Development and Validation of a Predictive Model of Severe Fatigue After Breast Cancer Diagnosis: Toward a Personalized Framework in Survivorship Care

Antonio Di Meglio, Julie Havas, Davide Soldato, Daniele Presti, Elise Martin, Barbara Pistilli, Gwenn Menvielle, Agnes Dumas, Cecile Charles, Sibille Everhard, Anne-Laure Martin, Charles Coutant, Carole Tarpin, Laurence Vanlemmens, Christelle Levy, Olivier Rigal, Suzette Delaloge, Nancy U Lin, Patricia A Ganz, Ann H Partridge, Fabrice André, Stefan Michiels, Ines Vaz-Luis, Antonio Di Meglio, Julie Havas, Davide Soldato, Daniele Presti, Elise Martin, Barbara Pistilli, Gwenn Menvielle, Agnes Dumas, Cecile Charles, Sibille Everhard, Anne-Laure Martin, Charles Coutant, Carole Tarpin, Laurence Vanlemmens, Christelle Levy, Olivier Rigal, Suzette Delaloge, Nancy U Lin, Patricia A Ganz, Ann H Partridge, Fabrice André, Stefan Michiels, Ines Vaz-Luis

Abstract

Purpose: Fatigue is common and troublesome among breast cancer survivors; however, limited tools exist to predict its risk.

Patients and methods: Participants with stage I-III breast cancer were prospectively included from CANTO (ClinicalTrials.gov identifier: NCT01993498), collecting longitudinal data at diagnosis (before the initiation of any cancer treatment) and 1 (T1), 2 (T2), and 4 (T3) years after diagnosis. The main outcome was severe global fatigue at T2 (score ≥ 40/100, European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-C30). Analyses at T3 were exploratory. Secondary outcomes included physical, emotional, and cognitive fatigue (EORTC Quality of Life Questionnaire-FA12). Multivariable logistic regression models retained associations with severe fatigue by bootstrapped Augmented Backward Elimination. Validation methods included 10-fold internal cross-validation, overoptimism-corrected area under the receiver operating characteristic curves, and external validation.

Results: Among 5,640, 5,000, and 3,400 patients at T1, T2, and T3, respectively, the prevalence of post-treatment severe global fatigue was 35.6%, 34.0%, and 31.5% in the development cohort. Retained risk factors for severe global fatigue at T2 were severe pretreatment fatigue (adjusted odds ratio v no 3.191 [95% CI, 2.704 to 3.767]); younger age (for 1-year decrement 1.015 [1.009 to 1.022]), higher body mass index (for unit increment 1.025 [1.012 to 1.038]), current smoking behavior (v never 1.552 [1.291 to 1.866]), worse anxiety (v noncase 1.265 [1.073 to 1.492]), insomnia (for unit increment 1.005 [1.003 to 1.007]), and pain at diagnosis (for unit increment 1.014 [1.010 to 1.017]), with an area under the receiver operating characteristic curve of 0.73 (95% CI, 0.72 to 0.75). Receipt of hormonal therapy was a risk factor for severe fatigue at T3 (v no 1.448 [1.165 to 1.799]). Dimension-specific risk factors included body mass index for physical fatigue and emotional distress for emotional and cognitive fatigue.

Conclusion: We propose a predictive model to assess fatigue among breast cancer survivors, within a personalized survivorship care framework. This may help clinicians to provide early management interventions or to correct modifiable risk factors and offer more tailored monitoring and education to patients at risk of severe post-treatment fatigue.

Conflict of interest statement

Barbara PistilliConsulting or Advisory Role: Puma Biotechnology, Pierre Fabre, Novartis, Myriad Genetics, AstraZeneca, Daiichi Sankyo/UCB JapanResearch Funding: Pfizer (Inst), Puma Biotechnology (Inst), Merus (Inst), Daiichi-Sankyo (Inst)Travel, Accommodations, Expenses: Pfizer, AstraZeneca, MSD Oncology, Novartis, Pierre Fabre Suzette DelalogeConsulting or Advisory Role: AstraZeneca (Inst), Pierre Fabre (Inst)Research Funding: AstraZeneca (Inst), Pfizer (Inst), Roche/Genentech (Inst), Puma Biotechnology (Inst), Lilly (Inst), Novartis (Inst), Sanofi (Inst), Exact Sciences (Inst)Travel, Accommodations, Expenses: Pfizer, AstraZeneca, Roche Nancy U. LinConsulting or Advisory Role: Seattle Genetics, Puma Biotechnology, Daiichi Sankyo, California Institute for Regenerative Medicine (CIRM), Denali Therapeutics, AstraZeneca, Prelude TherapeuticsResearch Funding: Genentech (Inst), Pfizer (Inst), Seattle Genetics (Inst), Merck (Inst), Zion (Inst)Patents, Royalties, Other Intellectual Property: Royalties for chapter in Up-to-Date regarding management of breast cancer brain metastases, Royalties, Jones & Bartlett Patricia A. GanzLeadership: Intrinsic LifeSciences (I)Stock and Other Ownership Interests: Xenon Pharma (I), Intrinsic LifeSciences (I), Silarus Therapeutics (I), Teva, Novartis, Merck, Johnson & Johnson, Pfizer, GlaxoSmithKline, Abbott LaboratoriesConsulting or Advisory Role: InformedDNA, Vifor Pharma (I), Ambys Medicines (I), Global Blood Therapeutics (I), GlaxoSmithKline (I), Ionis Pharmaceuticals (I), Akebia Therapeutics (I), Protagonist Therapeutics (I), Regeneron (I), Sierra Oncology (I), Rockwell Medical Technologies Inc (I), Astellas Pharma (I), Gossamer Bio (I), American Regent (I), Disc Medicine (I), Blue Note Therapeutics, GrailResearch Funding: Blue Note Therapeutics (Inst)Patents, Royalties, Other Intellectual Property: Related to iron metabolism and the anemia of chronic disease, Up-to-Date royalties for section editor on survivorship (I)Travel, Accommodations, Expenses: Intrinsic LifeSciences (I) Ann H. PartridgePatents, Royalties, Other Intellectual Property: I receive small royalty payments for coauthoring the breast cancer survivorship section of UpToDateOpen Payments Link: https://openpaymentsdata.cms.gov/physician/835197 Fabrice AndréStock and Other Ownership Interests: PegacsyResearch Funding: AstraZeneca (Inst), Novartis (Inst), Pfizer (Inst), Lilly (Inst), Roche (Inst), Daiichi (Inst)Travel, Accommodations, Expenses: Novartis, Roche, GlaxoSmithKline, AstraZeneca Stefan MichielsConsulting or Advisory Role: IDDI, Sensorion, Biophytis, Servier, Yuhan, Amaris Consulting, Roche Ines Vaz-LuisHonoraria: AstraZeneca (Inst), Amgen (Inst), Pfizer (Inst)No other potential conflicts of interest were reported.

Figures

FIG 1.
FIG 1.
Prevalence of severe global fatigue and of severe fatigue by dimension over time in (A) development cohort and (B) validation cohort. Baseline represents breast cancer diagnosis.

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