Dose Individualization for Phase I Cancer Trials With Broadened Eligibility
ABSTRACT Broadening eligibility criteria in cancer trials has been advocated to represent the intended patient population more accurately. The advantages are clear in terms of generalizability and recruitment, however there are some important considerations in terms of design for efficiency and pati...
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Veröffentlicht in: | Statistics in medicine 2024-12, Vol.43 (29), p.5534-5547 |
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creator | Silva, Rebecca B. Cheng, Bin Carvajal, Richard D. Lee, Shing M. |
description | ABSTRACT
Broadening eligibility criteria in cancer trials has been advocated to represent the intended patient population more accurately. The advantages are clear in terms of generalizability and recruitment, however there are some important considerations in terms of design for efficiency and patient safety. While toxicity may be expected to be homogeneous across these subpopulations, designs should be able to recommend safe and precise doses if subpopulations with different toxicity profiles exist. Dose‐finding designs accounting for patient heterogeneity have been proposed, but existing methods assume that the source of heterogeneity is known. We propose a broadened eligibility dose‐finding design to address the situation of unknown patient heterogeneity in phase I cancer clinical trials where eligibility is expanded, and multiple eligibility criteria could potentially lead to different optimal doses for patient subgroups. The design offers a two‐in‐one approach to dose‐finding by simultaneously selecting patient criteria that differentiate the maximum tolerated dose (MTD), using stochastic search variable selection, and recommending the subpopulation‐specific MTD if needed. Our simulation study compares the proposed design to the naive approach of assuming patient homogeneity and demonstrates favorable operating characteristics across a wide range of scenarios, allocating patients more often to their true MTD during the trial, recommending more than one MTD when needed, and identifying criteria that differentiate the patient population. The proposed design highlights the advantages of adding more variability at an early stage and demonstrates how assuming patient homogeneity can lead to unsafe or sub‐therapeutic dose recommendations. |
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Broadening eligibility criteria in cancer trials has been advocated to represent the intended patient population more accurately. The advantages are clear in terms of generalizability and recruitment, however there are some important considerations in terms of design for efficiency and patient safety. While toxicity may be expected to be homogeneous across these subpopulations, designs should be able to recommend safe and precise doses if subpopulations with different toxicity profiles exist. Dose‐finding designs accounting for patient heterogeneity have been proposed, but existing methods assume that the source of heterogeneity is known. We propose a broadened eligibility dose‐finding design to address the situation of unknown patient heterogeneity in phase I cancer clinical trials where eligibility is expanded, and multiple eligibility criteria could potentially lead to different optimal doses for patient subgroups. The design offers a two‐in‐one approach to dose‐finding by simultaneously selecting patient criteria that differentiate the maximum tolerated dose (MTD), using stochastic search variable selection, and recommending the subpopulation‐specific MTD if needed. Our simulation study compares the proposed design to the naive approach of assuming patient homogeneity and demonstrates favorable operating characteristics across a wide range of scenarios, allocating patients more often to their true MTD during the trial, recommending more than one MTD when needed, and identifying criteria that differentiate the patient population. The proposed design highlights the advantages of adding more variability at an early stage and demonstrates how assuming patient homogeneity can lead to unsafe or sub‐therapeutic dose recommendations.