DOI: 10.3886/icpsr39488.v1
title: Understanding Treatment Effect Estimates When Treatment Effects Are Heterogeneous for More Than One Outcome [Methods Study], United States, 2013-2018
title: Version 1

description: Current medical guidelines recommend a type of medicine called ACE/ARBs to help patients live longer and protect their kidneys after a stroke. But studies show that rates of kidney disease have gone up at the same time that more people have been using this medicine. Additional research may help show if some patients shouldn't take ACE/ARBs after a stroke.
In this study, the research team wanted to learn about the effects of taking ACE/ARBs for patients over age 65 who've had a stroke. The team reviewed Medicare claims for stroke survivors with and without chronic kidney disease, or CKD. CKD is a health problem in which the kidneys don't remove waste from the blood well. The team compared patients in areas of the country with different rates of ACE/ARB use. The team looked at how many patients lived and how many had kidney problems over two years.
description: To estimate the beneficial and detrimental effects of using angiotensin system antagonists (ACE/ARBs) for secondary stroke prevention among patients over age 65, with and without chronic kidney disease (CKD), who had a stroke and had Medicare. Specific objectives include:

 Use simulation methods to assess the properties of regression and instrumental variable (IV) estimators when both treatment benefits and detriments are heterogeneous across patients.
 Use regression and IV estimators to estimate the benefits and detriments associated with renin-angiotensin system antagonists (angiotensin-converting enzyme/angiotensin-receptor blockers [ACE/ARBs]) in secondary prevention for stroke patients with and without chronic kidney disease (CKD).
 Use chart abstraction data to assess the assumptions underlying the regression and IV estimators used in objective 2 and guide estimate interpretation accordingly.
description: In this empirical study, the research team applied linear probability and instrumental variable models to a clinical scenario in which the treatment has different beneficial and detrimental effects for different patients, but it is unclear which patient subgroups would benefit from the treatment. An instrumental variable is one that has a strong relationship with treatment choice but does not appear related to study outcomes. Because of geographic variation in practice, this study used local ACE/ARB treatment rates as the instrumental variable.
The research team analyzed the Medicare claims data for 35,679 patients who had a stroke in 2010. Of these, 25% had CKD. Among patients with CKD, 60% were female, 79% were white, 14% were black, and 7% were other races. Among patients without CKD, 66% were female, 85% were white, 9% were black, and 6% were other races.
Using standard regression and instrumental variable methods, the research team examined the effect of receiving ACE/ARBs after hospitalization for a stroke on patient survival and renal events, such as acute kidney failure or end-stage renal disease. In addition to the total population analysis, the team stratified the study population into patients with and without CKD to explore the differences in ACE/ARB treatment effects.
description: Datasets: 
DS1: Understanding Treatment Effect Estimates When Treatment Effects Are Heterogeneous for More Than One Outcome [Methods Study], United States, 2013-2018