Evidence map›Paper›PMID 40504480›Full record

ArticleJournal of cancer survivorship : research and practice2025

"Let's talk about risk": co-designing a pathway to assess, communicate and act on individual risk of long-term toxicities after breast cancer.

Maria Alice Franzoi, Carlota Santolaya, Elise Martin, Leonor Fasse, Pascal Rouby, Marie Sophie Minot-This, Antonio Di Meglio, Ines Vaz-Luis

Registry-linked trialAbstract read
PubMed Publisher
In one paragraph

Article in Journal of cancer survivorship : research and practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06479057 (Integrating PROACTive Care Pathways to Empower and Support Cancer Patients), which is not on this map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06479057 recruitingnot on this map

Integrating PROACTive Care Pathways to Empower and Support Cancer Patients (PROACT)

Typeobservational_patient_registrySponsorGustave Roussy, Cancer Campus, Grand ParisRan2024 to 2027Enrolled700ConditionsAny CancerArmsSupportive Care Pathway
3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Maria Alice FranzoiCancer Survivorship Group, Molecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France. mariaalice.borinelli-franzoi@gustaveroussy.fr.
Carlota SantolayaCancer Survivorship Group, Molecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.
Elise MartinCancer Survivorship Group, Molecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.
Leonor FasseDepartment for the Organization of Patient Pathways (DIOPP), Gustave Roussy, Villejuif, France.
Pascal RoubyDepartment for the Organization of Patient Pathways (DIOPP), Gustave Roussy, Villejuif, France.
Marie Sophie Minot-ThisDepartment of Medical Oncology, Gustave Roussy, 94800, Villejuif, France.
Antonio Di MeglioCancer Survivorship Group, Molecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.
Ines Vaz-LuisCancer Survivorship Group, Molecular Predictors and New Targets in Oncology, INSERM Unit 981, Gustave Roussy, Villejuif, France.

Funding

Breast Cancer Research Foundation ASCO CDAMaison des Sciences de l'Homme Paris INTERTOX
6 · The paper itself

Abstract

purposeSurvivors of breast cancer (BC) may endure significant and persistent post-treatment burdens that negatively impact overall quality of life. We previously developed risk prediction algorithms to identify individual patient profiles at increased risk for long-term toxicities. To prepare for the implementation of these risk algorithms in routine care, we performed a study to assess preferences, catalysts, and barriers concerning communication of individual risk of long-term BC toxicities. The goal was to co-design a pathway for risk assessment, communication, and management starting at diagnosis.

methodsA co-design study was performed using a participatory research framework and qualitative methods. Two phases of focus groups (FG) were conducted to assess the perspective of patients and providers through an iterative process of Exploration, Consultation, Prioritization, Integration and Co-design. Discussions were guided by four main questions: Who should communicate the risk? When should the risk be communicated? How should the risk be communicated? What information should be communicated, and care proposed?. FG discussions were recorded, pseudo-anonymized, transcribed and evaluated through a thematic content analysis. Results were reported following the consolidated criteria for reporting qualitative research (COREQ).

resultsSix FG were conducted between July 2022 and August 2023, with a total of 28 participants (8 patients and 20 providers). Results revealed a strong willingness to discuss the risk of long-term toxicities, particularly for patients who would present with a higher risk of toxicities. However, this willingness was contingent on the implementation of supportive care pathways that offer personalized communication strategies and risk mitigation approaches tailored to each patient's need.

conclusionsThis study found that both patients and providers are interested in, and willing to engage in, the assessment, communication and mitigation of long-term toxicities from the time of diagnosis. To address this need in routine care, a tailored pathway was co-designed and will undergo formal testing in a hybrid Type 3 effectiveness/implementation clinical trial (NCT06479057). IMPLICATIONS FOR CANCER SURVIVORS: This study assessed the needs, preferences and expectations of patients and providers for implementing a care pathway to assess, communicate and mitigate the risk of long-term toxicities after breast cancer treatment using risk prediction algorithms.

Indexed as

Breast cancer survivorshipImplementation scienceLong-term toxicitiesRisk communicationRisk prediction

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Registered trials

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