Prevalence and Correlates of Fatigue in Long-Term Survivors of Childhood Leukemia
http://www.100md.com
《临床肿瘤学》
the Department of Preventive Medicine and USC/Norris Comprehensive Cancer Center, and the Department of Pediatrics Keck School of Medicine
Pharmaceutical Economics and Policy, School of Pharmacy, University of Southern California
Division of Hematology-Oncology, Childrens Hospital, Los Angeles, CA
ABSTRACT
PURPOSE: To estimate the prevalence of fatigue, identify the factors associated with fatigue, and to explore the relationship between fatigue and quality of life (QOL) in long-term survivors of childhood acute lymphoblastic leukemia (ALL).
METHODS: One hundred sixty-one ALL survivors diagnosed at Childrens Hospital Los Angeles (Los Angeles, CA) before age 18 years and between January 1, 1975 and December 31, 1995, participated in a structured telephone interview. Participants were aged 18 to 41 years and off treatment for an average of 14 years. Four measures of fatigue, including the Revised–Piper Fatigue Scale, were used to assess fatigue; depression was assessed using the Center for Epidemiological Studies Depression Scale. Multivariate logistic regression models were developed to identify factors associated with fatigue and depression.
RESULTS: Prevalence of fatigue (30%) fell within the general population normal limits. Fatigue and depression were highly correlated (Pearson r = 0.75). Fatigue was associated with marriage (OR = 0.11; 95% CI, 0.02 to 0.50), having children (OR = 5.80; 95% CI, 1.30 to 25.82), sleep disturbances (OR = 6.15; 95% CI, 2.33 to 16.22), pain (OR = 5.56; 95% CI, 2.13 to 14.48), obesity (OR = 3.80; 95% CI, 1.41 to 10.26), cognitive impairment (OR = 2.56; 95% CI, 1.02 to 6.38), and exercise-induced symptoms (OR = 2.98; 95% CI, 1.11 to 8.02). Four factors associated with fatigue were also associated with depression: sleep disturbances, pain, obesity, and cognitive impairment. Fatigue was inversely related to QOL.
CONCLUSION: Some survivors of childhood ALL experience fatigue many years after treatment. Fatigued survivors represent a high-risk subgroup as they report more depression and poorer QOL than nonfatigued survivors and their peers.
INTRODUCTION
As the number of long-term survivors of childhood cancer grows, attention is directed increasingly toward treatment-related sequelae and their effects on quality of life (QOL).1-3 Although a number of late complications such as second cancers, hormone deficiencies, cardiac abnormalities, and cognitive impairments are well documented, others, such as fatigue, have received limited attention.4
Fatigue is one of the most common and distressing symptoms experienced by cancer patients.5,6 While results have been mixed, some follow-up studies report a higher prevalence of fatigue among survivors of adult cancers than among the general population.7,8 Although the underlying mechanisms are poorly understood, such fatigue causes considerable distress, impairs function, and has a profoundly negative effect on QOL.9,10
The first in-depth study of fatigue in survivors of childhood cancer, published in 2003,11 used a heterogeneous sample of childhood cancer survivors and was limited in its exploration of disease-specific associations. Since late effects in pediatric oncology tend to be disease- and treatment-specific, we limited this study of fatigue to a single cancer diagnosis, acute lymphoblastic leukemia (ALL). The objectives of the study were to estimate the prevalence of fatigue, identify the correlates of fatigue, and examine the relationship between fatigue and QOL in long-term survivors of childhood ALL.
METHODS
Subjects
Eligible subjects were children diagnosed with ALL at Childrens Hospital Los Angeles (Los Angeles, CA) before age 18 years and between January 1, 1975 and December 31, 1995, who were disease-free, off treatment for a minimum of 1 year, English speaking, and at least 18 years old at the time of the study.
We mailed an invitation letter to 364 eligible subjects, followed by a telephone call. A consent form, postage-paid return envelope, and an answer booklet were mailed to those subjects who agreed to participate. One hundred sixty-one cancer survivors (44%) provided written consent and participated in a 30- to 45-minute structured telephone interview, during which we collected demographic information, assessed fatigue, QOL, and health status. During the interview, subjects used the answer booklet that listed all of the response choices for each set of fixed response questions. Interviews were administered by investigators experienced in conducting structured interviews. Training for this study included mock interviews, using the study's procedural protocol as a guide. Disease and treatment information, such as date of diagnosis, treatment protocol, dates and doses of radiation therapy, and date of last treatment were abstracted from subjects' medical records. Study procedures were approved by Childrens Hospital Los Angeles' institutional review board in accordance with assurances approved by the US Department of Health and Human Services.
Of the 203 nonparticipants, 119 were lost to follow-up, 29 initially agreed to participate but did not submit their consent form, 13 were unable to participate due to severe developmental delay/mental retardation, six found it too stressful to discuss their past illness, and 36 were not interested in participating.
Measures
We used four well-established questionnaires to measure fatigue: the Revised–Piper Fatigue Scale (R-PFS), Profile of Mood State fatigue inertia subscale (POMS), Rand SF-36 (SF-36) vitality subscale, and Symptom Distress Scale (SDS). The R-PFS was our primary outcome measure for fatigue.
The R-PFS12 provides a total fatigue score and measures four dimensions of subjective fatigue: behavior (disruption in daily activities); sensory (physical symptoms); cognitive/mood (mental and mood states); and affective/emotional (meaning attributed to fatigue). The R-PFS (22 items) is scored from 0-10 with higher scores indicating greater fatigue. We used a modified version of the R-PFS that asked survivors to rate their fatigue over the past 4 weeks rather than the past week. We used this extended reference period to minimize the effect of acute situational events (such as travel and school exams) and to enhance our assessment of the survivor's general state of fatigue. Similar modifications have been used in a study of postpolio patients.13 The R-PFS has demonstrated high reliability and validity with adult cancer patients.14-16
The RAND SF-3617 is a generic QOL measure (36 items) that measures perceived health status during the previous 4 weeks. The SF-36 assesses vitality (fatigue), physical functioning, bodily pain, role limitations due to physical and emotional health, mental health, social functioning, and general health during the past four weeks.18 Two summary scores are calculated to represent physical (PCS) and mental (MCS) functioning. The SF-36 is scored on a scale of 0-100, with higher scores representing higher levels of functioning and health. The vitality subscale (four items) is a single-dimension measure of fatigue. With breast cancer patients, the vitality subscale correlates highly with the Piper Fatigue Scale and discriminates between breast cancer survivors and women with benign breast problems.7 The reliability and validity of the SF-36 has been extensively tested.19,20
The Profile of Mood States fatigue-inertia subscale (seven items)21 measures weariness, inertia, and low energy level during the past week, with lower scores indicating greater fatigue.
