Fatigue and Its Risk Factors in Cancer Patients Who Seek Emergency Care

Article Outline

• Abstract
• Introduction
• Patients and Methods
• Results
  • Sample Characteristics
  • General Sickness and Cancer-Related Fatigue
  • Role of Patient Characteristics in Cancer-Related Fatigue
  • Fatigue by Disease Severity and Cancer Treatment
  • The Prevalence of Moderate to Severe Fatigue and Pain in EC Patients
  • Fatigue and Anemia
  • Fatigue and Other Symptoms, Vital Signs, and Review of Systems
  • Risk Factors for Severe Fatigue in the EC
• Discussion
• Acknowledgments
• References
• Copyright

Abstract 

Cancer patients visiting the emergency center (EC) are seldom assessed or treated for severe fatigue, a common symptom in sick patients due to acute medical conditions arising from cancer and cancer treatment. We provide a profile of cancer-related fatigue within the EC setting. Using a single-item screening tool derived from the Brief Fatigue Inventory, 928 patients (636 with solid tumors, 292 with hematological malignancies) triaged in the EC of a tertiary cancer center rated their fatigue at its worst in the last 24hours. Patient demographic and clinical factors were retrospectively reviewed from medical records. The chief complaints of patients seeking emergency care included fever, pain, gastrointestinal symptoms, dyspnea, fatigue, and bleeding. More than half (54%) reported severe fatigue (seven or higher on a 0–10 scale) upon EC admission. Moderate to severe pain was highly associated with fatigue severity. Patients with severe fatigue were more likely to be unstable and unable to go home after EC care. In multivariate logistic regression analysis for severe fatigue, the significant risk factors for patients with solid tumors included dizziness (odds ratio [OR]=3.59), severe pain (OR=1.98), poor performance status (OR=1.81), and being female (OR=1.56). Dyspnea was significantly associated with severe fatigue in patients with hematological malignancies (OR=4.74). Although fatigue was not the major reason for an ER visit, single-item fatigue-severity screening demonstrated highly prevalent severe fatigue in sicker EC cancer patients and in those patients who also suffered from other symptoms.

Key Words: Cancer-related fatigue, emergency care, risk factor

Back to Article Outline

Introduction 

Cancer-related fatigue is a subjective sense of tiredness related to cancer or its treatment that interferes with usual functioning.¹, ², ³, ⁴ Understanding fatigue and how to manage it is a challenge for both researchers and clinicians, because fatigue is a multifactorial and multidimensional symptom that is difficult to define or measure in a standardized manner, and because there are no effective gold-standard therapies for treating it. Fatigue may be persistent and chronic, as it is in cancer survivors⁵, ⁶ and patients with advanced cancer,⁷ or it may be acute, as it is when the body responds to a particular insult, such as infection, trauma, high-dose chemotherapy⁸ or radiotherapy,⁹, ¹⁰, ¹¹ or major surgery.

The epidemiology of chronic fatigue has been well described in the setting of routine cancer treatment.¹² There are few empirical data, however, on fatigue in an acute-care setting such as an emergency center (EC), even though serious fatigue, often accompanied by a cluster of other sickness-related symptoms (e.g., poor appetite, disturbed sleep), has been observed in patients with cancer who seek emergency care. These patients are seldom quantitatively assessed for or offered relevant treatment for severe fatigue in the EC because they are in much more urgent need of evaluation and management of pressing, life-threatening medical issues, such as infection, severe pain, cancer therapy-related gastrointestinal toxicities, or other comorbid conditions. Patients in the EC who are experiencing severe cancer-related fatigue provide an opportunity to study the clinical relevance of this debilitating symptom.

Cancer-related fatigue has been reported in both solid tumors and hematological malignancies.¹¹, ¹³ Because our EC patient sample was unmatched as to age, sex, hemoglobin level, and current chemotherapy status, we conducted a retrospective study to separately profile fatigue in cancer patients with solid tumors or hematological malignancies who were being served in the EC. Patient self-report of fatigue severity and other clinical information was collected from patient records. We hypothesized that specific patient-related and clinical factors would be significantly associated with elevated fatigue in these very ill cancer patients. Gaining a better knowledge of the clinical features of fatigue in the EC could be an important step toward a better understanding of this complicated but most common symptom in cancer patients. It may lead to further research on the etiology of fatigue, which could in turn generate mechanism-driven fatigue interventions.

