Estimands for overall survival in clinical trials with treatment switching in oncology
An addendum of the ICH E9 guideline on Statistical Principles for Clinical Trials was released in November 2019 introducing the estimand framework. This new framework aims to align trial objectives and statistical analyses by requiring a precise definition of the inferential quantity of interest, th...
Gespeichert in:
Veröffentlicht in: | Pharmaceutical statistics : the journal of the pharmaceutical industry 2022-01, Vol.21 (1), p.150-162 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 162 |
---|---|
container_issue | 1 |
container_start_page | 150 |
container_title | Pharmaceutical statistics : the journal of the pharmaceutical industry |
container_volume | 21 |
creator | Manitz, Juliane Kan‐Dobrosky, Natalia Buchner, Hannes Casadebaig, Marie‐Laure Degtyarev, Evgeny Dey, Jyotirmoy Haddad, Vincent Jie, Fei Martin, Emily Mo, Mindy Rufibach, Kaspar Shentu, Yue Stalbovskaya, Viktoriya Tang, Rui Yung, Godwin Zhou, Jiangxiu |
description | An addendum of the ICH E9 guideline on Statistical Principles for Clinical Trials was released in November 2019 introducing the estimand framework. This new framework aims to align trial objectives and statistical analyses by requiring a precise definition of the inferential quantity of interest, that is, the estimand. This definition explicitly accounts for intercurrent events, such as switching to new anticancer therapies for the analysis of overall survival (OS), the gold standard in oncology. Traditionally, OS in confirmatory studies is analyzed using the intention‐to‐treat (ITT) approach comparing treatment groups as they were initially randomized regardless of whether treatment switching occurred and regardless of any subsequent therapy (treatment‐policy strategy). Regulatory authorities and other stakeholders often consider ITT results as most relevant. However, the respective estimand only yields a clinically meaningful comparison of two treatment arms if subsequent therapies are already approved and reflect clinical practice. We illustrate different scenarios where subsequent therapies are not yet approved drugs and thus do not reflect clinical practice. In such situations the hypothetical strategy could be more meaningful from patient's and prescriber's perspective. The cross‐industry Oncology Estimand Working Group (www.oncoestimand.org) was initiated to foster a common understanding and consistent implementation of the estimand framework in oncology clinical trials. This paper summarizes the group's recommendations for appropriate estimands in the presence of treatment switching, one of the key intercurrent events in oncology clinical trials. We also discuss how different choices of estimands may impact study design, data collection, trial conduct, analysis, and interpretation. |
doi_str_mv | 10.1002/pst.2158 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2579087902</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2579087902</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3498-20a7d63647d848b886d83d199499679fae6a538c74f81e56bb07a90bbd27e2e43</originalsourceid><addsrcrecordid>eNp1kE9LwzAAR4Mobk7BTyAFL146kzRJk6OM-QcGCk6vIW3TLSNrZtJu7NubuakgeAj5BR6P8AC4RHCIIMS3q9AOMaL8CPQRzUSKGMLHPxuSHjgLYQEhyrmgp6CXEQYpYrwP3sehNUvVVCGpnU_cWntlbRI6vzZrZRPTJKU1jSnjbr1RNiQb087j1qpd6qZNQnyXc9PMdqxrSmfdbHsOTurI6ovDPQBv9-Pp6DGdPD88je4maZkRwVMMVV6xjJG84oQXnLOKZxUSggjBclErzRTNeJmTmiNNWVHAXAlYFBXONdYkG4CbvXfl3UenQyuXJpTaWtVo1wWJaS4gjwdH9PoPunCdb-LvJGYYIU6ooL_C0rsQvK7lysc-fisRlLvWMraWu9YRvToIu2Kpqx_wO24E0j2wMVZv_xXJl9fpl_ATRqGH3A</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2621184595</pqid></control><display><type>article</type><title>Estimands for overall survival in clinical trials with treatment switching in oncology</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Manitz, Juliane ; Kan‐Dobrosky, Natalia ; Buchner, Hannes ; Casadebaig, Marie‐Laure ; Degtyarev, Evgeny ; Dey, Jyotirmoy ; Haddad, Vincent ; Jie, Fei ; Martin, Emily ; Mo, Mindy ; Rufibach, Kaspar ; Shentu, Yue ; Stalbovskaya, Viktoriya ; Tang, Rui ; Yung, Godwin ; Zhou, Jiangxiu</creator><creatorcontrib>Manitz, Juliane ; Kan‐Dobrosky, Natalia ; Buchner, Hannes ; Casadebaig, Marie‐Laure ; Degtyarev, Evgeny ; Dey, Jyotirmoy ; Haddad, Vincent ; Jie, Fei ; Martin, Emily ; Mo, Mindy ; Rufibach, Kaspar ; Shentu, Yue ; Stalbovskaya, Viktoriya ; Tang, Rui ; Yung, Godwin ; Zhou, Jiangxiu</creatorcontrib><description>An addendum of the ICH E9 guideline on Statistical Principles for