Evidence map›Paper›PMID 41310355›Full record

Articlenpj aging2025

Reporting quality, effect sizes, and biases for aging interventions: a methodological appraisal of the DrugAge database.

Austin Parish, John P A Ioannidis, Kevin Zhang, Diogo Barardo, William R Swindell, João Pedro de Magalhães

Abstract read
In one paragraph

Article in npj aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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.

Austin ParishDepartment of Emergency Medicine, Brookdale University Hospital Medical Center, Brooklyn, NY, USA. auparish@bhmcny.org.
John P A IoannidisMeta-Research Innovation Center at Stanford (METRICS), Stanford University, and Departments of Medicine, of Epidemiology and Population Health, and of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
Kevin ZhangHackensack Meridian School of Medicine, Nutley, NJ, USA.
Diogo BarardoNOVOS Labs, New York, NY, USA.
William R SwindellDepartment of Internal Medicine, Division of Hospital Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
João Pedro de MagalhãesGenomics of Ageing and Rejuvenation Lab, Department of Inflammation and Ageing, College of Medicine and Health, University of Birmingham, Birmingham, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Though interest has grown significantly over the past decades in interventions that may slow the aging process, most evidence for these interventions still comes from experiments in non-human animals. These studies may suffer from design, quality and reporting issues. The quality and reporting of preclinical studies have not yet been studied systematically in anti-aging research. Here we analyzed the DrugAge database, assessing reporting study quality, bias and effect sizes across 667 anti-aging preclinical studies. We found significant shortcomings in reporting of crucial design features such as randomization and blinding, as well as large variation in reporting quality and effects across species. Only one third of non-mammal findings translated to mammals. Although anti-aging interventions may have different effects depending on when they are started, most studies began giving the intervention under investigation very early in the organism's lifespan. Our findings suggest there is substantial room for improvement in preclinical anti-aging research.

Identifiers

PMID41310355
PMCPMC12660400

What OpenQuestion holds

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Registered trials

None linked

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.