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.

Fatigue in newly diagnosed acute myeloid leukaemia: General population comparison and predictive factors

Cuneo A.;
2021

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.
2021
Oswald, L. B.; Venditti, A.; Cella, D.; Cottone, F.; Candoni, A.; Melillo, L.; Cairoli, R.; Storti, G.; Salutari, P.; Luppi, M.; Albano, F.; Martelli, M. P.; Cuneo, A.; Tafuri, A.; Trisolini, S. M.; Tieghi, A.; Fazi, P.; Vignetti, M.; Efficace, F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2461762
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