The Symptom Distress Scale22 assesses current distress associated with cancer-related symptoms (fatigue, nausea, mood, appetite, insomnia, pain, mobility, bowel pattern, concentration, and appearance). Higher scores indicate greater distress.
The Center for Epidemiological Studies Depression Scale (CES-D; 20 items)23,24 measures symptoms of depression during the previous week. Scores higher than 15 indicate significant levels of depression. Subscales capture depressed affect, enervation, lack of positive affect, and interpersonal problems.25 The CES-D has demonstrated high internal consistency, adequate reliability, and good construct validity in both clinical and community samples.26,27
The Pittsburgh Sleep Quality Index (PSQI; 19 items)28 measures subjective sleep quality during the past month. A PSQI total score above five has a sensitivity and specificity greater than 87% in differentiating poor from good sleepers.28
In this study, the Cronbach alphas for the R-PFS, SF-36, POMS, SDS, CES-D, and PSQI were all greater than .75. The R-PFS was highly correlated with the SF-36 vitality subscale (r = –0.80), POMS (r = –0.85), and the SDS fatigue item (r = 0.71). These results demonstrate strong convergent validity and excellent internal reliability for the modified R-PFS used in this study.
We used the following question format to screen for late effects and comorbidites: "Have you ever been told by a doctor or other healthcare professional that you have or have had (specific health condition)? How old were you when you were first diagnosed with this condition? Are you currently taking prescription medication for this condition? Are any of your current activities limited by this condition? (no; yes, limited a little; yes, limited a lot)." Four questions were used to assess cognitive functioning: "Have you ever been diagnosed with a learning disability? In school were you ever in a learning disabled, special education, or resource program? Do you have difficulty concentrating at school/work? Do you have problems remembering things at school/work?" The last two questions were scored using a 0 (never) to 5 (all the time) scale.
Because most survivors in this study were treated on or according to Children's Cancer Group risk-adjusted protocols using established prognostic factors to assign patients to low, moderate, or high risk ALL categories,29-31 we used the child's treatment protocol assignment as a surrogate measure for treatment intensity. Relapsed patients were reclassified as high risk because of their exposure to additional treatment.
Statistical Analyses
Subjects with PSQI total scores 5 were classified as having sleep problems.28 Subjects with SF-36 pain scores lower than 72 (25th percentile score for the general population aged 25 to 34 years) were classified positive for pain.18 Body mass index was estimated using Quetelet's index (weight in kilograms divided by height in meters squared). Individuals with body mass index scores of 30 were categorized as obese.32 Survivors diagnosed with a learning disability and those who received special education placement or reported having concentration or memory problems "most of the time" were classified as cognitively impaired. We classified subjects with a Piper total fatigue score 4 as fatigued33 and those subjects with a CES-D score 16 as depressed.26
Standard statistical methods, including 2, t tests, Kappa statistics, and Pearson correlation coefficients were used to compare groups and estimate relationships between variables. Due to high collinearity between fatigue and depression, we assessed fatigue and depression separately in regression models. We fit univariate and multivariate unconditional logistic regression models, calculating odds ratios (OR) and corresponding 95% CI, to identify the correlates of fatigue and of depression.34 Tests of linear trend were calculated by fitting a variable representing ordinal categories of increasing exposure in the logistic models. We obtained a best-fitting multivariate logistic regression model, using a forward stepwise elimination procedure.
All P values presented are two-sided. Data analyses were conducted using SAS statistical software (Version 6.12; SAS Institute, Cary, NC).
RESULTS
Subjects
Participants were 18 to 41 years old (Table 1). Fifty percent of them were white and 40% were Hispanic. Eighty-two percent were working or attending school. Participants' average age at diagnosis was 7.4 years (range, 0 to 18 years) and their average time from end of therapy was 13.9 years (range, 4 to 23 years). Participants were more often female (2, P =.0001), older at diagnosis (P =.002), and off therapy for a shorter period of time (P =.02) than nonparticipants. Participants and nonparticipants did not differ significantly in current age, race, or their exposure to cranial irradiation.
Fatigue and Depression
Fatigue was the most frequently reported symptom (61%) on the SDS. Distress levels were higher for fatigue than for any other symptom. Survivors' average POMS fatigue-inertia score was 7.2 (standard deviation [SD], 6.3), which is within the normal range reported for college students.35 Survivors' SF-36 vitality mean score was 63.4 (SD, 23.2), which is slightly higher (more energy) than the norms for the general population (61.3; SD = 20.2).17
Average R-PFS scores are listed in Table 2. Forty-two percent of the survivors (n = 67) reported total scores 1.0 and only 6% (n = 10) reported scores 7.0. Forty-eight participants (30%) were classified as fatigued (total R-PFS score 4). Across all domains, R-PFS mean scores were significantly higher for the fatigued group than the nonfatigued group (all t test P values < .0001). There was a high correlation between R-PFS and the other measures of fatigue (SDS single fatigue item, r = 0.71; POMS, r = –0.85; SF-36 vitality subscale, r = –0.80).
