Evidence map›Paper›PMID 42465050›Full record

ArticleJournal of clinical and translational science2026

Individual patient data meta-analysis and systematic review evaluating camostat mesilate to treat COVID-19.

Haley Hedlin, Els Tobback, Justin Lee, Yiwen Wang, Ilaria Dragoni, Daniel C Anthony, Kevin Dhaliwal, John Norrie, Sarah Halford, Jose Gotes and 12 more

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2026. 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

22 authors.

Haley HedlinQuantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA, USA.ORCID https://orcid.org/0000-0002-0757-7959
Els TobbackDepartment of General Internal Medicine, University Hospital Ghent, Ghent, Belgium.
Justin LeeQuantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA, USA.
Yiwen WangQuantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA, USA.
Ilaria DragoniCancer Research UK, London, UK.
Daniel C AnthonyDepartment of Pharmacology, University of Oxford, Oxford, UK.
Kevin DhaliwalBaillie Gifford Pandemic Science Hub, Institute of Regeneration and Repair, University of Edinburgh, Edinburgh, UK.
John NorrieCentre for Public Health, Queen's University Belfast, Northern Ireland, UK.
Sarah HalfordCancer Research UK, London, UK.
Jose GotesInstituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico.
Mariana MoctezumaInstituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico.
Antonio Olivas-MartinezInstituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico.
Chaitan KhoslaSarafan ChEM-H and the Stanford Innovative Medicines Accelerator, Stanford University School of Medicine, Stanford, CA, USA.
Upinder SinghDepartment of Internal Medicine, University of Iowa Health Care, Iowa City, IA, USA.
Jesper Damsgaard GunstDepartment of Infectious Diseases, Aarhus University Hospital, Aarhus, Denmark.
Alonso ValdezInstituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico.
David KershenobichInstituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico.
David BoutboulHematology Department, Universite Paris Cite, Paris, France.
Ole S SøgaardDepartment of Infectious Diseases, Aarhus University Hospital, Aarhus, Denmark.
Marie-Angélique De ScheerderDepartment of General Internal Medicine, University Hospital Ghent, Ghent, Belgium.
Manisha DesaiQuantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA, USA.ORCID https://orcid.org/0000-0002-6949-2651
Julie ParsonnetDepartment of Medicine, Stanford University, Stanford, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In the COVID-19 pandemic, several phase II and III randomized trials were launched to evaluate the effectiveness of camostat, an orally administered TMPRSS2 inhibitor previously approved for other indications, for treating SARS-CoV-2 infections. Owing to the rapidly changing landscape during the pandemic, many of these trials were unable to reach completion. Further, methods for synthesizing trials that were launched and not completed were critical. Methods: This systematic review aimed to consolidate global evidence by identifying placebo controlled, randomized trials of camostat and analyzing their collective clinical and virologic impact on SARS-CoV-2 through an individual patient data meta-analysis (IPDMA). We harmonized data from the studies and utilized Bayesian statistical models to assess virologic outcomes (measured by the rate of change in viral shedding) and clinical outcomes (based on the time to the first of two consecutive symptom-free days), adjusting for age and sex. Results: The IPDMA incorporated data from six countries, totaling 431 patients across the studies; 118 patients contributed data for the primary virologic outcome and 240 for the clinical symptom outcome. Camostat did not improve the rate of change in viral load (difference in rate of change = 0.11 Ct value/day higher, 95% credible interval 2.04 lower to 2.23 higher) or time to symptom resolution (hazard ratio = 0.87, 95% credible interval 0.51, 1.55) when compared to placebo. Conclusions: Despite its theoretically promising mode of action, camostat did not demonstrate a statistically significant virologic or clinical benefit in treating COVID-19, highlighting the complexity of drug repurposing in emergency health situations.

Indexed as

COVID-19data harmonizationdata sharingglobal pandemicIndividual patient data meta-analysis

Identifiers

PMID42465050
PMCPMC13373606

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.