Back to Article Outline

Patients and Methods 

Via retrospective chart review, we assembled a sample of 928 patients (636 with solid tumors and 292 with hematological malignancies) who had been admitted to the EC at The University of Texas M. D. Anderson Cancer Center during a selected three-month period. The M. D. Anderson Cancer Center EC, accredited as a Level III center by the Joint Commission on Accreditation of Healthcare Organizations, is available for the acute care needs of patients being treated for cancer at M. D. Anderson. Institutional Review Board approval was obtained for this data collection.

Inclusion criteria included a diagnosis of cancer (regardless of stage or treatment), a record of the patient's rating of fatigue severity during EC triage, and a medical record and EC record. Every third patient evaluated in the EC who met the inclusion criteria was included in the analysis. If a patient had multiple admissions to the EC during the study period, we used data from the first admission only.

Data drawn from EC records and medical records of the selected patients included demographic information, type of cancer, vital signs, patient's chief complaint during the EC visit, physician-rated Eastern Cooperative Oncology Group performance status (ECOG PS), clinician review of systems, current cancer treatment, comorbid conditions, and medications administered upon EC admission. If the patient's medical record included complete blood count, electrolyte studies, or chemistry taken within one day of EC admission, these values were noted.

We also extracted from the EC record the patient's self-reported fatigue and pain at their worst on a 0–10 scale, which were the only two single-item screening results obtained during EC triage. The fatigue item routinely used for screening in this EC was adapted from the Brief Fatigue Inventory¹² and validated in the cancer population. Patients were asked, “What is your worst fatigue in the last 24hours on a 0–10 scale, with 10 being fatigue as bad as you can imagine?”

Descriptive statistics were used in the analysis, categorized by diagnosis group (solid tumor or hematological malignancy). We classified the patients in our sample as having severe fatigue (ratings of 7–10) or nonsevere fatigue (ratings of 0–6) in accordance with the Brief Fatigue Inventory validation study.¹² To ensure an experiment-wise error of no more than 5% due to multiple comparisons, we used the Dunn-Ŝĭdák correction.¹⁴ Thus, 37 univariate analyses for severe fatigue were each conducted at the 0.0014 significance level. In a multivariate logistic regression model of severe fatigue, candidate predictors of severe fatigue were considered on the basis of their clinical relevance to fatigue. Stepwise regression was performed and model fit was examined based on area under the receiver operating characteristics curve. The receiver operating characteristics area ranges from 0.5 (no predictive power) to 1.0 (total predictive power), and is used to estimate the discriminating power of the correlates of fatigue. Odds ratios (OR) and 95% confidence intervals (95% CI) are reported.

Back to Article Outline

Results 

Sample Characteristics 

Table 1 presents patient characteristics by disease group; 69% (636/928) of the sample had solid tumors, and the rest (292/928) had hematological malignancies. At the time of their EC visit, 50% of the sample had progressive disease or relapse, and 59% had poor ECOG PS (2–4). After triage, 44% of the sample was admitted to a hospital floor and 3% were admitted to the ICU; the remaining 53% were discharged to home after receiving medical care. The primary patient characteristics that might affect fatigue severity (age, sex, hemoglobin level, and current chemotherapy status) were significantly different between the solid tumor group and hematological disease group (all P<0.001).

