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Hodgkin's Disease Survivors More Fatigued Than the General Population

From the Department of Behavioral Sciences in Medicine, University of Oslo, Oslo; Palliative Medicine Unit, Department of Oncology and Radiotherapy, Trondheim University Hospital, Trondheim; The Norwegian Radium Hospital, Oslo; and Unit for Applied Clinical Research, The Norwegian University for Science and Technology, Trondheim, Norway.

Address reprint requests to Jon Håvard Loge, Department of Behavioral Sciences in Medicine, P.O. Box 1111 Blindern, N-0317 Oslo, Norway; Email j.h.loge{at}medisin.uio.no

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
PURPOSE: To estimate the level of fatigue and frequency of fatigue cases among Hodgkin's disease survivors (HDS) and compare them with normative data from the general population.

PATIENTS AND METHODS: A cross-sectional follow-up study was done of 557 HDS (age range, 19 to 74 years) treated at the Norwegian Radium Hospital from 1971 to 1991. The sample was approached by mail, and their data were compared with normative data from 2,214 controls (age range, 19 to 74 years) representative of the general Norwegian population. Of the 557 HDS, 459 (82%) responded. The mean age (± SD) at the time of study was 44 ± 12 years, and the mean observation time was 12 ± 6 years. The Fatigue Questionnaire (11 items) measures physical and mental fatigue. Two systems of scoring were used, dichotomized (0, 0, 1, and 1) and Likert (0, 1, 2, and 3). Total fatigue (TF) constitutes the sum of all the Likert scores. Caseness was defined as a total dichotomized score of 4 and fatigue that lasted 6 months or longer.

RESULTS: The HDS had significantly higher levels of TF than the controls (14.3 v 12.2) (P < .001). Fatigue among the HDS equaled that of the controls in poorest health. More HDS (61%) than controls (31%) reported fatigue symptoms lasting 6 months or longer (P < .001). Fatigue cases were more frequent among HDS (men, 24%; women, 27%) than among the controls (men, 9%; women, 12%) (P < .001). Disease stage/substage IB/IIB predicted fatigue caseness (P = .03). No significant associations were found between treatment characteristics and fatigue.

CONCLUSION: Hodgkin's disease survivors are considerably more fatigued than the general population and report fatigue of a substantially longer duration.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
FATIGUE IMPLIES A FEELING of tiredness, reduced energy level, reduced muscle strength, and cognitive impairments. Fatigue may strongly interfere with several aspects of daily life¹ and may therefore have a substantially negative impact on quality of life in general.^1,2

Operationalizing and measuring this subjective phenomenon has received renewed attention during the last 20 years. However, no specific medical tests exist, and one has to measure what the patients complain of, ie, subjectively experienced fatigue.³

Fatigue is prevalent in the general population, and prevalence estimates range from 11% to 45%.^4-6 The different estimates are related to how fatigue is measured and over what period of time.^5,6 Eleven percent of the general Norwegian population report substantial fatigue lasting 6 months or longer.⁵ In most cases, fatigue is transient and relieved by rest. Fatigue that lasts 6 months or longer is, by consensus, defined as chronic.⁶ Chronic fatigue is strongly associated with medical or psychiatric conditions.^7,8

Among cancer patients, fatigue has been cited as the most common symptom experienced by patients with "active disease," and prevalence estimates are 70% or higher.⁹ Fatigue can be a first symptom of a cancer, a symptom of active or terminal disease, or a side effect of treatment.¹⁰ It has been reported that more than 80% of cancer patients experience significant fatigue during chemotherapy.¹¹ Similar prevalence rates have been reported during radiotherapy.¹² Most of the patients will probably experience a reduction of fatigue symptoms after termination of treatment.¹³ However, systematic data on prevalence are insufficient,⁹ and most of the studies have methodologic weaknesses, such as lack of a control group, no control for possible confounding variables, and measures with limited reliability and validity.¹⁴

