PURPOSE/ OBJECTIVES: To investigate clinical subgroups using an empirically identified psychoneurologic symptom cluster (depressed mood, cognitive disturbance, fatigue, insomnia, and pain) and to examine the differences among subgroups in the selected demographic and clinical variables, as well as in patient outcome (i.e., functional performance). DESIGN: Secondary analysis. SETTING: A university health science center in Salt Lake City, UT, and a National Cancer Institute-designated comprehensive cancer center in Philadelphia, PA. SAMPLE: 282 patients with breast cancer undergoing chemotherapy or radiotherapy. METHODS: Cluster analyses were conducted to identify subgroups. Multinomial logistic regression and one-way analyses of variance were used to examine the differences among subgroups. MAIN RESEARCH VARIABLES: Depressed mood, cognitive disturbance, fatigue, insomnia, pain, and functional performance. FINDINGS: Patients were classified into four distinct subgroups based on their symptom cluster experience: all low symptom, high fatigue and low pain, high pain, and all high symptom. Such patient classification patterns were consistent across the treatment trajectory, although group memberships were inconsistent. After initiating treatment, two additional subgroups emerged: high depressed mood and cognitive disturbance, and high fatigue and insomnia. Subgroups differed in physical performance status at baseline, symptom burden, and treatment modality in a relatively consistent pattern across time points. Patients in the all-high-symptom subgroup experienced the most serious limitations in activities across all time points. CONCLUSIONS: Patient subgroups exist that share the unique experience of psychoneurologic symptoms. IMPLICATIONS FOR NURSING: Findings are useful to determine who needs more intensive symptom management during cancer treatment. Future studies should examine whether specific symptom management strategies are more efficient for certain subgroups.
PURPOSE/ OBJECTIVES: To investigate clinical subgroups using an empirically identified psychoneurologic symptom cluster (depressed mood, cognitive disturbance, fatigue, insomnia, and pain) and to examine the differences among subgroups in the selected demographic and clinical variables, as well as in patient outcome (i.e., functional performance). DESIGN: Secondary analysis. SETTING: A university health science center in Salt Lake City, UT, and a National Cancer Institute-designated comprehensive cancer center in Philadelphia, PA. SAMPLE: 282 patients with breast cancer undergoing chemotherapy or radiotherapy. METHODS: Cluster analyses were conducted to identify subgroups. Multinomial logistic regression and one-way analyses of variance were used to examine the differences among subgroups. MAIN RESEARCH VARIABLES: Depressed mood, cognitive disturbance, fatigue, insomnia, pain, and functional performance. FINDINGS:Patients were classified into four distinct subgroups based on their symptom cluster experience: all low symptom, high fatigue and low pain, high pain, and all high symptom. Such patient classification patterns were consistent across the treatment trajectory, although group memberships were inconsistent. After initiating treatment, two additional subgroups emerged: high depressed mood and cognitive disturbance, and high fatigue and insomnia. Subgroups differed in physical performance status at baseline, symptom burden, and treatment modality in a relatively consistent pattern across time points. Patients in the all-high-symptom subgroup experienced the most serious limitations in activities across all time points. CONCLUSIONS:Patient subgroups exist that share the unique experience of psychoneurologic symptoms. IMPLICATIONS FOR NURSING: Findings are useful to determine who needs more intensive symptom management during cancer treatment. Future studies should examine whether specific symptom management strategies are more efficient for certain subgroups.
Authors: Christine Miaskowski; Andrea Barsevick; Ann Berger; Rocco Casagrande; Patricia A Grady; Paul Jacobsen; Jean Kutner; Donald Patrick; Lani Zimmerman; Canhua Xiao; Martha Matocha; Sue Marden Journal: J Natl Cancer Inst Date: 2017-01-24 Impact factor: 13.506
Authors: Dale J Langford; Steven M Paul; Bruce Cooper; Kord M Kober; Judy Mastick; Michelle Melisko; Jon D Levine; Fay Wright; Marilyn J Hammer; Frances Cartwright; Kathryn A Lee; Bradley E Aouizerat; Christine Miaskowski Journal: Support Care Cancer Date: 2015-07-04 Impact factor: 3.603
Authors: Melissa Mazor; Janine K Cataldo; Kathryn Lee; Anand Dhruva; Bruce Cooper; Steven M Paul; Kimberly Topp; Betty J Smoot; Laura B Dunn; Jon D Levine; Yvette P Conley; Christine Miaskowski Journal: Eur J Oncol Nurs Date: 2017-12-19 Impact factor: 2.398