Clinical Trials was released in November 2019 introducing the estimand framework. This new framework aims to align trial objectives and statistical analyses by requiring a precise definition of the inferential quantity of interest, that is, the estimand. This definition explicitly accounts for intercurrent events, such as switching to new anticancer therapies for the analysis of overall survival (OS), the gold standard in oncology. Traditionally, OS in confirmatory studies is analyzed using the intention‐to‐treat (ITT) approach comparing treatment groups as they were initially randomized regardless of whether treatment switching occurred and regardless of any subsequent therapy (treatment‐policy strategy). Regulatory authorities and other stakeholders often consider ITT results as most relevant. However, the respective estimand only yields a clinically meaningful comparison of two treatment arms if subsequent therapies are already approved and reflect clinical practice. We illustrate different scenarios where subsequent therapies are not yet approved drugs and thus do not reflect clinical practice. In such situations the hypothetical strategy could be more meaningful from patient's and prescriber's perspective. The cross‐industry Oncology Estimand Working Group (www.oncoestimand.org) was initiated to foster a common understanding and consistent implementation of the estimand framework in oncology clinical trials. This paper summarizes the group's recommendations for appropriate estimands in the presence of treatment switching, one of the key intercurrent events in oncology clinical trials. We also discuss how different choices of estimands may impact study design, data collection, trial conduct, analysis, and interpretation.</description><identifier>ISSN: 1539-1604</identifier><identifier>EISSN: 1539-1612</identifier><identifier>DOI: 10.1002/pst.2158</identifier><identifier>PMID: 34605168</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Inc</publisher><subject>Clinical medicine ; Clinical trials ; cross‐over ; Data Interpretation, Statistical ; estimand ; Humans ; ITT ; Medical Oncology ; Neoplasms - drug therapy ; Oncology ; overall survival ; Research Design ; Treatment Switching</subject><ispartof>Pharmaceutical statistics : the journal of the pharmaceutical industry, 2022-01, Vol.21 (1), p.150-162</ispartof><rights>2021 John Wiley & Sons Ltd</rights><rights>2021 John Wiley & Sons Ltd.</rights><rights>2022 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3498-20a7d63647d848b886d83d199499679fae6a538c74f81e56bb07a90bbd27e2e43</citedby><cites>FETCH-LOGICAL-c3498-20a7d63647d848b886d83d199499679fae6a538c74f81e56bb07a90bbd27e2e43</cites><orcidid>0000-0003-0459-1453 ; 0000-0002-2634-1167</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fpst.2158$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fpst.2158$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27903,27904,45553,45554</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34605168$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Manitz, Juliane</creatorcontrib><creatorcontrib>Kan‐Dobrosky, Natalia</creatorcontrib><creatorcontrib>Buchner, Hannes</creatorcontrib><creatorcontrib>Casadebaig, Marie‐Laure</creatorcontrib><creatorcontrib>Degtyarev, Evgeny</creatorcontrib><creatorcontrib>Dey, Jyotirmoy</creatorcontrib><creatorcontrib>Haddad, Vincent</creatorcontrib><creatorcontrib>Jie, Fei</creatorcontrib><creatorcontrib>Martin, Emily</creatorcontrib><creatorcontrib>Mo, Mindy</creatorcontrib><creatorcontrib>Rufibach, Kaspar</creatorcontrib><creatorcontrib>Shentu, Yue</creatorcontrib><creatorcontrib>Stalbovskaya, Viktoriya</creatorcontrib><creatorcontrib>Tang, Rui</creatorcontrib><creatorcontrib>Yung, Godwin</creatorcontrib><creatorcontrib>Zhou, Jiangxiu</creatorcontrib><title>Estimands for overall survival in clinical trials with treatment switching in oncology</title><title>Pharmaceutical statistics : the journal of the pharmaceutical industry</title><addtitle>Pharm Stat</addtitle><description>An addendum of the ICH E9 guideline on Statistical Principles for Clinical Trials was released in November 2019 introducing the estimand framework. This new framework aims to align trial objectives and statistical analyses by requiring a precise definition of the inferential quantity of interest, that is, the estimand. This definition explicitly accounts for intercurrent events, such as switching to new anticancer therapies for the analysis of overall survival (OS), the gold standard in oncology. Traditionally, OS in