In analysis of randomized controlled trials (RCTs) with patient-reported outcome measures (PROMs), Item Response Theory (IRT) models that allow for heterogeneity in the treatment effect at the item level merit consideration. These models for ``item-level heterogeneous treatment effects'' (IL-HTE) can provide more accurate statistical inference, allow researchers to better generalize their results, and resolve critical identification problems in the estimation of interaction effects. In this study, we extend the IL-HTE model to polytomous data and apply the model to determine how the effect of selective serotonin reuptake inhibitors (SSRIs) on depression varies across the items on a depression rating scale. We first conduct a Monte Carlo simulation study to assess the performance of the polytomous IL-HTE model under a range of conditions. We then apply the IL-HTE model to item-level data from 28 RCTs measuring the effect of SSRIs on depression using the 17-item Hamilton Depression Rating Scale (HDRS-17) and estimate potential heterogeneity by subscale (HDRS-6). Our results show that the IL-HTE model provides more accurate statistical inference, allows for generalizability of results to out-of-sample items, and resolves identification problems in the estimation of interaction effects. Our empirical application shows that while the average effect of SSRIs on depression is beneficial (i.e., negative) and statistically significant, there is substantial IL-HTE, with estimates of the standard deviation of item-level effects nearly as large as the average effect. We show that this substantial IL-HTE is driven primarily by systematically larger effects on the HDRS-6 subscale items. The IL-HTE model has the potential to provide new insights for the inference, generalizability, and identification of treatment effects in clinical trials using patient reported outcome measures.

翻译：在采用患者报告结局指标（PROMs）的随机对照试验（RCTs）分析中，允许处理效应在条目水平存在异质性的项目反应理论（IRT）模型值得关注。这种"条目级异质性处理效应"（IL-HTE）模型能够提供更精确的统计推断，帮助研究者更好地泛化研究结果，并解决交互效应估计中的关键识别问题。本研究将IL-HTE模型扩展至多分类数据，并应用该模型确定选择性5-羟色胺再摄取抑制剂（SSRIs）对抑郁症的效应如何随抑郁评定量表各条目而变化。我们首先开展蒙特卡洛模拟研究，评估多分类IL-HTE模型在多种条件下的性能表现。随后将IL-HTE模型应用于28项采用17项汉密尔顿抑郁评定量表（HDRS-17）测量SSRIs抑郁效应的RCTs条目级数据，并估计各子量表（HDRS-6）的潜在异质性。结果表明：IL-HTE模型能提供更精确的统计推断，支持研究结果向样本外条目泛化，并解决交互效应估计中的识别问题。实证应用显示，虽然SSRIs对抑郁症的平均效应具显著获益（即负向效应），但存在显著的IL-HTE，条目级效应的标准差估计值几乎与平均效应量相当。这种显著异质性主要由HDRS-6子量表条目上系统性的更强效应驱动。IL-HTE模型有望为采用患者报告结局指标的临床试验提供关于处理效应推断、泛化与识别的新见解。