Trajectory of Symptoms in Patients Undergoing Autologous Stem Cell Transplant for Multiple Myeloma: A Population-Based Cohort Study of Patient-Reported Outcomes
Journal Articles
Overview
Research
Identity
Additional Document Info
View All
Overview
abstract
BACKGROUND: Autologous stem cell transplant (ASCT) is an established treatment for patients with newly diagnosed multiple myeloma (NDMM). Understanding the symptom burden associated with ASCT may be an important consideration for patients with NDMM when selecting treatment options. PATIENTS AND METHODS: We conducted a population-based study of patients who underwent an ASCT for NDMM in Ontario, Canada, between 2007 and 2018. The patient-reported outcome, Edmonton Symptom Assessment System (ESAS) score, which captures nine common cancer-associated symptoms and is routinely collected at all outpatient visits, was linked to provincial administrative healthcare data. The monthly prevalence of moderate or severe symptoms (ESAS ≥ 4) each month in the first year following ASCT was analyzed. A multivariable logistic regression model was used to identify factors associated with moderate to severe symptoms. RESULTS: In our final cohort of 1969 patients who had undergone an ASCT, a total of 12,820 unique assessments were captured. Symptom burden was highest at 1 month post-ASCT, with moderate to severe tiredness and impaired well-being being the two most common symptoms. Symptom burden substantially improved by 3 months post-ASCT, reaching a new baseline for the year following. On multivariable analysis, female sex, increased co-morbidities, earlier year of diagnosis, and myeloma-related end-organ damage (specifically, bone and kidney disease) were associated with a higher odds of reporting moderate to severe symptoms. CONCLUSION: In this large population-based study using patient-reported outcomes, there was a substantial burden of symptoms noted among NDMM patients 1 month post-ASCT, which improved over time. Tailored supportive care interventions should focus on strategies to optimize management of identified symptoms.
