ArticleCPT: pharmacometrics & systems pharmacology2026
Tutorial on Causal Mediation Analysis for Pharmacometricians.
Article in CPT: pharmacometrics & systems pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Tutorial on Causal Mediation Analysis for Pharmacometricians.CPT: pharmacometrics & systems pharmacology · 2026Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mediation analyses can support biomarker development by quantifying the part of the total treatment effect on clinical outcome that is mediated by the biomarker. Given that pharmacometricians are often involved in the analysis of biomarker data with pharmacokinetic-pharmacodynamic (PK-PD) models, mediation analysis can be a valuable addition to the pharmacometrics toolbox. The generalized nature of causal mediation analysis makes it particularly suited for use in pharmacometrics, where complex models with non-linearities or interaction effects are common. This tutorial covers the concepts of causal mediation analysis and how these might be applied within a pharmacometric context using a simulation-based workflow, including example code and datasets.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.