Departments of Surgery, University of Texas Medical Branch, Galveston, Texas; University of California, San Francisco-East Bay, Oakland, California.
Cancer. 2013 Nov 1;119(21):3861-9. doi: 10.1002/cncr.28295. Epub 2013 Aug 6.
A previous observational study reported that endoscopic ultrasound (EUS) is associated with improved survival in older patients with pancreatic cancer. The objective of this study was to reevaluate this association using different statistical methods to control for confounding and selection bias.
Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data (1992-2007) was used to identify patients with locoregional pancreatic cancer. Two-year survival in patients who did and did not receive EUS was compared by using standard Cox proportional hazards models, propensity score methodology, and instrumental variable analysis.
EUS was associated with improved survival in both unadjusted (hazard ratio [HR] = 0.67, 95% confidence interval [CI] = 0.63-0.72) and standard regression analyses (HR = 0.78, 95% CI = 0.73-0.84) which controlled for age, sex, race, marital status, tumor stage, SEER region, Charlson comorbidity, year of diagnosis, education, preoperative biliary stenting, chemotherapy, radiation, and pancreatic resection. Propensity score adjustment, matching, and stratification did not attenuate this survival benefit. In an instrumental variable analysis, the survival benefit was no longer observed (HR = 1.00, 95% CI = 0.73-1.36).
These results demonstrate the need to exercise caution in using administrative data to infer causal mortality benefits with diagnostic and/or treatment interventions in cancer research.
先前的观察性研究报告称,内镜超声(EUS)可改善老年胰腺癌患者的生存。本研究的目的是使用不同的统计方法重新评估这种关联,以控制混杂和选择偏倚。
利用监测、流行病学和最终结果(SEER)-医疗保险关联数据(1992-2007 年),确定局部区域性胰腺癌患者。使用标准 Cox 比例风险模型、倾向评分方法和工具变量分析,比较接受和未接受 EUS 的患者的两年生存率。
在未调整(风险比[HR] = 0.67,95%置信区间[CI] = 0.63-0.72)和标准回归分析(HR = 0.78,95% CI = 0.73-0.84)中,EUS 与生存改善相关,这些分析控制了年龄、性别、种族、婚姻状况、肿瘤分期、SEER 区域、Charlson 合并症、诊断年份、教育程度、术前胆道支架、化疗、放疗和胰腺切除术。倾向评分调整、匹配和分层并没有减弱这种生存获益。在工具变量分析中,这种生存获益不再存在(HR = 1.00,95% CI = 0.73-1.36)。
这些结果表明,在癌症研究中,使用行政数据推断诊断和/或治疗干预的因果死亡率获益时,需要谨慎行事。