Evidence map›Paper›PMID 35326967›Full record

ArticleHealthcare (Basel, Switzerland)2022

Impact of COVID-19 Pandemic Declaration on New Oncology Trial Commencements: An Interrupted Time Series with Segmented Regression Analysis.

Hyeon Uk Bin, Sohyun Jeong, Heeyoung Lee

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. 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

3 authors.

Hyeon Uk BinDepartment of Clinical Medicinal Sciences, Konyang University, Nonsan 32992, Korea.
Sohyun JeongMarcus Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School, Boston, MA 02131, USA.
Heeyoung LeeDepartment of Clinical Medicinal Sciences, Konyang University, Nonsan 32992, Korea.ORCID 0000-0001-8099-5025

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to assess the trend in oncology trial commencements registered on ClinicalTrials.gov and to evaluate the contributing factors by comparing the trends in the pre- and post-COVID-19 pandemic era. The ClinicalTrials.gov database was searched to identify oncology study trials starting from 1 January 2018 to 28 February 2021. Data on the variables of start/complete date, phase, status, funding source, center, country and study type were extracted. According to the time point of the COVID-19 pandemic declaration by the World Health Organization (WHO), March 2020, we analyzed the extracted data, including interrupted time series (ITS) analysis and multivariable regression analysis. We identified 18,561 new oncology trials during the study period. A total of 5678 oncology trials in the prepandemic period and 6134 in the postpandemic period were included in the comparative analysis. The year 2020 had the most newly launched trials (32.3%), and the majority of trials were planned to be conducted for longer than two years (70.3%). The results of ITS show the trend in the commencement of oncology trials was significantly increased after the pandemic declaration (coefficient = 27.99; 95% CI = 19.27 to 36.71). Drug intervention trials were the largest contributor to the increased trial number compared to different interventions, such as trials of devices or procedures (OR = 1.14; 95% CI = 1.03 to 1.26, OR = 1.09; 95% CI = 0.91 to 1.29, and OR = 1.12; 95% CI = 0.96 to 1.31, respectively), whereas the United Kingdom was the highest contributor to the number of decreased trials (OR = 0.67; 95% CI = 0.51 to 0.89

Indexed as

clinicaltrial.govCOVID-19oncologypandemic

Identifiers

PMID35326967
PMCPMC8953517

What OpenQuestion holds

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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.