A sensitivity analysis to separate bias due to confounding from bias due to predicting misclassification by a variable that does both

Variables that predict misclassification of exposure, outcome, or a confoun der cannot be controlled by techniques that adjust for predictors of risk. They must be controlled by external adjustments. We confronted an analysis in which a variable predicted misclassification of the exposure and of a co n founder. The same variable confounded the exposure-outcome relation. The analysis focused on the relation between less than-definitive therapy and b reast cancer mortality in the 5 years after diagnosis. Receipt of less-than -definitive prognostic evaluation predicted misclassification of definitive therapy (the exposure) and stage (a confounder). Prognostic evaluation als o confounded the therapy-breast cancer mortality relation, We used a sensit ivity analysis to separate the misclassification biases from the confoundin g bias. The relative hazard associated. with less-than definitive therapy i n the original multivariable model equaled 1.75 (95% confidence interval = 1.02-3.00), The median estimate in 2,500 repetitions of the sensitivity ana lysis was a relative hazard of 1.64, and 90% of the estimates fell between 1.47 and 1.83. The sensitivity analysis suggests that less-than definitive therapy confers an excess relative hazard of breast cancer mortality in the 5 years after diagnosis. The original analysis, which adjusted for confoun ding by prognostic evaluation but not its misclassification biases, overest imated the relative hazard.