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Improving observational study estimates of treatment effects using joint modeling of selection effects and outcomes:
A James O'Malley1, Philip Cotterill, Marc L Schermerhorn
1Department of Health Care Policy, Harvard Medical School, Boston, MA 02115-5899, USA. omalley@hcp.med.harvard.edu
Background:
When 2 treatment approaches are available, there are likely to be unmeasured confounders that influence choice of procedure, which complicates estimation of the causal effect of treatment on outcomes using observational data.
Objective:
To estimate the effect of endovascular (endo) versus open surgical (open) repair, including possible modification by institutional volume, on survival after treatment for abdominal aortic aneurysm, accounting for observed and unobserved confounding variables.
Research Design:
Observational study of data from the Medicare program using a joint model of treatment selection and survival given treatment to estimate the effects of type of surgery and institutional volume on survival.
Patients:
We studied 61,414 eligible repairs of intact abdominal aortic aneurysms during 2001 to 2004.
Measures:
The outcome, perioperative death, is defined as in-hospital death or death within 30 days of operation. The key predictors are use of endo, transformed endo and open volume, and endo-volume interactions.
Results:
There is strong evidence of nonrandom selection of treatment with potential confounding variables including institutional volume and procedure date, variables not typically adjusted for in clinical trials. The best fitting model included heterogeneous transformations of endo volume for endo cases and open volume for open cases as predictors. Consistent with our hypothesis, accounting for unmeasured selection reduced the mortality benefit of endo.
Conclusions:
The effect of endo versus open surgery varies nonlinearly with endo and open volume. Accounting for institutional experience and unmeasured selection enables better decision-making by physicians making treatment referrals, investigators evaluating treatments, and policy makers.
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