title: The relationships among physiologic variables, quality of life, and fatigue in patients with multiple myeloma.
abstract: OBJECTIVE
  To investigate the relationships among physiologic variables, fatigue, and quality of life (QOL) in patients with multiple myeloma.
  
  
  METHODS
  Cross-sectional, descriptive, exploratory.
  
  
  METHODS
  Outpatient ambulatory care clinics at a tertiary oncology center.
  
  
  METHODS
  56 patients with multiple myeloma were accrued consecutively via nonprobability sampling strategy.
  
  
  METHODS
  Study participants completed the European Organisation for Research and Treatment of Cancer QLQ-C30 and the Functional Assessment of Cancer Therapy-Fatigue. Physiologic variables and demographic data were collected from patient charts.
  
  
  METHODS
  Hemoglobin (hgb), C-reactive protein (CRP), fatigue, and QOL.
  
  
  RESULTS
  Statistically significant correlations were found among hgb and two measures of fatigue and QOL, as well as among CRP and two measures of fatigue and QOL. Regression analysis revealed that as soon as the effect of CRP was removed, hgb was no longer a significant predictor of fatigue or QOL.
  
  
  CONCLUSIONS
  Although significant relationships between hgb and fatigue and hgb and QOL were identified, CRP made a significant contribution to predicting the variance in fatigue and QOL, whereas hgb did not. The findings suggest that higher CRP is predictive of greater fatigue and lower QOL.
  
  
  CONCLUSIONS
  Nurses play an integral role in the assessment and management of cancer-related fatigue. Greater understanding of the pathophysiology of fatigue may lead to progress in assessment and intervention, with the ultimate goal of reducing cancer-related fatigue and improving QOL.
authors.affiliation: Alberta Blood and Marrow Transplant Program, Tom Baker Cancer Centre, Calgary, Canada. reannebo@cancerboard.ab.ca
authors.forename: Reanne
authors.initials: R
authors.lastname: Booker
authors.forename: Karin
authors.initials: K
authors.lastname: Olson
authors.forename: Linda M
authors.initials: LM
authors.lastname: Pilarski
authors.forename: Joseph P
authors.initials: JP
authors.lastname: Noon
authors.forename: Nizar J
authors.initials: NJ
authors.lastname: Bahlis
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D001294:Attitude to Health; D002097:C-Reactive Protein / Q000276:immunology / Q000378:metabolism; D002170:Canada / Q000453:epidemiology; D003430:Cross-Sectional Studies; D005221:Fatigue / Q000453:epidemiology / Q000209:etiology* / Q000503:physiopathology / Q000523:psychology*; D005260:Female; D006454:Hemoglobins / Q000378:metabolism; D006801:Humans; D007249:Inflammation; D015850:Interleukin-6 / Q000097:blood / Q000276:immunology; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009101:Multiple Myeloma / Q000097:blood / Q000150:complications*; D024802:Nurse's Role / Q000523:psychology; D015404:Nursing Methodology Research; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011788:Quality of Life / Q000523:psychology*; D012307:Risk Factors; D011795:Surveys and Questionnaires
chemical_list: D006454:Hemoglobins; D015850:Interleukin-6; D002097:C-Reactive Protein