ArticleTherapeutic innovation & regulatory science2026
Regulatory Experiences with the Use of Multiple Imputation for Missing Data in a Phase 3 Confirmatory Trial.
Article in Therapeutic innovation & regulatory science, 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Mixed Model for Repeated Measures (MMRM) is widely used in clinical trials, however, its reliance on the Missing at Random (MAR) assumption and the exclusion of subjects lacking post-baseline data have been points of scrutiny, particularly due to misalignment with the Intent-to-Treat (ITT) principle. This paper presents an application of Multiple Imputation (MI) to address missing data in a hypertension clinical trial and discusses the subsequent interactions with regulatory authorities requesting additional analyses predominantly based on a Missing not at Random (MNAR) assumption. While MNAR-based approaches have been traditionally used for sensitivity analyses, we present an example demonstrating that regulatory agencies are increasingly expecting their integration into primary analyses.
Indexed as
Identifiers
What OpenQuestion holds
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.