The mechanisms that produce fatigue in cancer patients are largely unknown.^9,10,14 Somatic factors that correlate with fatigue during active disease include pain, metabolic factors, nutrition status, immunologic factors, anemia, sleep disturbances, sedatives, and immobilization.^9,14

Fatigue may also be a symptom of depression and is one of the inclusion criteria for major depression in the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition.¹⁵ In general, the relative contributions of the physical and psychologic aspects of fatigue are debatable, and fatigue characteristics do not differentiate between fatigued patients with or without psychologic disorders.¹⁶ Although fatigue in the middle-aged general population is strongly associated with psychiatric morbidity,⁸ studies have identified excessive fatigue in patient populations, including cancer patients, without accompanying psychiatric morbidity.^13,17 Few studies have systematically explored the relationship between depression and fatigue among cancer patients, but a relationship between negative affect and fatigue has been reported.⁹ Therefore, in the absence of more specific tests, fatigue is at present best viewed as a multidetermined phenomenon in which both psychologic and biologic factors can contribute to the subjective experience.

Few studies have addressed persisting fatigue after cancer cure. In addition to two studies of posttreatment breast cancer patients,^18,19 four studies have reported significant fatigue symptoms among survivors of Hodgkin's disease (HD). Bloom et al²⁰ reported higher levels of fatigue and energy loss among male Hodgkin's disease survivors (HDS) than among survivors of testicular cancer. Devlen et al²¹ found frequent complaints about tiredness (32%), loss of energy (43%), poor concentration (15%), and memory impairment (19%) among 120 survivors of Hodgkin's disease and non-Hodgkin's lymphoma. Fobair et al²² also found persisting energy loss in 37% of 403 survivors of HD. Lacking a return of energy was associated with depression and difficulties at work.²² Joly et al²³ reported increased levels of fatigue in a French cohort of HDS.

None of the studies of fatigue among HDS used a validated and reliability-tested instrument specifically designed for measuring fatigue. Furthermore, the high prevalence of fatigue in the general population necessitates caution when interpreting the findings because only the study by Joly et al²³ took this into account. We therefore provided normative data from the general Norwegian population for comparison with the HDS.⁵

The main objectives of the present study were the following: (1) to estimate the level of fatigue and frequency of fatigue cases among HDS treated at the Norwegian Radium Hospital from 1971 to 1991, (2) to examine the relationship between fatigue among the HDS and disease/treatment characteristics, and (3) to compare fatigue among the HDS to normative data from the general Norwegian population.

	PATIENTS AND METHODS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Sampling
The study, approved by the Regional Committee for Ethics in Medical Research, included two samples: Hodgkin's disease survivors and general population controls. Before 1980, the Norwegian Radium Hospital (NRH) treated 92% of adult Norwegian HD patients aged 15 to 39 years, 80% of patients aged 40 to 59 years, and 53% of patients aged 60 years or older.²⁴ After 1980, four other centers gradually began to treat HD. Since 1985, all patients from a defined region constituting about one half of Norway's population have been admitted on the same criteria. Inclusion criteria in the present study were as follows: admittance to the NRH for a diagnosis of HD from 1971 to 1991, alive by the end of 1993, age 15 to 61 years at the time of diagnosis, and age 74 years or younger by the end of 1993. Patients who were 61 years or older at the time of diagnosis were excluded because of the selection to the hospital and the change in classification after around 1980. After 1980, an increasing number of older patients previously classified as having HD were classified as having non-Hodgkin's lymphoma.²⁴ A total of 557 HDS were approached in 1994.

In 1996, 3,500 Norwegian citizens (age range, 19 to 80 years) representative of the entire Norwegian population were randomly drawn from The National Register by the Norwegian Government Computer Center (Statens Datasentral).⁵ Subjects who were 74 years old or younger (n = 3,254) were considered eligible for study.

Both samples were mailed self-report questionnaires. The HDS also received several items on various aspects of quality of life not included in this article. In both samples, nonrespondents after the first mailing received one written reminder.

