Export Ready — 

Predicting effective adaptation to breast cancer to help women BOUNCE back: Protocol for a Multicenter Clinical Pilot Study

Bibliographic Details
Main Author: Pettini, Greta
Publication Date: 2022
Other Authors: Sanchini, Virginia, Pat-Horenczyk, Ruth, Sousa, Berta, Masiero, Marianna, Marzorati, Chiara, Galimberti, Viviana Enrica, Munzone, Elisabetta, Mattson, Johanna, Vehmanen, Leena, Utriainen, Meri, Roziner, Ilan, Lemos, Raquel, Frasquilho, Diana, Cardoso, Fatima, Oliveira-Maia, Albino J, Kolokotroni, Eleni, Stamatakos, Georgios, Leskelä, Riikka-Leena, Haavisto, Ira, Salonen, Juha, Richter, Robert, Karademas, Evangelos, Poikonen-Saksela, Paula, Mazzocco, Ketti
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.12/8883
Summary: Background: Despite the continued progress of medicine, dealing with breast cancer is becoming a major socioeconomic challenge, particularly due to its increasing incidence. The ability to better manage and adapt to the entire care process depends not only on the type of cancer but also on the patient’s sociodemographic and psychological characteristics as well as on the social environment in which a person lives and interacts. Therefore, it is important to understand which factors may contribute to successful adaptation to breast cancer. To our knowledge, no studies have been performed on the combination effect of multiple psychological, biological, and functional variables in predicting the patient’s ability to bounce back from a stressful life event, such as a breast cancer diagnosis. Here we describe the study protocol of a multicenter clinical study entitled “Predicting Effective Adaptation to Breast Cancer to Help Women to BOUNCE Back” or, in short, BOUNCE. Objective: The aim of the study is to build a quantitative mathematical model of factors associated with the capacity for optimal adjustment to cancer and to study resilience through the cancer continuum in a population of patients with breast cancer. Methods: A total of 660 women with breast cancer will be recruited from five European cancer centers in Italy, Finland, Israel, and Portugal. Biomedical and psychosocial variables will be collected using the Noona Healthcare platform. Psychosocial, sociodemographic, lifestyle, and clinical variables will be measured every 3 months, starting from presurgery assessment (ie, baseline) to 18 months after surgery. Temporal data mining, time-series prediction, sequence classification methods, clustering time-series data, and temporal association rules will be used to develop the predictive model. Results: The recruitment process stared in January 2019 and ended in November 2021. Preliminary results have been published in a scientific journal and are available for consultation on the BOUNCE project website. Data analysis and dissemination of the study results will be performed in 2022. Conclusions: This study will develop a predictive model that is able to describe individual resilience and identify different resilience trajectories along the care process. The results will allow the implementation of tailored interventions according to patients’ needs, supported by eHealth technologies. Trial Registration: ClinicalTrials.gov NCT05095675; https://clinicaltrials.gov/ct2/show/NCT05095675 International Registered Report Identifier (IRRID): DERR1-10.2196/34564
id RCAP_0aa285dacf61d2a741a82c4b6d3e105f
oai_identifier_str oai:repositorio.ispa.pt:10400.12/8883
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Predicting effective adaptation to breast cancer to help women BOUNCE back: Protocol for a Multicenter Clinical Pilot StudyResiliencePersonalityCopingDecision-makingCancerQuality of lifeBackground: Despite the continued progress of medicine, dealing with breast cancer is becoming a major socioeconomic challenge, particularly due to its increasing incidence. The ability to better manage and adapt to the entire care process depends not only on the type of cancer but also on the patient’s sociodemographic and psychological characteristics as well as on the social environment in which a person lives and interacts. Therefore, it is important to understand which factors may contribute to successful adaptation to breast cancer. To our knowledge, no studies have been performed on the combination effect of multiple psychological, biological, and