Evidence map›Paper›PMID 36760246›Full record

ArticleAnnals of translational medicine2023

New reporting items and recommendations for randomized trials impacted by COVID-19 and force majeure events: a targeted approach.

Tiffany H Leung, James C Ho, Aya El Helali, Everett E Vokes, Xiaofei Wang, Herbert Pang

Abstract read
In one paragraph

Article in Annals of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
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.

Tiffany H Leung *Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
James C Ho *Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
Aya El HelaliDepartment of Clinical Oncology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
Everett E VokesUniversity of Chicago Medicine and Biological Sciences, Chicago, IL, USA.
Xiaofei WangDepartment of Biostatistics and Bioinformatics, Duke University of Medicine, Durham, NC, USA.
Herbert PangDepartment of Biostatistics and Bioinformatics, Duke University of Medicine, Durham, NC, USA.

Funding

Statistical Methods for Cancer Clinical TrialsP01CA142538 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KOSOROK, MICHAEL R · 2010 to 2019
$21.3M
Transforming Clinical Trials for Elderly and Rare Cancers through Intelligent and Robust Information BorrowingR01AG066883 · NIA · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Xiaofei Wang, Shu Yang · 2020 to 2026
$2.0M
NCI NIH HHS P01 CA142538NIA NIH HHS R01 AG066883
6 · The paper itself

Abstract

Background: Appropriate analyses and reporting are essential to the reproducibility and interpretation of clinical trials. However, the coronavirus disease 19 (COVID-19) pandemic and other force majeure events, like the war in Ukraine, have impacted the conduct of clinical trials. Methods: The number of clinical trials potentially impacted were estimated from clinicaltrials.gov. To identify reporting items considered vital for assessing the impact of COVID-19, we reviewed 35 randomized phase III trials from three top oncology journals published between July and December 2020. For validation, we reviewed 29 phase III trials published between January and December 2021. Results: Our results show that the number of clinical trials being potentially impacted in cancer, cardiovascular diseases, and diabetes is at least 1,484, 535, and 145, respectively. The magnitude of disruption is most significant in oncology trials. Based on the review of 35 trials, a modified checklist with ten new and four modified items covering pandemic's impact on trial conduct, protocol changes, delays, data capture, analysis and interpretation was developed to ensure comprehensive and transparent reporting. Our validation shows that six out of seven applicable reporting items were reported in less than 21% of the articles. Conclusions: Our recommendations were proposed to improve the reporting of randomized clinical trials impacted by COVID-19 and force majeure events that are broadly applicable to different areas of medical research.

Indexed as

Coronavirus disease 19 (COVID-19)oncologyrandomized trialsreporting qualityresearch design

Identifiers

PMID36760246
PMCPMC9906209

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.