Faculty Collaboration Database

Using Group-based Trajectory Models and Propensity Score Weighting to Detect Heterogeneous Treatment Effects: The Case Study of Generic Hormonal Therapy for Women With Breast Cancer. Med Care 2019 Jan;57(1):85-93

Date

11/30/2018

Pubmed ID

30489546

Pubmed Central ID

PMC6291347

DOI

10.1097/MLR.0000000000001019

Scopus ID

2-s2.0-85057760197 (requires institutional sign-in at Scopus site)   11 Citations

Abstract

BACKGROUND: We extend an interrupted time series study design to identify heterogenous treatment effects using group-based trajectory models (GBTMs) to identify groups before a new policy and then examine if the effects of the policy has consistent impacts across groups using propensity score weighting to balance individuals within trajectory groups who are and are not exposed to the policy change. We explore this by examining how adherence to endocrine therapy (ET) for women with breast cancer was impacted by reducing copayments for medications by the introduction of generic ETs among women who do not receive a subsidy (the "treatment" group) to those that do receive a subsidy and are not exposed to any changes in copayments (the "control" group).

METHODS: We examined monthly adherence to ET using the proportion of days covered for women diagnosed with breast cancer between 2008 and 2009 using SEER-Medicare data. To account for baseline trends, we characterize adherence for 1 year before generic approval of ET using GBTMs, within each groups we generate inverse probability treatment weights of not receiving a subsidy. We compared adherence after generic entry within each GBTM using a modified Poisson model.

RESULTS: GBTMs for adherence in the 1-year pregeneric identified 6 groups. When comparing patients who did and did not receive a subsidy we found no overall effect of generic introduction. However, 1 of the 6 identified adherence groups postgeneric adherence increased [the "consistently low" (risk ratio=1.91; 95% confidence interval=1.34-2.72)].

CONCLUSIONS: This study describes a new approach to identify heterogenous effects when using an interrupted time series research design.

Author List

Winn AN, Fergestrom NM, Neuner JM

MESH terms used to index this publication - Major topics in bold

Aged
Antineoplastic Agents, Hormonal
Breast Neoplasms
Drugs, Generic
Female
Health Expenditures
Humans
Medicare Part D
Medication Adherence
Propensity Score
SEER Program
Time Factors
Treatment Outcome
United States