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Fatigue in newly diagnosed acute myeloid leukaemia: general population comparison and predictive factors
  1. Laura B Oswald1,
  2. Adriano Venditti2,3,
  3. David Cella4,
  4. Francesco Cottone5,
  5. Anna Candoni6,
  6. Lorella Melillo7,
  7. Roberto Cairoli8,
  8. Gabriella Storti9,
  9. Prassede Salutari10,
  10. Mario Luppi11,
  11. Francesco Albano12,
  12. Maria Paola Martelli13,
  13. Antonio Cuneo14,
  14. Agostino Tafuri15,
  15. Silvia Maria Trisolini16,
  16. Alessia Tieghi17,
  17. Paola Fazi5,
  18. Marco Vignetti5 and
  19. Fabio Efficace4,5
  1. 1Health Outcomes and Behavior Program, Moffitt Cancer Center, Tampa, Florida, USA
  2. 2Policlinico Tor Vergata, Roma, Italy
  3. 3Hematology, Department of Biomedicine and Prevention, University Tor Vergata, Roma, Italy
  4. 4Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
  5. 5Data Centre and Health Outcomes Research Unit, Italian Group for Adult Haematological Diseases (GIMEMA), Roma, Italy
  6. 6Hematology, Azienda Sanitaria Universitaria Integrata di Udine, Udine, Italy
  7. 7UO di Ematologia, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
  8. 8Ospedale Niguarda Ca Granda, Milano, Italy
  9. 9Azienda Ospedaliera S G Moscati, Avellino, Italy
  10. 10Azienda USL di Pescara, Pescara, Italy
  11. 11Ematologia, Dipartimento di Scienze Mediche e Chirurgiche Materno-Infantili e dell'Adulto, Università degli Studi di Modena e Reggio Emilia, Modena, Italy
  12. 12Ematologia, Dipartimento dell'Emergenza e dei Trapianti di Organi, Università degli Studi di Bari Aldo Moro, Bari, Italy
  13. 13Hematology and Clinical Immunology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
  14. 14Azienda Ospedaliero Universitaria di Ferrara Arcispedale Sant'Anna, Cona, Italy
  15. 15Azienda Ospedaliera Sant'Andrea, Roma, Italy
  16. 16DAI Ematologia, AOU Policlinico Umberto I Università Sapienza Roma, Roma, Italy
  17. 17Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Reggio Emilia, Italy
  1. Correspondence to Dr Fabio Efficace, Data Centre and Health Outcomes Research Unit, Italian Group for Adult Haematological Diseases (GIMEMA), Roma, Lazio, Italy; f.efficace{at}gimema.it

Abstract

Objectives This study compared the burden of fatigue between treatment-naïve patients with newly diagnosed acute myeloid leukaemia (AML) and the general population and investigated patient factors associated with fatigue severity.

Methods Pretreatment patient-reported fatigue was assessed with the Functional Assessment of Chronic Illness Therapy-Fatigue questionnaire in a sample of 463 newly diagnosed patients with AML who were enrolled in a clinical trial. Multivariable linear regression models were used to estimate the adjusted mean differences in fatigue between patients with AML and adults from the general population (n=847) by AML disease risk categories. A clinically meaningful difference in fatigue was defined as ≥3 points. Univariable and multivariable linear regression models were used to identify sociodemographic, clinical and molecular correlates of worse fatigue in patients with AML.

Results Patients with AML reported adjusted mean fatigue scores that were 7.5 points worse than the general population (95% CI −8.6 to −6.4, p<0.001). Across AML disease risk categories, adjusted mean differences in fatigue compared with the general population ranged from 6.7 points worse (patients with favourable risk: 95% CI −8.6 to −4.8, p<0.001) to 8.9 points worse (patients with poor risk, 95% CI −10.5 to −7.2, p<0.001). Overall, 91% of patients with AML reported fatigue that was equal to or worse than the general population’s median fatigue score. Higher pretreatment fatigue was independently associated with female sex, WHO performance status ≥1 and lower platelet levels.

Conclusions Patients with newly diagnosed AML reported worse fatigue than the general population, and mean differences exceeded twice the threshold for clinical significance. Our findings may help to identify patients with AML most likely to benefit from supportive care interventions to reduce fatigue.

  • quality of life
  • fatigue
  • leukaemia
  • supportive care
  • symptoms and symptom management

Data availability statement

Data are available upon reasonable request.

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Data availability statement

Data are available upon reasonable request.

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Footnotes

  • Contributors Conception and design: LBO, FE, FC, DC, AV. Statistical analysis: FC, FE. Data analysis and interpretation: all authors. Manuscript writing: LBO, AV, DC, FC, FE. Final approval of manuscript: all authors.

  • Funding This work was in part supported by the Associazione Italiana contro le Leucemie, Linfomi e Mieloma (AIL). The grant number is not available as 'AIL' is a non-profit charity organisation which partly funded the original clinical trial. LBO was supported by a National Institutes of Health, National Cancer Institute training grant at the time this work was completed (T32CA193193).

  • Competing interests ACa: advisory board participation and consultancy: Celgene, Janssen, Merck, Novartis, Gilead, Pfizer, Jazz and Amgen. ATa: grants: Celgene, Roche, Novartis and AbbVie, outside the submitted work. DC: president of FACIT.org. FE: personal fees from AbbVie, Janssen, Orsenix and Takeda, and grants and personal fees from Amgen, outside the submitted work. ML: advisory boards: Celgene, AbbVie, Gilead Sciences, Novartis, Daiichi Sankyo, MSD and Sanofi, outside the submitted work. MPM: advisory board and speaker bureau: Novartis, Astellas, Jazz Pharmaceuticals, Amgen, AbbVie and Janssen; advisory board: Celgene and Pfizer, outside the submitted work. MV: personal fees from Amgen, Millennium Pharmaceuticals, Celgene, Janssen, Novartis and Incyte. All other authors have no conflicts of interest to disclose.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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