Measures
Fatigue Questionnaire. The Fatigue Questionnaire (FQ) (11 items) is intended to measure fatigue severity and to detect fatigue cases in clinical and epidemiologic studies.^8,17,25,26 The FQ asks about fatigue symptoms experienced during the last month compared with how the subject felt when she or he was last feeling well. Additionally, two items ask about the duration and extent of fatigue. Seven items cover physical fatigue (PF): Do you have problems with tiredness? Do you need to rest more? Do you feel sleepy or drowsy? Do you have problems starting things? Do you lack energy? Do you have less strength in your muscles? Do you feel weak? Four items cover mental fatigue (MF): Do you have difficulty concentrating? Do you make slips of the tongue when speaking? Do you find it more difficult to find the correct word? How is your memory? Each item has four response choices.²⁶ Each response was scored both on a Likert scale (0, 1, 2, 3) and a dichotomized scale (0, 0, 1, 1). The dichotomized scale was used only for case definition. The total sum of the Likert scores is designated total fatigue (TF). Higher scores imply more fatigue.

The FQ was originally validated in primary care and has good face and discriminant validity.²⁶ The two-dimensional structure (mental and physical fatigue) was confirmed in our norm study, and the two subscales correlated moderately (r = .46).⁵ Discriminant validity was further supported by the differences in TF between subjects in different health states.⁵ Cronbach's alphas were 0.73 (MF), 0.86 (PF), and 0.86 (TF),⁵ confirming the findings of the validation study.²⁶ By comparing the FQ to the fatigue question in the Revised Clinical Interview Schedule (CIS-R), a relative operating characteristic analysis suggested 4 or higher as the optimum cut-off for case definition (sensitivity, 76; specificity, 75).²⁶ Fatigue caseness was therefore defined by total dichotomized scores of 4 or higher and symptom duration of 6 months or longer.^6,26

The questionnaire received by the HDS also included the Hospital Anxiety and Depression Scale (HADS), which measures anxiety and depression in two separate subscales (seven items each).²⁷ Among the HDS, the HADS-anxiety and HADS-depression subscales had a correlation of 0.63. Total fatigue had a correlation of 0.44 and 0.49 with the HADS-anxiety and HADS-depression subscales, respectively. A principal component analysis followed by varimax rotation was performed and included all the items in the FQ and the HADS (not tabulated). Four factors were suggested (eigenvalues 1). These corresponded with the dimensions in the questionnaires, ie, anxiety, depression, physical fatigue, and mental fatigue. However, the HADS-depression item on retardation ("I feel as if I am slowed down") had its highest loading on physical fatigue (0.45). When this item was removed, the HADS-depression correlation with TF was 0.41. This strongly supports the divergent validity of the FQ among the HDS. In FQs with missing data in four or fewer items, the missing values were replaced with the means of the corresponding known variable values from each sample.

Diseases and health problems. Among the HDS, information on date of diagnosis, stage, histology, treatment, and current disease status (relapsed or not) was based on the hospital records, which were available through the tumor registry of the NRH.²⁸

The controls were asked about past and present health problems. One set of questions asked whether they had ever had any of the following specific diseases: hypertension, myocardial infarction, heart failure, cancer, and diabetes. Another set of questions asked whether they were suffering at present from any of the following medical conditions: chronic allergy, back pain, visual impairments, chronic skin problems, chronic lung problems, deafness or hearing problems, functional impairment in leg or arm, and other chronic health problems. On the basis of the responses to these items, the controls were divided into four groups as follows: group 1, no specific diseases or current medical conditions; group 2, specific diseases but no current medical conditions; group 3, current medical conditions but no specific diseases; and group 4, specific diseases and current medical conditions.⁵

By comparing the HDS with controls grouped by health state, we attempted to anchor the level of fatigue among the HDS to different health states in the general population. Such anchor-based interpretations are recommended for new quality of life measures because assessment of the clinical significance of differences then becomes possible.²⁹

Sociodemographic items. The data files from the NRH tumor registry and the national registry supported information on age and sex for the HDS and controls, respectively. Both samples were asked about their educational status and marital status.

