R D Nipp1, N K Horick2, A M Deal3, L J Rogak4, C Fuh5, J A Greer6, A C Dueck7, E Basch3, J S Temel5, A El-Jawahri5. 1. Department of Medicine, Division of Hematology & Oncology, Massachusetts General Hospital Cancer Center & Harvard Medical School, Boston, USA. Electronic address: RNipp@MGH.Harvard.edu. 2. Biostatistics Center, Massachusetts General Hospital, Boston, USA. 3. Department of Medicine, Division of Hematology & Oncology, Lineberger Comprehensive Cancer Center at University of North Carolina, Chapel Hill, USA. 4. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, USA. 5. Department of Medicine, Division of Hematology & Oncology, Massachusetts General Hospital Cancer Center & Harvard Medical School, Boston, USA. 6. Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Boston, USA. 7. Alliance Statistics and Data Center, Division of Health Sciences Research, Mayo Clinic, Scottsdale, USA.
Abstract
BACKGROUND: Symptom monitoring interventions enhance patient outcomes, including quality of life (QoL), health care utilization, and survival, but it remains unclear whether older and younger patients with cancer derive similar benefits. We explored whether age moderates the improved outcomes seen with an outpatient electronic symptom monitoring intervention. PATIENTS AND METHODS: We carried out a secondary analysis of data from a randomized trial of 766 patients receiving chemotherapy for metastatic solid tumors. Patients received an electronic symptom monitoring intervention integrated with oncology care or usual oncology care alone. The intervention consisted of patients reporting their symptoms, which were provided to their physicians at clinic visits, and nurses receiving alerts for severe/worsening symptoms. We used regression models to determine whether age (older or younger than 70 years) moderated the effects of the intervention on QoL (EuroQol EQ-5D), emergency room (ER) visits, hospitalizations, and survival outcomes. RESULTS: Enrollment rates for younger (589/777 = 75.8%) and older (177/230 = 77.0%) patients did not differ. Older patients (median age = 75 years, range 70-91 years) were more likely to have an education level of high school or less (26.6% versus 20.9%, P = 0.029) and to be computer inexperienced (50.3% versus 23.4%, P < 0.001) compared with younger patients (median age = 58 years, range 26-69 years). Younger patients receiving the symptom monitoring intervention experienced lower risk of ER visits [hazard ratio (HR) = 0.74, P = 0.011] and improved survival (HR = 0.76, P = 0.011) compared with younger patients receiving usual care. However, older patients did not experience significantly lower risk of ER visits (HR = 0.90, P = 0.613) or improved survival (HR = 1.06, P = 0.753) with the intervention. We found no moderation effects based on age for QoL and risk of hospitalizations. CONCLUSIONS: Among patients with advanced cancer, age moderated the effects of an electronic symptom monitoring intervention on the risk of ER visits and survival, but not QoL. Symptom monitoring interventions may need to be tailored to the unique needs of older adults with cancer.
BACKGROUND: Symptom monitoring interventions enhance patient outcomes, including quality of life (QoL), health care utilization, and survival, but it remains unclear whether older and younger patients with cancer derive similar benefits. We explored whether age moderates the improved outcomes seen with an outpatient electronic symptom monitoring intervention. PATIENTS AND METHODS: We carried out a secondary analysis of data from a randomized trial of 766 patients receiving chemotherapy for metastatic solid tumors. Patients received an electronic symptom monitoring intervention integrated with oncology care or usual oncology care alone. The intervention consisted of patients reporting their symptoms, which were provided to their physicians at clinic visits, and nurses receiving alerts for severe/worsening symptoms. We used regression models to determine whether age (older or younger than 70 years) moderated the effects of the intervention on QoL (EuroQol EQ-5D), emergency room (ER) visits, hospitalizations, and survival outcomes. RESULTS: Enrollment rates for younger (589/777 = 75.8%) and older (177/230 = 77.0%) patients did not differ. Older patients (median age = 75 years, range 70-91 years) were more likely to have an education level of high school or less (26.6% versus 20.9%, P = 0.029) and to be computer inexperienced (50.3% versus 23.4%, P < 0.001) compared with younger patients (median age = 58 years, range 26-69 years). Younger patients receiving the symptom monitoring intervention experienced lower risk of ER visits [hazard ratio (HR) = 0.74, P = 0.011] and improved survival (HR = 0.76, P = 0.011) compared with younger patients receiving usual care. However, older patients did not experience significantly lower risk of ER visits (HR = 0.90, P = 0.613) or improved survival (HR = 1.06, P = 0.753) with the intervention. We found no moderation effects based on age for QoL and risk of hospitalizations. CONCLUSIONS: Among patients with advanced cancer, age moderated the effects of an electronic symptom monitoring intervention on the risk of ER visits and survival, but not QoL. Symptom monitoring interventions may need to be tailored to the unique needs of older adults with cancer.
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