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Development of a Database of Registered Clinical Trials Using Convalescent Plasma for Treatment of COVID-19: Is Data Harmonization Possible?

Background/Case Studies: COVID-19 convalescent plasma (CCP) is a promising therapeutic option, but efficacy remains unknown In response to the emerging pandemic, multiple clinical trials assessing the efficacy and/or safety of CCP were registered in quick succession on ClinicalTrials gov (CTG) However, concern is growing that several trials may not reach stated enrollment goals We hypothesize that data harmonization among these trials may yield meaningful data that could not be obtained from underpowered individual trials We have developed a multidimensional grid of relevant US clinical trials, with the goal of determining if data harmonization can be achievable by identifying common data standards Study Design/Methods: All US trials registered on CTG as of 5/30/20 with CCP as treatment for COVID-19 patients were considered for inclusion Studies were excluded if they were designed solely for compassionate use (expanded access), assessed the feasibility of CCP collection or delivery per se (no treatment endpoint), were exclusively in children, or were duplicates Key parameters such as study design, patient population(s), and clinical and laboratory endpoints were extracted Trials were grouped based on target patient populations and study design Results/Findings: Between 3/22/20 and 5/30/20, 37 trials involving CCP were registered on CTG 12 were excluded based on above criteria The remaining 25 trials were organized based on patient populations and study design, yielding five distinct groups: (A) double blind randomized control trials (DBRCT) involving outpatients (N=4);(B) DBRCTs involving inpatients (N=6);(C) randomized open label trials involving inpatients (N=2);(D) single-arm open label trials involving inpatients (N=10);(E) single-arm open label trials involving both inpatients and outpatients (N=3) Among the 12 trials randomizing to two arms (groups A, B, C), the non-intervention arm varied (standard plasma, 5% albumin, LR, “standard care”) Among the 21 studies involving inpatients (groups B-E), both clinical severity of patients enrolled, and outcomes analyzed varied greatly Conclusions: Meaningful groupings of CCP clinical trials based on common parameters were developed in the above framework Overlaps as well as sources of heterogeneity among trials were identified This framework allows the generation of preliminary recommendations to facilitate data harmonization across trials that may face accrual problems Prospective pre-statistical harmonization of data across clinical trials by adoption of common data standards, including inclusion and exclusion criteria, study populations, intervention protocols, outcome measures and data dictionaries, can facilitate pooling of data and improve statistical power Both trial-level and individual-patient-level meta-analyses may be employed as statistical strategies to analyze data