Survivors' CES-D mean score was 12.6 (SD, 11.7) with 50 participants (31%) classified as depressed. In comparison, average scores for community samples range from 7.8 to 9.9 (SD, 7.5 to 9.3) with 20% classified as depressed.25 The average CES-D score for depressed survivors was 27.2, a value that falls within the 24 to 36 range reported for severely depressed populations.26,36
R-PFS total and CES-D scores were highly correlated (Pearson r = 0.75). The relationship between fatigue and depression remained strong, even when the enervation subscale items (n = 8) were removed from the CES-D scale (r = 0.74). Fatigued survivors were 33 times more likely to be depressed than nonfatigued survivors (OR = 32.9; 95% CI, 12.8 to 80.1). Thirty-eight (79%) of the 48 fatigued survivors were also classified as depressed (Kappa = 0.68; 95% CI, 0.55 to 0.80). Depressed survivors reported significantly higher fatigue levels than nondepressed survivors (all t test P < .0001).
Univariate Logistic Regression Analyses for Fatigue and Depression
Female sex, Hispanic ethnicity, having children, being unemployed, and not attending school were demographic factors associated with fatigue, whereas Hispanic ethnicity, being unemployed, not attending school, and working part-time were demographic factors associated with depression (Table 3). Subjects who relapsed were two and a half times more likely to be fatigued than those without a relapse. Results were similar for depression, although they did not achieve statistical significance. No other disease- or treatment-related factor was associated with fatigue or depression.
The number of late effects/medical conditions reported by a subject was highly associated with risk of fatigue and depression (Table 4). Cognitive problems, frequent headaches/migraines, history of seizures, obesity, cardiac problems, exercise-induced symptoms, thyroid abnormalities, sleep problems, and pain were each significantly associated with fatigue and depression. Gonadal failure, menopausal symptoms, and surgical procedures following cancer treatment were associated with fatigue but not with depression.
Multivariate Logistic Regression Models for Fatigue and Depression
We fit multivariate logistic regression models separately for demographic factors, disease and treatment factors, and late effects and comorbidities (data not shown). In the demographic model, factors associated with fatigue were not working or attending school, being married, and having children. Significant factors related to depression were Hispanic ethnicity, working part time, and not working or attending school. In the diagnosis/treatment models, relapse was associated with fatigue, whereas no factor was associated with depression. In the late effects and comorbidities models, neurocognitive impairments, obesity, sleep problems, and pain significantly increased survivors' risk of fatigue and depression.
The multivariate logistic regression models for fatigue and depression assessed all factors (demographic, disease and treatment, and late effects and comorbidities). The final (best fitting) fatigue model included two demographic and five late effects/medical comorbidity factors (Table 5). Having children, sleep problems, pain, obesity, cognitive problems, and exercise-induced symptoms increased fatigue risk whereas marriage decreased that risk. The final depression model included four of the above factors associated with fatigue: sleep problems, pain, obesity, and cognitive problems (Table 5). The final multivariate models for fatigue and depression did not include any disease or treatment factors.
Fatigue and QOL
The R-PFS mean scores were negatively correlated with SF-36 mean scores (all P < .0001). Figure 1 compares fatigued and nonfatigued survivors' SF-36 mean scores with published norms. Across all domains, fatigued survivor scores fell significantly below (poorer QOL) normative values (t test P < .0001). In contrast, nonfatigued survivor scores were significantly higher (better QOL) than the scores of their peers in vitality, role function–emotional, mental health, social functioning, and MCS.
Although the numbers are small, QOL scores were lowest for survivors who were both fatigued and depressed (n = 38) compared with those who were only fatigued (n = 10) and those who were only depressed (n = 12). With the summary scores, group differences were greater for MCS than PCS (fatigued and depressed v fatigued: MCS mean difference = –11.3, t test P < .005; PCS mean difference = –1.5, P > .10; fatigued and depressed v depressed: MCS mean difference = –15.5, P < .005; PCS mean difference = –4.9, P > .10).
DISCUSSION
The prevalence of fatigue (30%) among ALL survivors is similar to that reported for survivors of adult cancers (range, 17% to 30%)8,37-40 and the general population (range, 11% to 45%).41 Our results are also consistent with the other two published studies of fatigue in childhood cancer survivors. Zeltzer et al42 found with POMS that ALL survivors and sibling controls reported similar levels of fatigue; Langeveld et al11 also found no excess fatigue among childhood cancer survivors compared with healthy controls.
Fatigue and depression were closely related, with 79% of the fatigued survivors meeting the criteria for depression. While studies of adult cancer survivors report similar findings, with correlations between off-treatment fatigue and depression ranging from r = 0.32 to 0.68,7,43,44 the relationship was even stronger in our childhood cancer survivors (r = 0.75). This association between fatigue and depression remained strong even when the fatigue items were removed from the CES-D scale, demonstrating that this relationship is not driven completely by the cross over of fatigue/depression symptoms. This study's modeling of fatigue and depression as separate outcomes and the identification of common factors (sleep problems, pain, obesity, and cognitive problems) provide valuable information on the interrelationship of these constructs.
The relationship between fatigue and depression is complex. Fatigue is a recognized symptom of clinical depression,45 yet chronic fatigue can lead to depression.46 Recent studies suggest further that fatigue and depression may originate from the same underlying pathology, such as drug-induced neurotoxicities.47-51 This hypothesis may be relevant to our study because CNS late effects (late developing neurotoxicities), including functional (neuroendocrine abnormalities and cognitive impairments)52,53 and structural changes (cortical atrophy, mineralizing microangiography, and demyelination)54,55 are well documented in ALL survivors, especially those who received cranial irradiation. It has been proposed that a centrally mediated mechanism, such as neurotransmitter dysfunction following CNS prophylaxis, may play a role in the development of depression and fatigue.56
Developmental factors may also help to explain why the cross over of symptoms is greater among childhood cancer survivors than among survivors of adult cancers.57 Survivors in this study are young adults whose life goals include establishing families, professional careers, and financial security. If persistent cancer-related fatigue interferes with these goals, one might expect higher levels of despair than among survivors of adult cancers who have achieved such goals before becoming ill.