</description><identifier>ISSN: 0277-6715</identifier><identifier>ISSN: 1097-0258</identifier><identifier>EISSN: 1097-0258</identifier><identifier>DOI: 10.1002/sim.10264</identifier><identifier>PMID: 39479896</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Antineoplastic Agents - administration & dosage ; Antineoplastic Agents - adverse effects ; Antineoplastic Agents - therapeutic use ; Bayesian variable selection ; Cancer ; Clinical outcomes ; Clinical trials ; Clinical Trials, Phase I as Topic - methods ; Computer Simulation ; dose selection ; Dose-Response Relationship, Drug ; Drug dosages ; Humans ; Maximum Tolerated Dose ; Models, Statistical ; Neoplasms - drug therapy ; patient heterogeneity ; Patient Selection ; phase I ; Research Design ; Toxicity</subject><ispartof>Statistics in medicine, 2024-12, Vol.43 (29), p.5534-5547</ispartof><rights>2024 John Wiley & Sons Ltd.</rights><rights>2024 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2434-bf7ca28285a899e6ab87a648bc040e5e323a58a68c1970f1939dc7e8269dcb3b3</cites><orcidid>0000-0001-8295-2467</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%2Fsim.10264$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fsim.10264$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39479896$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Silva, Rebecca B.</creatorcontrib><creatorcontrib>Cheng, Bin</creatorcontrib><creatorcontrib>Carvajal, Richard D.</creatorcontrib><creatorcontrib>Lee, Shing M.</creatorcontrib><title>Dose Individualization for Phase I Cancer Trials With Broadened Eligibility</title><title>Statistics in medicine</title><addtitle>Stat Med</addtitle><description>ABSTRACT
Broadening eligibility criteria in cancer trials has been advocated to represent the intended patient population more accurately. The advantages are clear in terms of generalizability and recruitment, however there are some important considerations in terms of design for efficiency and patient safety. While toxicity may be expected to be homogeneous across these subpopulations, designs should be able to recommend safe and precise doses if subpopulations with different toxicity profiles exist. Dose‐finding designs accounting for patient heterogeneity have been proposed, but existing methods assume that the source of heterogeneity is known. We propose a broadened eligibility dose‐finding design to address the situation of unknown patient heterogeneity in phase I cancer clinical trials where eligibility is expanded, and multiple eligibility criteria could potentially lead to different optimal doses for patient subgroups. The design offers a two‐in‐one approach to dose‐finding by simultaneously selecting patient criteria that differentiate the maximum tolerated dose (MTD), using stochastic search variable selection, and recommending the subpopulation‐specific MTD if needed. Our simulation study compares the proposed design to the naive approach of assuming patient homogeneity and demonstrates favorable operating characteristics across a wide range of scenarios, allocating patients more often to their true MTD during the trial, recommending more than one MTD when needed, and identifying criteria that differentiate the patient population. The proposed design highlights the advantages of adding more variability at an early stage and demonstrates how assuming patient homogeneity can lead to unsafe or sub‐therapeutic dose recommendations.</description><subject>Antineoplastic Agents - administration & dosage</subject><subject>Antineoplastic Agents - adverse effects</subject><subject>Antineoplastic Agents - therapeutic use</subject><subject>Bayesian variable selection</subject><subject>Cancer</subject><subject>Clinical outcomes</subject><subject>Clinical trials</subject><subject>Clinical Trials, Phase I as Topic - methods</subject><subject>Computer Simulation</subject><subject>dose selection</subject><subject>Dose-Response Relationship, Drug</subject><subject>Drug dosages</subject><subject>Humans</subject><subject>Maximum Tolerated Dose</subject><subject>Models, Statistical</subject><subject>Neoplasms - drug therapy</subject><subject>patient heterogeneity</subject><subject>Patient Selection</subject><subject>phase I</subject><subject>Research Design</subject><subject>Toxicity</subject><issn>0277-6715</issn><issn>1097-0258</issn><issn>1097-0258</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kMtKw0AUQAdRbK0u_AEJuNFF7DySeSy1Vi0qClZcDpNkYqekmTqTKPXrnZrqQnB1L9zD4XIAOETwDEGIh94swoJpsgX6CAoWQ5zybdCHmLGYMpT2wJ73cwgRSjHbBT0iEia4oH1we2m9jiZ1Yd5N0arKfKrG2DoqrYseZ2p9i0aqzrWLps6oykcvpplFF86qQte6iMaVeTWZqUyz2gc7ZSD0wWYOwPPVeDq6ie8eriej87s4xwlJ4qxkucIc81RxITRVGWeKJjzLYQJ1qgkmKuWK8hwJBkskiChypjmmYWYkIwNw0nmXzr612jdyYXyuq0rV2rZeEoRDi4SKNKDHf9C5bV0dvgsUCcbQgQbqtKNyZ713upRLZxbKrSSCcl1YhsLyu3BgjzbGNlvo4pf8SRqAYQd8mEqv_jfJp8l9p_wC0p-Daw</recordid><startdate>20241220</startdate><enddate>20241220</enddate><creator>Silva, Rebecca B.</creator><creator>Cheng, Bin</creator><creator>Carvajal, Richard D.</creator><creator>Lee, Shing M.