title: Identification of latent classes in patients who are receiving biotherapy based on symptom experience and its effect on functional status and quality of life.
abstract: OBJECTIVE
  to identify subgroups of patients receiving biotherapy with pain, fatigue, sleep disturbance, and depression and to determine functional status and quality of life differences between subgroups.
  
  
  METHODS
  a descriptive, prospective, cohort study design.
  
  
  METHODS
  internet-based survey.
  
  
  METHODS
  187 patients with cancer receiving biotherapy.
  
  
  METHODS
  pain intensity, Piper Fatigue Scale, General Sleep Disturbance Scale, Center for Epidemiological Studies-Depression, Karnofsky Performance Scale, and the Multidimensional Quality of Life Scale-Cancer were used at two time points one month apart (T1 and T2). Latent profile analysis identified subgroups.
  
  
  METHODS
  biotherapy, symptoms, functional status, and quality of life.
  
  
  RESULTS
  At T1 (N = 187), five patient subgroups were identified, ranging from subgroup 1 (mild fatigue and sleep disturbance) to subgroup 5 (severe on all four symptoms). At T2 (N = 114), three patient subgroups were identified, ranging from subgroup 1 (mild pain, fatigue, and sleep disturbance without depression) to subgroup 3 (mild pain, moderate fatigue, and sleep disturbance with severe depression). At each time point, the patient subgroup with the most severe symptoms showed significantly lower functional status and quality of life.
  
  
  CONCLUSIONS
  as with other cancer treatments, biotherapy can be divided into similar patient subgroups with four prevalent symptoms. Subgroups of patients differ in functional status and quality of life as a result of symptom severity.
  
  
  CONCLUSIONS
  clinicians should assess and identify patients with severe levels of the four prevalent symptoms and offer appropriate interventions. Future study is needed to investigate the factors that contribute to symptom severity and to examine the occurrence of symptom clusters that may place patients at increased risk for poorer outcomes.
authors.affiliation: Department of Physiological Nursing in the School of Nursing, University of California, San Francisco, USA. marylin.dodd@nursing.ucsf.edu
authors.forename: Marylin J
authors.initials: MJ
authors.lastname: Dodd
authors.forename: Maria H
authors.initials: MH
authors.lastname: Cho
authors.forename: Bruce A
authors.initials: BA
authors.lastname: Cooper
authors.forename: Judy
authors.initials: J
authors.lastname: Petersen
authors.forename: Kayee Alice
authors.initials: KA
authors.lastname: Bank
authors.forename: Kathryn A
authors.initials: KA
authors.lastname: Lee
authors.forename: Christine
authors.initials: C
authors.lastname: Miaskowski
mesh_terms: D000328:Adult; D000368:Aged; D001691:Biological Therapy / Q000009:adverse effects*; D015331:Cohort Studies; D005221:Fatigue / Q000209:etiology / Q000451:nursing; D005260:Female; D006306:Health Surveys; D006801:Humans; D020407:Internet; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000188:drug therapy* / Q000451:nursing; D009859:Oncology Nursing / Q000379:methods*; D010146:Pain / Q000209:etiology / Q000451:nursing; D011446:Prospective Studies; D011788:Quality of Life; D011795:Surveys and Questionnaires