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Evaluating the ability of an artificial-intelligence cloud-based platform designed to provide information prior to locoregional therapy for breast cancer in improving patient's satisfaction with therapy: The CINDERELLA trial.
Kaidar-Person, Orit; Antunes, Marilia; Cardoso, Jaime S; Ciani, Oriana; Cruz, Helena; Di Micco, Rosa; Gentilini, Oreste D; Gonçalves, Tiago; Gouveia, Pedro; Heil, Jörg; Kabata, Pawel; Lopes, Daniela; Martinho, Marta; Martins, Henrique; Mavioso, Carlos; Mika, Martin; Montenegro, Helena; Oliveira, Helder P; Pfob, André; Rotmensz, Nicole; Schinköthe, Timo; Silva, Giovani; Tarricone, Rosana; Cardoso, Maria-Joao.
Afiliación
  • Kaidar-Person O; Breast Cancer Radiation Therapy Unit, Sheba Medical Center, Ramat Gan, Israel.
  • Antunes M; School of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
  • Cardoso JS; Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.
  • Ciani O; Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal.
  • Cruz H; Center for Research on Health and Social Care Management (CERGAS), SDA Bocconi University, Milan, Italy.
  • Di Micco R; Champalimaud Foundation, Breast Unit, Lisbon, Portugal.
  • Gentilini OD; Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Porto, Portugal.
  • Gonçalves T; Faculty of Engineering, University of Porto (FEUP), Porto, Portugal.
  • Gouveia P; Breast Surgery Unit, San Raffaele University and Research Hospital, Milano, Italy.
  • Heil J; Breast Surgery Unit, San Raffaele University and Research Hospital, Milano, Italy.
  • Kabata P; Center for Research on Health and Social Care Management (CERGAS), SDA Bocconi University, Milan, Italy.
  • Lopes D; Champalimaud Foundation, Breast Unit, Lisbon, Portugal.
  • Martinho M; Faculty of Engineering, University of Porto (FEUP), Porto, Portugal.
  • Martins H; Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal.
  • Mavioso C; Instituto Universitario de Lisboa (ISCTE), Lisboa, Portugal.
  • Mika M; CANKADO GmbH, Ottobrunn, Germany.
  • Montenegro H; Faculty of Engineering, University of Porto (FEUP), Porto, Portugal.
  • Oliveira HP; Faculty of Engineering, University of Porto (FEUP), Porto, Portugal.
  • Pfob A; Faculty of Engineering, University of Porto (FEUP), Porto, Portugal.
  • Rotmensz N; Centro de Estatística e Aplicações, Faculdade de Ciências, Universidade de Lisboa (CEAUL), Lisboa, Portugal.
  • Schinköthe T; Faculty of Engineering, University of Porto (FEUP), Porto, Portugal.
  • Silva G; Department of Surgical Oncology, Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland.
  • Tarricone R; Center for Research on Health and Social Care Management (CERGAS), SDA Bocconi University, Milan, Italy.
  • Cardoso MJ; Champalimaud Foundation, Breast Unit, Lisbon, Portugal.
PLoS One ; 18(8): e0289365, 2023.
Article en En | MEDLINE | ID: mdl-37535564
ABSTRACT

BACKGROUND:

Breast cancer therapy improved significantly, allowing for different surgical approaches for the same disease stage, therefore offering patients different aesthetic outcomes with similar locoregional control. The purpose of the CINDERELLA trial is to evaluate an artificial-intelligence (AI) cloud-based platform (CINDERELLA platform) vs the standard approach for patient education prior to therapy.

METHODS:

A prospective randomized international multicentre trial comparing two methods for patient education prior to therapy. After institutional ethics approval and a written informed consent, patients planned for locoregional treatment will be randomized to the intervention (CINDERELLA platform) or controls. The patients in the intervention arm will use the newly designed web-application (CINDERELLA platform, CINDERELLA APProach) to access the information related to surgery and/or radiotherapy. Using an AI system, the platform will provide the patient with a picture of her own aesthetic outcome resulting from the surgical procedure she chooses, and an objective evaluation of this aesthetic outcome (e.g., good/fair). The control group will have access to the standard approach. The primary objectives of the trial will be i) to examine the differences between the treatment arms with regards to patients' pre-treatment expectations and the final aesthetic outcomes and ii) in the experimental arm only, the agreement of the pre-treatment AI-evaluation (output) and patient's post-therapy self-evaluation.

DISCUSSION:

The project aims to develop an easy-to-use cost-effective AI-powered tool that improves shared decision-making processes. We assume that the CINDERELLA APProach will lead to higher satisfaction, better psychosocial status, and wellbeing of breast cancer patients, and reduce the need for additional surgeries to improve aesthetic outcome.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Inteligencia Artificial Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Inteligencia Artificial Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2023 Tipo del documento: Article