Table 1. Demographic and Disease-Related Characteristics

Characteristic	Patient Group
	Solid Tumor (n=636)		Hematological Malignancy (n=292)
	n	%	n	%
Age, mean (range)	56.3 (19.7–92.6)		53.2 (18.4–85.1)
<40 years	90	14.2	68	23.3
40–70 years	450	70.8	188	64.4
70+ years	96	15.1	36	12.3
Sex
Female	326	51.3	112	38.4
Race
White non-Hispanic	453	71.2	209	74.4
African American	79	12.8	21	7.5
Hispanic	61	9.9	45	16.0
Asian	18	2.9	6	2.1
Cancer diagnosis	Breast	18.7	Lymphoma	32.9
	Lung	15.5	Acute leukemia	32.2
	Gastrointestinal	13.7	Chronic leukemia	17.8
	Genitourinary	10.8	Myeloma	9.9
	Sarcoma	9.0	Myelodysplastic syndrome	3.8
	Gynecologic	7.9	Hodgkin's Disease	3.1
	Colorectal	6.9
	Melanoma	4.7
	Others	1.7
ECOG PS
0–1	189	41.1	86	38.7
2	140	30.4	73	32.9
3–4	131	28.5	63	28.4
Current cancer treatment
Chemotherapy	239	37.6	162	55.5
Radiotherapy	90	14.2	8	2.7
Other	30 (surgery)	4.7	11 (transplantation)	3.8
Chief complaints
All types of pain	151	24.0	50	25.3
Fever	109	17.1	119	40.8
Diarrhea	67	10.5	16	5.5
Dyspnea	54	8.5	8	2.7
Fatigue/weakness	41	6.5	7	2.4
Bleeding	23	3.6	17	5.8
All others	225	35.8	81	27.8
Abnormal range in laboratory tests
Hemoglobin	157	26.3	144	50.5
Absolute neutrophil count	29	5.5	47	22.9
Magnesium	32	5.8	31	12.2
Albumin	31	7.3	19	9.0
Glucose	39	7.9	12	5.2
Abnormal vital signs
Systolic blood pressure (mmHg)	53	8.4	18	6.2
Diastolic blood pressure (mmHg)	29	4.6	12	4.1
Temperature >37.4°C	65	10.4	57	19.7
Review of systems
Constipation	72	11.3	18	6.2
Diarrhea	59	9.3	21	7.2
Nausea	133	20.9	47	16.1
Vomiting	104	16.4	26	8.9
Dizziness	56	8.8	26	8.9
Current medications
Opioids	288	45.3	76	26.0
Antidepressants	89	14.0	33	11.3
Antibiotics	127	20.2	175	60.6
Antiemetics	165	25.9	56	19.2
Steroids	62	9.7	44	15.1

The six chief complaints reported by 72% of the sample at the time of their EC visit included fever (25%), pain of any type (22%), gastrointestinal symptoms (diarrhea, nausea and vomiting, constipation) (9%), dyspnea (7%), fatigue/weakness (6%), and bleeding (4%). The remaining 28% of the sample had complained of more than 20 other ailments.

General Sickness and Cancer-Related Fatigue 

As expected, the patient's self-reported severe fatigue was significantly related to clinician ratings of the patient's sickness (OR=1.594; 95% CI=1.103–2.304; P<0.01) and unstable level (OR=2.001; 95% CI=1.361–2.940; P<0.001). Also, severe fatigue at triage was associated with the patient's being admitted to an inpatient hospital unit, the operating room, or hospice, and with patient death (rather than the patient's being sent home after EC treatment) (OR=1.492; 95% CI=1.152–1.932; P<0.001).

Role of Patient Characteristics in Cancer-Related Fatigue 

Univariate analysis of patient demographic variables showed that age, sex, and race (white vs. nonwhite) were not significantly associated with mean fatigue severity levels in the hematological malignancy group. However, women and elderly patients in the solid tumor group had significantly higher fatigue levels (both P<0.05, see Table 2).

Table 2. Severity of Cancer-Related Fatigue^a by Patient and Disease Characteristics

