Item-Level Heterogeneous Treatment Effects of Selective Serotonin Reuptake Inhibitors (SSRIs) on Depression: Implications for Inference, Generalizability, and Identification
SSRIs 对抑郁症的条目层面异质性治疗效应AI 解读 ↓
← 返回论文列表与筛选
阅读说明
本页整理公开书目信息，不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成，未完成全文核验，可能有误；具体假设、证明与结论请核对原文。摘要保留来源文本，未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要；缺少可靠材料时保留待补状态。
本页为预印本版本；arXiv 收录、作者填写的期刊信息以及作者既有发表经历，都不单独证明本篇已接收。作者发表记录按 OpenAlex 身份与完整姓名、本站覆盖期刊 ISSN 及正式卷期核对，只展示已核实例，档案仍可能误合并。
引用量采用 OpenAlex 单条关联记录，不合计多个记录；关联记录可能包含正式发表版本，不等于此版本单独引用。缺失不视为零，引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配，同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列，再参考通用方法与发表日期。
分类依据与纠错
AI 根据所提供的论文材料归类：摘要使用随机试验研究异质性治疗效应，并讨论治疗效应的推断、推广与识别。
反馈分类问题
正在核对关联版本…
代码、数据与补充材料
正在核对对应版本的资源…
SSRIs 对抑郁症的条目层面异质性治疗效应
- 研究问题
- SSRIs 对抑郁量表不同条目的治疗效应是否存在异质性？忽略这种差异会如何影响统计推断、向未观测条目的推广及交互效应识别？
- 方法与思路
- 作者将条目层面异质性治疗效应的项目反应模型扩展到多分类评分，开展蒙特卡洛模拟，并分析使用 HDRS-17 的 28 项随机试验。
- 材料陈述的贡献
- 摘要称，该模型改善推断、支持向样本外条目推广并解决交互效应识别问题；应用显示显著条目异质性，主要来自 HDRS-6 条目的较大效应。
- 阅读关注点
- 应核对量表测量模型、条目与试验之间的层级结构、交互效应的识别条件，以及推广到样本外条目所需的可比性与抽样假设。
- 阅读边界
- 依据所给 arXiv 预印本摘要，不能确认同行评审或期刊接收。摘要未说明完整模型假设和效应数值，条目推广也不能直接等同于患者总体推广。
原文摘要
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.