Clinical relevance of fatigue levels in cancer patients at a Veterans Administration Medical Center

Authors

  • Shirley S. Hwang R.N., M.S.,

    Corresponding author
    1. Section Hematology/Oncology (111), Veterans Administration New Jersey Health Care System at East Orange, East Orange, New Jersey
    2. Patient Care Service, Veterans Administration New Jersey Health Care System, East Orange, New Jersey
    3. University of Medicine and Dentistry of New Jersey/School of Nursing, Newark, New Jersey
    • Section of Hematology/Oncology (111), VA New Jersey Health Care System, 385 Tremont Avenue, East Orange, NJ 07019
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    • Fax: (973) 395-7089

  • Victor T. Chang M.D.,

    1. Section Hematology/Oncology (111), Veterans Administration New Jersey Health Care System at East Orange, East Orange, New Jersey
    2. Department of Medicine, University of Medicine and Dentistry of New Jersey/New Jersey Medical School, Newark, New Jersey
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  • Janet Cogswell R.N., M.S.,

    1. Section Hematology/Oncology (111), Veterans Administration New Jersey Health Care System at East Orange, East Orange, New Jersey
    2. Patient Care Service, Veterans Administration New Jersey Health Care System, East Orange, New Jersey
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  • Basil S. Kasimis M.D., D.Sc.

    1. Section Hematology/Oncology (111), Veterans Administration New Jersey Health Care System at East Orange, East Orange, New Jersey
    2. Department of Medicine, University of Medicine and Dentistry of New Jersey/New Jersey Medical School, Newark, New Jersey
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  • The views expressed herein do not necessarily reflect the views of the Department of Veterans Affairs or the U.S. Government.

Abstract

BACKGROUND

The correlation of fatigue levels with functional interference, symptom distress, and quality of life may help determine clinically significant fatigue levels.

METHODS

One hundred eighty consecutive patients with cancer completed the Functional Assessment of Cancer Therapy (FACT) General and Fatigue subscales (FACT-G and FACT-F, respectively), the Memorial Symptom Assessment Scale-Short Form (MSAS-SF), the Depression Scale (Zung), and the Brief Fatigue Inventory (BFI). The Karnofsky performance status (KPS) was determined for each patient. Multivariate analyses of variance were performed to compare fatigue models with different cut-off points to categorize fatigue levels. Cox proportional hazards analysis was performed to assess the association between fatigue severity and survival.

RESULTS

Increased fatigue levels were associated with greater symptom distress and decreased quality of life. A model with usual fatigue cut-off points of 0 (no fatigue), 1–2 (mild fatigue), 3–6 (moderate fatigue), and 7–10 (severe fatigue) was optimal in relation to functional interference items (Wilks λ, 0.36; F = 11.61; P < 0.0001), symptom distress scores (Wilks λ, 0.52; F = 10.41; P < 0.0001), and quality-of-life scores (Wilks λ, 0.50; F = 0.50; P < 0.0001). Fatigue severity predicted survival in univariate analysis (chi-square test, 25.42; P < 0.0001). The KPS, stage of disease, and number of symptoms independently predicted survival in patients with fatigue.

CONCLUSIONS

Clinically relevant fatigue levels are correlated with symptom and quality-of-life measurements. Patients with a usual fatigue severity > 3 or a worst fatigue severity > 4 on a 1–10 scale may require further assessment. Cancer 2002;94:2481–9. © 2002 American Cancer Society.

DOI 10.1002/cncr.10507

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