The IMPACT of COVID-19 Pandemic on Clinical Trials for Various Disease Areas.
Author(s)
ABSTRACT WITHDRAWN
OBJECTIVES: The COVID-19 pandemic disrupted the conduct of clinical trials leading to premature termination and delays in registration of new studies. This study aims to analyse the impact of COVID-19 pandemic on clinical trials. METHODS: Snapshots from the ClinicalTrials.gov database (CTDB) were downloaded in 2020 and updated early 2021. Time series exponential smoothing regression models were fitted to data from pre-COVID-19 period (2007-2019) and used to forecast the hypothetical trends in 2020 without Covid-19 pandemic. Records presenting adequate information were categorised according to 20 disease areas using MeSH classification. COVID-19 impact was assessed by comparing observed vs forecasted number of trials. RESULTS: A total of 299,337 (82.8% of the total number of trials) were classified into predefined disease areas. Of those, the number of ongoing studies in the domains of infectious diseases exceeded the forecasted trends for Q2-Q4 of 2020, which was driven mainly by COVID-19-related trials. For all diseases areas other than non-infectious diseases, the quarterly numbers of ongoing studies were lower than forecasts for respective quarters of 2020 (-1.6% to -9.3%). Although the rates of newly registered trials significantly increased in the second half of 2020, the overall numbers of ongoing trials did not catch-up with the expected level before the end of the year. CONCLUSIONS: The COVID-19 pandemic has impaired the conduct of the clinical trials and redirected the efforts towards the investigation of technologies targeting the COVID-19 pandemic. The observed obstruction, especially in the field of non-communicable diseases may, in the global perspective, translate into a significant loss of clinical benefit through a delayed implementation of new technologies.
Conference/Value in Health Info
2021-05, ISPOR 2021, Montreal, Canada
Value in Health, Volume 24, Issue 5, S1 (May 2021)
Code
PMU52
Topic
Methodological & Statistical Research, Organizational Practices, Real World Data & Information Systems
Topic Subcategory
Artificial Intelligence, Machine Learning, Predictive Analytics, Distributed Data & Research Networks, Industry
Disease
No Specific Disease