functional variables in predicting the patient’s ability to bounce back from a stressful life event, such as a breast cancer diagnosis. Here we describe the study protocol of a multicenter clinical study entitled “Predicting Effective Adaptation to Breast Cancer to Help Women to BOUNCE Back” or, in short, BOUNCE. Objective: The aim of the study is to build a quantitative mathematical model of factors associated with the capacity for optimal adjustment to cancer and to study resilience through the cancer continuum in a population of patients with breast cancer. Methods: A total of 660 women with breast cancer will be recruited from five European cancer centers in Italy, Finland, Israel, and Portugal. Biomedical and psychosocial variables will be collected using the Noona Healthcare platform. Psychosocial, sociodemographic, lifestyle, and clinical variables will be measured every 3 months, starting from presurgery assessment (ie, baseline) to 18 months after surgery. Temporal data mining, time-series prediction, sequence classification methods, clustering time-series data, and temporal association rules will be used to develop the predictive model. Results: The recruitment process stared in January 2019 and ended in November 2021. Preliminary results have been published in a scientific journal and are available for consultation on the BOUNCE project website. Data analysis and dissemination of the study results will be performed in 2022. Conclusions: This study will develop a predictive model that is able to describe individual resilience and identify different resilience trajectories along the care process. The results will allow the implementation of tailored interventions according to patients’ needs, supported by eHealth technologies. Trial Registration: ClinicalTrials.gov NCT05095675; https://clinicaltrials.gov/ct2/show/NCT05095675 International Registered Report Identifier (IRRID): DERR1-10.2196/34564JMIR Publications Inc.Repositório do ISPAPettini, GretaSanchini, VirginiaPat-Horenczyk, RuthSousa, BertaMasiero, MariannaMarzorati, ChiaraGalimberti, Viviana EnricaMunzone, ElisabettaMattson, JohannaVehmanen, LeenaUtriainen, MeriRoziner, IlanLemos, RaquelFrasquilho, DianaCardoso, FatimaOliveira-Maia, Albino JKolokotroni, EleniStamatakos, GeorgiosLeskelä, Riikka-LeenaHaavisto, IraSalonen, JuhaRichter, RobertKarademas, EvangelosPoikonen-Saksela, PaulaMazzocco, Ketti2022-12-26T16:16:56Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.12/8883eng1929074810.2196/34564info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-07T14:59:56Zoai:repositorio.ispa.pt:10400.12/8883Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T01:04:31.554882Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Predicting effective adaptation to breast cancer to help women BOUNCE back: Protocol for a Multicenter Clinical Pilot Study
title Predicting effective adaptation to breast cancer to help women BOUNCE back: Protocol for a Multicenter Clinical Pilot Study
spellingShingle Predicting effective adaptation to breast cancer to help women BOUNCE back: Protocol for a Multicenter Clinical Pilot Study
Pettini, Greta
Resilience
Personality
Coping
Decision-making
Cancer
Quality of life
title_short Predicting effective adaptation to breast cancer to help women BOUNCE back: Protocol for a Multicenter Clinical Pilot Study
title_full Predicting effective adaptation to breast cancer to help women BOUNCE back: Protocol for a Multicenter Clinical Pilot Study
title_fullStr Predicting effective adaptation to breast cancer to help women BOUNCE back: Protocol for a Multicenter Clinical Pilot Study
title_full_unstemmed Predicting effective adaptation to breast cancer to help women BOUNCE back: Protocol for a Multicenter Clinical Pilot Study
title_sort Predicting effective adaptation to breast cancer to help women BOUNCE back: Protocol for a Multicenter Clinical Pilot Study
author Pettini, Greta
author_facet Pettini, Greta
Sanchini, Virginia
Pat-Horenczyk, Ruth
Sousa, Berta
Masiero, Marianna
Marzorati, Chiara
Galimberti, Viviana Enrica
Munzone, Elisabetta
Mattson, Johanna
Vehmanen, Leena
Utriainen, Meri
Roziner, Ilan
Lemos, Raquel
Frasquilho, Diana
Cardoso, Fatima
Oliveira-Maia, Albino J
Kolokotroni, Eleni
Stamatakos, Georgios
Leskelä, Riikka-Leena
Haavisto, Ira
Salonen, Juha
Richter, Robert
