Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer

Autores
Wang, Lu; Rotnitzky, Andrea Gloria; Lin, Xihong; Millikan, Randall; Thall, Peter
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We present new statistical analyses of data arising from a clinical trial designed to compare two-stage dynamic treatment regimes (DTRs) for advanced prostate cancer. The trial protocol mandated that patients be initially randomized among four chemotherapies, and that those who responded poorly be re-randomized to one of the remaining candidate therapies. The primary aim was to compare the DTRs' overall success rates, with success defined by the occurrence of successful responses in each of two consecutive courses of the patient's therapy. Of the 150 study participants, 47 did not complete their therapy as per the algorithm. However, 35 of them did so for reasons that precluded further chemotherapy, that is, toxicity and/or progressive disease. Consequently, rather than comparing the overall success rates of the DTRs in the unrealistic event that these patients had remained on their assigned chemotherapies, we conducted an analysis that compared viable switch rules defined by the per-protocol rules but with the additional provision that patients who developed toxicity or progressive disease switch to a non-prespecified therapeutic or palliative strategy. This modification involved consideration of bivariate per-course outcomes encoding both efficacy and toxicity.We used numerical scores elicited from the trial's principal investigator to quantify the clinical desirability of each bivariate per-course outcome, and defined one endpoint as their average over all courses of treatment. Two other simpler sets of scores as well as log survival time were also used as endpoints. Estimation of each DTR-specific mean score was conducted using inverse probability weighted methods that assumed that missingness in the 12 remaining dropouts was informative but explainable in that it only depended on past recorded data.We conducted additional worst-and best-case analyses to evaluate sensitivity of our findings to extreme departures from the explainable dropout assumption.
Fil: Wang, Lu. University of Michigan; Estados Unidos
Fil: Rotnitzky, Andrea Gloria. Universidad Torcuato Di Tella. Departamento de Economía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lin, Xihong. Harvard University; Estados Unidos
Fil: Millikan, Randall. University of Texas; Estados Unidos
Fil: Thall, Peter. University of Texas; Estados Unidos
Materia
CAUSAL INFERENCE
EFFICIENCY
INFORMATIVE DROPOUT
INVERSE PROBABILITY WEIGHTING
MARGINAL STRUCTURAL MODELS
OPTIMAL REGIME
SIMULTANEOUS CONFIDENCE INTERVALS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/199411

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network_name_str CONICET Digital (CONICET)
spelling Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancerWang, LuRotnitzky, Andrea GloriaLin, XihongMillikan, RandallThall, PeterCAUSAL INFERENCEEFFICIENCYINFORMATIVE DROPOUTINVERSE PROBABILITY WEIGHTINGMARGINAL STRUCTURAL MODELSOPTIMAL REGIMESIMULTANEOUS CONFIDENCE INTERVALShttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1We present new statistical analyses of data arising from a clinical trial designed to compare two-stage dynamic treatment regimes (DTRs) for advanced prostate cancer. The trial protocol mandated that patients be initially randomized among four chemotherapies, and that those who responded poorly be re-randomized to one of the remaining candidate therapies. The primary aim was to compare the DTRs' overall success rates, with success defined by the occurrence of successful responses in each of two consecutive courses of the patient's therapy. Of the 150 study participants, 47 did not complete their therapy as per the algorithm. However, 35 of them did so for reasons that precluded further chemotherapy, that is, toxicity and/or progressive disease. Consequently, rather than comparing the overall success rates of the DTRs in the unrealistic event that these patients had remained on their assigned chemotherapies, we conducted an analysis that compared viable switch rules defined by the per-protocol rules but with the additional provision that patients who developed toxicity or progressive disease switch to a non-prespecified therapeutic or palliative strategy. This modification involved consideration of bivariate per-course outcomes encoding both efficacy and toxicity.We used numerical scores elicited from the trial's principal investigator to quantify the clinical desirability of each bivariate per-course outcome, and defined one endpoint as their average over all courses of treatment. Two other simpler sets of scores as well as log survival time were also used as endpoints. Estimation of each DTR-specific mean score was conducted using inverse probability weighted methods that assumed that missingness in the 12 remaining dropouts was informative but explainable in that it only depended on past recorded data.We conducted additional worst-and best-case analyses to evaluate sensitivity of our findings to extreme departures from the explainable dropout assumption.Fil: Wang, Lu. University of Michigan; Estados UnidosFil: Rotnitzky, Andrea Gloria. Universidad Torcuato Di Tella. Departamento de Economía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lin, Xihong. Harvard University; Estados UnidosFil: Millikan, Randall. University of Texas; Estados UnidosFil: Thall, Peter. University of Texas; Estados UnidosAmerican Statistical Association2012-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/199411Wang, Lu; Rotnitzky, Andrea Gloria; Lin, Xihong; Millikan, Randall; Thall, Peter; Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer; American Statistical Association; Journal of The American Statistical Association; 107; 498; 12-2012; 493-5080162-1459CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1080/01621459.2011.641416info:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/abs/10.1080/01621459.2011.641416info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:00:59Zoai:ri.conicet.gov.ar:11336/199411instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:00:59.362CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer
title Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer
spellingShingle Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer
Wang, Lu
CAUSAL INFERENCE
EFFICIENCY
INFORMATIVE DROPOUT
INVERSE PROBABILITY WEIGHTING
MARGINAL STRUCTURAL MODELS
OPTIMAL REGIME
SIMULTANEOUS CONFIDENCE INTERVALS
