Addressing the Impact of the COVID-19 Pandemic on Survival Outcomes in Randomized Phase III Oncology Trials

We assessed the impact of the coronavirus disease 2019 (COVID-19) pandemic on the statistical analysis of time-to-event outcomes in late-phase oncology trials. Using a simulated case study that mimics a Phase III ongoing trial during the pandemic, we evaluated the impact of COVID-19-related deaths,...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of Data Science 2023-10, Vol.21 (4), p.781-798
Hauptverfasser: Ye, Jiabu, Yu, Binbing, Mann, Helen, Sabin, Antony, Szijgyarto, Zsolt, Wright, David, Mukhopadhyay, Pralay, Massacesi, Cristian, Ghiorghiu, Serban, Iacona, Renee
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 798
container_issue 4
container_start_page 781
container_title Journal of Data Science
container_volume 21
creator Ye, Jiabu
Yu, Binbing
Mann, Helen
Sabin, Antony
Szijgyarto, Zsolt
Wright, David
Mukhopadhyay, Pralay
Massacesi, Cristian
Ghiorghiu, Serban
Iacona, Renee
description We assessed the impact of the coronavirus disease 2019 (COVID-19) pandemic on the statistical analysis of time-to-event outcomes in late-phase oncology trials. Using a simulated case study that mimics a Phase III ongoing trial during the pandemic, we evaluated the impact of COVID-19-related deaths, time off-treatment and missed clinical visits due to the pandemic, on overall survival and/or progression-free survival in terms of test size (also referred to as Type 1 error rate or alpha level), power, and hazard ratio (HR) estimates. We found that COVID-19-related deaths would impact both size and power, and lead to biased HR estimates; the impact would be more severe if there was an imbalance in COVID-19-related deaths between the study arms. Approaches censoring COVID-19-related deaths may mitigate the impact on power and HR estimation, especially if study data cut-off was extended to recover censoring-related event loss. The impact of COVID-19-related time off-treatment would be modest for power, and moderate for size and HR estimation. Different rules of censoring cancer progression times result in a slight difference in the power for the analysis of progression-free survival. The simulations provided valuable information for determining whether clinical-trial modifications should be required for ongoing trials during the COVID-19 pandemic.
doi_str_mv 10.6339/22-JDS1079
format Article
fullrecord <record><control><sourceid>airiti_cross</sourceid><recordid>TN_cdi_crossref_primary_10_6339_22_JDS1079</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><airiti_id>16838602_N202310170006_00010</airiti_id><sourcerecordid>16838602_N202310170006_00010</sourcerecordid><originalsourceid>FETCH-LOGICAL-a1859-905c38b176e53d64d21ee2afba77caf8543e81a7abb4703a290da0941fcdb95a3</originalsourceid><addsrcrecordid>eNpNkEtPwzAQhC0EEqVw4Rf4jBRY23n5WLU8gipS0cLVcmyndWliZKeVyq8npT1w2dmVRqOdD6FbAvcpY_yB0uh1MieQ8TM0IGnOojwFev5vv0RXIawBKIccBuhrpLU3Idh2ibuVwUXzLVWHXf13jcvPYhIRjmey1aaxCrsWz7d-Z3dyg8ttp1xjArYtfu8NrrE_RuPZSoY-qChw2Sq3ccs9XngrN-EaXdS9mJuTDtHH0-Ni_BJNy-diPJpGkuQJjzgkiuUVyVKTMJ3GmhJjqKwrmWVK1nkSM5MTmcmqijNgsm-iJfCY1EpXPJFsiO6Oucq7ELypxbe3jfR7QUAcMAlKxQlTb2ZHs7Tedlas3da3_XfiQOwATLxRoIwAyQAgFf0gwH4BV6BowQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Addressing the Impact of the COVID-19 Pandemic on Survival Outcomes in Randomized Phase III Oncology Trials</title><source>DOAJ Directory of Open Access Journals</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Ye, Jiabu ; Yu, Binbing ; Mann, Helen ; Sabin, Antony ; Szijgyarto, Zsolt ; Wright, David ; Mukhopadhyay, Pralay ; Massacesi, Cristian ; Ghiorghiu, Serban ; Iacona, Renee</creator><creatorcontrib>Ye, Jiabu ; Yu, Binbing ; Mann, Helen ; Sabin, Antony ; Szijgyarto, Zsolt ; Wright, David ; Mukhopadhyay, Pralay ; Massacesi, Cristian ; Ghiorghiu, Serban ; Iacona, Renee</creatorcontrib><description>We assessed the impact of the coronavirus disease 2019 (COVID-19) pandemic on the statistical analysis of time-to-event outcomes in late-phase oncology trials. Using a simulated case study that mimics a Phase III ongoing trial during the pandemic, we evaluated the impact of COVID-19-related deaths, time off-treatment and missed clinical visits due to the pandemic, on overall survival and/or progression-free survival in terms of test size (also referred to as Type 1 error