Heterogeneity of treatment effect (HTE) refers to the nonrandom variation in the magnitude or direction of a treatment effect across levels of a covariate, as measured on a selected scale, against a clinical outcome. In randomized controlled trials (RCTs), HTE is typically examined through a subgroup analysis that contrasts effects in groups of patients defined "1 variable at a time" (for example, male vs. female or old vs. young). The authors of this statement present guidance on an alternative approach to HTE analysis, "predictive HTE analysis." The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneously. The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed using a multidisciplinary technical expert panel, targeted literature reviews, simulations to characterize potential problems with predictive approaches, and a deliberative process engaging the expert panel. The authors distinguish 2 categories of predictive HTE approaches: a "risk-modeling" approach, wherein a multivariable model predicts the risk for an outcome and is applied to disaggregate patients within RCTs to define risk-based variation in benefit, and an "effect-modeling" approach, wherein a model is developed on RCT data by incorporating a term for treatment assignment and interactions between treatment and baseline covariates. Both approaches can be used to predict differential absolute treatment effects, the most relevant scale for clinical decision making. The authors developed 4 sets of guidance: criteria to determine when risk-modeling approaches are likely to identify clinically important HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. The PATH Statement, together with its explanation and elaboration document, may guide future analyses and reporting of RCTs.

中文翻译：

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治疗效果异质性 (PATH) 声明的预测方法。

治疗效果的异质性 (HTE) 是指在协变量水平上治疗效果的大小或方向的非随机变化，根据临床结果以选定的尺度进行测量。在随机对照试验 (RCT) 中，通常通过亚组分析来检查 HTE，该分析对比定义为“一次 1 个变量”的患者组（例如，男性与女性或老年人与年轻人）的效果。本声明的作者提出了 HTE 分析的替代方法“预测 HTE 分析”的指导。预测性 HTE 分析的目标是提供以患者为中心的干预与不干预结果风险估计，同时考虑所有相关患者属性。PATH（治疗效果异质性的预测方法）声明是通过多学科技术专家小组、有针对性的文献综述、用预测方法描述潜在问题的模拟以及专家小组参与的审议过程制定的。作者区分了两类预测性 HTE 方法：“风险建模”方法，其中多变量模型预测结果的风险，并应用于随机对照试验中分解患者，以定义基于风险的获益变化；以及“效果-建模”方法，其中通过合并治疗分配术语以及治疗与基线协变量之间的相互作用，在 RCT 数据上开发模型。两种方法均可用于预测差异绝对治疗效果，这是临床决策最相关的量表。作者制定了 4 套指南：确定风险建模方法何时可能识别临床上重要的 HTE 的标准、风险建模方法的方法学方面、转化为临床实践的注意事项以及使用效果模型时的注意事项和注意事项接近。PATH 声明及其解释和阐述文件可以指导未来的随机对照试验分析和报告。