Data_Sheet_1_Semantic and Geographical Analysis of COVID-19 Trials Reveals a Fragmented Clinical Research Landscape Likely to Impair Informativeness.docx

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.

背景：新冠疫情对现代社会造成的前所未有的冲击，掀起了针对有效治疗与诊断策略的“淘金热”，经济、科研及人力资源大规模向专属临床研究倾斜。本研究旨在描述这一快速演变领域的发展趋势，为合理配置资源提供参考依据。
方法：我们搭建了在线知识库新冠试验监测平台（COVID Trial Monitor），以实时分析新冠相关临床试验的增长速率、地域分布及特征。我们采用受控词汇构建结构化语义本体，用于对试验干预措施、研究终点及研究设计进行分类。相关分析结果可通过公开链接https://bioinfo.ieo.it/shiny/app/CovidCT获取。
结果：我们观察到单中心试验占比显著偏高，且研究终点异质性极强；同时试验地域分布与疾病流行程度显著脱节，这意味着多数国家若要完成入组，需要招募占本国现有确诊病例总数比例极不现实的受试者。
结论：这种地域与方法学层面均存在不一致的试验增长态势，引发了人们对当地达成目标样本量的实际可行性，以及多数此类试验能否得出可靠且可推广结果的诸多质疑。我们呼吁统一新冠临床试验的设计标准，并更多采用融入自适应设计（adaptive designs）元素的大型主方案（master protocols）。新冠试验监测平台（COVID Trial Monitor）识别了当前新冠相关临床研究中存在的关键问题，可为研究人员与政策制定者提升相关试验的质量与效率提供实用资源。