Development of an External Control Arm Using Electronic Health Record-Based Real-World Data to Evaluate the Efficacy of COVID-19 Treatment.

To protect people from severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection, tremendous research efforts have been made toward coronavirus disease 19 (COVID-19) treatment development. Externally controlled trials (ECTs) may help reduce their development time. To evaluate whether ECT using real-world data (RWD) of patients with COVID-19 is feasible enough to be used for regulatory decision making, we built an external control arm (ECA) based on RWD as a control arm of a previously conducted randomized controlled trial (RCT), and compared it to the control arm of the RCT. The electronic health record (EHR)-based COVID-19 cohort dataset was used as RWD, and three Adaptive COVID-19 Treatment Trial (ACTT) datasets were used as RCTs. Among the RWD datasets, eligible patients were evaluated as a pool of external control subjects of the ACTT-1, ACTT-2, and ACTT-3 trials, respectively. The ECAs were built using propensity score matching, and the balance of age, sex, and baseline clinical status ordinal scale as covariates between the treatment arms of Asian patients in each ACTT and the pools of external control subjects was assessed before and after 1:1 matching. There was no statistically significant difference in time to recovery between ECAs and the control arms of each ACTT. Among the covariates, the baseline status ordinal score had the greatest influence on the building of ECA. This study demonstrates that ECA based on EHR data of COVID-19 patients could sufficiently replace the control arm of an RCT, and it is expected to help develop new treatments faster in emergency situations, such as the COVID-19 pandemic.

Obesity and Coronavirus Disease 2019.

Obesity, which is one of the most important noncommunicable diseases, has become an epidemic. With the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, the collision of these two health risks has increased the threat of adverse events and serious threats to public health. In this review, the impact of obesity on COVID-19 severity and mortality is presented. The mechanism by which obesity increases susceptibility and severity is discussed. As a low-grade inflammatory disease, obesity provides a pro-inflammatory milieu by which adipose tissue expressing angiotensin converting enzyme 2, which is known as a receptor for severe acute respiratory syndrome coronavirus 2, works as a viral reservoir. Finally, the role of metabolic and bariatric surgeries during the COVID-19 era will be discussed.

Evaluation of a blockchain-based dynamic consent platform (METORY) in a decentralized and multicenter clinical trial using virtual drugs.

Blockchain is a novel data architecture characterized by a chronological sequence of blocks in a decentralized manner. We aimed to evaluate the real-world feasibility of a blockchain-based dynamic consent platform (METORY) in a decentralized and multicenter trial. The study consisted of three visits (i.e., screening and 2 follow-up visits) with a 2-week interval. Each subject was required to report the self-measured body temperatures and take a virtual investigational drug by entering the unique drug code on the application. To simulate real-world study settings, two major (i.e., changes in the schedule of body temperature measurement) and three minor protocol amendments (i.e., nonsignificant changes without any changes in the procedures) were set. Overall study completion rates, proportion of consent, and response time to each protocol amendment and adherence were evaluated. A total of 60 subjects (30 in each center) were enrolled in two study centers. All subjects completed the study, and the overall proportion of consent to each protocol amendment was 95.7 ± 13.7% (mean ± SD), with a median response time of 0.2 h. Overall, subjects took 90.8% ± 19.2% of the total drug, whereas compliance with the schedule was 69.1% ± 27.0%. Subjects reported 96.7% ± 4.2% of the total body temperature measurements whereas the adherence to the schedule was 59.0% ± 25.0%, which remarkably decreased after major protocol amendments. In conclusion, we evaluated a blockchain-based dynamic consent platform in real clinical trial settings. The results suggested that major changes should be avoided unless subjects' proper understanding is warranted.

Genomic and phylogenetic analyses of SARS-CoV-2 strains isolated in the city of Gwangju, South Korea (preprint)

Since the first identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China in late December 2019, the coronavirus disease 2019 (COVID-19) has spread fast around the world. RNA viruses, including SARS-CoV-2, have higher gene mutations than DNA viruses during virus replication. Variations in SARS-CoV-2 genome could contribute to efficiency of viral spread and severity of COVID-19. In this study, we analyzed the locations of genomic mutations to investigate the genetic diversity among isolates of SARS-CoV-2 in Gwangju. We detected non-synonymous and frameshift mutations in various parts of SARS-CoV-2 genome. The phylogenetic analysis for whole genome showed that SARS-CoV-2 genomes in Gwangju isolates are clustered within clade V and G. Our findings not only provide a glimpse into changes of prevalent virus clades in Gwangju, South Korea, but also support genomic surveillance of SARS-CoV-2 to aid in the development of efficient therapeutic antibodies and vaccines against COVID-19.