rate or alpha level), power, and hazard ratio (HR) estimates. We found that COVID-19-related deaths would impact both size and power, and lead to biased HR estimates; the impact would be more severe if there was an imbalance in COVID-19-related deaths between the study arms. Approaches censoring COVID-19-related deaths may mitigate the impact on power and HR estimation, especially if study data cut-off was extended to recover censoring-related event loss. The impact of COVID-19-related time off-treatment would be modest for power, and moderate for size and HR estimation. Different rules of censoring cancer progression times result in a slight difference in the power for the analysis of progression-free survival. The simulations provided valuable information for determining whether clinical-trial modifications should be required for ongoing trials during the COVID-19 pandemic.</description><identifier>ISSN: 1683-8602</identifier><identifier>ISSN: 1680-743X</identifier><identifier>EISSN: 1683-8602</identifier><identifier>DOI: 10.6339/22-JDS1079</identifier><language>eng</language><publisher>中華資料採礦協會</publisher><ispartof>Journal of Data Science, 2023-10, Vol.21 (4), p.781-798</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a1859-905c38b176e53d64d21ee2afba77caf8543e81a7abb4703a290da0941fcdb95a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,782,786,866,27931,27932</link.rule.ids></links><search><creatorcontrib>Ye, Jiabu</creatorcontrib><creatorcontrib>Yu, Binbing</creatorcontrib><creatorcontrib>Mann, Helen</creatorcontrib><creatorcontrib>Sabin, Antony</creatorcontrib><creatorcontrib>Szijgyarto, Zsolt</creatorcontrib><creatorcontrib>Wright, David</creatorcontrib><creatorcontrib>Mukhopadhyay, Pralay</creatorcontrib><creatorcontrib>Massacesi, Cristian</creatorcontrib><creatorcontrib>Ghiorghiu, Serban</creatorcontrib><creatorcontrib>Iacona, Renee</creatorcontrib><title>Addressing the Impact of the COVID-19 Pandemic on Survival Outcomes in Randomized Phase III Oncology Trials</title><title>Journal of Data Science</title><description>We assessed the impact of the coronavirus disease 2019 (COVID-19) pandemic on the statistical analysis of time-to-event outcomes in late-phase oncology trials. Using a simulated case study that mimics a Phase III ongoing trial during the pandemic, we evaluated the impact of COVID-19-related deaths, time off-treatment and missed clinical visits due to the pandemic, on overall survival and/or progression-free survival in terms of test size (also referred to as Type 1 error rate or alpha level), power, and hazard ratio (HR) estimates. We found that COVID-19-related deaths would impact both size and power, and lead to biased HR estimates; the impact would be more severe if there was an imbalance in COVID-19-related deaths between the study arms. Approaches censoring COVID-19-related deaths may mitigate the impact on power and HR estimation, especially if study data cut-off was extended to recover censoring-related event loss. The impact of COVID-19-related time off-treatment would be modest for power, and moderate for size and HR estimation. Different rules of censoring cancer progression times result in a slight difference in the power for the analysis of progression-free survival. The simulations provided valuable information for determining whether clinical-trial modifications should be required for ongoing trials during the COVID-19 pandemic.</description><issn>1683-8602</issn><issn>1680-743X</issn><issn>1683-8602</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNpNkEtPwzAQhC0EEqVw4Rf4jBRY23n5WLU8gipS0cLVcmyndWliZKeVyq8npT1w2dmVRqOdD6FbAvcpY_yB0uh1MieQ8TM0IGnOojwFev5vv0RXIawBKIccBuhrpLU3Idh2ibuVwUXzLVWHXf13jcvPYhIRjmey1aaxCrsWz7d-Z3dyg8ttp1xjArYtfu8NrrE_RuPZSoY-qChw2Sq3ccs9XngrN-EaXdS9mJuTDtHH0-Ni_BJNy-diPJpGkuQJjzgkiuUVyVKTMJ3GmhJjqKwrmWVK1nkSM5MTmcmqijNgsm-iJfCY1EpXPJFsiO6Oucq7ELypxbe3jfR7QUAcMAlKxQlTb2ZHs7Tedlas3da3_XfiQOwATLxRoIwAyQAgFf0gwH4BV6BowQ</recordid><startdate>20231001</startdate><enddate>20231001</enddate><creator>Ye, Jiabu</creator><creator>Yu, Binbing</creator><creator>Mann, Helen</creator><creator>Sabin, Antony</creator><creator>Szijgyarto, Zsolt</creator><creator>Wright, David</creator><creator>Mukhopadhyay, Pralay</creator><creator>Massacesi, Cristian</creator><creator>Ghiorghiu, Serban</creator><creator>Iacona, Renee</creator><general>中華資料採礦協會</general><scope>188</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20231001</creationdate><title>Addressing