confirmatory studies is analyzed using the intention‐to‐treat (ITT) approach comparing treatment groups as they were initially randomized regardless of whether treatment switching occurred and regardless of any subsequent therapy (treatment‐policy strategy). Regulatory authorities and other stakeholders often consider ITT results as most relevant. However, the respective estimand only yields a clinically meaningful comparison of two treatment arms if subsequent therapies are already approved and reflect clinical practice. We illustrate different scenarios where subsequent therapies are not yet approved drugs and thus do not reflect clinical practice. In such situations the hypothetical strategy could be more meaningful from patient's and prescriber's perspective. The cross‐industry Oncology Estimand Working Group (www.oncoestimand.org) was initiated to foster a common understanding and consistent implementation of the estimand framework in oncology clinical trials. This paper summarizes the group's recommendations for appropriate estimands in the presence of treatment switching, one of the key intercurrent events in oncology clinical trials. We also discuss how different choices of estimands may impact study design, data collection, trial conduct, analysis, and interpretation.</description><subject>Clinical medicine</subject><subject>Clinical trials</subject><subject>cross‐over</subject><subject>Data Interpretation, Statistical</subject><subject>estimand</subject><subject>Humans</subject><subject>ITT</subject><subject>Medical Oncology</subject><subject>Neoplasms - drug therapy</subject><subject>Oncology</subject><subject>overall survival</subject><subject>Research Design</subject><subject>Treatment Switching</subject><issn>1539-1604</issn><issn>1539-1612</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kE9LwzAAR4Mobk7BTyAFL146kzRJk6OM-QcGCk6vIW3TLSNrZtJu7NubuakgeAj5BR6P8AC4RHCIIMS3q9AOMaL8CPQRzUSKGMLHPxuSHjgLYQEhyrmgp6CXEQYpYrwP3sehNUvVVCGpnU_cWntlbRI6vzZrZRPTJKU1jSnjbr1RNiQb087j1qpd6qZNQnyXc9PMdqxrSmfdbHsOTurI6ovDPQBv9-Pp6DGdPD88je4maZkRwVMMVV6xjJG84oQXnLOKZxUSggjBclErzRTNeJmTmiNNWVHAXAlYFBXONdYkG4CbvXfl3UenQyuXJpTaWtVo1wWJaS4gjwdH9PoPunCdb-LvJGYYIU6ooL_C0rsQvK7lysc-fisRlLvWMraWu9YRvToIu2Kpqx_wO24E0j2wMVZv_xXJl9fpl_ATRqGH3A</recordid><startdate>202201</startdate><enddate>202201</enddate><creator>Manitz, Juliane</creator><creator>Kan‐Dobrosky, Natalia</creator><creator>Buchner, Hannes</creator><creator>Casadebaig, Marie‐Laure</creator><creator>Degtyarev, Evgeny</creator><creator>Dey, Jyotirmoy</creator><creator>Haddad, Vincent</creator><creator>Jie, Fei</creator><creator>Martin, Emily</creator><creator>Mo, Mindy</creator><creator>Rufibach, Kaspar</creator><creator>Shentu, Yue</creator><creator>Stalbovskaya, Viktoriya</creator><creator>Tang, Rui</creator><creator>Yung, Godwin</creator><creator>Zhou, Jiangxiu</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-0459-1453</orcidid><orcidid>https://orcid.org/0000-0002-2634-1167</orcidid></search><sort><creationdate>202201</creationdate><title>Estimands for overall survival in clinical trials with treatment switching in oncology</title><author>Manitz, Juliane ; Kan‐Dobrosky, Natalia ; Buchner, Hannes ; Casadebaig, Marie‐Laure ; Degtyarev, Evgeny ; Dey, Jyotirmoy ; Haddad, Vincent ; Jie, Fei ; Martin, Emily ; Mo, Mindy ; Rufibach, Kaspar ; Shentu, Yue ; Stalbovskaya, Viktoriya ; Tang, Rui ; Yung, Godwin ; Zhou, Jiangxiu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3498-20a7d63647d848b886d83d199499679fae6a538c74f81e56bb07a90bbd27e2e43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Clinical medicine</topic><topic>Clinical trials</topic><topic>cross‐over</topic><topic>Data Interpretation, Statistical</topic><topic>estimand</topic><topic>Humans</topic><topic>ITT</topic><topic>Medical Oncology</topic><topic>Neoplasms - drug therapy</topic><topic>Oncology</topic><topic>overall survival</topic><topic>Research Design</topic><topic>Treatment Switching</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Manitz, Juliane</creatorcontrib><creatorcontrib>Kan‐Dobrosky, Natalia</creatorcontrib><creatorcontrib>Buchner, Hannes</creatorcontrib><creatorcontrib>Casadebaig, Marie‐Laure</creatorcontrib><creatorcontrib>Degtyarev, Evgeny</creatorcontrib><creatorcontrib>Dey, Jyotirmoy</creatorcontrib><creatorcontrib>Haddad, Vincent</creatorcontrib><creatorcontrib>Jie, Fei</creatorcontrib><creatorcontrib>Martin, Emily</creatorcontrib><creatorcontrib>Mo, Mindy</creatorcontrib><creatorcontrib>Rufibach, Kaspar</creatorcontrib><creatorcontrib>Shentu, Yue</creatorcontrib><creatorcontrib>Stalbovskaya, Viktoriya</creatorcontrib><creatorcontrib>Tang, Rui</creatorcontrib><creatorcontrib>Yung, Godwin</creatorcontrib><creatorcontrib>Zhou, Jiangxiu</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Pharmaceutical