Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances
Autor(a) principal: | |
---|---|
Data de Publicação: | 2019 |
Outros Autores: | , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da FIOCRUZ (ARCA) |
Texto Completo: | https://www.arca.fiocruz.br/handle/icict/39607 |
Resumo: | The 100 Million Brazilian Cohort project funded by the Wellcome Trust. Grant code: 202912/B/16/Z. |
id |
CRUZ_d2c6f42e55d1240b16ef661a0e7fc73c |
---|---|
oai_identifier_str |
oai:www.arca.fiocruz.br:icict/39607 |
network_acronym_str |
CRUZ |
network_name_str |
Repositório Institucional da FIOCRUZ (ARCA) |
repository_id_str |
2135 |
spelling |
Ali, M. SanniAlhambra, Daniel PrietoLopes, Luciane CruzRamos, DandaraBispo, NiveaIchihara, Maria Y.Pescarini, Julia M.Williamson, ElizabethFiaccone, Rosemeire L.Barreto, Mauricio LimaSmeeth, Liam2020-01-29T18:13:14Z2020-01-29T18:13:14Z2019ALI, M Sanni et al. Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances. Frontiers in Pharmacology, p. 1-19, 2019.1663-9812https://www.arca.fiocruz.br/handle/icict/3960710.3389/fphar.2019.00973The 100 Million Brazilian Cohort project funded by the Wellcome Trust. Grant code: 202912/B/16/Z.London School of Hygiene and Tropical Medicine. Faculty of Epidemiology and Population Health. London, United Kingdom / University of Oxford. Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences. Center for Statistics in Medicine. Oxford, United Kingdom / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / Universitat Autònoma de Barcelona. Research Group (Idiap Jordi Gol) and Musculoskeletal Research Unit (Fundació IMIM-Parc Salut Mar). Barcelona, Spain.University of Sorocaba. Sorocaba, SP, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / University of Bahia. Institute of Public Health. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.London School of Hygiene and Tropical Medicine. Faculty of Epidemiology and Population Health. London, United Kingdom.London School of Hygiene and Tropical Medicine. Faculty of Epidemiology and Population Health. London, United Kingdom / University of Oxford. Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences. Center for Statistics in Medicine. Oxford, United KingdomFundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / University of Bahia. Institute of Public Health. Salvador, BA, Brasil / Federal University of Bahia. Department of Statistics. Salvador, BA, Brazil.London School of Hygiene and Tropical Medicine. Faculty of Epidemiology and Population Health. London, United Kingdom / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Randomized clinical trials (RCT) are accepted as the gold-standard approaches to measure effects of intervention or treatment on outcomes. They are also the designs of choice for health technology assessment (HTA). Randomization ensures comparability, in both measured and unmeasured pretreatment characteristics, of individuals assigned to treatment and control or comparator. However, even adequately powered RCTs are not always feasible for several reasons such as cost, time, practical and ethical constraints, and limited generalizability. RCTs rely on data collected on selected, homogeneous population under highly controlled conditions; hence, they provide evidence on efficacy of interventions rather than on effectiveness. Alternatively, observational studies can provide evidence on the relative effectiveness or safety of a health technology compared to one or more alternatives when provided under the setting of routine health care practice. In observational studies, however, treatment assignment is a non-random process based on an individual's baseline characteristics; hence, treatment groups may not be comparable in their pretreatment characteristics. As a result, direct comparison of outcomes between treatment groups might lead to biased estimate of the treatment effect. Propensity score approaches have been used to achieve balance or comparability of treatment groups in terms of their measured pretreatment covariates thereby controlling for confounding bias in estimating treatment effects. Despite the popularity of propensity scores methods and recent important methodological advances, misunderstandings on their applications and limitations are all too common. In this article, we present a review of the propensity scores methods, extended applications, recent advances, and their strengths and limitations.engFrontiers MediaViésConfusãoEficáciaAvaliação de tecnologias em saúdeEscore de propensãoSegurançaSecundárioBiasBonfoundingEffectivenessHealth technology assessmentPropensity scoreSafetySecondaryPropensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advancesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txtlicense.txttext/plain; charset=utf-82991https://www.arca.fiocruz.br/bitstream/icict/39607/1/license.txt5a560609d32a3863062d77ff32785d58MD51ORIGINALAli