Department of Thoracic Surgery, CHU Dijon, France.
J Thorac Cardiovasc Surg. 2011 Feb;141(2):449-58. doi: 10.1016/j.jtcvs.2010.06.044. Epub 2010 Aug 9.
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.
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).
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.
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.
风险调整住院死亡率的评估对于使每个胸外科团队与国家基准进行比较至关重要。本研究的目的是开发和验证肺切除术后死亡率的风险模型。
共有 18049 例非小细胞肺癌肺切除术被纳入法国国家数据库 Epithor。主要结局是院内死亡率。对合并症变量进行了两次独立分析。第一次分析包括作为独立预测二元合并症的变量（模型 1）。第二次分析包括每位患者的合并症数量（模型 2）。
在模型 1 中，死亡率的预测因素为年龄、性别、美国麻醉医师协会评分、体力状态、用力呼气量（占百分比）、体重指数（千克/平方米）、侧别、肺切除术类型、扩大切除术、分期、慢性支气管炎、心律失常、冠心病、充血性心力衰竭、酗酒、恶性疾病史和既往胸部手术史。在模型 2 中，预测因素为年龄、性别、美国麻醉医师协会评分、体力状态、用力呼气量、体重指数、侧别、肺切除术类型、扩大切除术、分期和每位患者的合并症数量。模型 1 和模型 2 的校准情况良好，斜率校正因子分别为 0.96 和 0.972。模型 1 的受试者工作特征曲线下面积为 0.784（95%置信区间，0.76-0.8），模型 2 的面积为 0.78（95%置信区间，0.76-0.797）。
我们更倾向于校准良好的模型 2，因为它在实践中更容易用于估计癌症肺切除术的调整后术后死亡率。
