between 1994 and 2001. Independent studied variables were: age patient, body mass index, predicted postoperative forced expiratory volume in first second (ppoFEV1%), cardiovascular co-morbidity, diabetes mellitus, induction chemotherapy, tumour staging, extent resection, chest wall perioperative blood transfusion. analyzed outcome occurrence complications prospectively recorded codified. Variables with an influence on univariate analysis were entered model. calculated probabilities complication compared its actual 53 consecutive cases operated January June 2002 receiver operating characteristic (ROC) curve constructed. On analysis, (P < 0.001) ppoFEV1 = 0.003) independently correlated outcome. accuracy prediction (area under ROC curve) 0.55 (95% CI: 0.31-0.78). These data show that fails individual patients.