Risk model of in-hospital mortality after pulmonary resection for cancer: A national database of the French Society of Thoracic and Cardiovascular Surgery (Epithor)
- 28 February 2011
- journal article
- research article
- Published by Elsevier BV in The Journal of Thoracic and Cardiovascular Surgery
- Vol. 141 (2), 449-458
- https://doi.org/10.1016/j.jtcvs.2010.06.044
Abstract
Objectives The estimation of risk-adjusted in-hospital mortality is essential to allow each thoracic surgery team to be compared with national benchmarks. The objective of this study is to develop and validate a risk model of mortality after pulmonary resection. Methods A total of 18,049 lung resections for non–small cell lung cancer were entered into the French national database Epithor. The primary outcome was in-hospital mortality. Two independent analyses were performed with comorbidity variables. The first analysis included variables as independent predictive binary comorbidities (model 1). The second analysis included the number of comorbidities per patient (model 2). Results In model 1 predictors for mortality were age, sex, American Society of Anesthesiologists score, performance status, forced expiratory volume (as a percentage), body mass index (in kilograms per meter squared), side, type of lung resection,extended resection, stage, chronic bronchitis, cardiac arrhythmia, coronary artery disease, congestive heart failure, alcoholism, history of malignant disease, and prior thoracic surgery. In model 2 predictors were age, sex, American Society of Anesthesiologists score, performance status, forced expiratory volume, body mass index, side, type of lung resection, extended resection, stage, and number of comorbidities per patient. Models 1 and 2 were well calibrated, with a slope correction factor of 0.96 and of 0.972, respectively. The area under the receiver operating characteristic curve was 0.784 (95% confidence interval, 0.76–0.8) in model 1 and 0.78 (95% confidence interval, 0.76–0.797) in model 2. Conclusions Our preference is for the well-calibrated model 2 because it is easier to use in practice to estimate the adjusted postoperative mortality of lung resections for cancer.Keywords
This publication has 22 references indexed in Scilit:
- The European Thoracic Database project: composite performance score to measure quality of care after major lung resection☆European Journal of Cardio-Thoracic Surgery, 2009
- Cardiac comorbidity is not a risk factor for mortality and morbidity following surgery for primary non-small cell lung cancer☆European Journal of Cardio-Thoracic Surgery, 2009
- Data from The Society of Thoracic Surgeons General Thoracic Surgery database: The surgical management of primary lung tumorsThe Journal of Thoracic and Cardiovascular Surgery, 2008
- Risk factors for 30-day mortality after resection of lung cancer and prediction of their magnitudeThorax, 2007
- Morbidity of Lung Resection After Prior Lobectomy: Results from the Veterans Affairs National Surgical Quality Improvement ProgramThe Annals of Thoracic Surgery, 2007
- Recent results of postoperative mortality for surgical resections in lung cancerThe Annals of Thoracic Surgery, 2004
- Lactate dehydrodgenase levels predict pulmonary morbidity after lung resection for non-small cell lung cancerEuropean Journal of Cardio-Thoracic Surgery, 2004
- Internal validation of predictive modelsJournal of Clinical Epidemiology, 2001
- POSSUM scoring system as an instrument of audit in lung resection surgeryThe Annals of Thoracic Surgery, 1999
- Optimizing selection of patients for major lung resectionThe Journal of Thoracic and Cardiovascular Surgery, 1995