The clustering of fatigue, depression, pain, and sleep problems found in this study has been well documented in adult cancer populations.7,10,43,58-61 Pain, reported by 30% of the survivors, was positively associated with age (trend per year, OR = 1.10; 95% CI, 1.01 to 1.19) and unrelated to age at diagnosis, years from treatment, or treatment protocol. Although the majority of childhood cancer survivors experiences at least one cancer-related late effect,62,63 there is limited information on the survivors' experience with post-treatment pain. In a recent report from the Children's Cancer Survivor Study (CCSS), 8.6% of ALL survivors reported pain "as a result of their cancer and its treatment."63 Data on the specific source and nature of the pain were not collected in this CCSS study or in our study. Pain, its prevalence, etiology, and relationship to past therapy needs further evaluation in childhood cancer survivors. Clinical assessment of pain and its management must be incorporated in all long-term follow-up clinics.
Nearly 50% of the survivors reported sleep problems, whereas 15% to 35% of the general population reports such problems.64 Although many factors, including pain, depression, endocrine dysfunction, and post-traumatic stress can disrupt sleep, sleep quality among ALL survivors has never been systematically studied nor is it routinely assessed in follow-up clinics. This is another area of research that needs further development.
The three remaining factors associated with fatigue (obesity, exercise-induced symptoms, and cognitive impairment) are late effects that have been well described in ALL survivors. Our findings that 30% of the survivors were obese and that cranial irradiation increased the survivors' risk of obesity (OR = 2.11; 95% CI, 0.97 to 4.57) have been previously reported.63,65,66 Although the specific mechanisms underlying obesity in ALL survivors are unclear, it has been postulated that subtle growth hormone deficiencies secondary to cranial irradiation may alter body composition (decrease in muscle mass and increase in adipose tissue).67 Decreased energy expenditure during exercise and reduced levels of physical activity, documented in ALL survivors, is also thought to contribute to the development and maintenance of obesity.67-70 In one study, 42% of the children previously treated for ALL reported some degree of exercise intolerance.71
Twenty-six percent of our survivors reported "exercise-induced symptoms," defined as severe chest pain, palpitations, and shortness of breath with exercise. These symptoms were positively associated with total cumulative doses of anthracyclines (total anthracycline dose > 350 mg/m2 compared with those who received no anthracyclines; OR = 1.62; 95% CI, 0.95 to 2.75). Cardiomyopathy, ranging from minor ECG abnormalities to congestive heart failure, is associated with higher cumulative doses of anthracyclines and longer follow-up.71-74 Although exercise-induced symptoms reported in this study may represent sub-clinical cardiac abnormalities, this cannot be determined without a complete cardiac evaluation. Prior studies found that exercise intolerance, although common among ALL survivors, does not predict cardiac abnormalities.71
It is possible that exercise-induced symptoms and obesity may be related to physical inactivity. In the general population, inactivity doubles the risk of fatigue.75 As with fatigue and depression, the causal relationship is often unclear. Recent studies with adult cancer patients, however, provide strong evidence that increasing physical activity decreases fatigue and improves mood.76 Physical inactivity may represent one mechanism underlying fatigue in ALL survivors. Future studies should include its assessment and explore the value of physical activity as an intervention.
In this study, 39% of survivors reported some degree of impairment in cognition. Risk of impairment was greater for those who had received cranial irradiation (OR = 3.46; 95% CI, 1.64 to 7.30). Impairments in memory, attention, academic achievement, and intelligence have been documented in long-term ALL survivors, especially those treated with cranial irradiation.52,53
Directed attention requires mental effort. When demands exceed capacity, individuals tend to experience mental fatigue. Such fatigue further reduces capacity to pay attention or concentrate.77 Although cognitive fatigue has not been previously quantified in this population, neuropsychologists and schoolteachers have described a "fatigue effect" that interferes with school performance.78,79 In this study, survivors with cognitive impairments reported significantly more fatigue in the cognitive, affective, and behavioral domains than nonimpaired survivors. What role centrally mediated mechanisms may play in the development of fatigue and depression needs further exploration in these survivors who have received intensive CNS therapy during childhood.
Persistent fatigue following cancer treatment has a negative impact on QOL. The fatigued survivors' physical and mental health was significantly poorer than nonfatigued survivors and their peers. Their SF-36 summary scores indicate "substantial functional limitations, severe social and role disabilities, distress, and a very unfavorable evaluation of health status and outlook."80
While our final models for fatigue and depression were very similar, there was a significant decrease in QOL (mental health) among survivors who were both fatigued and depressed. This study's cross-sectional design limits our understanding of this relationship. In a longitudinal study, Bisser and Smets et al81 were able to document a different trajectory for fatigue and depression in adult cancer patients on treatment. In a randomized clinical trial with adult patients, investigators found that antidepressants improved depression but not fatigue.82 These types of studies need to be conducted with cancer survivors to better delineate the differences between fatigue and depression.
Our nonparticipation rate and lack of a control group are limitations of this study. The inclusion of age-matched control groups in future studies is necessary to understand how fatigue in cancer patients differs from fatigue in the general population. Such studies could determine if factors such as obesity and cognitive impairment, which are known to be associated with ALL and its treatment, play a larger role in fatigue among cancer survivors than in the general population. Lack of clinical validation of self-reported late effects/comorbidities is another limitation. Underreporting of late effects/comorbidities may have occurred due to poor recall or inadequate follow-up. Such underreporting, if equally distributed among fatigued and nonfatigued individuals, would reduce relative risk estimates toward the null value.
Fatigue, a symptom frequently overlooked by clinicians, appears to be a powerful predictor of poor QOL among survivors of childhood ALL. It is imperative that clinicians in long-term follow-up clinics screen survivors routinely for fatigue symptoms. A simple assessment can be obtained by asking the patient to rate his/her fatigue on a 0 to 10 numerical scale. Patients with a fatigue score of 4 or higher require further assessment.33 Our study indicates that these assessments should include areas such as pain, sleep, cardiac function, physical activity, weight, and cognition. Due to the strong relationship between fatigue and depression, survivors reporting persistent fatigue symptoms should receive a thorough psychological evaluation. Only when the underlying mechanisms of fatigue have been identified can appropriate interventions be implemented.
Authors' Disclosures of Potential Conflicts of Interest
The authors indicated no potential conflicts of interest.
Acknowledgment
We thank Irene Tham, Suzette Alvarez, and Heidi Mankowski for their research assistance and dedication to this project.
NOTES
Supported by Grant No. 5P30 CA 14089-25 from the National Cancer Institute, and by the Toys "" Us Children's Foundation.
