FCCC LOGO Faculty Publications
Handorf EA , Bekelman JE , Heitjan DF , Mitra N
Evaluating Costs with Unmeasured Confounding: A Sensitivity Analysis for the Treatment Effect
Ann Appl Stat. 2013 Dec;7(4) :2062-2080
PMID: 24587844    PMCID: PMC3935434    URL: https://www.ncbi.nlm.nih.gov/pubmed/24587844
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Abstract
Estimates of the effects of treatment on cost from observational studies are subject to bias if there are unmeasured confounders. It is therefore advisable in practice to assess the potential magnitude of such biases. We derive a general adjustment formula for loglinear models of mean cost and explore special cases under plausible assumptions about the distribution of the unmeasured confounder. We assess the performance of the adjustment by simulation, in particular, examining robustness to a key assumption of conditional independence between the unmeasured and measured covariates given the treatment indicator. We apply our method to SEER-Medicare cost data for a stage II/III muscle-invasive bladder cancer cohort. We evaluate the costs for radical cystectomy vs. combined radiation/chemotherapy, and find that the significance of the treatment effect is sensitive to plausible unmeasured Bernoulli, Poisson and Gamma confounders.
Notes
Handorf, Elizabeth A Bekelman, Justin E Heitjan, Daniel F Mitra, Nandita eng K07 CA163616/CA/NCI NIH HHS/ P30 CA006927/CA/NCI NIH HHS/ P30 CA016520/CA/NCI NIH HHS/ UC2 CA148310/CA/NCI NIH HHS/ Ann Appl Stat. 2013;7(4):2062-2080. doi: 10.1214/13-AOAS665.