Long-term behavioral symptom clusters among survivors of early-stage breast cancer. development and validation of a predictive model.


Journal

Journal of the National Cancer Institute
ISSN: 1460-2105
Titre abrégé: J Natl Cancer Inst
Pays: United States
ID NLM: 7503089

Informations de publication

Date de publication:
09 Sep 2024
Historique:
received: 25 03 2024
revised: 19 07 2024
accepted: 03 09 2024
medline: 9 9 2024
pubmed: 9 9 2024
entrez: 9 9 2024
Statut: aheadofprint

Résumé

Fatigue, cognitive impairment, anxiety, depression, and sleep disturbance are cancer-related behavioral symptoms (CRBS) that may persist years after early-stage breast cancer (BC), affecting quality of life. We aimed at generating a predictive model of long-term CRBS clusters among BC survivors four years post-diagnosis. Patients with early-stage BC were included from the CANcer TOxicity (NCT01993498). Our outcome was the proportion of patients reporting CRBS clusters four years post-diagnosis (≥3 severe CRBS). Predictors, including clinical, behavioral, and treatment-related characteristics, Behavioral Symptoms Score (BSS; 1 point per severe CRBS at diagnosis) and a pro-inflammatory cytokine (IL-1b, IL-6, TNFα)-genetic risk score, were tested using multivariable logistic regression, implementing bootstrapped Augmented Backwards Elimination. A two-sided p-value < 0.05 defined statistical significance. In the development cohort (N = 3555), 642 patients (19.0%) reported a cluster of CRBS at diagnosis and 755 (21.2%) did so four years post-diagnosis. Younger age (adjusted Odds Ratio [aOR] for 1-year decrement: 1.012; 95% Confidence Interval [CI] 1.003-1.020); previous psychiatric disorders (aOR vs no: 1.27; 95% CI 1.01-1.60); and BSS (aOR ranged from 2.17 [1.66-2.85] for BSS = 1 vs 0 to 12.3 [7.33-20.87] for BSS = 5 vs 0) were predictors of reporting a cluster of CRBS (AUC 0.73 [95%CI 0.71-0.75]). Genetic risk score was not predictive of CRBS. Results were confirmed in the validation cohort (N = 1533). Younger patients with previous psychiatric disorders and higher baseline symptom burden have greater risk of long-term clusters of CRBS. Our model might be implemented in clinical pathways to improve management and test the effectiveness of risk mitigation interventions among breast cancer survivors.

Sections du résumé

BACKGROUND BACKGROUND
Fatigue, cognitive impairment, anxiety, depression, and sleep disturbance are cancer-related behavioral symptoms (CRBS) that may persist years after early-stage breast cancer (BC), affecting quality of life. We aimed at generating a predictive model of long-term CRBS clusters among BC survivors four years post-diagnosis.
METHODS METHODS
Patients with early-stage BC were included from the CANcer TOxicity (NCT01993498). Our outcome was the proportion of patients reporting CRBS clusters four years post-diagnosis (≥3 severe CRBS). Predictors, including clinical, behavioral, and treatment-related characteristics, Behavioral Symptoms Score (BSS; 1 point per severe CRBS at diagnosis) and a pro-inflammatory cytokine (IL-1b, IL-6, TNFα)-genetic risk score, were tested using multivariable logistic regression, implementing bootstrapped Augmented Backwards Elimination. A two-sided p-value < 0.05 defined statistical significance.
RESULTS RESULTS
In the development cohort (N = 3555), 642 patients (19.0%) reported a cluster of CRBS at diagnosis and 755 (21.2%) did so four years post-diagnosis. Younger age (adjusted Odds Ratio [aOR] for 1-year decrement: 1.012; 95% Confidence Interval [CI] 1.003-1.020); previous psychiatric disorders (aOR vs no: 1.27; 95% CI 1.01-1.60); and BSS (aOR ranged from 2.17 [1.66-2.85] for BSS = 1 vs 0 to 12.3 [7.33-20.87] for BSS = 5 vs 0) were predictors of reporting a cluster of CRBS (AUC 0.73 [95%CI 0.71-0.75]). Genetic risk score was not predictive of CRBS. Results were confirmed in the validation cohort (N = 1533).
CONCLUSION CONCLUSIONS
Younger patients with previous psychiatric disorders and higher baseline symptom burden have greater risk of long-term clusters of CRBS. Our model might be implemented in clinical pathways to improve management and test the effectiveness of risk mitigation interventions among breast cancer survivors.

