. Author manuscript; available in PMC: 2020 Dec 21.

Published in final edited form as: Ann Intern Med. 2019 Nov 12;172(1):W1–W25. doi: 10.7326/M18-3668

Table 3.

Methodological Literature on the Conduct of Regression Modeling Approaches to Treatment Effect Heterogeneity Analysis

Approach	Description
Risk-modeling approaches^{7;45;62;98;117;118;120;183–186}	Using a multivariable risk model developed blinded to treatment effect, analyze the relationship between baseline risk and treatment effect on the relative and on the absolute scale. While treatment effect modification on the relative scale across different levels of baseline risk is considered, treatment effect modification on the relative scale for individual risk factors is not.
Treatment effect modeling approaches^{120;143-145;151;186–193} Subgroup identification (2-step process)^143;^144;187 Individualized treatment effects (1-step process)^{120;145;186;188–190}	Use both the main effects of risk factors and interaction effects with treatment assignment (on the relative scale) to estimate more individualized treatment effects. They can be used either for defining patient subgroups with similar expected treatment effects or for predicting individualized treatment effects on the absolute scale for future patients.
Optimal treatment regimens^132–142	Classify patients into those who benefit from treatment (positive individualized treatment effect) and those who do not (negative individualized treatment effect), through the identification of modifiers of treatment effects on the relative scale.