Authors' disclosures of potential conflicts of interest are found at the end of this article.
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Pharmaceutical Economics and Policy, School of Pharmacy, University of Southern California
Division of Hematology-Oncology, Childrens Hospital, Los Angeles, CA
ABSTRACT
PURPOSE: To estimate the prevalence of fatigue, identify the factors associated with fatigue, and to explore the relationship between fatigue and quality of life (QOL) in long-term survivors of childhood acute lymphoblastic leukemia (ALL).
METHODS: One hundred sixty-one ALL survivors diagnosed at Childrens Hospital Los Angeles (Los Angeles, CA) before age 18 years and between January 1, 1975 and December 31, 1995, participated in a structured telephone interview. Participants were aged 18 to 41 years and off treatment for an average of 14 years. Four measures of fatigue, including the Revised–Piper Fatigue Scale, were used to assess fatigue; depression was assessed using the Center for Epidemiological Studies Depression Scale. Multivariate logistic regression models were developed to identify factors associated with fatigue and depression.
RESULTS: Prevalence of fatigue (30%) fell within the general population normal limits. Fatigue and depression were highly correlated (Pearson r = 0.75). Fatigue was associated with marriage (OR = 0.11; 95% CI, 0.02 to 0.50), having children (OR = 5.80; 95% CI, 1.30 to 25.82), sleep disturbances (OR = 6.15; 95% CI, 2.33 to 16.22), pain (OR = 5.56; 95% CI, 2.13 to 14.48), obesity (OR = 3.80; 95% CI, 1.41 to 10.26), cognitive impairment (OR = 2.56; 95% CI, 1.02 to 6.38), and exercise-induced symptoms (OR = 2.98; 95% CI, 1.11 to 8.02). Four factors associated with fatigue were also associated with depression: sleep disturbances, pain, obesity, and cognitive impairment. Fatigue was inversely related to QOL.
CONCLUSION: Some survivors of childhood ALL experience fatigue many years after treatment. Fatigued survivors represent a high-risk subgroup as they report more depression and poorer QOL than nonfatigued survivors and their peers.
INTRODUCTION
As the number of long-term survivors of childhood cancer grows, attention is directed increasingly toward treatment-related sequelae and their effects on quality of life (QOL).1-3 Although a number of late complications such as second cancers, hormone deficiencies, cardiac abnormalities, and cognitive impairments are well documented, others, such as fatigue, have received limited attention.4
Fatigue is one of the most common and distressing symptoms experienced by cancer patients.5,6 While results have been mixed, some follow-up studies report a higher prevalence of fatigue among survivors of adult cancers than among the general population.7,8 Although the underlying mechanisms are poorly understood, such fatigue causes considerable distress, impairs function, and has a profoundly negative effect on QOL.9,10
The first in-depth study of fatigue in survivors of childhood cancer, published in 2003,11 used a heterogeneous sample of childhood cancer survivors and was limited in its exploration of disease-specific associations. Since late effects in pediatric oncology tend to be disease- and treatment-specific, we limited this study of fatigue to a single cancer diagnosis, acute lymphoblastic leukemia (ALL). The objectives of the study were to estimate the prevalence of fatigue, identify the correlates of fatigue, and examine the relationship between fatigue and QOL in long-term survivors of childhood ALL.
METHODS
Subjects
Eligible subjects were children diagnosed with ALL at Childrens Hospital Los Angeles (Los Angeles, CA) before age 18 years and between January 1, 1975 and December 31, 1995, who were disease-free, off treatment for a minimum of 1 year, English speaking, and at least 18 years old at the time of the study.
We mailed an invitation letter to 364 eligible subjects, followed by a telephone call. A consent form, postage-paid return envelope, and an answer booklet were mailed to those subjects who agreed to participate. One hundred sixty-one cancer survivors (44%) provided written consent and participated in a 30- to 45-minute structured telephone interview, during which we collected demographic information, assessed fatigue, QOL, and health status. During the interview, subjects used the answer booklet that listed all of the response choices for each set of fixed response questions. Interviews were administered by investigators experienced in conducting structured interviews. Training for this study included mock interviews, using the study's procedural protocol as a guide. Disease and treatment information, such as date of diagnosis, treatment protocol, dates and doses of radiation therapy, and date of last treatment were abstracted from subjects' medical records. Study procedures were approved by Childrens Hospital Los Angeles' institutional review board in accordance with assurances approved by the US Department of Health and Human Services.
Of the 203 nonparticipants, 119 were lost to follow-up, 29 initially agreed to participate but did not submit their consent form, 13 were unable to participate due to severe developmental delay/mental retardation, six found it too stressful to discuss their past illness, and 36 were not interested in participating.
Measures
We used four well-established questionnaires to measure fatigue: the Revised–Piper Fatigue Scale (R-PFS), Profile of Mood State fatigue inertia subscale (POMS), Rand SF-36 (SF-36) vitality subscale, and Symptom Distress Scale (SDS). The R-PFS was our primary outcome measure for fatigue.
The R-PFS12 provides a total fatigue score and measures four dimensions of subjective fatigue: behavior (disruption in daily activities); sensory (physical symptoms); cognitive/mood (mental and mood states); and affective/emotional (meaning attributed to fatigue). The R-PFS (22 items) is scored from 0-10 with higher scores indicating greater fatigue. We used a modified version of the R-PFS that asked survivors to rate their fatigue over the past 4 weeks rather than the past week. We used this extended reference period to minimize the effect of acute situational events (such as travel and school exams) and to enhance our assessment of the survivor's general state of fatigue. Similar modifications have been used in a study of postpolio patients.13 The R-PFS has demonstrated high reliability and validity with adult cancer patients.14-16
The RAND SF-3617 is a generic QOL measure (36 items) that measures perceived health status during the previous 4 weeks. The SF-36 assesses vitality (fatigue), physical functioning, bodily pain, role limitations due to physical and emotional health, mental health, social functioning, and general health during the past four weeks.18 Two summary scores are calculated to represent physical (PCS) and mental (MCS) functioning. The SF-36 is scored on a scale of 0-100, with higher scores representing higher levels of functioning and health. The vitality subscale (four items) is a single-dimension measure of fatigue. With breast cancer patients, the vitality subscale correlates highly with the Piper Fatigue Scale and discriminates between breast cancer survivors and women with benign breast problems.7 The reliability and validity of the SF-36 has been extensively tested.19,20
The Profile of Mood States fatigue-inertia subscale (seven items)21 measures weariness, inertia, and low energy level during the past week, with lower scores indicating greater fatigue.
