PURPOSE/ OBJECTIVES: To examine the relationships among pain, fatigue, insomnia, and gender while controlling for age, comorbidities, and stage of cancer in patients newly diagnosed with lung cancer within 56 days of receiving chemotherapy. DESIGN: Secondary data analysis. SETTING:Accrual from four sites: two clinical community oncology programs and two comprehensive cancer centers. SAMPLE: 80 patients newly diagnosed with lung cancer. METHODS: Analysis from baseline observation of a randomized clinical intervention trial. Multinomial log-linear modeling was performed to explain the relationships among pain, fatigue, insomnia, and gender. MAIN RESEARCH VARIABLES: Pain, fatigue, insomnia, and gender. FINDINGS: For all people with lung cancer, fatigue (97%) and pain (69%) were the most frequently occurring symptoms; insomnia occurred 51% of the time. A model containing all main effects (two-way interactions of pain and fatigue, pain and insomnia, and insomnia and gender; and the three-way interaction of pain, fatigue, and insomnia, along with three covariates [age, comorbidities, and stage of cancer]) was a good fit to the data. Parameter estimates indicated that a statistically significant effect from the model was the three-way interaction of pain, fatigue, and insomnia. Gender did not make a difference. Age, comorbidities, and stage of cancer were not significant covariates. CONCLUSIONS: For people newly diagnosed with lung cancer undergoingchemotherapy, multiple symptoms occur simultaneously rather than in isolation; a symptom cluster exists, consisting of pain, fatigue, and insomnia; and no relationship was found among gender, pain, fatigue, and insomnia. IMPLICATIONS FOR NURSING: By understanding this symptom cluster, healthcare providers can target specific troublesome symptoms to optimize symptom management and achieve the delivery of high-quality cancer care.
RCT Entities:
PURPOSE/ OBJECTIVES: To examine the relationships among pain, fatigue, insomnia, and gender while controlling for age, comorbidities, and stage of cancer in patients newly diagnosed with lung cancer within 56 days of receiving chemotherapy. DESIGN: Secondary data analysis. SETTING: Accrual from four sites: two clinical community oncology programs and two comprehensive cancer centers. SAMPLE: 80 patients newly diagnosed with lung cancer. METHODS: Analysis from baseline observation of a randomized clinical intervention trial. Multinomial log-linear modeling was performed to explain the relationships among pain, fatigue, insomnia, and gender. MAIN RESEARCH VARIABLES: Pain, fatigue, insomnia, and gender. FINDINGS: For all people with lung cancer, fatigue (97%) and pain (69%) were the most frequently occurring symptoms; insomnia occurred 51% of the time. A model containing all main effects (two-way interactions of pain and fatigue, pain and insomnia, and insomnia and gender; and the three-way interaction of pain, fatigue, and insomnia, along with three covariates [age, comorbidities, and stage of cancer]) was a good fit to the data. Parameter estimates indicated that a statistically significant effect from the model was the three-way interaction of pain, fatigue, and insomnia. Gender did not make a difference. Age, comorbidities, and stage of cancer were not significant covariates. CONCLUSIONS: For people newly diagnosed with lung cancer undergoing chemotherapy, multiple symptoms occur simultaneously rather than in isolation; a symptom cluster exists, consisting of pain, fatigue, and insomnia; and no relationship was found among gender, pain, fatigue, and insomnia. IMPLICATIONS FOR NURSING: By understanding this symptom cluster, healthcare providers can target specific troublesome symptoms to optimize symptom management and achieve the delivery of high-quality cancer care.
Authors: Carolyn Miller Reilly; Deborah Watkins Bruner; Sandra A Mitchell; Lori M Minasian; Ethan Basch; Amylou C Dueck; David Cella; Bryce B Reeve Journal: Support Care Cancer Date: 2013-01-12 Impact factor: 3.603
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Authors: Edward J Stepanski; Mark S Walker; Lee S Schwartzberg; L Johnetta Blakely; Jason C Ong; Arthur C Houts Journal: J Clin Sleep Med Date: 2009-04-15 Impact factor: 4.062