Surgical lung cancer: Risk operative analysis

Abstract Study objective: To identify those variables that are associated with operative morbidity or mortality in cases of thoracotomy in lung cancer. Setting: Third level university hospital. Patients: Consecutive patients with thoracotomy due to lung cancer operated on between 1994 and 1997 ( n =115). Methods: Pre- and postoperative variables potentially associated with operative morbidity or mortality were retrieved prospectively as follows: demographic and clinical characteristics of the patients, cardiopulmonary function characteristics, tumour characteristics, and treatment characteristics. A bivariate analysis of all variables under evaluation was carried out in order to identify those variables associated with operative morbidity and mortality. A multivariable analysis of the selected variables was then conducted using a logistic model. Results: The predicted postoperative product (predicted FEV1×predicted diffusing capacity of carbon monoxide), the carbon monoxide diffusion coefficient (Kco) and the contralateral pulmonary perfusion are variables that relate to the overall morbidity or mortality (number of events 63, 55%) (−2 log likelihood χ 2 =22.9; R 2 =0.27). For variables associated with postoperative morbidity, the best associative model combines functional variables (diffusion, predicted FEV1), endoscopic variables (obstructed segments to be resected), clinical variables (comorbidity) and an important postoperative variable, the pathological tumoural staging (pN) (number of events 49, 43%) (−2 log likelihood χ 2 =32.9; R 2 =0.36). Conclusion: The numerous variables under analysis are poorly associated with morbidity or mortality after thoracotomy in lung cancer. With regard to postoperative morbidity, the best associative models combine information that is known pre- and postoperatively and which is provided by both the patient and the tumour.