Characteristic	Patient Group
	Solid Tumor (n=636)		Hematological Malignancy (n=292)
	Mean (SD)	P value	Mean (SD)	P value
Age
<40 years	5.58 (3.32)	0.020		NS
40–70 years	6.47 (3.21)
70+ years	6.81 (2.87)
Sex
Male	6.14 (3.20)	0.047		NS
Female	6.64 (3.17)
ECOG PS
0–1	5.46 (3.39)	<0.001	5.22 (3.40)	0.003
2–4	6.98 (2.99)		6.51 (3.01)
Taking opioids
No		NS	5.59 (3.31)	0.034
Yes			6.50 (2.86)
Anemia
<10g/dL	6.93 (2.95)	0.013	6.59 (2.81)	<0.001
≥10g/dL	6.21 (3.25)		5.05 (3.48)
Fever		NS		NS
Diarrhea
No	6.25 (3.26)	0.001	5.74 (3.21)	0.048
Yes	7.64 (2.17)		7.38 (3.22)
Dyspnea
No	6.25 (3.19)	0.013	5.53 (3.16)	<0.001
Yes	7.08 (3.06)		7.51 (3.14)
Severe paina
0–6	6.12 (3.12)	0.002		NS
7–10	6.97 (3.21)
Dizziness
No	6.30 (3.21)	0.014		NS
Yes	7.39 (2.83)
Nausea
No	6.23 (3.27)	0.012	5.55 (3.26)	0.001
Yes	7.01 (2.81)		7.26 (2.66)
Systolic blood pressure
Abnormal	7.45 (2.63)	0.011		NS
Normal	6.29 (3.23)
Diastolic blood pressure
Abnormal	8.07 (2.43)	0.004	7.75 (3.39)	0.035
Normal	6.30 (3.21)		5.74 (3.20)

NS=not significant.

Fatigue by Disease Severity and Cancer Treatment 

Patients with solid tumors had significantly higher fatigue (6.4 vs. 5.8, P<0.01) and pain (4.2 vs. 3.2, P<0.001) than patients with hematological malignancies. For both groups, patients whose cancer was evaluated as “progressive disease” or “relapsed” had significantly higher levels of fatigue than patients with stable disease (P<0.05). In both groups, as expected, poor performance status (ECOG PS 2–4) was strongly associated with higher levels of fatigue, which was exacerbated by acute illness as affected by disease condition (all P<0.01).

At the time of their admission to the EC, more than half (52%) of the subjects were undergoing some type of cancer treatment (chemotherapy, radiation therapy, hormonal or biological therapy, or a combination). Active chemotherapy was not related to severe fatigue in the study sample. The most common types of medications that patients were taking at the time of admission to the EC included analgesics, antipyretics, gastrointestinal medications, and cardiac agents. Taking opioids was associated with higher fatigue levels in the hematology group (P<0.05).

The Prevalence of Moderate to Severe Fatigue and Pain in EC Patients 

The top symptom among the chief complaints reported by this sample of EC patients was pain. In this EC cancer patient sample, approximately 40% of patients with solid tumors simultaneously reported moderate-to-severe levels (ratings 5 or higher on the 0–10 scale) of both fatigue and pain, and approximately 27% with hematological malignancies rated both symptoms as moderate to severe (Table 3). Patients reported higher levels of fatigue than pain in both the moderate-to-severe range (75% compared with 45%) and the severe range (54% compared with 31%).

Table 3. Prevalence of Cancer-Related Fatigue and Pain for Cancer Patients Seeking Emergency Care

Patient Group	Fatigue≥5a	Pain≥5a	Both Fatigue and Pain≥5a	Predictors of Having Both Symptoms≥5a
Solid tumor	77.2%	48.9%	40.5%b	Poor ECOG PS (OR=1.7; 95% CI=1.11–2.6; P=0.014)
	72.2% when pain 0–4	37.3% when fatigue 0–4
	82.7% when pain≥5	52.4% when fatigue≥5
Hematological malignancy	70%	36.5%	27.4%	On opioids (OR=2.88; 95% CI=1.44–5.75; P=0.003)
	66.1% when pain 0–4	28.7% when fatigue 0–4
	76.2% when pain≥5	39.8% when fatigue≥5
Entire sample	75%	45%	36%

For 391 of the 636 patients with solid tumors, the factor that was most significantly associated with levels of both fatigue and pain was poor ECOG PS (OR=1.7; 95% CI=1.11–2.26; P<0.01). We observed a significant interaction between fatigue and pain in this group (OR=1.846; 95% CI=1.258–2.711; P<0.01), where 83% of patients with moderate-to-severe pain also reported moderate-to-severe fatigue, and 52% of patients with moderate-to-severe fatigue also reported moderate-to-severe pain. For 189 of the 292 patients with hematological malignancies, taking opioids was the only item associated with both significant fatigue and pain (OR=2.88; 95% CI=1.44–5.75; P<0.01).