Analysis
Statistical procedures included frequency tables, ² statistics (categorical variables), two-sided t tests (independent samples), and one-way analysis of variance when appropriate. The latter was performed using Scheffe's test for post hoc comparisons. We adjusted for the effect of age by entering age as a covariate in analyses of variance.

Multiple logistic regression with subjects' status (0 = HDS, 1 = controls) as the dependent variable was performed to test for differences in subjects' characteristics between the HDS and the controls. Analysis of variance with multiple classification analysis was performed to test for differences in PF, MF, and TF in relation to disease and treatment variables and to estimate the adjusted TF scores within these variables. Multiple logistic regression was performed to assess the effects upon fatigue caseness of predictors among the disease and treatment variables.

Multiple linear regressions were performed to test for the independent effect of survivorship (0 = normal controls, 1 = HDS) on TF adjusted for the effect of age, sex, and marital and educational status (the two latter variables were entered as dummy variables). The effect of survivorship on MF and PF was tested by multiple linear regressions and by adjusting for the effects of age, sex, and educational level. In the comparisons between HDS and controls grouped by health states, multiple linear regressions were used that adjusted for the effects of age, sex, and educational level. Hodgkin's disease survivors and each subsample of controls were compared in separate regressions.

The level of significance was set at P < .05. The data were analyzed using the SPSS for Windows version 6.1 software (SPSS, Inc., Chicago, IL).

Sample Characteristics
Four hundred fifty-nine HDS replied (response rate, 82%). Responders and nonresponders did not differ in age at the time of diagnosis, age at the time of the study, disease stage, type of treatment, or time from diagnosis. The response rate tended to be higher among the females (86%) than among the males (80%) (P = . 05).

Among the 3,254 normal controls aged 74 years or younger, 2,214 (68%) responded. More females (70%) than males (66%) responded (P = .02). The lowest response rates were found among the youngest men (29 years or younger) and the oldest women (60 years or older) (62% and 65%, respectively). Among the responders, 74% answered before the reminder. The late responders tended to be older (1.4 years). Late responding was more common among the men (27%) than among the women (24%). As described in the norm study, the late responders tended to be slightly more fatigued than the responders after the first mailing.⁵ The characteristics of the respondents are listed in Table 1.

The mean observation period (± SD) among the HDS was 12 ± 5.5 years. Stage I and II patients without risk factors for relapse had received irradiation alone. Since 1980, patients with risk factors for relapse have been treated with four cycles of chemotherapy before radiation. Before 1980, stage III patients received total nodal irradiation (mantle and inverted Y-field). After 1980, they received eight cycles of chemotherapy. Stage IV patients received eight cycles of chemotherapy. After chemotherapy, stage III and IV patients received irradiation to bulky or residual mass. Chlorambucil, vinblastine, procarbazine, and prednisone and mustine, vinblastine, procarbazine, and prednisone (the latter regimen was only given before 1980) were the most frequently administered chemotherapeutic regimens (38%). Mantle field irradiation was the most frequently administered type of irradiation (56%). Fifty-seven HDS had experienced a relapse, seven within the 2 years preceding the present study.

Differences in Subjects' Characteristics Between the Samples
The sex and age distributions, educational levels, and marital status differed between the two samples. Among the HDS, males were overrepresented, more were middle-aged, more had education at the lowest level, and fewer were living single. Since the latter two characteristics may have been accounted for by age and sex differences between the two samples, multiple logistic regression was performed with subject status (controls = 0, HDS = 1) as the dependent variable. After an adjustment for the effects of age and sex, marital status no longer predicted subject status. Educational level still differed between the two samples.

