Quality Assessment of the Chinese Clinical Trial Protocols Regarding Treatments for Coronavirus Disease 2019.

ABSTRACT

BACKGROUND: With the global spread of coronavirus disease 2019 (COVID-19), an increasing number of clinical trials are being designed and executed to evaluate the efficacy and safety of various therapies for COVID-19. We conducted this survey to assess the methodological quality of registry protocols on potential treatments for COVID-19. METHODS: Clinical trial protocols were identified on the ClinicalTrials.gov and the Chinese Clinical Trial Registry. Protocols were screened by two investigators independently against pre-defined eligibility criteria. Quality of the included protocols was assessed according to the modified 14-item SPIRIT (Standard Protocol Items Recommendations for Interventional Trials) 2013 Statement. RESULTS: We included 82 randomized controlled trial (RCT) protocols investigating treatment modalities for COVID-19. These ongoing trials are being conducted in 16 provinces, autonomous regions, and municipalities of China, and study interventions were either Western medicines (n = 56) or traditional Chinese medicine (n = 26). Findings of our quality assessment indicated that the existing trial protocols could be further improved on several aspects, including selection and definition of outcome measures, descriptions of study interventions and comparators, study subject recruitment time, definition of study inclusion and exclusion criteria, and allocation concealment methods. Descriptions of random sequence generation methodologies were accurate for the majority of included trial protocols (n = 64; 78.05%); however, reporting of allocation concealment remained unclear in 63 (76.83%) protocols. Therefore, the overall risk of selection bias across these RCTs was judged to be unclear. A total of 52 (63.41%) included RCT protocols were open-label trials and are thus associated with a high risk of performance bias and detection bias. CONCLUSION: Quality of currently available RCT protocols on the treatments for COVID-19 could be further improved. For transparency and effective knowledge translation in real-world clinically settings, it is important for trial investigators to standardize baseline treatments for patients with COVID-19 and assess clinically important core outcome measures. Despite eager anticipation from the public on the results of effectiveness trials in COVID-19, robust design, execution, and reporting of these trials should be regarded as high priority.