Fatigue and Anemia 

Examination of laboratory results (Table 2) revealed that only hemoglobin levels were significantly associated with severe fatigue in both patient groups. Patients with hematological cancer had high levels of fatigue when they were anemic (hemoglobin<10g/dL; P<0.001) or had abnormal levels of magnesium (P<0.05).

Fatigue and Other Symptoms, Vital Signs, and Review of Systems 

Of the five chief complaints (excluding fatigue) in this study sample, gastrointestinal symptoms (diarrhea, nausea and vomiting, constipation) had the highest association with fatigue severity, followed in order by dyspnea, fever, all types of pain, and bleeding (Table 2). In univariate analysis, diarrhea was significantly associated with severe fatigue (OR=2.274; 95% CI=1.397–3.714; P<0.001).

Assessment of vital signs revealed that fatigue severity was higher for patients with fever (P=0.05), abnormal pulse (P=0.02), or abnormal blood pressure (P=0.004 for systolic, P<0.001 for diastolic). In the review of systems, wherein patients are asked whether they are experiencing certain conditions, fatigue severity was higher when patients had chest pain (P=0.05), constipation (P=0.008), nausea and vomiting (P=0.001), dyspnea (P<0.001), depression (P=0.05), or dizziness (P=0.002).

More than half of the total sample (480/928, 51%) had at least one comorbidity, such as diabetes mellitus, hypertension, coronary artery disease, hypothyroidism, renal insufficiency, chronic obstructive pulmonary disease, or depression (based on physician notation and use of at least one antidepressant medication). None of these were associated with severe fatigue.

Risk Factors for Severe Fatigue in the EC 

Multivariate logistic regression was fitted to the two diagnosis groups to evaluate the association of covariates with severe fatigue. The candidate factors considered in the stepwise variable selection process were those with significant results in univariate analysis, including sex, ECOG PS, hemoglobin level, magnesium level, systolic blood pressure, severe pain, diarrhea, nausea, dizziness, constipation, nausea, vomiting, depression, dyspnea, and taking opioids. We included presence of chronic obstructive pulmonary disease, which is highly clinically relevant to fatigue severity, even though it was not significant in the univariate analysis. Some variables were not considered in the model, even though their P-values were less than or equal to 0.05 in the univariate analysis, because only a few patients had abnormal levels.

Table 4 summarizes the results of the stepwise process for the two disease groups. In the hematological malignancy group model (n=188), dyspnea was the only significant factor associated with severe fatigue (P<0.005). In the solid tumor group (n=403), dizziness, severe pain, poor ECOG PS (all P<0.01) and being a woman (P<0.05) were the significant factors associated with severe fatigue. The receiver operating characteristics curves for these fitted models were 0.586 and 0.664, respectively, demonstrating the sufficient power of the tests.

Table 4. Multivariate Analysis of the Risk Factors for Severe Fatigue in Cancer Patients Seeking Emergency Care

Predictors	OR	95% CI of OR	P Value
Hematological malignancy group
Dyspnea	4.74	1.72–13.04	0.0026
Solid tumor group
Dizziness	3.59	1.49–8.64	0.0044
Severe pain	1.98	1.25–3.12	0.0035
Poor ECOG PS	1.81	1.19–2.77	0.0058
Being female	1.57	1.03–2.36	0.0381

Back to Article Outline

Discussion 

This initial report describes fatigue in a unique clinical setting that has not been previously explored—the EC of a cancer hospital. The current study evidenced that 54% of the patients admitted to the EC in a cancer hospital suffered from severe fatigue (seven or higher on a 0–10 scale) during the 24hours preceding EC admission, surpassing the percentage of outpatients with severe fatigue in the same institution (32%).¹², ¹⁵ This study also demonstrated that although fatigue was not the primary reason patients visited the EC (only 6% of the sample seeking EC care named fatigue as their chief complaint), a simple screening process revealed it to be a predominant symptom that was more prevalent than moderate-to-severe pain, which was the second most named chief complaint (75% vs. 45%). The study also identified potential risk factors for severe fatigue in patients visiting the EC, providing clinicians insight into the complexities associated with fatigue in an emergency situation.

