Harmonizing Heterogeneous Endpoints in Coronavirus Disease 2019 Trials Without Loss of Information
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
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.
Article activity feed
-
SciScore for 10.1101/2020.03.31.20049007: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Besides these potentials, both of the proposed multistate models have the limitation that they do not account for patient triage possibly necessitated by ICU congestion (19). Additional research is needed to avoid selection …
SciScore for 10.1101/2020.03.31.20049007: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Besides these potentials, both of the proposed multistate models have the limitation that they do not account for patient triage possibly necessitated by ICU congestion (19). Additional research is needed to avoid selection bias arising from this special clinical situation. Finally, our proposal should be understood as a complement for the primary analysis. Rather than suggesting COS for COVID-19 trials, we provide a way for simultaneous evaluation of multiple endpoints within COS using information all of the available data. To conclude, we recommend to complement the primary analysis with a stacked probability plot for the clinical events mechanical ventilation, discharge alive and death.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
-
-
SciScore for 10.1101/2020.03.31.20049007: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization Currently, cases in randomized trials are comprised of community-acquired infections. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore …
SciScore for 10.1101/2020.03.31.20049007: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization Currently, cases in randomized trials are comprised of community-acquired infections. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, please follow this link.
-