The Symptom Distress Scale22 assesses current distress associated with cancer-related symptoms (fatigue, nausea, mood, appetite, insomnia, pain, mobility, bowel pattern, concentration, and appearance). Higher scores indicate greater distress.
The Center for Epidemiological Studies Depression Scale (CES-D; 20 items)23,24 measures symptoms of depression during the previous week. Scores higher than 15 indicate significant levels of depression. Subscales capture depressed affect, enervation, lack of positive affect, and interpersonal problems.25 The CES-D has demonstrated high internal consistency, adequate reliability, and good construct validity in both clinical and community samples.26,27
The Pittsburgh Sleep Quality Index (PSQI; 19 items)28 measures subjective sleep quality during the past month. A PSQI total score above five has a sensitivity and specificity greater than 87% in differentiating poor from good sleepers.28
In this study, the Cronbach alphas for the R-PFS, SF-36, POMS, SDS, CES-D, and PSQI were all greater than .75. The R-PFS was highly correlated with the SF-36 vitality subscale (r = –0.80), POMS (r = –0.85), and the SDS fatigue item (r = 0.71). These results demonstrate strong convergent validity and excellent internal reliability for the modified R-PFS used in this study.
We used the following question format to screen for late effects and comorbidites: "Have you ever been told by a doctor or other healthcare professional that you have or have had (specific health condition)? How old were you when you were first diagnosed with this condition? Are you currently taking prescription medication for this condition? Are any of your current activities limited by this condition? (no; yes, limited a little; yes, limited a lot)." Four questions were used to assess cognitive functioning: "Have you ever been diagnosed with a learning disability? In school were you ever in a learning disabled, special education, or resource program? Do you have difficulty concentrating at school/work? Do you have problems remembering things at school/work?" The last two questions were scored using a 0 (never) to 5 (all the time) scale.
Because most survivors in this study were treated on or according to Children's Cancer Group risk-adjusted protocols using established prognostic factors to assign patients to low, moderate, or high risk ALL categories,29-31 we used the child's treatment protocol assignment as a surrogate measure for treatment intensity. Relapsed patients were reclassified as high risk because of their exposure to additional treatment.
Statistical Analyses
Subjects with PSQI total scores 5 were classified as having sleep problems.28 Subjects with SF-36 pain scores lower than 72 (25th percentile score for the general population aged 25 to 34 years) were classified positive for pain.18 Body mass index was estimated using Quetelet's index (weight in kilograms divided by height in meters squared). Individuals with body mass index scores of 30 were categorized as obese.32 Survivors diagnosed with a learning disability and those who received special education placement or reported having concentration or memory problems "most of the time" were classified as cognitively impaired. We classified subjects with a Piper total fatigue score 4 as fatigued33 and those subjects with a CES-D score 16 as depressed.26
Standard statistical methods, including 2, t tests, Kappa statistics, and Pearson correlation coefficients were used to compare groups and estimate relationships between variables. Due to high collinearity between fatigue and depression, we assessed fatigue and depression separately in regression models. We fit univariate and multivariate unconditional logistic regression models, calculating odds ratios (OR) and corresponding 95% CI, to identify the correlates of fatigue and of depression.34 Tests of linear trend were calculated by fitting a variable representing ordinal categories of increasing exposure in the logistic models. We obtained a best-fitting multivariate logistic regression model, using a forward stepwise elimination procedure.
All P values presented are two-sided. Data analyses were conducted using SAS statistical software (Version 6.12; SAS Institute, Cary, NC).
RESULTS
Subjects
Participants were 18 to 41 years old (Table 1). Fifty percent of them were white and 40% were Hispanic. Eighty-two percent were working or attending school. Participants' average age at diagnosis was 7.4 years (range, 0 to 18 years) and their average time from end of therapy was 13.9 years (range, 4 to 23 years). Participants were more often female (2, P =.0001), older at diagnosis (P =.002), and off therapy for a shorter period of time (P =.02) than nonparticipants. Participants and nonparticipants did not differ significantly in current age, race, or their exposure to cranial irradiation.
Fatigue and Depression
Fatigue was the most frequently reported symptom (61%) on the SDS. Distress levels were higher for fatigue than for any other symptom. Survivors' average POMS fatigue-inertia score was 7.2 (standard deviation [SD], 6.3), which is within the normal range reported for college students.35 Survivors' SF-36 vitality mean score was 63.4 (SD, 23.2), which is slightly higher (more energy) than the norms for the general population (61.3; SD = 20.2).17
Average R-PFS scores are listed in Table 2. Forty-two percent of the survivors (n = 67) reported total scores 1.0 and only 6% (n = 10) reported scores 7.0. Forty-eight participants (30%) were classified as fatigued (total R-PFS score 4). Across all domains, R-PFS mean scores were significantly higher for the fatigued group than the nonfatigued group (all t test P values < .0001). There was a high correlation between R-PFS and the other measures of fatigue (SDS single fatigue item, r = 0.71; POMS, r = –0.85; SF-36 vitality subscale, r = –0.80).
Survivors' CES-D mean score was 12.6 (SD, 11.7) with 50 participants (31%) classified as depressed. In comparison, average scores for community samples range from 7.8 to 9.9 (SD, 7.5 to 9.3) with 20% classified as depressed.25 The average CES-D score for depressed survivors was 27.2, a value that falls within the 24 to 36 range reported for severely depressed populations.26,36
R-PFS total and CES-D scores were highly correlated (Pearson r = 0.75). The relationship between fatigue and depression remained strong, even when the enervation subscale items (n = 8) were removed from the CES-D scale (r = 0.74). Fatigued survivors were 33 times more likely to be depressed than nonfatigued survivors (OR = 32.9; 95% CI, 12.8 to 80.1). Thirty-eight (79%) of the 48 fatigued survivors were also classified as depressed (Kappa = 0.68; 95% CI, 0.55 to 0.80). Depressed survivors reported significantly higher fatigue levels than nondepressed survivors (all t test P < .0001).