the Impact of the COVID-19 Pandemic on Survival Outcomes in Randomized Phase III Oncology Trials</title><author>Ye, Jiabu ; Yu, Binbing ; Mann, Helen ; Sabin, Antony ; Szijgyarto, Zsolt ; Wright, David ; Mukhopadhyay, Pralay ; Massacesi, Cristian ; Ghiorghiu, Serban ; Iacona, Renee</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a1859-905c38b176e53d64d21ee2afba77caf8543e81a7abb4703a290da0941fcdb95a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Ye, Jiabu</creatorcontrib><creatorcontrib>Yu, Binbing</creatorcontrib><creatorcontrib>Mann, Helen</creatorcontrib><creatorcontrib>Sabin, Antony</creatorcontrib><creatorcontrib>Szijgyarto, Zsolt</creatorcontrib><creatorcontrib>Wright, David</creatorcontrib><creatorcontrib>Mukhopadhyay, Pralay</creatorcontrib><creatorcontrib>Massacesi, Cristian</creatorcontrib><creatorcontrib>Ghiorghiu, Serban</creatorcontrib><creatorcontrib>Iacona, Renee</creatorcontrib><collection>Airiti Library</collection><collection>CrossRef</collection><jtitle>Journal of Data Science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ye, Jiabu</au><au>Yu, Binbing</au><au>Mann, Helen</au><au>Sabin, Antony</au><au>Szijgyarto, Zsolt</au><au>Wright, David</au><au>Mukhopadhyay, Pralay</au><au>Massacesi, Cristian</au><au>Ghiorghiu, Serban</au><au>Iacona, Renee</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Addressing the Impact of the COVID-19 Pandemic on Survival Outcomes in Randomized Phase III Oncology Trials</atitle><jtitle>Journal of Data Science</jtitle><date>2023-10-01</date><risdate>2023</risdate><volume>21</volume><issue>4</issue><spage>781</spage><epage>798</epage><pages>781-798</pages><issn>1683-8602</issn><issn>1680-743X</issn><eissn>1683-8602</eissn><abstract>We assessed the impact of the coronavirus disease 2019 (COVID-19) pandemic on the statistical analysis of time-to-event outcomes in late-phase oncology trials. Using a simulated case study that mimics a Phase III ongoing trial during the pandemic, we evaluated the impact of COVID-19-related deaths, time off-treatment and missed clinical visits due to the pandemic, on overall survival and/or progression-free survival in terms of test size (also referred to as Type 1 error rate or alpha level), power, and hazard ratio (HR) estimates. We found that COVID-19-related deaths would impact both size and power, and lead to biased HR estimates; the impact would be more severe if there was an imbalance in COVID-19-related deaths between the study arms. Approaches censoring COVID-19-related deaths may mitigate the impact on power and HR estimation, especially if study data cut-off was extended to recover censoring-related event loss. The impact of COVID-19-related time off-treatment would be modest for power, and moderate for size and HR estimation. Different rules of censoring cancer progression times result in a slight difference in the power for the analysis of progression-free survival. The simulations provided valuable information for determining whether clinical-trial modifications should be required for ongoing trials during the COVID-19 pandemic.</abstract><pub>中華資料採礦協會</pub><doi>10.6339/22-JDS1079</doi><tpages>18</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1683-8602
ispartof Journal of Data Science, 2023-10, Vol.21 (4), p.781-798
issn 1683-8602
1680-743X
1683-8602
language eng
recordid cdi_crossref_primary_10_6339_22_JDS1079
source DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals
title Addressing the Impact of the COVID-19 Pandemic on Survival Outcomes in Randomized Phase III Oncology Trials
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-03T20%3A31%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-airiti_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Addressing%20the%20Impact%20of%20the%20COVID-19%20Pandemic%20on%20Survival%20Outcomes%20in%20Randomized%20Phase%20III%20Oncology%20Trials&rft.jtitle=Journal%20of%20Data%20Science&rft.au=Ye,%20Jiabu&rft.date=2023-10-01&rft.volume=21&rft.issue=4&rft.spage=781&rft.epage=798&rft.pages=781-798&rft.issn=1683-8602&rft.eissn=1683-8602&rft_id=info:doi/10.6339/22-JDS1079&rft_dat=%3Cairiti_cross%3E16838602_N202310170006_00010%3C/airiti_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_airiti_id=16838602_N202310170006_00010&rfr_iscdi=true