Randomized Controlled Trials for COVID-19: Evaluation of Optimal Randomization Methodologies - Need for the Data Validation of the Completed Trials, and to Improve the Ongoing and Future Randomized Trial Designs

Emani, Venkata R.; Goswami, Sanjeev; Nandanoor, Dheeraj; Emani, Shaila R.; Reddy, Nidhi K.; Reddy, Raghunath

During this emerging COVID-19 pandemic, initially there were no proven treatment options. With the release of randomized controlled trial results, we are beginning to see possible treatment options for COVID-19. The Recovery trials showed an Absolute Risk Reduction (ARR) in mortality by 2.8% with Dexamethasone, and the ACTT-1 trial showed that the treatment with Remdesivir reduced the Time to recovery by 4 days. The Hydroxychloroquine and Lopinavir/Ritonavir treatments did not show any mortality benefit in both the Recovery and WHO Solidarity trials. The NIH Hydroxychloroquine and Brazilian Hydroxychloroquine trials did not show any benefit for Hydroxychloroquine based on the 7-point ordinal scale outcomes. The randomization methodologies utilized in these controlled trials and the quality of published data were reviewed to examine their adaptability to treat patients. We found that the randomization methodologies of these trials were suboptimal for matching the studied groups based on disease severity among critically ill hospitalized COVID-19 patients with high mortality rates. The published literature is very limited about the disease severity metrics among the compared groups, and failed to show that the data is without fatal sampling errors and sampling biases. We also found that there is a definite need for the validation of data in these trials along with additional important disease severity metrics to ensure that the trials’ conclusions were accurate. We also propose proper randomization methodologies for the design of randomized controlled trials for COVID-19, and guidance for the publication of COVID-19 trial results.