Purpose: The Edmonton Symptom Assessment Scale (ESAS) is a validated tool used in patients with varied cancer diagnoses to measure patient symptoms. The present manuscript will review the literature assessing the ability of the ESAS to predict patient-related outcomes in breast cancer patients.
Methods: A literature search was conducted of Cochrane Central Register of Controlled Trials databases, Ovid MEDLINE, and Embase for English articles that investigated the use of predictive modelling with the ESAS in the breast cancer population. Study type, publication year, sample size, patient demographics, predicted outcomes, and strongest predictive factors/symptoms were summarized for each study.
Results: A total of nine articles were included in this review. Five articles used the ESAS in predictive models to determine patient time to death. ESAS was also used to predict emergency department visits, determine symptoms associated with decreased quality of life, and generate a Health Utility Score. Lack of appetite was the most common ESAS symptom, as it was reported in five studies to be associated with decreased survival. In four of the nine articles, an additional survey investigating physical functioning was used in combination with ESAS to strengthen the predictive models.
Conclusions: Included studies support the use of ESAS in predictive models, particularly for predicting survival. Using the ESAS as a predictive tool allows for more accurate time to death predictions, potentially improving symptom management and preventing overtreatment of palliative patients near the end of life.
Keywords: Breast cancer; Edmonton Symptom Assessment Scale; Predictive modelling.