期刊
STATISTICS IN MEDICINE
卷 28, 期 10, 页码 1498-1511出版社
WILEY
DOI: 10.1002/sim.3557
关键词
missing data; sensitivity analysis; cancer; survival analysis
类别
资金
- NIH [P30 CA 06927]
Having substantial missing data is a common problem in administrative and cancer registry data. We propose a sensitivity analysis to evaluate the impact of a covariate that is potentially missing not at random in survival analysis using Weibull proportional hazards regressions. We apply the method to an investigation of the impact of missing grade on post-surgical mortality outcomes in individuals with metastatic kidney cancer. Data came from the Surveillance Epidemiology and End Results (SEER) registry which provides population-based information on those undergoing cytoreductive nephrectomy. Tumor grade is an important component of risk stratification for patients with both localized and metastatic kidney, cancer. Many individuals in SEER with metastatic kidney cancer are missing tumor grade information. We found that surgery was protective, but that the magnitude of the effect depended on assumptions about the relationship of grade with missingness. Copyright (C) 2009 John Wiley & Sons, Ltd.
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