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Impact of COVID-19 pandemic on oncology clinical trial design, data collection and analysis
BACKGROUND: To identify and assess via simulation the impact of COVID-19 pandemic on oncology trials and discuss potential mitigation strategies for study design, data collection, endpoints and analyses. METHODS: We simulated clinical trials to evaluate the COVID-19 impact on overall survival and pr...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8935956/ https://www.ncbi.nlm.nih.gov/pubmed/35331946 http://dx.doi.org/10.1016/j.cct.2022.106736 |
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author | Tang, Rui (Sammi) Zhu, Jian Chen, Tai-Tsang Liu, Fang Jiang, Xun Huang, Bo Lee, J. Jack Beckman, Robert A. |
author_facet | Tang, Rui (Sammi) Zhu, Jian Chen, Tai-Tsang Liu, Fang Jiang, Xun Huang, Bo Lee, J. Jack Beckman, Robert A. |
author_sort | Tang, Rui (Sammi) |
collection | PubMed |
description | BACKGROUND: To identify and assess via simulation the impact of COVID-19 pandemic on oncology trials and discuss potential mitigation strategies for study design, data collection, endpoints and analyses. METHODS: We simulated clinical trials to evaluate the COVID-19 impact on overall survival and progression-free survival. We evaluated survival in single-region trials with different proportions of impacted patients across treatment arms, and in multi-region randomized trials with different proportions of impacted patients across regions. We also assessed the impact on PFS when the missingness of disease assessment and censoring rules vary. Impact on the trial success and robustness of statistical inference was summarized. RESULTS: Without regional impact, the impact on OS analysis is minimal if proportions of impacted patients are similar across arms, however, if a larger proportion of treatment arm patients are impacted, trials may suffer substantial power loss and underestimate treatment effect size. For multi-region trials, if more treatment arm patients are enrolled from more severely impacted regions, trials also have poorer performance. For PFS analysis, the intent-to-treat rule performs well even when the treatment arm patients are more likely to miss disease assessments, while the consecutive-missing censoring rule may lead to poorer performance. CONCLUSION: COVID-19 affects oncology trials. Simulations would be highly informative to Data Monitoring Committee in understanding the impact and making appropriate recommendations, upon which the sponsor could start planning potential remedies. We also recommend a decision tree for choosing the appropriate methods for PFS evaluation in the presence of missing disease assessments due to COVID-19. |
format | Online Article Text |
id | pubmed-8935956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89359562022-03-22 Impact of COVID-19 pandemic on oncology clinical trial design, data collection and analysis Tang, Rui (Sammi) Zhu, Jian Chen, Tai-Tsang Liu, Fang Jiang, Xun Huang, Bo Lee, J. Jack Beckman, Robert A. Contemp Clin Trials Article BACKGROUND: To identify and assess via simulation the impact of COVID-19 pandemic on oncology trials and discuss potential mitigation strategies for study design, data collection, endpoints and analyses. METHODS: We simulated clinical trials to evaluate the COVID-19 impact on overall survival and progression-free survival. We evaluated survival in single-region trials with different proportions of impacted patients across treatment arms, and in multi-region randomized trials with different proportions of impacted patients across regions. We also assessed the impact on PFS when the missingness of disease assessment and censoring rules vary. Impact on the trial success and robustness of statistical inference was summarized. RESULTS: Without regional impact, the impact on OS analysis is minimal if proportions of impacted patients are similar across arms, however, if a larger proportion of treatment arm patients are impacted, trials may suffer substantial power loss and underestimate treatment effect size. For multi-region trials, if more treatment arm patients are enrolled from more severely impacted regions, trials also have poorer performance. For PFS analysis, the intent-to-treat rule performs well even when the treatment arm patients are more likely to miss disease assessments, while the consecutive-missing censoring rule may lead to poorer performance. CONCLUSION: COVID-19 affects oncology trials. Simulations would be highly informative to Data Monitoring Committee in understanding the impact and making appropriate recommendations, upon which the sponsor could start planning potential remedies. We also recommend a decision tree for choosing the appropriate methods for PFS evaluation in the presence of missing disease assessments due to COVID-19. Elsevier Inc. 2022-05 2022-03-21 /pmc/articles/PMC8935956/ /pubmed/35331946 http://dx.doi.org/10.1016/j.cct.2022.106736 Text en © 2022 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Tang, Rui (Sammi) Zhu, Jian Chen, Tai-Tsang Liu, Fang Jiang, Xun Huang, Bo Lee, J. Jack Beckman, Robert A. Impact of COVID-19 pandemic on oncology clinical trial design, data collection and analysis |
title | Impact of COVID-19 pandemic on oncology clinical trial design, data collection and analysis |
title_full | Impact of COVID-19 pandemic on oncology clinical trial design, data collection and analysis |
title_fullStr | Impact of COVID-19 pandemic on oncology clinical trial design, data collection and analysis |
title_full_unstemmed | Impact of COVID-19 pandemic on oncology clinical trial design, data collection and analysis |
title_short | Impact of COVID-19 pandemic on oncology clinical trial design, data collection and analysis |
title_sort | impact of covid-19 pandemic on oncology clinical trial design, data collection and analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8935956/ https://www.ncbi.nlm.nih.gov/pubmed/35331946 http://dx.doi.org/10.1016/j.cct.2022.106736 |
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