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Development of an External Control Arm Using Electronic Health Record-Based Real-World Data to Evaluate the Efficacy
Ji-Young Jeon1,2, Min-Ji Kim1,3, Yong-Jin Im1,2
1Center for Clinical Pharmacology, Jeonbuk National University Hospital, Jeonju, Korea.
Abstract:
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.
Insights
Building an external control arm (ECA) using real-world data (RWD) from COVID-19 patients showed no significant difference in recovery time compared to traditional randomized controlled trials (RCTs). This approach can accelerate new treatment development during pandemics.
Area of Science:
- Clinical Trials
- Real-World Evidence
- Health Informatics
Background:
- Developing treatments for severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is crucial for public health.
- Externally controlled trials (ECTs) offer a potential method to expedite drug development timelines.
- Evaluating the feasibility of ECTs using real-world data (RWD) is essential for regulatory decision-making.
Purpose of the Study:
- To assess the feasibility of using an external control arm (ECA) derived from RWD for coronavirus disease 19 (COVID-19) treatment trials.
- To compare an ECA built from electronic health record (EHR) data against the control arm of a randomized controlled trial (RCT).
Main Methods:
- An ECA was constructed using RWD from an EHR-based COVID-19 cohort.
- The ECA served as the control for previously conducted Adaptive COVID-19 Treatment Trials (ACTT).
- Propensity score matching was employed to balance covariates (age, sex, baseline clinical status) between the ECA and RCT control groups.
Main Results:
- No statistically significant differences were observed in the time to recovery between the ECAs and the control arms of the ACTT trials.
- The baseline clinical status ordinal score was the most influential covariate in constructing the ECA.
- Propensity score matching successfully balanced key patient characteristics.
Conclusions:
- External control arms built from EHR-derived RWD are a viable substitute for traditional RCT control arms in COVID-19 treatment studies.
- This methodology can significantly accelerate the development of novel therapeutics, particularly during public health emergencies.
- ECTs using RWD hold promise for more efficient drug development and regulatory review processes.
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