4.6 Article

An update in symptom clusters using the Edmonton Symptom Assessment System in a palliative radiotherapy clinic

Journal

SUPPORTIVE CARE IN CANCER
Volume 25, Issue 11, Pages 3321-3327

Publisher

SPRINGER
DOI: 10.1007/s00520-017-3749-x

Keywords

Edmonton Symptom Assessment System; Quality of life; Symptom clusters; Cancer

Funding

  1. Bratty Family Fund
  2. Michael and Karyn Goldstein Cancer Research Fund
  3. Joey and Mary Furfari Cancer Research Fund
  4. Pulenzas Cancer Research Fund
  5. Joseph and Silvana Melara Cancer Research Fund
  6. Ofelia Cancer Research Fund

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Purpose To identify symptom clusters in advanced cancer patients attending a palliative radiotherapy clinic using the Edmonton Symptom Assessment System (ESAS). Methods Principal component analysis (PCA), exploratory factor analysis (EFA), and hierarchical cluster analysis (HCA) were used to identify symptom clusters among the nine ESAS items using scores from each patient's first visit. Results ESAS scores from 182 patients were analyzed. The PCA identified three symptom clusters (cluster 1: depressionanxiety-well-being, cluster 2: pain-tiredness-drowsiness, cluster 3: nausea-dyspnea-loss of appetite). The EFA identified two clusters (cluster 1: tiredness-drowsiness-loss of appetite-well-being-pain-nausea-dyspnea, cluster 2: depression-anxiety). The HCA identified three clusters similar to the PCA with an exception of the loss of appetite item being classified under cluster 1 rather than 3. Two to three symptom clusters were identified using three analytical methods, with similar patterns reported in the literature. Particular groups of items co-occurred consistently across all three analyses: depression and anxiety; nausea and dyspnea; as well as pain, tiredness, and drowsiness. Conclusion Three similar symptom clusters were identified in our patient population using the PCA and HCA; whereas, the EFA produced two clusters: one physical and one psychological cluster. Given the implications of symptom clusters in the management of quality of life, clinicians should be aware of these clusters to aid in the palliative treatment of patients.

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