Long-Term Longitudinal Patterns of Patient-Reported Fatigue After Breast Cancer: A Group-Based Trajectory Analysis

Ines Vaz-Luis, Antonio Di Meglio, Julie Havas, Mayssam El-Mouhebb, Pietro Lapidari, Daniele Presti, Davide Soldato, Barbara Pistilli, Agnes Dumas, Gwenn Menvielle, Cecile Charles, Sibille Everhard, Anne-Laure Martin, Paul H Cottu, Florence Lerebours, Charles Coutant, Sarah Dauchy, Suzette Delaloge, Nancy U Lin, Patricia A Ganz, Ann H Partridge, Fabrice André, Stefan Michiels, Ines Vaz-Luis, Antonio Di Meglio, Julie Havas, Mayssam El-Mouhebb, Pietro Lapidari, Daniele Presti, Davide Soldato, Barbara Pistilli, Agnes Dumas, Gwenn Menvielle, Cecile Charles, Sibille Everhard, Anne-Laure Martin, Paul H Cottu, Florence Lerebours, Charles Coutant, Sarah Dauchy, Suzette Delaloge, Nancy U Lin, Patricia A Ganz, Ann H Partridge, Fabrice André, Stefan Michiels

Abstract

Purpose: Fatigue is recognized as one of the most burdensome and long-lasting adverse effects of cancer and cancer treatment. We aimed to characterize long-term fatigue trajectories among breast cancer survivors.

Methods: We performed a detailed longitudinal analysis of fatigue using a large ongoing national prospective clinical study (CANcer TOxicity, ClinicalTrials.gov identifier: NCT01993498) of patients with stage I-III breast cancer treated from 2012 to 2015. Fatigue was assessed at diagnosis and year 1, 2, and 4 postdiagnosis. Baseline clinical, sociodemographic, behavioral, tumor-related, and treatment-related characteristics were available. Trajectories of fatigue and risk factors of trajectory-group membership were identified by iterative estimates of group-based trajectory models.

Results: Three trajectory groups were identified for severe global fatigue (n = 4,173). Twenty-one percent of patients were in the high-risk group, having risk estimates of severe global fatigue of 94.8% (95% CI, 86.6 to 100.0) at diagnosis and 64.6% (95% CI, 59.2 to 70.1) at year 4; 19% of patients clustered in the deteriorating group with risk estimates of severe global fatigue of 13.8% (95% CI, 6.7 to 20.9) at diagnosis and 64.5% (95% CI, 57.3 to 71.8) at year 4; 60% were in the low-risk group with risk estimates of 3.6% (95% CI, 2.5 to 4.7) at diagnosis and 9.6% (95% CI, 7.5 to 11.7) at year 4. The distinct dimensions of fatigue clustered in different trajectory groups than those identified by severe global fatigue, being differentially affected by sociodemographic, clinical, and treatment-related factors.

Conclusion: Our findings highlight the multidimensional nature of cancer-related fatigue and the complexity of its risk factors. This study helps to identify patients with increased risk of severe fatigue and to inform personalized interventions to ameliorate this problem.

Conflict of interest statement

Ines Vaz-LuisHonoraria: AstraZeneca (Inst), Amgen (Inst), Pfizer (Inst) 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 Paul H. CottuHonoraria: Pfizer, Novartis (Inst), Roche, NanoString Technologies (Inst), LillyConsulting or Advisory Role: Pfizer, LillyResearch Funding: Pfizer (Inst)Travel, Accommodations, Expenses: Roche, Pfizer Florence LereboursConsulting or Advisory Role: AstraZeneca, Eisai, Lilly, Pierre Fabre, Roche, PfizerTravel, Accommodations, Expenses: Lilly, Novartis, Pfizer, Roche, Pierre Fabre Sarah DauchyHonoraria: Servier, Novartis, MSD Oncology, BMS, NutriciaTravel, Accommodations, Expenses: Servier Suzette DelalogeConsulting or Advisory Role: AstraZeneca (Inst), Sanofi (Inst), Besins Healthcare (Inst), Rappta Therapeutics (Inst)Research Funding: AstraZeneca (Inst), Pfizer (Inst), Roche/Genentech (Inst), Puma Biotechnology (Inst), Lilly (Inst), Novartis (Inst), Sanofi (Inst), Exact Sciences (Inst), Bristol Myers Squibb (Inst)Travel, Accommodations, Expenses: Pfizer, AstraZeneca, Novartis (Inst) Nancy U. LinConsulting or Advisory Role: Seattle Genetics, Puma Biotechnology, Daiichi Sankyo, Denali Therapeutics, AstraZeneca, Prelude Therapeutics, Voyager Therapeutics, Affinia Therapeutics, PfizerResearch 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 LifeSciencesStock and Other Ownership Interests: Xenon Pharma, Intrinsic LifeSciences, Silarus Therapeutics, Teva, Novartis, Merck, Johnson & Johnson, Pfizer, GlaxoSmithKline, Abbott LaboratoriesConsulting or Advisory Role: InformedDNA, Vifor Pharma, Ambys Medicines, Global Blood Therapeutics, GlaxoSmithKline, Ionis Pharmaceuticals, Akebia Therapeutics, Protagonist Therapeutics, Regeneron, Sierra Oncology, Rockwell Medical Technologies Inc, Astellas Pharma, Gossamer Bio, American Regent, Disc Medicine, 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 survivorshipTravel, Accommodations, Expenses: Intrinsic LifeSciences 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, RocheNo other potential conflicts of interest were reported.

Figures

FIG 1.
FIG 1.
Trajectory groups according to the best-fitting prediction model of (A) severe global fatigue, (B) severe physical fatigue, (C) severe emotional fatigue, and (D) severe cognitive fatigue. Solid lines represent the predicted trajectories of risk estimate, and dashed lines represent the respective 95% CIs of risk estimate. T, time.
FIG 2.
FIG 2.
A comprehensive patient-centered survivorship care model building on predicted longitudinal symptom patterns to avoid long-term deterioration. BMI, body mass index.

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Source: PubMed

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