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- Title
Sensitivity analysis to investigate the impact of a missing covariate on survival analyses using cancer registry data.
- Authors
Egleston, Brian L.; Wong, Yu-Ning
- Abstract
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 analyses 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 © 2009 John Wiley & Sons, Ltd.
- Publication
Statistics in Medicine, 2009, Vol 28, Issue 10, p1498
- ISSN
0277-6715
- Publication type
Article
- DOI
10.1002/sim.3557