Identifiants

pubmed: 39250750
pii: 7754082
doi: 10.1093/jnci/djae222
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Auteurs

Martina Pagliuca (M)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.
Departement of Breast and Thoracic Oncology, Division of Breast Medical Oncology, Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale", Napoli, Italia.

Julie Havas (J)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.

Emilie Thomas (E)

Labex DEV2CAN, Institut Convergence Plascan, Centre Léon Bérard, Gilles Thomas Bioinformatics Platform, UMR INSERM 1052, CNRS 5286, Université Claude Bernard, Lyon 1, Lyon, France.

Youenn Drouet (Y)

Labex DEV2CAN, Institut Convergence Plascan, Centre Léon Bérard, Gilles Thomas Bioinformatics Platform, UMR INSERM 1052, CNRS 5286, Université Claude Bernard, Lyon 1, Lyon, France.

Davide Soldato (D)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.

Maria Alice Franzoi (MA)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.

Joana Ribeiro (J)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.

Camila K Chiodi (CK)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.

Emma Gillanders (E)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.

Barbara Pistilli (B)

Medical Oncology Department, INSERM U981, Gustave Roussy, Villejuif, France.

Gwenn Menvielle (G)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.

Florence Joly (F)

Clinical Research Depatment, Inserm U1086 Anticipe, Centre Francois Baclesse, University UniCaen, Caen, France.

Florence Lerebours (F)

Medical Oncology Department, Institut Curie Saint Cloud, Saint Cloud, France.

Olivier Rigal (O)

Medical Oncology Department, Centre Henri Becquerel, Rouen, France.

Thierry Petit (T)

Medical Oncology Department, Institute of Cancer Strasbourg (ICANS), Strasbourg, France.

Sylvie Giacchetti (S)

Department of Breast Disease, APHP, University Hospital Saint Louis, Senopole, Paris, France.

Florence Dalenc (F)

Medical Oncology Department, Oncopole Claudius Regaud, Institut Universitaire du Cancer, Toulouse, France.

Johanna Wassermann (J)

Medical Oncology Department, Pitié Salpêtrière University Hospital, Cancer University Institute, AP-HP, Paris, France.

Olivier Arsene (O)

Medical Oncology Department, Centre Hospitalier de Blois, Blois, France.

Anne Laure Martin (AL)

Direction des Data et des Partenariats, UNICANCER, Paris, France.

Sibille Everhard (S)

Direction des Data et des Partenariats, UNICANCER, Paris, France.

Olivier Tredan (O)

Labex DEV2CAN, Institut Convergence Plascan, Centre Léon Bérard, Gilles Thomas Bioinformatics Platform, UMR INSERM 1052, CNRS 5286, Université Claude Bernard, Lyon 1, Lyon, France.

Sandrine Boyault (S)

Labex DEV2CAN, Institut Convergence Plascan, Centre Léon Bérard, Gilles Thomas Bioinformatics Platform, UMR INSERM 1052, CNRS 5286, Université Claude Bernard, Lyon 1, Lyon, France.

Michelino De Laurentiis (M)

Departement of Breast and Thoracic Oncology, Division of Breast Medical Oncology, Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale", Napoli, Italia.

Alain Viari (A)

Labex DEV2CAN, Institut Convergence Plascan, Centre Léon Bérard, Gilles Thomas Bioinformatics Platform, UMR INSERM 1052, CNRS 5286, Université Claude Bernard, Lyon 1, Lyon, France.

Jean Francois Deleuze (JF)

Centre National de Recherche en Génomique Humaine CNRGH-CEA, Laboratory of Excellence in Medical Genomics, GENMED, Évry-Courcouronnes, France.

Aurelie Bertaut (A)

Unit of Methodology and Biostatistics, George-François Leclerc Cancer Center, Dijon, France.

Fabrice André (F)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.

Ines Vaz-Luis (I)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.
Department for the Organization of Patient Pathways (DIOPP), Gustave Roussy, Villejuif, France.

Antonio Di Meglio (A)

Cancer Survivorship Research Group, INSERM U981, Gustave Roussy, Villejuif, France.

Classifications MeSH