HETEROGENEITY IN TREATMENT EFFECT TIMING IN GERIATRICS AND PALLIATIVE CARE STUDIES

老年病学和姑息治疗研究中治疗效果时机的异质性

• 批准号: 10228270
• 负责人: Melissa M Garrido
• 金额: $ 41.25万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-17 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10228270
• 关键词: Academy; Accounting; Address; Adult; Attitude; Characteristics; Communities; Data; Data Adjustments; Data Collection; Data Pooling; Elderly; Equilibrium; Evaluation; Event; Geriatrics; Goals; Health and Retirement Study; Healthcare; Healthcare Systems; Heterogeneity; Intervention; Lead; Length; Longitudinal Studies; Medical center; Medicine; Methods; Monte Carlo Method; Observational Study; Outcome; Palliative Care; Participant; Performance; Persons; Policies; Probability; Process; Randomized Controlled Trials; Research Personnel; Retrospective cohort; Retrospective cohort study; Sampling; Services; Surveys; System; Time; Veterans; Weight; analytical method; base; care systems; cohort; design; end of life care; health care quality; improved; interest; programs; secondary analysis; simulation; treatment effect; treatment group; vector

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.

在对老年姑息治疗计划、政策或治疗的真实世界研究中，治疗启动可能需要 以不受调查员控制的方式在各个单位交错。如果不同队列之间的差异 或在与治疗时机和结果相关的组织特征方面不受控制 分析，它们可能会模糊对真正治疗效果的估计。当前对治疗进行核算的方法 影响时序的异质性要么不能解释混淆，要么可能由于以下原因而引入额外的偏差 回归平均数。潜在的解决方案涉及要调整的治疗权重的逆概率(IPTW) 用于通过接收时间定义的跨治疗组的混淆，但IPTW导致在 比较多种治疗方法的横断面评估。我们开发了另一种方法，矢量法- 基于核加权(VBKW)，在横截面评估中优于IPTW。在多大程度上 与IPTW相比，VBKW在纵向应用中减少了偏置并提高了效率，但尚未被探索。 我们建议评估从观测设计产生的数据中估计的偏差和效率。 具有交错的数据收集和/或交错的治疗定时。我们的目标是：1)比较偏差和 使用VBKW、IPTW估计的平均处理效果的效率，以及不调整差值。 队列内错开治疗时间的回溯性队列研究的差异分析，2)比较 使用VBKW、IPTW和不对纵向面板数据进行调整的估计的偏差和效率 治疗效果在数据收集的不同波之间和波内可能不同的研究，以及3)确定程度 VBKW和IPTW的治疗效果异质性需要导致不同的推断。 我们将使用蒙特卡罗(MC)和等离子体模式模拟来获得平均治疗效果的估计 使用VBKW、IPTW或不使用交错数据收集调整从观察性研究获得的数据 和/或错开治疗时机。对调查者生成的数据(n=900,9600)进行MC模拟将允许我们 为了检查不同分析情景的影响(例如，样本在治疗计时组中的分布， 开始治疗的不同次数)对VBKW和IPTW的相对性能的影响 估计。等离子体模式模拟将使我们能够验证我们的结果对于数据生成过程是稳健的 将通过对退伍军人以参与者为导向的护理服务和 社区(n=848,500人月，38个医疗中心)和健康和退休研究(HRS)。 我们将评估偏倚、效率和协变量平衡。 我们将确定VBKW和IPTW在评估不同治疗方案的效果方面哪个更好 泰晤士报。我们将在对调查人员的实际指导中总结我们的结果。我们的结果会有所改善 研究人员从老年姑息治疗研究中产生严格证据的能力 无法控制事件时间。