Background: The unprecedented impact of the COVID-19 pandemic on modern society has ignited a “gold rush” for effective treatment and diagnostic strategies, with a significant diversion of economic, scientific, and human resources toward dedicated clinical research. We aimed to describe trends in this rapidly changing landscape to inform adequate resource allocation. Methods: We developed an online repository (COVID Trial Monitor) to analyze in real time the growth rate, geographical distribution, and characteristics of COVID-19 related trials. We defined structured semantic ontologies with controlled vocabularies to categorize trial interventions, study endpoints, and study designs. Analyses are publicly available at https://bioinfo.ieo.it/shiny/app/CovidCT. Results: We observe a clear prevalence of monocentric trials with highly heterogeneous endpoints and a significant disconnect between geographic distribution and disease prevalence, implying that most countries would need to recruit unrealistic percentages of their total prevalent cases to fulfill enrolment. Conclusions: This geographically and methodologically incoherent growth casts doubts on the actual feasibility of locally reaching target sample sizes and the probability of most of these trials providing reliable and transferable results. We call for the harmonization of clinical trial design criteria for COVID-19 and the increased use of larger master protocols incorporating elements of adaptive designs. COVID Trial Monitor identifies critical issues in current COVID-19-related clinical research and represents a useful resource with which researchers and policymakers can improve the quality and efficiency of related trials.

Semantic and geographical analysis of COVID-19 trials reveals a fragmented clinical research landscape likely to impair informativeness / G. Tini, B.A. Duso, F. Bellerba, F. Corso, S. Gandini, S. Minucci, P.G. Pelicci, L. Mazzarella. - In: FRONTIERS IN MEDICINE. - ISSN 2296-858X. - 7:(2020), pp. 367.1-367.7. [10.3389/fmed.2020.00367]

Semantic and geographical analysis of COVID-19 trials reveals a fragmented clinical research landscape likely to impair informativeness

F. Bellerba;S. Gandini;S. Minucci;P.G. Pelicci;L. Mazzarella
2020

Abstract

Background: The unprecedented impact of the COVID-19 pandemic on modern society has ignited a “gold rush” for effective treatment and diagnostic strategies, with a significant diversion of economic, scientific, and human resources toward dedicated clinical research. We aimed to describe trends in this rapidly changing landscape to inform adequate resource allocation. Methods: We developed an online repository (COVID Trial Monitor) to analyze in real time the growth rate, geographical distribution, and characteristics of COVID-19 related trials. We defined structured semantic ontologies with controlled vocabularies to categorize trial interventions, study endpoints, and study designs. Analyses are publicly available at https://bioinfo.ieo.it/shiny/app/CovidCT. Results: We observe a clear prevalence of monocentric trials with highly heterogeneous endpoints and a significant disconnect between geographic distribution and disease prevalence, implying that most countries would need to recruit unrealistic percentages of their total prevalent cases to fulfill enrolment. Conclusions: This geographically and methodologically incoherent growth casts doubts on the actual feasibility of locally reaching target sample sizes and the probability of most of these trials providing reliable and transferable results. We call for the harmonization of clinical trial design criteria for COVID-19 and the increased use of larger master protocols incorporating elements of adaptive designs. COVID Trial Monitor identifies critical issues in current COVID-19-related clinical research and represents a useful resource with which researchers and policymakers can improve the quality and efficiency of related trials.
COVID; Design; Endpoint; Geography; Trial
Settore MED/04 - Patologia Generale
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/930385
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