Predicting Effective Adaptation to Breast Cancer to Help Women BOUNCE Back
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| Publication Date: | 2022 |
| Other Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Article |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | http://hdl.handle.net/10362/145249 |
Summary: | Funding: This work has been funded by the European Commission and the Horizon 2020 framework. |
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Predicting Effective Adaptation to Breast Cancer to Help Women BOUNCE BackProtocol for a Multicenter Clinical Pilot StudySDG 3 - Good Health and Well-beingFunding: This work has been funded by the European Commission and the Horizon 2020 framework.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.NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)RUNPettini, GretaSanchini, VirginiaPat-Horenczyk, RuthSousa, BertaMasiero, MariannaMarzorati, ChiaraGalimberti, Viviana EnricaMunzone, ElisabettaMattson, JohannaVehmanen, LeenaUtriainen, MeriRoziner, IlanLemos, RaquelFrasquilho, DianaCardoso, FatimaOliveira-Maia, AJKolokotroni, EleniStamatakos, GeorgiosLeskelä, Riikka-LeenaHaavisto, IraSalonen, JuhaRichter, RobertKarademas, EvangelosPoikonen-Saksela, PaulaMazzocco, Ketti2022-11-04T22:11:16Z2022-10-122022-10-12T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/145249eng1929-0748PURE: 47465865https://doi.org/10.2196/34564info: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:RCAAP2025-05-26T01:40:27Zoai:run.unl.pt:10362/145249Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:37:01.489147Repositórios 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 |
| spellingShingle |
Predicting Effective Adaptation to Breast Cancer to Help Women BOUNCE Back Pettini, Greta SDG 3 - Good Health and Well-being |
| title_short |
Predicting Effective Adaptation to Breast Cancer to Help Women BOUNCE Back |
| title_full |
Predicting Effective Adaptation to Breast Cancer to Help Women BOUNCE Back |
| title_fullStr |
Predicting Effective Adaptation to Breast Cancer to Help Women BOUNCE Back |
| title_full_unstemmed |
Predicting Effective Adaptation to Breast Cancer to Help Women BOUNCE Back |
| title_sort |
Predicting Effective Adaptation to Breast Cancer to Help Women BOUNCE Back |
| 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, AJ 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, AJ 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 |
NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM) RUN |
| 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, AJ 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 |
SDG 3 - Good Health and Well-being |
| topic |
SDG 3 - Good Health and Well-being |
| description |
Funding: This work has been funded by the European Commission and the Horizon 2020 framework. |
| publishDate |
2022 |
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2022-11-04T22:11:16Z 2022-10-12 2022-10-12T00:00:00Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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http://hdl.handle.net/10362/145249 |
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http://hdl.handle.net/10362/145249 |
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eng |
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eng |
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1929-0748 PURE: 47465865 https://doi.org/10.2196/34564 |
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openAccess |
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