Univariate Logistic Regression Analyses for Fatigue and Depression
Female sex, Hispanic ethnicity, having children, being unemployed, and not attending school were demographic factors associated with fatigue, whereas Hispanic ethnicity, being unemployed, not attending school, and working part-time were demographic factors associated with depression (Table 3). Subjects who relapsed were two and a half times more likely to be fatigued than those without a relapse. Results were similar for depression, although they did not achieve statistical significance. No other disease- or treatment-related factor was associated with fatigue or depression.
The number of late effects/medical conditions reported by a subject was highly associated with risk of fatigue and depression (Table 4). Cognitive problems, frequent headaches/migraines, history of seizures, obesity, cardiac problems, exercise-induced symptoms, thyroid abnormalities, sleep problems, and pain were each significantly associated with fatigue and depression. Gonadal failure, menopausal symptoms, and surgical procedures following cancer treatment were associated with fatigue but not with depression.
Multivariate Logistic Regression Models for Fatigue and Depression
We fit multivariate logistic regression models separately for demographic factors, disease and treatment factors, and late effects and comorbidities (data not shown). In the demographic model, factors associated with fatigue were not working or attending school, being married, and having children. Significant factors related to depression were Hispanic ethnicity, working part time, and not working or attending school. In the diagnosis/treatment models, relapse was associated with fatigue, whereas no factor was associated with depression. In the late effects and comorbidities models, neurocognitive impairments, obesity, sleep problems, and pain significantly increased survivors' risk of fatigue and depression.
The multivariate logistic regression models for fatigue and depression assessed all factors (demographic, disease and treatment, and late effects and comorbidities). The final (best fitting) fatigue model included two demographic and five late effects/medical comorbidity factors (Table 5). Having children, sleep problems, pain, obesity, cognitive problems, and exercise-induced symptoms increased fatigue risk whereas marriage decreased that risk. The final depression model included four of the above factors associated with fatigue: sleep problems, pain, obesity, and cognitive problems (Table 5). The final multivariate models for fatigue and depression did not include any disease or treatment factors.
Fatigue and QOL
The R-PFS mean scores were negatively correlated with SF-36 mean scores (all P < .0001). Figure 1 compares fatigued and nonfatigued survivors' SF-36 mean scores with published norms. Across all domains, fatigued survivor scores fell significantly below (poorer QOL) normative values (t test P < .0001). In contrast, nonfatigued survivor scores were significantly higher (better QOL) than the scores of their peers in vitality, role function–emotional, mental health, social functioning, and MCS.
Although the numbers are small, QOL scores were lowest for survivors who were both fatigued and depressed (n = 38) compared with those who were only fatigued (n = 10) and those who were only depressed (n = 12). With the summary scores, group differences were greater for MCS than PCS (fatigued and depressed v fatigued: MCS mean difference = –11.3, t test P < .005; PCS mean difference = –1.5, P > .10; fatigued and depressed v depressed: MCS mean difference = –15.5, P < .005; PCS mean difference = –4.9, P > .10).
DISCUSSION
The prevalence of fatigue (30%) among ALL survivors is similar to that reported for survivors of adult cancers (range, 17% to 30%)8,37-40 and the general population (range, 11% to 45%).41 Our results are also consistent with the other two published studies of fatigue in childhood cancer survivors. Zeltzer et al42 found with POMS that ALL survivors and sibling controls reported similar levels of fatigue; Langeveld et al11 also found no excess fatigue among childhood cancer survivors compared with healthy controls.
Fatigue and depression were closely related, with 79% of the fatigued survivors meeting the criteria for depression. While studies of adult cancer survivors report similar findings, with correlations between off-treatment fatigue and depression ranging from r = 0.32 to 0.68,7,43,44 the relationship was even stronger in our childhood cancer survivors (r = 0.75). This association between fatigue and depression remained strong even when the fatigue items were removed from the CES-D scale, demonstrating that this relationship is not driven completely by the cross over of fatigue/depression symptoms. This study's modeling of fatigue and depression as separate outcomes and the identification of common factors (sleep problems, pain, obesity, and cognitive problems) provide valuable information on the interrelationship of these constructs.
The relationship between fatigue and depression is complex. Fatigue is a recognized symptom of clinical depression,45 yet chronic fatigue can lead to depression.46 Recent studies suggest further that fatigue and depression may originate from the same underlying pathology, such as drug-induced neurotoxicities.47-51 This hypothesis may be relevant to our study because CNS late effects (late developing neurotoxicities), including functional (neuroendocrine abnormalities and cognitive impairments)52,53 and structural changes (cortical atrophy, mineralizing microangiography, and demyelination)54,55 are well documented in ALL survivors, especially those who received cranial irradiation. It has been proposed that a centrally mediated mechanism, such as neurotransmitter dysfunction following CNS prophylaxis, may play a role in the development of depression and fatigue.56
Developmental factors may also help to explain why the cross over of symptoms is greater among childhood cancer survivors than among survivors of adult cancers.57 Survivors in this study are young adults whose life goals include establishing families, professional careers, and financial security. If persistent cancer-related fatigue interferes with these goals, one might expect higher levels of despair than among survivors of adult cancers who have achieved such goals before becoming ill.
The clustering of fatigue, depression, pain, and sleep problems found in this study has been well documented in adult cancer populations.7,10,43,58-61 Pain, reported by 30% of the survivors, was positively associated with age (trend per year, OR = 1.10; 95% CI, 1.01 to 1.19) and unrelated to age at diagnosis, years from treatment, or treatment protocol. Although the majority of childhood cancer survivors experiences at least one cancer-related late effect,62,63 there is limited information on the survivors' experience with post-treatment pain. In a recent report from the Children's Cancer Survivor Study (CCSS), 8.6% of ALL survivors reported pain "as a result of their cancer and its treatment."63 Data on the specific source and nature of the pain were not collected in this CCSS study or in our study. Pain, its prevalence, etiology, and relationship to past therapy needs further evaluation in childhood cancer survivors. Clinical assessment of pain and its management must be incorporated in all long-term follow-up clinics.