That 75% of the study sample reported moderate-to-severe fatigue substantiates the importance of a better understanding of this symptom. Patient-reported outcome tools for measuring subjective symptoms have recently been promoted by the U.S. Food and Drug Administration as a way to more accurately evaluate therapeutic agents.¹⁶ Patient-reported outcome measures are especially important in light of the fact that most patients with cancer do not voluntarily speak to clinicians about their fatigue in the oncology care setting. In a study conducted in a palliative care setting, patients most often volunteered that they were experiencing pain, yet a systematic screening assessment identified fatigue as the most common symptom.¹⁷ Clinicians with overwhelmingly sick patients in an acute-care setting are often reluctant to bring up the subject of fatigue because they have no gold-standard intervention for treating it, such as they do for pain, other than addressing reversible causes (e.g., anemia or electrolyte imbalances) and checking for hypothyroidism or drug interactions. The results of this study demonstrate that the use of a simple, 0–10 scale, single-item fatigue assessment tool can break the ice between cancer patients and care providers in terms of communicating about fatigue, even during triage for acute sickness in a busy cancer center's specialized EC. Our findings support the feasibility of using simple patient-reported outcome tools to routinely screen for fatigue and pain in sick cancer patients.

Beyond disease-related and cancer treatment-related symptoms, other acute medical conditions, especially dizziness, pain, and respiratory symptoms, were associated with higher levels of fatigue in EC cancer patients. Although ratings of fatigue severity do not provide specific diagnostic information, the patients with severe fatigue at triage were more likely to require further medical care in the hospital, which fit well with the EC clinician's judgment of the patient's sickness. Being female was associated with severe fatigue in the solid tumor group. Being female was often reported but was not a conclusive predictor of fatigue in a previous study of patients with cancer.¹⁸, ¹⁹ Poorer ECOG PS, which was significantly associated with cancer-related fatigue in the solid tumor group, could be inherently related to both acute and chronic physical and psychological distress brought on by more extensive malignant disease and additional comorbidities.²⁰

Medically ill patients may experience multiple nonspecific symptoms. Under common pathophysiological conditions, symptom interaction may magnify symptom severity. Fatigue and pain are good examples. That these two symptoms covary in onset and severity has been observed in patients with many types of cancer-related or treatment-related symptoms. Pain and the use of analgesics have been shown to be independently associated with fatigue, and, therefore, the inclusion of severe pain as a factor in our model is understandable.⁹, ¹³, ²¹, ²² The contribution of moderate-to-severe pain to significant cancer-related fatigue in sick patients in the EC provides evidence that symptoms may exacerbate the severity of one another. Future longitudinal symptom studies may show whether this effect goes only one way—that significant pain exacerbates fatigue severity—or whether the converse is also true.

Several limitations resulted from the retrospective nature of the study. First, our cross-sectional data set allowed us to present only association, but not a causal relationship, between fatigue and its risk factors. Second, information about the impact of severe fatigue on functional status in this targeted sample was unavailable. Third, this population of cancer patients with acute-care needs was heterogeneous; investigating a more homogeneous group may reveal a better model fit and result in a more specific clinical lead for intervention. In addition, the study was conducted in a large, urban tertiary cancer center, and the findings may not be entirely generalizable to all cancer patients in other settings.

We are aware that the higher fatigue severity in the solid tumor group in relation to the hematological malignancy group is quite possibly inaccurate. Some sicker patients with hematological malignancy, such as patients in the acute phase of transplantation, are likely to be closely followed as inpatients or in specific clinics by treating hematologists rather than in the EC, which could result in a lower level of fatigue severity in the hematological cancer patients in the EC setting. Therefore, the true prevalence of severe fatigue in the EC setting is not necessarily equal to the prevalence of fatigue in all medically ill patients with cancer.

