CovidChloroV1, Main, Corpus, bibRecord, 000B26

How the clinical research community responded to the COVID-19 pandemic: An analysis of the COVID-19 clinical studies in ClinicalTrials.gov.

Identifieur interne : 000B26 ( Main/Corpus ); précédent : 000B25; suivant : 000B27

How the clinical research community responded to the COVID-19 pandemic: An analysis of the COVID-19 clinical studies in ClinicalTrials.gov.

Auteurs : Zhe He ; Fnu Erdengasileng ; Xiao Luo ; Aiwen Xing ; Neil Charness ; Jiang Bian

Source :

medRxiv : the preprint server for health sciences ; 2020.

RBID : pubmed:32995807

Abstract

OBJECTIVE

The novel coronavirus disease (COVID-19), broke out in December 2019, is a global pandemic. Rapidly in the past few months, a large number of clinical studies have been initiated worldwide to find effective therapeutics, vaccines, and preventive strategies. In this study, we aim to understand the landscape of COVID-19 clinical research and identify the gaps and issues that may cause difficulty in recruitment and the lack of population representativeness.

MATERIALS AND METHODS

We analyzed 2,034 COVID-19 studies registered in the largest public registry - ClinicalTrials.gov. Leveraging natural language processing, descriptive analysis, association analysis, and clustering analysis, we characterized COVID-19 clinical studies by phase and design features. Particularly, we analyzed their eligibility criteria to understand: (1) whether they considered the reported underlying health conditions that may lead to severe illnesses, and (2) if these studies excluded older adults, either explicitly or implicitly, which may reduce the generalizability of these studies in older adults.

RESULTS

The 5 most frequently tested drugs are Hydroxychloroquine (N=148), Azithromycin (N=46), Tocilizumab (N=29), Lopinavir (N=20), and Ritonavir (N=20). Most trials did not have an upper age limit and did not exclude patients with common chronic conditions such as hypertension and diabetes that are prevalent in older adults. However, known risk factors that may lead to severe illnesses have not been adequately considered by existing studies.

CONCLUSIONS

A careful examination of the registered COVID-19 clinical studies can identify the research gaps and inform future COVID-19 trial design towards balanced internal validity and generalizability.

DOI: 10.1101/2020.09.16.20195552
PubMed: 32995807
PubMed Central: PMC7523146

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<author><name sortKey="He, Zhe" sort="He, Zhe" uniqKey="He Z" first="Zhe" last="He">Zhe He</name>
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<author><name sortKey="Erdengasileng, Fnu" sort="Erdengasileng, Fnu" uniqKey="Erdengasileng F" first="Fnu" last="Erdengasileng">Fnu Erdengasileng</name>
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<author><name sortKey="Luo, Xiao" sort="Luo, Xiao" uniqKey="Luo X" first="Xiao" last="Luo">Xiao Luo</name>
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<author><name sortKey="Xing, Aiwen" sort="Xing, Aiwen" uniqKey="Xing A" first="Aiwen" last="Xing">Aiwen Xing</name>
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<author><name sortKey="Charness, Neil" sort="Charness, Neil" uniqKey="Charness N" first="Neil" last="Charness">Neil Charness</name>
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<author><name sortKey="Bian, Jiang" sort="Bian, Jiang" uniqKey="Bian J" first="Jiang" last="Bian">Jiang Bian</name>
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<front><div type="abstract" xml:lang="en"><p><b>OBJECTIVE</b>
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<p>The novel coronavirus disease (COVID-19), broke out in December 2019, is a global pandemic. Rapidly in the past few months, a large number of clinical studies have been initiated worldwide to find effective therapeutics, vaccines, and preventive strategies. In this study, we aim to understand the landscape of COVID-19 clinical research and identify the gaps and issues that may cause difficulty in recruitment and the lack of population representativeness.</p>
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<div type="abstract" xml:lang="en"><p><b>MATERIALS AND METHODS</b>
</p>
<p>We analyzed 2,034 COVID-19 studies registered in the largest public registry - ClinicalTrials.gov. Leveraging natural language processing, descriptive analysis, association analysis, and clustering analysis, we characterized COVID-19 clinical studies by phase and design features. Particularly, we analyzed their eligibility criteria to understand: (1) whether they considered the reported underlying health conditions that may lead to severe illnesses, and (2) if these studies excluded older adults, either explicitly or implicitly, which may reduce the generalizability of these studies in older adults.</p>
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<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>The 5 most frequently tested drugs are Hydroxychloroquine (N=148), Azithromycin (N=46), Tocilizumab (N=29), Lopinavir (N=20), and Ritonavir (N=20). Most trials did not have an upper age limit and did not exclude patients with common chronic conditions such as hypertension and diabetes that are prevalent in older adults. However, known risk factors that may lead to severe illnesses have not been adequately considered by existing studies.</p>
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<div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b>
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<p>A careful examination of the registered COVID-19 clinical studies can identify the research gaps and inform future COVID-19 trial design towards balanced internal validity and generalizability.</p>
</div>
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How the clinical research community responded to the COVID-19 pandemic: An analysis of the COVID-19 clinical studies in ClinicalTrials.gov.

How the clinical research community responded to the COVID-19 pandemic: An analysis of the COVID-19 clinical studies in ClinicalTrials.gov.

Source :

Abstract

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

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