Nearly 50% of the survivors reported sleep problems, whereas 15% to 35% of the general population reports such problems.64 Although many factors, including pain, depression, endocrine dysfunction, and post-traumatic stress can disrupt sleep, sleep quality among ALL survivors has never been systematically studied nor is it routinely assessed in follow-up clinics. This is another area of research that needs further development.
The three remaining factors associated with fatigue (obesity, exercise-induced symptoms, and cognitive impairment) are late effects that have been well described in ALL survivors. Our findings that 30% of the survivors were obese and that cranial irradiation increased the survivors' risk of obesity (OR = 2.11; 95% CI, 0.97 to 4.57) have been previously reported.63,65,66 Although the specific mechanisms underlying obesity in ALL survivors are unclear, it has been postulated that subtle growth hormone deficiencies secondary to cranial irradiation may alter body composition (decrease in muscle mass and increase in adipose tissue).67 Decreased energy expenditure during exercise and reduced levels of physical activity, documented in ALL survivors, is also thought to contribute to the development and maintenance of obesity.67-70 In one study, 42% of the children previously treated for ALL reported some degree of exercise intolerance.71
Twenty-six percent of our survivors reported "exercise-induced symptoms," defined as severe chest pain, palpitations, and shortness of breath with exercise. These symptoms were positively associated with total cumulative doses of anthracyclines (total anthracycline dose > 350 mg/m2 compared with those who received no anthracyclines; OR = 1.62; 95% CI, 0.95 to 2.75). Cardiomyopathy, ranging from minor ECG abnormalities to congestive heart failure, is associated with higher cumulative doses of anthracyclines and longer follow-up.71-74 Although exercise-induced symptoms reported in this study may represent sub-clinical cardiac abnormalities, this cannot be determined without a complete cardiac evaluation. Prior studies found that exercise intolerance, although common among ALL survivors, does not predict cardiac abnormalities.71
It is possible that exercise-induced symptoms and obesity may be related to physical inactivity. In the general population, inactivity doubles the risk of fatigue.75 As with fatigue and depression, the causal relationship is often unclear. Recent studies with adult cancer patients, however, provide strong evidence that increasing physical activity decreases fatigue and improves mood.76 Physical inactivity may represent one mechanism underlying fatigue in ALL survivors. Future studies should include its assessment and explore the value of physical activity as an intervention.
In this study, 39% of survivors reported some degree of impairment in cognition. Risk of impairment was greater for those who had received cranial irradiation (OR = 3.46; 95% CI, 1.64 to 7.30). Impairments in memory, attention, academic achievement, and intelligence have been documented in long-term ALL survivors, especially those treated with cranial irradiation.52,53
Directed attention requires mental effort. When demands exceed capacity, individuals tend to experience mental fatigue. Such fatigue further reduces capacity to pay attention or concentrate.77 Although cognitive fatigue has not been previously quantified in this population, neuropsychologists and schoolteachers have described a "fatigue effect" that interferes with school performance.78,79 In this study, survivors with cognitive impairments reported significantly more fatigue in the cognitive, affective, and behavioral domains than nonimpaired survivors. What role centrally mediated mechanisms may play in the development of fatigue and depression needs further exploration in these survivors who have received intensive CNS therapy during childhood.
Persistent fatigue following cancer treatment has a negative impact on QOL. The fatigued survivors' physical and mental health was significantly poorer than nonfatigued survivors and their peers. Their SF-36 summary scores indicate "substantial functional limitations, severe social and role disabilities, distress, and a very unfavorable evaluation of health status and outlook."80
While our final models for fatigue and depression were very similar, there was a significant decrease in QOL (mental health) among survivors who were both fatigued and depressed. This study's cross-sectional design limits our understanding of this relationship. In a longitudinal study, Bisser and Smets et al81 were able to document a different trajectory for fatigue and depression in adult cancer patients on treatment. In a randomized clinical trial with adult patients, investigators found that antidepressants improved depression but not fatigue.82 These types of studies need to be conducted with cancer survivors to better delineate the differences between fatigue and depression.
Our nonparticipation rate and lack of a control group are limitations of this study. The inclusion of age-matched control groups in future studies is necessary to understand how fatigue in cancer patients differs from fatigue in the general population. Such studies could determine if factors such as obesity and cognitive impairment, which are known to be associated with ALL and its treatment, play a larger role in fatigue among cancer survivors than in the general population. Lack of clinical validation of self-reported late effects/comorbidities is another limitation. Underreporting of late effects/comorbidities may have occurred due to poor recall or inadequate follow-up. Such underreporting, if equally distributed among fatigued and nonfatigued individuals, would reduce relative risk estimates toward the null value.
Fatigue, a symptom frequently overlooked by clinicians, appears to be a powerful predictor of poor QOL among survivors of childhood ALL. It is imperative that clinicians in long-term follow-up clinics screen survivors routinely for fatigue symptoms. A simple assessment can be obtained by asking the patient to rate his/her fatigue on a 0 to 10 numerical scale. Patients with a fatigue score of 4 or higher require further assessment.33 Our study indicates that these assessments should include areas such as pain, sleep, cardiac function, physical activity, weight, and cognition. Due to the strong relationship between fatigue and depression, survivors reporting persistent fatigue symptoms should receive a thorough psychological evaluation. Only when the underlying mechanisms of fatigue have been identified can appropriate interventions be implemented.
Authors' Disclosures of Potential Conflicts of Interest
The authors indicated no potential conflicts of interest.
Acknowledgment
We thank Irene Tham, Suzette Alvarez, and Heidi Mankowski for their research assistance and dedication to this project.
NOTES
Supported by Grant No. 5P30 CA 14089-25 from the National Cancer Institute, and by the Toys "" Us Children's Foundation.
Authors' disclosures of potential conflicts of interest are found at the end of this article.
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