title_short Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer
title_full Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer
title_fullStr Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer
title_full_unstemmed Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer
title_sort Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer
dc.creator.none.fl_str_mv Wang, Lu
Rotnitzky, Andrea Gloria
Lin, Xihong
Millikan, Randall
Thall, Peter
author Wang, Lu
author_facet Wang, Lu
Rotnitzky, Andrea Gloria
Lin, Xihong
Millikan, Randall
Thall, Peter
author_role author
author2 Rotnitzky, Andrea Gloria
Lin, Xihong
Millikan, Randall
Thall, Peter
author2_role author
author
author
author
dc.subject.none.fl_str_mv CAUSAL INFERENCE
EFFICIENCY
INFORMATIVE DROPOUT
INVERSE PROBABILITY WEIGHTING
MARGINAL STRUCTURAL MODELS
OPTIMAL REGIME
SIMULTANEOUS CONFIDENCE INTERVALS
topic CAUSAL INFERENCE
EFFICIENCY
INFORMATIVE DROPOUT
INVERSE PROBABILITY WEIGHTING
MARGINAL STRUCTURAL MODELS
OPTIMAL REGIME
SIMULTANEOUS CONFIDENCE INTERVALS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We present new statistical analyses of data arising from a clinical trial designed to compare two-stage dynamic treatment regimes (DTRs) for advanced prostate cancer. The trial protocol mandated that patients be initially randomized among four chemotherapies, and that those who responded poorly be re-randomized to one of the remaining candidate therapies. The primary aim was to compare the DTRs' overall success rates, with success defined by the occurrence of successful responses in each of two consecutive courses of the patient's therapy. Of the 150 study participants, 47 did not complete their therapy as per the algorithm. However, 35 of them did so for reasons that precluded further chemotherapy, that is, toxicity and/or progressive disease. Consequently, rather than comparing the overall success rates of the DTRs in the unrealistic event that these patients had remained on their assigned chemotherapies, we conducted an analysis that compared viable switch rules defined by the per-protocol rules but with the additional provision that patients who developed toxicity or progressive disease switch to a non-prespecified therapeutic or palliative strategy. This modification involved consideration of bivariate per-course outcomes encoding both efficacy and toxicity.We used numerical scores elicited from the trial's principal investigator to quantify the clinical desirability of each bivariate per-course outcome, and defined one endpoint as their average over all courses of treatment. Two other simpler sets of scores as well as log survival time were also used as endpoints. Estimation of each DTR-specific mean score was conducted using inverse probability weighted methods that assumed that missingness in the 12 remaining dropouts was informative but explainable in that it only depended on past recorded data.We conducted additional worst-and best-case analyses to evaluate sensitivity of our findings to extreme departures from the explainable dropout assumption.
Fil: Wang, Lu. University of Michigan; Estados Unidos
Fil: Rotnitzky, Andrea Gloria. Universidad Torcuato Di Tella. Departamento de Economía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lin, Xihong. Harvard University; Estados Unidos
Fil: Millikan, Randall. University of Texas; Estados Unidos
Fil: Thall, Peter. University of Texas; Estados Unidos
description We present new statistical analyses of data arising from a clinical trial designed to compare two-stage dynamic treatment regimes (DTRs) for advanced prostate cancer. The trial protocol mandated that patients be initially randomized among four chemotherapies, and that those who responded poorly be re-randomized to one of the remaining candidate therapies. The primary aim was to compare the DTRs' overall success rates, with success defined by the occurrence of successful responses in each of two consecutive courses of the patient's therapy. Of the 150 study participants, 47 did not complete their therapy as per the algorithm. However, 35 of them did so for reasons that precluded further chemotherapy, that is, toxicity and/or progressive disease. Consequently, rather than comparing the overall success rates of the DTRs in the unrealistic event that these patients had remained on their assigned chemotherapies, we conducted an analysis that compared viable switch rules defined by the per-protocol rules but with the additional provision that patients who developed toxicity or progressive disease switch to a non-prespecified therapeutic or palliative strategy. This modification involved consideration of bivariate per-course outcomes encoding both efficacy and toxicity.We used numerical scores elicited from the trial's principal investigator to quantify the clinical desirability of each bivariate per-course outcome, and defined one endpoint as their average over all courses of treatment. Two other simpler sets of scores as well as log survival time were also used as endpoints. Estimation of each DTR-specific mean score was conducted using inverse probability weighted methods that assumed that missingness in the 12 remaining dropouts was informative but explainable in that it only depended on past recorded data.We conducted additional worst-and best-case analyses to evaluate sensitivity of our findings to extreme departures from the explainable dropout assumption.
publishDate 2012
dc.date.none.fl_str_mv 2012-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/199411
Wang, Lu; Rotnitzky, Andrea Gloria; Lin, Xihong; Millikan, Randall; Thall, Peter; Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer; American Statistical Association; Journal of The American Statistical Association; 107; 498; 12-2012; 493-508
0162-1459
CONICET Digital
CONICET
url http://hdl.handle.net/11336/199411
identifier_str_mv Wang, Lu; Rotnitzky, Andrea Gloria; Lin, Xihong; Millikan, Randall; Thall, Peter; Evaluation of viable dynamic treatment regimes in a sequentially randomized trial of advanced prostate cancer; American Statistical Association; Journal of The American Statistical Association; 107; 498; 12-2012; 493-508
0162-1459
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1080/01621459.2011.641416
info:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/abs/10.1080/01621459.2011.641416
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Statistical Association
publisher.none.fl_str_mv American Statistical Association
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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