Finally, because only two self-reported single-symptom assessments were available, we do not have a comprehensive evaluation of how fatigue clusters with other symptoms in sickness. The use of a multiple-symptom assessment tool to assess levels of other, co-occurring symptoms would be of great benefit. In fact, we would expect to see that the multiple symptoms experienced by cancer patients in acute-response conditions appear to parallel animal “sickness behavior,” a term that describes the co-occurring behavioral and physiological responses of animals receiving exogenous cytokines, infectious agents, or endotoxins.²³, ²⁴, ²⁵, ²⁶, ²⁷, ²⁸, ²⁹ Evidence of causal association between systemic inflammatory response and sickness behavior in EC patients could be helpful for interpreting and better understanding the mechanisms underlying the development of severe fatigue in these sicker cancer patients.

In conclusion, our findings suggest a great need for more understanding of the development of fatigue and related symptoms that often appear together in sick cancer patients. The discovery of a mechanism-driven approach to fatigue management could bring about true change in the way we deal with the severe fatigue experienced by patients with cancer or other diseases. As we learn more about the acute and chronic fatigue experienced by patients with cancer,³⁰, ³¹ we believe we may become more adept in addressing, evaluating, successfully treating, and, perhaps one day, substantially preventing fatigue in very sick cancer patients.

Back to Article Outline

Acknowledgments 

The authors acknowledge with appreciation the editorial assistance of Jeanie F. Woodruff, ELS, in the Department of Symptom Research at M. D. Anderson Cancer Center.