statistics : the journal of the pharmaceutical industry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Manitz, Juliane</au><au>Kan‐Dobrosky, Natalia</au><au>Buchner, Hannes</au><au>Casadebaig, Marie‐Laure</au><au>Degtyarev, Evgeny</au><au>Dey, Jyotirmoy</au><au>Haddad, Vincent</au><au>Jie, Fei</au><au>Martin, Emily</au><au>Mo, Mindy</au><au>Rufibach, Kaspar</au><au>Shentu, Yue</au><au>Stalbovskaya, Viktoriya</au><au>Tang, Rui</au><au>Yung, Godwin</au><au>Zhou, Jiangxiu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimands for overall survival in clinical trials with treatment switching in oncology</atitle><jtitle>Pharmaceutical statistics : the journal of the pharmaceutical industry</jtitle><addtitle>Pharm Stat</addtitle><date>2022-01</date><risdate>2022</risdate><volume>21</volume><issue>1</issue><spage>150</spage><epage>162</epage><pages>150-162</pages><issn>1539-1604</issn><eissn>1539-1612</eissn><abstract>An addendum of the ICH E9 guideline on Statistical Principles for Clinical Trials was released in November 2019 introducing the estimand framework. This new framework aims to align trial objectives and statistical analyses by requiring a precise definition of the inferential quantity of interest, that is, the estimand. This definition explicitly accounts for intercurrent events, such as switching to new anticancer therapies for the analysis of overall survival (OS), the gold standard in oncology. Traditionally, OS in confirmatory studies is analyzed using the intention‐to‐treat (ITT) approach comparing treatment groups as they were initially randomized regardless of whether treatment switching occurred and regardless of any subsequent therapy (treatment‐policy strategy). Regulatory authorities and other stakeholders often consider ITT results as most relevant. However, the respective estimand only yields a clinically meaningful comparison of two treatment arms if subsequent therapies are already approved and reflect clinical practice. We illustrate different scenarios where subsequent therapies are not yet approved drugs and thus do not reflect clinical practice. In such situations the hypothetical strategy could be more meaningful from patient's and prescriber's perspective. The cross‐industry Oncology Estimand Working Group (www.oncoestimand.org) was initiated to foster a common understanding and consistent implementation of the estimand framework in oncology clinical trials. This paper summarizes the group's recommendations for appropriate estimands in the presence of treatment switching, one of the key intercurrent events in oncology clinical trials. We also discuss how different choices of estimands may impact study design, data collection, trial conduct, analysis, and interpretation.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Inc</pub><pmid>34605168</pmid><doi>10.1002/pst.2158</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-0459-1453</orcidid><orcidid>https://orcid.org/0000-0002-2634-1167</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1539-1604 |
ispartof | Pharmaceutical statistics : the journal of the pharmaceutical industry, 2022-01, Vol.21 (1), p.150-162 |
issn | 1539-1604 1539-1612 |
language | eng |
recordid | cdi_proquest_miscellaneous_2579087902 |
source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
subjects | Clinical medicine Clinical trials cross‐over Data Interpretation, Statistical estimand Humans ITT Medical Oncology Neoplasms - drug therapy Oncology overall survival Research Design Treatment Switching |
title | Estimands for overall survival in clinical trials with treatment switching in oncology |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T10%3A45%3A17IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Estimands%20for%20overall%20survival%20in%20clinical%20trials%20with%20treatment%20switching%20in%20oncology&rft.jtitle=Pharmaceutical%20statistics%20:%20the%20journal%20of%20the%20pharmaceutical%20industry&rft.au=Manitz,%20Juliane&rft.date=2022-01&rft.volume=21&rft.issue=1&rft.spage=150&rft.epage=162&rft.pages=150-162&rft.issn=1539-1604&rft.eissn=1539-1612&rft_id=info:doi/10.1002/pst.2158&rft_dat=%3Cproquest_cross%3E2579087902%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2621184595&rft_id=info:pmid/34605168&rfr_iscdi=true |