A Comparison of Quality of Life between Intense and Non-Intense Treatment for Patients with Acute Myeloid Leukemia and High-Risk Myelodysplastic Syndrome

Acute myeloid leukemia (AML) and high-risk myelodysplastic syndrome (MDS) are hematologic malignancies that occur most frequently in the sixth and seventh decades of life. Both disorders are associated with a poor prognosis, with median survival of one year or less. An overall five-year survival rate for both disorders, regardless of treatment, is less than 10%. A primary goal of treatment is to improve quality of life (QOL) because cure is improbable. The purpose of this longitudinal cohort study was to compare QOL between groups, intensive, non-intensive therapy, and supportive care. The sample consisted of 85 patients with high risk MDS and AML recruited from Moffitt Cancer Center. Functional Assessment of Cancer Therapy-Leukemia (FACT-Leu) was used to measure QOL. The aims for the study were to: 1) To compare the difference in QOL scores measured by the Functional Assessment of Cancer Therapy –Leukemia version for intensive chemotherapy, non-intensive therapy and supportive care within 7 days of new treatment and one month after initiation of treatment; 2) To determine QOL predictors of AML and high risk MDS from age, comorbidity, fatigue, and diagnosis; 3) To test the moderating effect of treatment with age, comorbidity, and fatigue on QOL. The first aim was analyzed with repeated measures analysis of variance (ANOVA). The supportive care group was not included in the analysis because of low accrual. Results indicated that there was a significant group by time interaction (with p=.040). Follow up tests revealed that the intensive treatment group had a significant improvement in their QOL scores at 1 month post treatment (p=.020). The second aim was conducted using Pearson’s correlations with age, comorbidity, fatigue, and diagnosis with significant correlations found between fatigue and QOL (r=-.693, p\u3c .001). These findings identify an important relationship between fatigue and QOL. This was a negative correlation, showing that as fatigue increases QOL decreases. The third aim was explored using regression with Hayes (2013) application for moderation analysis. Scores for QOL for age, comorbidity, and fatigue were not moderated by treatment. These findings suggest that the most intensive treatment approach improves QOL. In addition, fatigue is a significant predictor of QOL. As fatigue increases, QOL scores decrease. Additional studies with a larger, more diverse sample is needed to explore the relationship between treatment approaches and QOL. In addition, intervention studies can be developed in AML and high risk MDS focused on fatigue management. It is anticipated that the results of this study will be used to inform patients and health care providers when making decisions concerning treatment based on QOL outcomes