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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/199411
Ver los metadatos del registro completo
id |
CONICETDig_0b84100b20ed57e701d1c0554ae12154 |
---|---|
oai_identifier_str |
oai:ri.conicet.gov.ar:11336/199411 |
network_acronym_str |
CONICETDig |
repository_id_str |
3498 |
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 |
_version_ |
1844613798162333696 |
score |
13.070432 |