M S Propensity Score Methods Front Pharmacol.pdfAli M S Propensity Score Methods Front Pharmacol.pdfapplication/pdf2721230https://www.arca.fiocruz.br/bitstream/icict/39607/2/Ali%20M%20S%20Propensity%20Score%20Methods%20Front%20Pharmacol.pdf1bce7454ce0c8143f5248332ec20f71eMD52TEXTAli M S Propensity Score Methods Front Pharmacol.pdf.txtAli M S Propensity Score Methods Front Pharmacol.pdf.txtExtracted texttext/plain116559https://www.arca.fiocruz.br/bitstream/icict/39607/3/Ali%20M%20S%20Propensity%20Score%20Methods%20Front%20Pharmacol.pdf.txt50d4249a86d927c2b6bfd28559c4265aMD53icict/396072023-03-15 14:34:19.765oai:www.arca.fiocruz.br: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ório InstitucionalPUBhttps://www.arca.fiocruz.br/oai/requestrepositorio.arca@fiocruz.bropendoar:21352023-03-15T17:34:19Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ)false |
dc.title.pt_BR.fl_str_mv |
Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances |
title |
Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances |
spellingShingle |
Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances Ali, M. Sanni Viés Confusão Eficácia Avaliação de tecnologias em saúde Escore de propensão Segurança Secundário Bias Bonfounding Effectiveness Health technology assessment Propensity score Safety Secondary |
title_short |
Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances |
title_full |
Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances |
title_fullStr |
Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances |
title_full_unstemmed |
Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances |
title_sort |
Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances |
author |
Ali, M. Sanni |
author_facet |
Ali, M. Sanni Alhambra, Daniel Prieto Lopes, Luciane Cruz Ramos, Dandara Bispo, Nivea Ichihara, Maria Y. Pescarini, Julia M. Williamson, Elizabeth Fiaccone, Rosemeire L. Barreto, Mauricio Lima Smeeth, Liam |
author_role |
author |
author2 |
Alhambra, Daniel Prieto Lopes, Luciane Cruz Ramos, Dandara Bispo, Nivea Ichihara, Maria Y. Pescarini, Julia M. Williamson, Elizabeth Fiaccone, Rosemeire L. Barreto, Mauricio Lima Smeeth, Liam |
author2_role |
author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Ali, M. Sanni Alhambra, Daniel Prieto Lopes, Luciane Cruz Ramos, Dandara Bispo, Nivea Ichihara, Maria Y. Pescarini, Julia M. Williamson, Elizabeth Fiaccone, Rosemeire L. Barreto, Mauricio Lima Smeeth, Liam |
dc.subject.other.pt_BR.fl_str_mv |
Viés Confusão Eficácia Avaliação de tecnologias em saúde Escore de propensão Segurança Secundário |
topic |
Viés Confusão Eficácia Avaliação de tecnologias em saúde Escore de propensão Segurança Secundário Bias Bonfounding Effectiveness Health technology assessment Propensity score Safety Secondary |
dc.subject.en.pt_BR.fl_str_mv |
Bias Bonfounding Effectiveness Health technology assessment Propensity score Safety Secondary |
description |
The 100 Million Brazilian Cohort project funded by the Wellcome Trust. Grant code: 202912/B/16/Z. |
publishDate |
2019 |
dc.date.issued.fl_str_mv |
2019 |
dc.date.accessioned.fl_str_mv |
2020-01-29T18:13:14Z |
dc.date.available.fl_str_mv |
2020-01-29T18:13:14Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
ALI, M Sanni et al. Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances. Frontiers in Pharmacology, p. 1-19, 2019. |
dc.identifier.uri.fl_str_mv |
https://www.arca.fiocruz.br/handle/icict/39607 |
dc.identifier.issn.pt_BR.fl_str_mv |
1663-9812 |
dc.identifier.doi.none.fl_str_mv |
10.3389/fphar.2019.00973 |
identifier_str_mv |
ALI, M Sanni et al. Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances. Frontiers in Pharmacology, p. 1-19, 2019. 1663-9812 10.3389/fphar.2019.00973 |
url |
https://www.arca.fiocruz.br/handle/icict/39607 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Frontiers Media |
publisher.none.fl_str_mv |
Frontiers Media |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da FIOCRUZ (ARCA) instname:Fundação Oswaldo Cruz (FIOCRUZ) instacron:FIOCRUZ |
instname_str |
Fundação Oswaldo Cruz (FIOCRUZ) |
instacron_str |
FIOCRUZ |
institution |
FIOCRUZ |
reponame_str |
Repositório Institucional da FIOCRUZ (ARCA) |
collection |
Repositório Institucional da FIOCRUZ (ARCA) |
bitstream.url.fl_str_mv |
https://www.arca.fiocruz.br/bitstream/icict/39607/1/license.txt https://www.arca.fiocruz.br/bitstream/icict/39607/2/Ali%20M%20S%20Propensity%20Score%20Methods%20Front%20Pharmacol.pdf https://www.arca.fiocruz.br/bitstream/icict/39607/3/Ali%20M%20S%20Propensity%20Score%20Methods%20Front%20Pharmacol.pdf.txt |
bitstream.checksum.fl_str_mv |
5a560609d32a3863062d77ff32785d58 1bce7454ce0c8143f5248332ec20f71e 50d4249a86d927c2b6bfd28559c4265a |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ) |
repository.mail.fl_str_mv |
repositorio.arca@fiocruz.br |
_version_ |
1813008893576478720 |