Medical College of Wisconsin, Milwaukee, WI.
Med Care. 2019 Jan;57(1):85-93. doi: 10.1097/MLR.0000000000001019.
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).
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.
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)].
This study describes a new approach to identify heterogenous effects when using an interrupted time series research design.
我们扩展了一个中断时间序列研究设计，使用基于群组的轨迹模型（GBTMs）来识别新政策之前的群组，然后使用倾向评分加权来平衡轨迹组内暴露于政策变化的个体和未暴露于政策变化的个体，以检查政策的效果是否在群组之间具有一致的影响。我们通过检查在不享受补贴的女性中引入通用内分泌治疗药物（ET）以降低药物自付额（“治疗”组）对那些享受补贴且不承担任何自付额变化的女性（“对照”组）后，乳腺癌女性的 ET 依从性如何受到影响来探索这一点。
我们使用 SEER-Medicare 数据，检查了 2008 年至 2009 年间诊断为乳腺癌的女性每月 ET 的依从性，用覆盖天数的比例来表示。为了考虑到基线趋势，我们使用 GBTMs 描述了 ET 通用批准前一年的依从性，在每个组内，我们生成了不接受补贴的逆概率治疗权重。我们在每个 GBTM 内使用修正泊松模型比较了通用进入后的依从性。
GBTMs 在 1 年前识别出了 6 个依从性组。在比较接受和不接受补贴的患者时，我们发现通用引入没有总体效果。然而，在通用引入后的 6 个依从性组中，有 1 个组的依从性增加[“持续低”（风险比=1.91；95%置信区间=1.34-2.72）]。
本研究描述了一种在使用中断时间序列研究设计时识别异质效应的新方法。
