Journal
MEDICAL CARE
Volume 45, Issue 10, Pages S123-S130Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/MLR.0b013e318070c069
Keywords
heterogeneity; effectiveness; instrumental variables; risk adjustment; treatment rates
Categories
Funding
- NCI NIH HHS [N01-PC-85063-20] Funding Source: Medline
Ask authors/readers for more resources
Objectives: To contrast the interpretations of treatment effect estimates using risk adjustment and instrumental variable (IV) estimation methods using observational data when the effects of treatment are heterogeneous across patients. We demonstrate these contrasts by examining the effect of breast conserving surgery plus irradiation (BCSI) relative to mastectomy on early stage breast cancer (ESBC) survival. Methods: We estimated discrete time survival models for 6185 ESBC patients in the 1989-1994 Iowa Cancer Registry via IV estimation using 2 distinct instruments (distance of the patient's residence from the nearest radiation center, and local area BCSI rate) and controlling for cancer stage, grade, and location; age; comorbidity; hospital access; payer; diagnosis year; and area poverty level. We then estimated comparable risk adjustment survival models using linear probability methods with robust standard errors. Results: Risk adjustment models yielded average survival estimates similar to trial results. With favorable BCSI selection, these estimates represent an upper bound of the true effect for patients receiving BCSI. IV estimates showed a BCSI survival risk for patients whose surgery choices were affected by the instruments and these estimates varied with the instrument specification. Conclusions: When treatment benefits are heterogeneous across patients, treatment effect estimates from observational data can still be useful to policymakers, but they must be interpreted correctly. Risk adjustment methods yield estimates that can assess whether the patients who received treatment benefited from the treatment, but the direction of bias must be considered. In contrast, IV estimates can assess the effect of treatment rate changes, but characteristics of patients whose choices were affected by the instruments must be considered when making such inferences.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available