Literature DB >> 21839608

Identification of factors associated with fatigue in advanced cancer: a subset analysis of the European palliative care research collaborative computerized symptom assessment data set.

Ollie Minton1, Florian Strasser, Lukas Radbruch, Patrick Stone.   

Abstract

CONTEXT: This is a subset analysis of fatigue data and associated clinical variables collected as part of the European Palliative Care Research Collaborative Computerized Symptom Assessment (CSA) study. The overall aim of CSA was to determine the prevalence of common symptoms in a mixed advanced cancer group using an electronic data collection system.
OBJECTIVES: This analysis was conducted to identify factors independently associated with fatigue.
METHODS: Only patient records containing complete data for all three measured blood parameters in the CSA study (C-reactive protein [CRP], hemoglobin, and albumin) were included in our subset analysis (n=720). Participants with locoregional or metastatic disease of all tumor types were included (with or without concurrent palliative anticancer treatment). A large number of symptoms were recorded using a predesigned computer program and widely used symptom measurement scales. Fatigue was measured using a well-validated three-item fatigue scale taken from the European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire. A logistic regression model was developed using a cutoff score based on the available normative data to define the presence or the absence of severe fatigue.
RESULTS: Cases of fatigue were independently associated with chemotherapy treatment and experiencing other symptoms such as pain and depression. There was a moderate association with hemoglobin level. However, there was no link to cachexia, albumin, or CRP.
CONCLUSION: Severe fatigue is linked with treatment history and hemoglobin levels rather than CRP, mood, and other common symptoms in a mixed advanced cancer group.
Copyright © 2012 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 21839608     DOI: 10.1016/j.jpainsymman.2011.03.025

Source DB:  PubMed          Journal:  J Pain Symptom Manage        ISSN: 0885-3924            Impact factor:   3.612


  19 in total

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