Evidence map›Paper›PMID 36050911›Full record

ArticleBiostatistics (Oxford, England)2023

Cross-direct effects in settings with two mediators.

Erin E Gabriel, Arvid Sjölander, Dean Follmann, Michael C Sachs

Abstract read
In one paragraph

Article in Biostatistics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Erin E GabrielSection of Biostatistics, Department of Public Health, University of Copenhagen, Øster Farimagsgade 5, 1353 Køpenhavn, Denmark.ORCID 0000-0002-0504-8404
Arvid SjölanderDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Stockholm 17177, Sweden.ORCID 0000-0001-5226-6685
Dean FollmannBiostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda, 5601 Fishers Lane, Rockville, MD 20892, USA.
Michael C SachsSection of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0002-1279-8676

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When multiple mediators are present, there are additional effects that may be of interest beyond the well-known natural (NDE) and controlled direct effects (CDE). These effects cross the type of control on the mediators, setting one to a constant level and one to its natural level, which differs across subjects. We introduce five such estimands for the cross-CDE and -NDE when two mediators are measured. We consider both the scenario where one mediator is influenced by the other, referred to as sequential mediators, and the scenario where the mediators do not influence each other. Such estimands may be of interest in immunology, as we discuss in relation to measured immunological responses to SARS-CoV-2 vaccination. We provide identifying expressions for the estimands in observational settings where there is no residual confounding, and where intervention, outcome, and mediators are of arbitrary type. We further provide tight symbolic bounds for the estimands in randomized settings where there may be residual confounding of the outcome and mediator relationship and all measured variables are binary.

Indexed as

COVID-19Models, StatisticalCOVID-19 VaccinesHumansSARS-CoV-2COVID-19 VaccinesCausal pathwaysMultiple mediationSymbolic bounds

Identifiers

PMID36050911
PMCPMC10583720

What OpenQuestion holds

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Registered trials

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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.