Evidence map›Paper›PMID 41473761›Full record

ArticleFrontiers in psychiatry2025

A novel strategy for detecting multiple mediators in high-dimensional mediation models.

Pei-Shan Yen, Zhaoliang Zhou, Soumya Sahu, Debarghya Nandi, Olusola Ajilore, Dulal Bhaumik

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2025. 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

6 authors.

Pei-Shan YenDivision of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, IL, United States.
Zhaoliang ZhouDivision of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, IL, United States.
Soumya SahuDivision of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, IL, United States.
Debarghya NandiDivision of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, IL, United States.
Olusola AjiloreDepartment of Psychiatry, University of Illinois at Chicago, Chicago, IL, United States.
Dulal BhaumikDivision of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, IL, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article presents a novel methodology for detecting multiple biomarkers in high-dimensional mediation models by utilizing a modified Least Absolute Shrinkage and Selection Operator (LASSO) alongside Pathway LASSO. This approach effectively addresses the problem of overestimating direct effects, which can result in the inaccurate identification of mediators with nonzero indirect effects. To mitigate this overestimation and improve the true positive rate for detecting mediators, two constraints on the

Indexed as

biomarker detectionchoice of penaltyLASSOmediation analysisoverestimationPathway LASSO

Identifiers

PMID41473761
PMCPMC12745155

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.