</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/0000-0001-8295-2467</orcidid></search><sort><creationdate>20241220</creationdate><title>Dose Individualization for Phase I Cancer Trials With Broadened Eligibility</title><author>Silva, Rebecca B. ; Cheng, Bin ; Carvajal, Richard D. ; Lee, Shing M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2434-bf7ca28285a899e6ab87a648bc040e5e323a58a68c1970f1939dc7e8269dcb3b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Antineoplastic Agents - administration & dosage</topic><topic>Antineoplastic Agents - adverse effects</topic><topic>Antineoplastic Agents - therapeutic use</topic><topic>Bayesian variable selection</topic><topic>Cancer</topic><topic>Clinical outcomes</topic><topic>Clinical trials</topic><topic>Clinical Trials, Phase I as Topic - methods</topic><topic>Computer Simulation</topic><topic>dose selection</topic><topic>Dose-Response Relationship, Drug</topic><topic>Drug dosages</topic><topic>Humans</topic><topic>Maximum Tolerated Dose</topic><topic>Models, Statistical</topic><topic>Neoplasms - drug therapy</topic><topic>patient heterogeneity</topic><topic>Patient Selection</topic><topic>phase I</topic><topic>Research Design</topic><topic>Toxicity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Silva, Rebecca B.</creatorcontrib><creatorcontrib>Cheng, Bin</creatorcontrib><creatorcontrib>Carvajal, Richard D.</creatorcontrib><creatorcontrib>Lee, Shing M.</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>Statistics in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Silva, Rebecca B.</au><au>Cheng, Bin</au><au>Carvajal, Richard D.</au><au>Lee, Shing M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dose Individualization for Phase I Cancer Trials With Broadened Eligibility</atitle><jtitle>Statistics in medicine</jtitle><addtitle>Stat Med</addtitle><date>2024-12-20</date><risdate>2024</risdate><volume>43</volume><issue>29</issue><spage>5534</spage><epage>5547</epage><pages>5534-5547</pages><issn>0277-6715</issn><issn>1097-0258</issn><eissn>1097-0258</eissn><abstract>ABSTRACT
Broadening eligibility criteria in cancer trials has been advocated to represent the intended patient population more accurately. The advantages are clear in terms of generalizability and recruitment, however there are some important considerations in terms of design for efficiency and patient safety. While toxicity may be expected to be homogeneous across these subpopulations, designs should be able to recommend safe and precise doses if subpopulations with different toxicity profiles exist. Dose‐finding designs accounting for patient heterogeneity have been proposed, but existing methods assume that the source of heterogeneity is known. We propose a broadened eligibility dose‐finding design to address the situation of unknown patient heterogeneity in phase I cancer clinical trials where eligibility is expanded, and multiple eligibility criteria could potentially lead to different optimal doses for patient subgroups. The design offers a two‐in‐one approach to dose‐finding by simultaneously selecting patient criteria that differentiate the maximum tolerated dose (MTD), using stochastic search variable selection, and recommending the subpopulation‐specific MTD if needed. Our simulation study compares the proposed design to the naive approach of assuming patient homogeneity and demonstrates favorable operating characteristics across a wide range of scenarios, allocating patients more often to their true MTD during the trial, recommending more than one MTD when needed, and identifying criteria that differentiate the patient population. The proposed design highlights the advantages of adding more variability at an early stage and demonstrates how assuming patient homogeneity can lead to unsafe or sub‐therapeutic dose recommendations.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>39479896</pmid><doi>10.1002/sim.10264</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-8295-2467</orcidid></addata></record> |
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subjects | Antineoplastic Agents - administration & dosage Antineoplastic Agents - adverse effects Antineoplastic Agents - therapeutic use Bayesian variable selection Cancer Clinical outcomes Clinical trials Clinical Trials, Phase I as Topic - methods Computer Simulation dose selection Dose-Response Relationship, Drug Drug dosages Humans Maximum Tolerated Dose Models, Statistical Neoplasms - drug therapy patient heterogeneity Patient Selection phase I Research Design Toxicity |
title | Dose Individualization for Phase I Cancer Trials With Broadened Eligibility |
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