Multidimensional independent predictors of cancer-related fatigue

Abstract

The purpose of this study was to identify independent predictors of clinically significant fatigue based upon a multidimensional model. A total of 180 cancer patients completed the Brief Fatigue Inventory (BFI), Functional Assessment of Cancer Therapy-Fatigue (FACT-F), Memorial Symptom Assessment Scale Short Form (MSAS-SF), and the Zung Self-Rating Depression Scale (SDS). Additional data included Karnofsky Performance Status (KPS) score, laboratory tests, and demographic information. The BFI usual fatigue severity > or =3/10 was defined as clinically significant fatigue. Possible independent variables were identified from a biopsychosocial model of fatigue. Fisher's exact test was used to univariately assess the association of each variable with clinically significant fatigue. Multiple logistic regression analyses were used to identify independent predictors of fatigue within each dimension, and then across dimensions. Fatigue was present in 113 (62%) patients, and 80 (44.4%) patients had usual fatigue > or =3/10. The unidimensional independent predictors were use of analgesics (situation dimension); hemoglobin and serum sodium (biomedical dimension); feeling drowsy, dyspnea, pain and lack of appetite (physical symptom dimension); and feeling sad and feeling irritable (psychological symptom dimension). In a multidimensional model, dyspnea, pain, lack of appetite, feeling drowsy, feeling sad, and feeling irritable predicted fatigue independently with good calibration (Hosmer Lemeshow Chi Square=5.73, P=0.68) and discrimination (area under the receiver operating characteristic curve=0.88). Physical and psychological symptoms predict fatigue independently in the multidimensional model, and superseded laboratory data. These findings support a symptom-oriented approach to assessment of cancer-related fatigue.

A multidimensional examination of correlates of fatigue during radiotherapy

“…Each subscale consists of 4 items, 2 indicative of fatigue and 2 contraindicative (subscale score range, [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. The responder indicates on a scale of 1 to 5 to what extent the statement applies to him or her.…”

“…6 Although inconsistent terminology has been applied when categorizing fatigue dimensions, common classification themes include the physical, psychologic, and motivational dimensions. [7][8][9] For some purposes, a unidimensional assessment of cancer-related fatigue is arguably an appropriate approach (eg, when researching changes in fatigue intensity). For other purposes, such as evaluating treatments targeted at specific dimensions of fatigue, it is arguably more important to examine specific fatigue dimensions.…”

Fatigue in colorectal cancer patients: prevalence and associated factors

“…The intensity of the symptom is also considerable, with mean scores ranging from 2.6 to 6.9, depending on the cancer site and staging (3)(4) .…”

“…On the other hand, fatigueassociated factors in patients with advanced cancer are basically related to other signs and symptoms present in terminally ill patients (e.g. pain, dyspnea, decreased appetite, depression, weakness sensation, anxiety, low hemoglobin levels and others) (3)(4)(13)(14) . Interestingly, among cancer survivors, fatigue predictors include not only performance and symptoms, but also cognitive impairment (stress, coping, self-efficacy) (5) .…”

“…New studies are necessary, which attempt to identify other risk factors that increase the sensitivity of the model. No study with logistic regressions for the predictive factors identifying fatigue in patients with rectal cancer was found and, among the three studies that used the logistic regression method involving patients with other tumors, only one mentioned the discriminatory capacity of the model = 0.88 (3) . In that study, conducted with men with cancers in several sites, the predictors were sadness, dizziness, pain, appetite loss, irritability and dyspnea (3) .…”