Karademas, Evangelos
Poikonen-Saksela, Paula
Mazzocco, Ketti
author_role author
author2 Sanchini, Virginia
Pat-Horenczyk, Ruth
Sousa, Berta
Masiero, Marianna
Marzorati, Chiara
Galimberti, Viviana Enrica
Munzone, Elisabetta
Mattson, Johanna
Vehmanen, Leena
Utriainen, Meri
Roziner, Ilan
Lemos, Raquel
Frasquilho, Diana
Cardoso, Fatima
Oliveira-Maia, Albino J
Kolokotroni, Eleni
Stamatakos, Georgios
Leskelä, Riikka-Leena
Haavisto, Ira
Salonen, Juha
Richter, Robert
Karademas, Evangelos
Poikonen-Saksela, Paula
Mazzocco, Ketti
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório do ISPA
dc.contributor.author.fl_str_mv Pettini, Greta
Sanchini, Virginia
Pat-Horenczyk, Ruth
Sousa, Berta
Masiero, Marianna
Marzorati, Chiara
Galimberti, Viviana Enrica
Munzone, Elisabetta
Mattson, Johanna
Vehmanen, Leena
Utriainen, Meri
Roziner, Ilan
Lemos, Raquel
Frasquilho, Diana
Cardoso, Fatima
Oliveira-Maia, Albino J
Kolokotroni, Eleni
Stamatakos, Georgios
Leskelä, Riikka-Leena
Haavisto, Ira
Salonen, Juha
Richter, Robert
Karademas, Evangelos
Poikonen-Saksela, Paula
Mazzocco, Ketti
dc.subject.por.fl_str_mv Resilience
Personality
Coping
Decision-making
Cancer
Quality of life
topic Resilience
Personality
Coping
Decision-making
Cancer
Quality of life
description Background: Despite the continued progress of medicine, dealing with breast cancer is becoming a major socioeconomic challenge, particularly due to its increasing incidence. The ability to better manage and adapt to the entire care process depends not only on the type of cancer but also on the patient’s sociodemographic and psychological characteristics as well as on the social environment in which a person lives and interacts. Therefore, it is important to understand which factors may contribute to successful adaptation to breast cancer. To our knowledge, no studies have been performed on the combination effect of multiple psychological, biological, and functional variables in predicting the patient’s ability to bounce back from a stressful life event, such as a breast cancer diagnosis. Here we describe the study protocol of a multicenter clinical study entitled “Predicting Effective Adaptation to Breast Cancer to Help Women to BOUNCE Back” or, in short, BOUNCE. Objective: The aim of the study is to build a quantitative mathematical model of factors associated with the capacity for optimal adjustment to cancer and to study resilience through the cancer continuum in a population of patients with breast cancer. Methods: A total of 660 women with breast cancer will be recruited from five European cancer centers in Italy, Finland, Israel, and Portugal. Biomedical and psychosocial variables will be collected using the Noona Healthcare platform. Psychosocial, sociodemographic, lifestyle, and clinical variables will be measured every 3 months, starting from presurgery assessment (ie, baseline) to 18 months after surgery. Temporal data mining, time-series prediction, sequence classification methods, clustering time-series data, and temporal association rules will be used to develop the predictive model. Results: The recruitment process stared in January 2019 and ended in November 2021. Preliminary results have been published in a scientific journal and are available for consultation on the BOUNCE project website. Data analysis and dissemination of the study results will be performed in 2022. Conclusions: This study will develop a predictive model that is able to describe individual resilience and identify different resilience trajectories along the care process. The results will allow the implementation of tailored interventions according to patients’ needs, supported by eHealth technologies. Trial Registration: ClinicalTrials.gov NCT05095675; https://clinicaltrials.gov/ct2/show/NCT05095675 International Registered Report Identifier (IRRID): DERR1-10.2196/34564
publishDate 2022
dc.date.none.fl_str_mv 2022-12-26T16:16:56Z
2022
2022-01-01T00:00:00Z
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.uri.fl_str_mv http://hdl.handle.net/10400.12/8883
url http://hdl.handle.net/10400.12/8883
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 19290748
10.2196/34564
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv JMIR Publications Inc.
publisher.none.fl_str_mv JMIR Publications Inc.
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833600824452841472