Nancy E Avis1, Beverly Levine2, Sarah A Marshall3, Edward H Ip4. 1. Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. Electronic address: navis@wakehealth.edu. 2. Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. 3. Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. 4. Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA; Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
Abstract
CONTEXT: Identification of cancer patients with similar symptom profiles may facilitate targeted symptom management. OBJECTIVES: To identify subgroups of breast cancer survivors based on differential experience of symptoms, examine change in subgroup membership over time, and identify relevant characteristics and quality of life (QOL) among subgroups. METHODS: Secondary analyses of data from 653 breast cancer survivors recruited within eight months of diagnosis who completed questionnaires at five time points. Hidden Markov modeling was used to 1) formulate symptom profiles based on prevalence and severity of eight symptoms commonly associated with breast cancer and 2) estimate probabilities of changing subgroup membership over 18 months of follow-up. Ordinal repeated measures were used to 3) identify patient characteristics related to subgroup membership and 4) evaluate the relationship between symptom subgroup and QOL. RESULTS: A seven-subgroup model provided the best fit: 1) low symptom burden, 2) mild fatigue, 3) mild fatigue and mild pain, 4) moderate fatigue and moderate pain, 5) moderate fatigue and moderate psychological, 6) moderate fatigue, mild pain, mild psychological, and 7) high symptom burden. Seventy percent of survivors remained in the same subgroup over time. In multivariable analyses, chemotherapy and greater illness intrusiveness were significantly related to greater symptom burden, while not being married or partnered, no difficulty paying for basics, and greater social support were protective. Higher symptom burden was associated with lower QOL. Survivors who reported psychological symptoms had significantly lower QOL than did survivors with pain symptoms. CONCLUSION: Cancer survivors can be differentiated by their symptom profiles.
CONTEXT: Identification of cancerpatients with similar symptom profiles may facilitate targeted symptom management. OBJECTIVES: To identify subgroups of breast cancer survivors based on differential experience of symptoms, examine change in subgroup membership over time, and identify relevant characteristics and quality of life (QOL) among subgroups. METHODS: Secondary analyses of data from 653 breast cancer survivors recruited within eight months of diagnosis who completed questionnaires at five time points. Hidden Markov modeling was used to 1) formulate symptom profiles based on prevalence and severity of eight symptoms commonly associated with breast cancer and 2) estimate probabilities of changing subgroup membership over 18 months of follow-up. Ordinal repeated measures were used to 3) identify patient characteristics related to subgroup membership and 4) evaluate the relationship between symptom subgroup and QOL. RESULTS: A seven-subgroup model provided the best fit: 1) low symptom burden, 2) mild fatigue, 3) mild fatigue and mild pain, 4) moderate fatigue and moderate pain, 5) moderate fatigue and moderate psychological, 6) moderate fatigue, mild pain, mild psychological, and 7) high symptom burden. Seventy percent of survivors remained in the same subgroup over time. In multivariable analyses, chemotherapy and greater illness intrusiveness were significantly related to greater symptom burden, while not being married or partnered, no difficulty paying for basics, and greater social support were protective. Higher symptom burden was associated with lower QOL. Survivors who reported psychological symptoms had significantly lower QOL than did survivors with pain symptoms. CONCLUSION:Cancer survivors can be differentiated by their symptom profiles.
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