Data Quality
Among the HDS, 400 FQs were complete. An additional 42 questionnaires lacked responses in four or fewer items, thus yielding 442 questionnaires (96%) accessible for analysis. Incomplete questionnaires were related to higher age (43.0 years, complete, v 48.0 years, incomplete; t = 2.7; P = .007).

Among the controls, 2,095 FQs were complete, and after missing values were substituted, 2,186 questionnaires (99%) were accessible for analysis. The relationship between incomplete questionnaires and higher age has previously been demonstrated.⁵ In both samples, mean TF was unchanged after the missing values were replaced.

	RESULTS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Prevalence of Fatigue Among the HDS
The mean TF score (± SD) was 14.1 ± 4.6 among the males and 14.5 ± 4.7 among the females (NS) (Table 2). No difference in sex was found in regard to mental fatigue (MF-mean all, 4.9 ± 1.6) or physical fatigue (PF-mean all, 9.4 ± 4.6). Physical fatigue and mental fatigue correlated moderately (r = .55).

As presented in Table 2, subjects 60 years or older (PF-mean, 10.6 ± 3.6) had higher PF scores than subjects 29 years old or younger (PF-mean, 7.9 ± 3.0) (F = 4.07, P < .05). Total fatigue was highest among the oldest subjects (TF-mean, 15.6 ± 4.5) and was higher among the oldest subjects than among the youngest (TF-mean, 12.7 ± 4.3) (F = 2.62, P < .05). Mental fatigue did not differ significantly between the age groups.

Subjects with the lowest education level had the highest TF and PF scores (15.0 and 9.9, respectively). The lowest TF and PF scores were found among the best educated (13.5 and 8.7, respectively). The differences failed to reach statistical significance when adjustments were made for age.

Twenty-six percent of the survivors (n = 113) were fatigue cases, and cases were found most frequently among the oldest survivors (52% of the females and 39% of the males) and least frequently among the youngest survivors (12% of the males and 12.5% of the females) (² for trend = 13.43, df = 1, P < .001) (Table 2). The lowest proportion of cases was found among the best educated, but the proportion of cases in relation to educational level did not reach statistical significance (Table 2).

Fatigue and Disease/Treatment Characteristics
In the univariate analyses, neither years since diagnosis, disease severity (stage/substage), type of primary treatment, nor having relapsed were associated with statistically significant differences in MF, PF, or TF. Also, there were no differences in relation to type of irradiation, type of chemotherapy regimens, and number of chemotherapy cycles.

As shown in Table 3, neither stage/substage, type of primary treatment, having relapse, nor observational period was associated with significant differences in TF in a multivariate analysis of variance, adjusting for the effects of age, sex, and the other variables. None of these disease/treatment variables were associated with statistically significant differences in MF or PF after adjustment for age and sex. Age exerted a significant effect upon TF and PF (P = .003 and P < .001, respectively).

In the univariate analyses, the proportions of cases were not statistically significantly associated with stage/substage, type of primary treatment, having relapsed, or observational period (Table 3). A close to significant association was found in relation to disease severity. Forty percent of the subjects with stage IB/IIB were fatigue cases (P = . 05). Type of primary treatment, observational period, and having relapsed were not statistically significant predictors of caseness in a multiple logistic regression analysis, adjusting for age and sex. Age (odds ratio, 1.04; beta, 0.04; P < .001) and stage/substage IB/IIB (odds ratio, 2.3; beta, 0.82; P =. 03) (reference category: stage/substage IA/IIA) were the only statistically significant predictors.

Hodgkin's Disease Survivors Versus Normal Controls
The HDS had higher scores on TF (14.3 ± 4.9 v 12.2 ± 3.9), PF (9.4 ± 3.5 v 7.9 ± 3.1), and MF (4.9 ± 1.6 v 4.3 ± 1.4) than the controls (P < .001). When the samples were grouped by sex and age group, only among females aged 19 to 29 and 50 to 59 did the difference in TF between the HDS and the controls fail to reach statistical significance. The difference in TF ranged from 0.9 (subjects aged 19 to 29 years) to 2.6 (subjects aged 60 to 74 years).

