Validation of a Model to Predict Perioperative Mortality from Lung Cancer Resection in the Elderly
Validation of a Model to Predict Perioperative Mortality from Lung Cancer Resection in the Elderly
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DOI：
10.1164/rccm.200808-1342oc
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发表时间：
2009-03-01
影响因子：
24.7
通讯作者：
Wisnivesky, Juan P.
中科院分区：
文献类型：
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作者：
Kates, Max;Perez, Xavier;Wisnivesky, Juan P.
基本原理：手术切除是局部非小细胞肺癌（NSCLC）的主要治疗方法，但由于担心手术相关的发病率和死亡率，老年患者不太可能接受手术治疗。目的：验证和完善一个临床模型，预测老年肺癌根治性切除患者的30天围手术期死亡率（POM）。我们从与医疗保险索赔相关的监测、流行病学和最终结果登记处确定了14，297例年龄在65岁及以上的I、II或IIIA期NCSLC患者。我们使用逻辑回归分析，以确定独立的危险因素，POM和验证和完善以前推导的预测model. Measures和主要结果：总体而言，POM为4.6%（95%的置信区间，4.2-4.9%）。多元回归分析显示，年龄较大、男性、多叶切除、晚期、肿瘤较大和某些合并症与POM风险增加相关。这些风险因素与先前模型中观察到的风险因素相似。结论：在老年肺癌患者中，预测规则可以识别出手术致死性并发症的高风险患者。进一步的研究应该评估使用该模型是否可以改善治疗决策。
Rationale: Surgical resection is the mainstay therapy for localized non-small cell lung cancer (NSCLC), yet elderly patients are less likely to be treated due to concerns about morbidity and mortality related to surgery.Objectives: To validate and refine a clinical model to predict 30-day perioperative mortality (POM) in elderly patients undergoing curative resection for lung cancer.Methods: We identified 14,297 patients aged 65 years and older with stage I, II, or IIIA NCSLC from the Surveillance, Epidemiology, and End-Results Registry linked to Medicare claims. We used logistic regression analysis to identify independent risk factors for POM and to validate and refine a previously derived prediction model.Measurements and Main Results: Overall, POM was 4.6% (95% confidence interval, 4.2-4.9%). Multiple regression analysis revealed that greater age, male sex, resections of multiple lobes, advanced stage, greater tumor size, and certain comorbidities were associated with increased risk for POM. These risk factors were similar to those observed in the prior model. When patients were stratified according to their predicted risk of POM, the observed mortality increased from 1.2 to more than 10%.Conclusions: Among elderly patients with lung cancer, a prediction rule can identify those patients at higher risk for fatal complications from surgery. Further studies should evaluate whether use of the model can lead to improvements in treatment decision making.