Back to Article Outline

References 

1. Mock V, Atkinson A, Barsevick A, et al. NCCN practice guidelines for cancer-related fatigue. Oncology (Williston Park). 2000;14(11A):151–161
   • View In Article
   • MEDLINE
2. National Comprehensive Cancer Network . Cancer-related fatigue and anemia: treatment guidelines for patients. Accessed June 2, 2007. Available at http://www.nccn.org/patients/patient_gls/_english/pdf/NCCN%20Fatigue%20Guidelines.pdf
   • View In Article
3. Cleeland CS, Wang XS. Measuring and understanding fatigue. Oncology. 1999;13(11A):91–97
   • View In Article
4. Lawrence DP, Kupelnick B, Miller K, Devine D, Lau J. Evidence report on the occurrence, assessment, and treatment of fatigue in cancer patients. J Natl Cancer Inst Monogr. 2004;32:40–50
   • View In Article
5. Bower JE, Ganz PA, Desmond KA, et al. Fatigue in breast cancer survivors: occurrence, correlates, and impact on quality of life. J Clin Oncol. 2000;18(4):743–753
   • View In Article
   • MEDLINE
6. Servaes P, Verhagen S, Bleijenberg G. Determinants of chronic fatigue in disease-free breast cancer patients: a cross-sectional study. Ann Oncol. 2002;13(4):589–598
   • View In Article
   • MEDLINE
   • CrossRef
7. Coackley A, Hutchinson T, Saltmarsh P, et al. Assessment and management of fatigue in patients with advanced cancer: developing guidelines. Int J Palliat Nurs. 2002;8(8):381–388
   • View In Article
   • MEDLINE
8. Knobel H, Loge JH, Nordoy T, et al. High level of fatigue in lymphoma patients treated with high dose therapy. J Pain Symptom Manage. 2000;19(6):446–456
   • View In Article
   • Abstract
   • Full Text
   • Full-Text PDF (139 KB)
   • CrossRef
9. Wang XS, Janjan NA, Guo H, et al. Fatigue during preoperative chemoradiation for resectable rectal cancer. Cancer. 2001;92(6 Suppl):1725–1732
   • View In Article
   • MEDLINE
   • CrossRef
10. Wang XS, Fairclough DL, Liao Z, et al. Longitudinal study of the relationship between chemoradiation therapy for non-small-cell lung cancer and patient symptoms. J Clin Oncol. 2006;24(27):4485–4491
    • View In Article
    • CrossRef
11. Jacobsen PB, Stein K. Is fatigue a long-term side effect of breast cancer treatment?. Cancer Control. 1999;6(3):256–263
    • View In Article
12. Mendoza TR, Wang XS, Cleeland CS, et al. The rapid assessment of fatigue severity in cancer patients: use of the Brief Fatigue Inventory. Cancer. 1999;85(5):1186–1196
    • View In Article
    • MEDLINE
    • CrossRef
13. Wang XS, Giralt SA, Mendoza TR, et al. Clinical factors associated with cancer-related fatigue in patients being treated for leukemia and non-Hodgkin's lymphoma. J Clin Oncol. 2002;20(5):1319–1328
    • View In Article
    • MEDLINE
    • CrossRef
14. Ŝĭdák Z. Rectangular confidence regions for the means of multivariate normal distributions. J Am Stat Assoc. 1967;62:626–633
    • View In Article
15. Cleeland CS, Mendoza TR, Wang XS, et al. Assessing symptom distress in cancer patients: the M.D. Anderson Symptom Inventory. Cancer. 2000;89(7):1634–1646
    • View In Article
    • MEDLINE
    • CrossRef
16. Food and Drug Administration . Guidelines for industry (draft). Patient-reported outcome measures: Use in medical product development to support labeling claims. Rockville MD: U.S. Department of Health and Human Services; 2006;
    • View In Article
17. Homsi J, Walsh D, Rivera N, et al. Symptom evaluation in palliative medicine: patient report vs systematic assessment. Support Care Cancer. 2006;14(5):444–453
    • View In Article
    • MEDLINE
    • CrossRef
18. Miaskowski C. Gender differences in pain, fatigue, and depression in patients with cancer. J Natl Cancer Inst Monogr. 2004;32:139–143
    • View In Article
19. Schmidt CE, Bestmann B, Kuchler T, et al. Gender differences in quality of life of patients with rectal cancer: a five-year prospective study. World J Surg. 2005;29(12):1630–1641
    • View In Article
    • MEDLINE
20. Brown DJ, McMillan DC, Milroy R. The correlation between fatigue, physical function, the systemic inflammatory response, and psychological distress in patients with advanced lung cancer. Cancer. 2005;103(2):377–382
    • View In Article
    • MEDLINE
    • CrossRef
21. Hwang SS, Chang VT, Rue M, Kasimis B. Multidimensional independent predictors of cancer-related fatigue. J Pain Symptom Manage. 2003;26(1):604–614
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (142 KB)
    • CrossRef
22. Stone P, Richardson A, Ream E, et al. Cancer-related fatigue: inevitable, unimportant and untreatable? Results of a multi-centre patient survey. Cancer Fatigue Forum. Ann Oncol. 2000;11(8):971–975
    • View In Article
    • MEDLINE
    • CrossRef
23. Cleeland CS, Bennett GJ, Dantzer R, et al. Are the symptoms of cancer and cancer treatment due to a shared biologic mechanism? A cytokine-immunologic model of cancer symptoms. Cancer. 2003;97(11):2919–2925
    • View In Article
    • MEDLINE
    • CrossRef
24. Dantzer R, Bluthe RM, Laye S, et al. Cytokines and sickness behavior. Ann N Y Acad Sci. 1998;840:586–590
    • View In Article
    • MEDLINE
    • CrossRef
25. Larson SJ, Dunn AJ. Behavioral effects of cytokines. Brain Behav Immun. 2001;15(4):371–387
    • View In Article
    • MEDLINE
    • CrossRef
26. Lee BN, Dantzer R, Langley KE, et al. A cytokine-based neuroimmunologic mechanism of cancer-related symptoms. Neuroimmunomodulation. 2004;11(5):279–292
    • View In Article
    • MEDLINE
    • CrossRef
27. Dantzer R. Cytokine-induced sickness behavior: where do we stand?. Brain Behav Immun. 2001;15(1):7–24
    • View In Article
    • MEDLINE
    • CrossRef
28. McCarthy DO, Kluger MJ, Vander AJ. Suppression of food intake during infection: is interleukin-1 involved?. Am J Clin Nutr. 1985;42(6):1179–1182
    • View In Article
    • MEDLINE
29. Plata-Salaman CR. Brain mechanisms in cytokine-induced anorexia. Psychoneuroendocrinology. 1999;24(1):25–41
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (234 KB)
    • CrossRef
30. Escalante CP. Treatment of cancer-related fatigue: an update. Support Care Cancer. 2003;11(2):79–83
    • View In Article
    • MEDLINE
31. Escalante CP, Manzullo E, Valdres R. A cancer-related fatigue clinic: opportunities and challenges. J Natl Compr Canc Netw. 2003;1(3):333–343
    • View In Article