Dataset Information

Harmonizing Heterogeneous Endpoints in Coronavirus Disease 2019 Trials Without Loss of Information.

ABSTRACT:

Objectives

Many trials investigate potential effects of treatments for coronavirus disease 2019. To provide sufficient information for all involveddecision-makers (clinicians, public health authorities, and drug regulatory agencies), a multiplicity of endpoints must be considered. The objectives are to provide hands-on statistical guidelines for harmonizing heterogeneous endpoints in coronavirus disease 2019 clinical trials.

Design

Randomized controlled trials for patients infected with coronavirus disease 2019.

Setting

General methods that apply to any randomized controlled trial for patients infected with coronavirus disease 2019.

Patients

Coronavirus disease 2019 positive individuals.

Interventions

None.

Measurements and main results

We develop a multistate model that is based on hospitalization, mechanical ventilation, death, and discharge. These events are both categories of the ordinal endpoint recommended by the World Health Organization and also within the core outcome set of the Core Outcome Measures in Effectiveness Trials initiative for coronavirus disease 2019 trials. To support our choice of states in the multistate model, we also perform a brief review of registered coronavirus disease 2019 clinical trials. Based on the multistate model, we give recommendation for compact, informative illustration of time-dynamic treatment effects and explorative statistical analysis. A majority of coronavirus disease 2019 clinical trials collect information on mechanical ventilation, hospitalization, and death. Using reconstructed and real data of coronavirus disease 2019 trials, we show how a stacked probability plot provides a detailed understanding of treatment effects on the patients' course of hospital stay. It contributes to harmonizing multiple endpoints and differing lengths of follow-up both within and between trials.

Conclusions

All ongoing clinical trials should include a stacked probability plot in their statistical analysis plan as descriptive analysis. While primary analysis should be on an early endpoint with appropriate capability to be a surrogate (parameter), our multistate model provides additional detailed descriptive information and links results within and between coronavirus disease 2019 trials.

SUBMITTER: von Cube M

PROVIDER: S-EPMC7737851 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Harmonizing Heterogeneous Endpoints in Coronavirus Disease 2019 Trials Without Loss of Information.

von Cube Maja M Grodd Marlon M Wolkewitz Martin M Hazard Derek D Wengenmayer Tobias T Canet Emmanuel E Lambert Jêrome J

Critical care medicine 20210101 1

<h4>Objectives</h4>Many trials investigate potential effects of treatments for coronavirus disease 2019. To provide sufficient information for all involveddecision-makers (clinicians, public health authorities, and drug regulatory agencies), a multiplicity of endpoints must be considered. The objectives are to provide hands-on statistical guidelines for harmonizing heterogeneous endpoints in coronavirus disease 2019 clinical trials.<h4>Design</h4>Randomized controlled trials for patients infecte ...[more]

PMID: 33148952

Similar Datasets

Project description:BackgroundSince the outbreak of coronavirus disease 2019 (COVID-19), many researchers in China have performed related clinical research. However, systematic reviews of the registered clinical trials are still lacking. Therefore, we conducted a systematic review of clinical trials for COVID-19 to summarize their characteristics.MethodsThis study is based on the PRISMA recommendations in the Cochrane handbook. The Chinese Clinical Registration Center and the ClinicalTrials.gov databases were searched to identify registered clinical trials related to COVID-19. The retrieval inception date was February 9, 2020. Two researchers independently selected the literature based on the inclusion and exclusion criteria, extracted data, and evaluated the risk of bias.ResultsA total of 75 registered clinical trials (63 interventional studies and 12 observational studies) for COVID-19 were identified. The majority of clinical trials were sponsored by Chinese hospitals. Only 11 trials have begun to recruit patients, and none of the registered clinical trials have been completed; 34 trials were early clinical exploratory trials or in the pre-experiment stage, 13 trials were phase III, and four trials were phase IV. The intervention methods included traditional Chinese medicine in 26 trials, Western medicine in 30 trials, and integrated traditional Chinese medicine and Western medicine in 19 trials. The subjects were primarily non-critical adult patients (≥ 18 years old). The median sample size of the trials was 100 (IQR: 60-200), and the median length of the trial periods was 179 d (IQR: 94-366 d). The main outcomes were clinical observation and examinations. Overall, the methodological quality of both the interventional trials and observational studies was low.ConclusionsIntensive clinical trials on the treatment of COVID-19 using traditional Chinese medicine and Western medicine are ongoing or will be performed in China. However, based on the uncertain methodological quality, small sample size, and long trial duration, we will not be able to obtain reliable, high-quality clinical evidence regarding the treatment of COVID-19 in the near future. Improving the quality of study design, prioritizing promising drugs, and using different designs and statistical methods are worth advocating and recommending for clinical trials of COVID-19 in the future.

Dataset Information

Harmonizing Heterogeneous Endpoints in Coronavirus Disease 2019 Trials Without Loss of Information.

Objectives

Design

Setting

Patients

Interventions

Measurements and main results

Conclusions

Publications

Harmonizing Heterogeneous Endpoints in Coronavirus Disease 2019 Trials Without Loss of Information.

Similar Datasets

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