HETEROGENEITY IN TREATMENT EFFECT TIMING IN GERIATRICS AND PALLIATIVE CARE STUDIES

在老年姑息治疗计划、政策或治疗的现实世界研究中，治疗开始可能需要 以调查员无法控制的方式在各个单位之间交错排列。如果不同群体之间存在差异 或与治疗时间和结果相关的组织特征不受控制 分析时，它们可能会模糊对真实治疗效果的估计。当前的治疗核算方法 效应时间异质性要么不能解释混杂因素，要么可能由于以下原因引入额外的偏差 回归均值。一个潜在的解决方案涉及治疗权重的逆概率（IPTW）来调整 对于由接收时间定义的治疗组之间的混淆，但 IPTW 会导致有偏差的估计 比较多种治疗方法的横断面评估。我们开发了一种替代方法，向量- 基于核加权（VBKW），在横截面评估中优于 IPTW。程度 VBKW 在纵向应用中比 IPTW 减少偏差并提高效率尚未得到探索。 我们建议评估观察设计生成的数据估计的偏差和效率 交错的数据收集和/或交错的治疗时间。我们的目标是：1）比较偏差和 使用 VBKW、IPTW 估计平均治疗效果的效率，并且不调整差异 队列内错开治疗时间的回顾性队列研究的差异分析，2) 比较 使用 VBKW、IPTW 进行估计的偏差和效率，且未对纵向面板数据进行调整 研究中治疗效果可能会因数据收集波次和数据收集波次而异，并且 3) 确定程度 VBKW 和 IPTW 所需的治疗效果异质性导致不同的推论。 我们将使用蒙特卡罗 (MC) 和等离子体模拟来获得平均治疗效果的估计 使用 VBKW、IPTW 或不对通过交错数据收集的观察性研究获得的数据进行调整 和/或错开治疗时间。对研究者生成的数据 (n=900, 9600) 进行 MC 模拟将使我们能够 检查不同分析场景的影响（例如，治疗时间组之间的样本分布， 开始治疗的不同次数）对 VBKW 和 IPTW 相对性能的影响 估计。 Plasmode 模拟将使我们能够验证我们的结果对于数据生成过程是否稳健 并将通过对退伍军人参与式护理服务和住院天数的观察分析得出 社区（n=848,500 人月，38 个医疗中心）和健康与退休研究 (HRS)。 我们将评估偏差、效率和协变量平衡。 我们将确定 VBKW 或 IPTW 何时更适合评估不同地点提供的治疗效果 次。我们将总结我们的结果，为研究人员提供实用指南。我们的成绩将会改善 研究人员从老年姑息治疗研究中得出严格证据的能力，其中治疗或 事件时间无法控制。

In real-world studies of geriatric palliative care programs, policies, or treatments, treatment initiation may need to be staggered across units in ways that are outside of an investigator's control. If differences across cohorts or in organizational characteristics associated with both treatment timing and outcome are not controlled for in analyses, they may obscure estimates of true treatment effects. Current methods for accounting for treatment effect timing heterogeneity either do not account for confounding or may introduce additional bias due to regression to the mean. A potential solution involves inverse probability of treatment weights (IPTW) to adjust for confounding across treatment groups defined by receipt timing, but IPTWs lead to biased estimates in cross-sectional evaluations comparing multiple treatments. We have developed an alternative method, vector- based kernel weighting (VBKW), that outperforms IPTW in cross-sectional evaluations. The degree to which VBKW reduces bias and improves efficiency over IPTW in longitudinal applications has not yet been explored. We propose to evaluate the bias and efficiency of estimates in data generated from observational designs with staggered data collection and/or staggered treatment timing. We aim to: 1) Compare the bias and efficiency of estimated average treatment effects using VBKW, IPTW, and no adjustment in difference-in- difference analyses of retrospective cohort studies with staggered treatment timing within a cohort, 2) Compare the bias and efficiency of estimates using VBKW, IPTW, and no adjustment on data from longitudinal panel studies where treatment effects may vary across and within waves of data collection, and 3) Identify the degree of treatment effect heterogeneity required for VBKW and IPTW to lead to different inferences. We will use Monte Carlo (MC) and plasmode simulations to obtain estimates of average treatment effects with VBKW, IPTW, or no adjustment of data obtained from observational studies with staggered data collection and/or staggered treatment timing. MC simulations on investigator-generated data (n=900, 9600) will allow us to examine the impact of different analytic scenarios (e.g., sample distribution across treatment timing groups, number of distinct times in which treatment is initiated) on the relative performance of VBKW and IPTW estimates. Plasmode simulations will allow us to verify that our results are robust to data generating process and will be derived from an observational analysis of veterans' participant-directed care services and days in the community (n=848,500 person-months, 38 medical centers) and the Health and Retirement Study (HRS). We will evaluate bias, efficiency, and covariate balance. We will identify when VBKW or IPTW is superior for estimating the effect of a treatment provided at different times. We will summarize our results in practical guidance for investigators. Our results will improve investigators' ability to generate rigorous evidence from studies of geriatric palliative care in which treatment or event timing cannot be controlled.