Advance of Novel Coronavirus Registration Clinical Trial

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Abstract

Background

To analyze the characteristics and heterogeneity of clinical trials of Novel Coronavirus(COVID-19) registered in the China Clinical Trial Registry (ChiCTR), and provide data bases and information references for clinical treatment

Methods

Statistics of COVID-19 clinical trials registered with ChiCTR as of February 24, 2020 were collected. Descriptive analysis of registration characteristics. The chi-square test is used to compare statistical differences between different study types, intervention methods, study stage, and Primary sponsor.

Results

232 COVID-19 studies registered at the ChiCTR were collected. The overall number of COVID-19 registrations was increased. Hubei Province, China has the largest number of registrations. There were significant differences between the number of participants(P=0.000), study duration(P=0.008), study assignment(P=0.000), and blind method(P=0.000) for different study types. Significant differences could be seen in the dimensions of multicenter study(P=0.022), of participants numbe(P=0.000), study duration(P=0.000) and study assignment(P=0.001) for the four intervention methods. There were significant differences in study assignment(P=0.043) between the early and late studies. CMT drugs with high research frequency are chloroquine, lopinavir / ritonavir, and I-IFN; BI was Cell therapy, plasma therapy, Thymosin, and M/P-AB.

Conclusions

Different study design characteristics have led to significant differences in some aspects of the COVID-19 clinical trial. Timely summary analysis can provide more treatment options and evidence for clinical practice.

Article activity feed

  1. SciScore for 10.1101/2020.03.16.20034934: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationIt is defined as: (1) Number of study locations: Single study location or Multiple study locations; (2) Number of participants: <100, 100 to 300, 301 to 1000,> 1000. (3) Study duration(month): <1, 1 to 3, 4 to 12,> 12. (4) Blind method: open, single blind, double blind, unspecified. (5) Study assignment: randomized, non-randomized, factorial grouping, continuous grouping, and others. (6) key inclusion/exclusion criteria: yes.
    BlindingIt is defined as: (1) Number of study locations: Single study location or Multiple study locations; (2) Number of participants: <100, 100 to 300, 301 to 1000,> 1000. (3) Study duration(month): <1, 1 to 3, 4 to 12,> 12. (4) Blind method: open, single blind, double blind, unspecified. (5) Study assignment: randomized, non-randomized, factorial grouping, continuous grouping, and others. (6) key inclusion/exclusion criteria: yes.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Two reviewers (Gao Song and Mengqun Cheng) were transferred to SPSS and checked to determine the final dataset.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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:
    This study has some limitations. The data for this study were derived only from ChiCTR. There may be other databases containing COVID-19 clinical studies. The time limit for research registration is short, and relevant registration information has not been filled in, and it cannot truly reflect its true quantity and level. However, the innovation of this article is to summarize and analyze the registration of ChiCTR’s COVID-19 clinical research in a timely manner, reflecting the research status and development trend of clinical trials in this field, which is “time-effective”.

    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.

    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 checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.