Longitudinal Symptom Burden Trajectories in a Population-Based Cohort of Women with Metastatic Breast Cancer: A Group-Based Trajectory Modeling Analysis.
Suman BudhwaniRahim MoineddinWalter P WodchisCamilla ZimmermannDoris HowellPublished in: Current oncology (Toronto, Ont.) (2021)
Understanding the symptom burden trajectory for metastatic breast cancer patients can enable the provision of appropriate supportive care for symptom management. The aim of this study was to describe the longitudinal trajectories of symptom burden for metastatic breast cancer patients at the population-level. A cohort of 995 metastatic breast cancer patients with 16,146 Edmonton Symptom Assessment System (ESAS) assessments was constructed using linked population-level health administrative databases. The patient-reported ESAS total symptom distress score (TSDS) was studied over time using group-based trajectory modeling, and covariate influences on trajectory patterns were examined. Cohort patients experienced symptom burden that could be divided into six distinct trajectories. Patients experiencing a higher baseline TSDS were likely to be classified into trajectory groups with high, uncontrolled TSDS within the study follow-up period (χ2 (1, N = 995) = 136.25, p < 0.001). Compared to patients classified in the group trajectory with the highest relative TSDS (Group 6), patients classified in the lowest relative TSDS trajectory group (Group 1) were more likely to not have comorbidities (97.34% (for Groups 1-3) vs. 91.82% (for Group 6); p < 0.05), more likely to receive chemotherapy (86.52% vs. 80.50%; p < 0.05), and less likely to receive palliative care (52.81% vs. 79.25%; p < 0.0001). Receiving radiotherapy was a significant predictor of how symptom burden was experienced in all identified groups. Overall, metastatic breast cancer patients follow heterogeneous symptom burden trajectories over time, with some experiencing a higher, uncontrolled symptom burden. Understanding trajectories can assist in establishing risk-stratified care pathways for patients.
Keyphrases
- patient reported
- end stage renal disease
- palliative care
- metastatic breast cancer
- newly diagnosed
- ejection fraction
- healthcare
- chronic kidney disease
- prognostic factors
- small cell lung cancer
- squamous cell carcinoma
- public health
- risk assessment
- deep learning
- radiation induced
- quality improvement
- chronic pain
- human health