Estimation of Heterogeneous Causal Mediation Effects in a Hypertension Treatment Trial
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| Format: | Preprint |
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2025
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| _version_ | 1866909959464157184 |
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| author | Zhao, Yi Li, Chengyun Tu, Wanzhu |
| author_facet | Zhao, Yi Li, Chengyun Tu, Wanzhu |
| contents | Hypertension is a highly prevalent condition and a major risk factor for cardiovascular disease. The landmark Systolic Blood Pressure Intervention Trial (SPRINT) showed that lowering systolic blood pressure (BP) goals from 140 mmHg to 120 mmHg leads to significantly reduced BP, cardiovascular mortality, and morbidity. However, the underlying mechanisms are not yet fully elucidated. In patients with impaired renal function, early reduction of albuminuria has been proposed as a potential mediation pathway. Evidence from the standard causal mediation analysis (CMA), however, yields inconsistent results, possibly due to heterogeneous mediation effects across individuals. To disseminate the heterogeneity, a new framework that incorporates covariate-treatment and mediator-treatment interactions within a linear structural equation modeling system is introduced. Causal assumptions are discussed and heterogeneous natural direct and indirect effects are parameterized as functions of patient characteristics. A modified covariate approach is proposed to relax the hierarchical constraints and the generalized lasso regularization is employed to ensure parsimony in high-dimensional settings. Asymptotic properties are studied. Simulation studies demonstrate good estimation and inference performance. Analysis of the SPRINT data reveals substantial heterogeneity in mediation effects, identifying a subset of patients who stand to gain from therapies targeting albuminuria. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2512_12043 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Estimation of Heterogeneous Causal Mediation Effects in a Hypertension Treatment Trial Zhao, Yi Li, Chengyun Tu, Wanzhu Applications Hypertension is a highly prevalent condition and a major risk factor for cardiovascular disease. The landmark Systolic Blood Pressure Intervention Trial (SPRINT) showed that lowering systolic blood pressure (BP) goals from 140 mmHg to 120 mmHg leads to significantly reduced BP, cardiovascular mortality, and morbidity. However, the underlying mechanisms are not yet fully elucidated. In patients with impaired renal function, early reduction of albuminuria has been proposed as a potential mediation pathway. Evidence from the standard causal mediation analysis (CMA), however, yields inconsistent results, possibly due to heterogeneous mediation effects across individuals. To disseminate the heterogeneity, a new framework that incorporates covariate-treatment and mediator-treatment interactions within a linear structural equation modeling system is introduced. Causal assumptions are discussed and heterogeneous natural direct and indirect effects are parameterized as functions of patient characteristics. A modified covariate approach is proposed to relax the hierarchical constraints and the generalized lasso regularization is employed to ensure parsimony in high-dimensional settings. Asymptotic properties are studied. Simulation studies demonstrate good estimation and inference performance. Analysis of the SPRINT data reveals substantial heterogeneity in mediation effects, identifying a subset of patients who stand to gain from therapies targeting albuminuria. |
| title | Estimation of Heterogeneous Causal Mediation Effects in a Hypertension Treatment Trial |
| topic | Applications |
| url | https://arxiv.org/abs/2512.12043 |