In a multiple regression analysis (Table 4), subject status (0 = controls, 1 = HDS), age, and educational level were all significant predictors of TF, whereas marital status, sex, and the interaction of sex and subject status were not. Marital status was consequently not included in the subsequent analysis. After adjustment for age, sex, and educational level, subjects' status also significantly predicted MF (beta, 0.58; 95% confidence interval [CI], 0.4 to 0.7; P < .001) and PF (beta, 1.5; 95% CI, 1.2 to 1.8; P < .001).

The HDS and the controls reporting fatigue at any level were asked how long their fatigue had lasted. Whereas 33% (n = 494) of the controls reporting fatigue stated their fatigue had lasted for 1 week or less, only 10% (n = 24) of the HDS reporting fatigue stated fatigue duration of such length. In contrast, 61% of HDS (n = 155) and 31% of controls (n = 473) reporting fatigue stated their fatigue had lasted 6 months or longer (P < .001).

Fatigue cases were more frequent among HDS than among the controls (Table 5). Among the men, 24% (n = 60) of the HDS and 9% (n = 101) of the controls were fatigue cases (P < .001). Among the women, the proportion of fatigue cases among the HDS and controls was 27% (n = 53) and 12% (n = 135), respectively (P < .001).

As shown in Figure 1, the level of TF among the HDS was higher than among controls grouped by health state (four groups). In four separate multiple linear regressions with TF as the dependent variable and adjustments for the effect of age, sex, and educational level, the HDS group was compared with each of the four control groups (grouped by health state) (Table 6). The regression coefficients (with 95% CI) for the controls versus the HDS then ranged from 3.0 (95% CI, 2.6 to 3.5) (controls without specific diseases or current medical conditions) to 0.7 (95% CI, -0.05 to 1.4) (controls with specific diseases and current medical conditions). Except for the latter (P = .07), these were all statistically significant after correction of the significance level according to the Bonferroni method (0.05/4). Similar analysis of the two subscales (MF and PF) did not depart from this pattern.

View larger version (30K): [in this window] [in a new window]   Fig 1. Total fatigue in Hodgkin's disease survivors and controls in different health states by age group.

	DISCUSSION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Among HDS, late medical complications, such as secondary cancers, cardiopulmonary problems, infertility, and hypothyroidism, are well documented.³⁰ Late effects in subjective health are less well documented. The present study was inspired by clinical reports from HDS. They had consulted physicians and psychiatrists and felt rejected because no one could explain or treat their fatigue. Our results confirm that fatigue is highly prevalent among HDS.^20-23

The present sample of HDS is relatively large and unselected, and all the patients were treated at one institution according to standardized protocols. This yields excellent material for long-term follow-up studies. By comparing the HDS with normative data from the general Norwegian population,⁵ the level of fatigue among the HDS is anchored to the population as a whole. Our main findings imply a nearly 20% higher level of fatigue among HDS than in the general population, equaling the general population in poorest health. The HDS also report fatigue of longer duration than the general population, and the frequency of cases is more than doubled.

Norm-based interpretations answer questions of whether an observed score is (a)typical and make interpretations of clinical meaningfulness possible.²⁹ In the norm study, we found that the level of fatigue in the general population was affected by sex, age, and health state.⁵ No firm associations between fatigue and social variables were found.⁵ The normal controls were representative of the general Norwegian population.⁵

Still, the samples differed on some aspects that possibly affected the comparisons, although we statistically controlled for the differences in age and sex distributions and educational level. First, the response rates differed between the two samples. Among the HDS, the response rate was high and equal to³¹ or somewhat lower than that in previous Norwegian surveys of cancer survivors.³² The observation period in the latter study was considerably shorter (3 to 7 years). The response rate among the controls was similar to that in other recent general population surveys.^33,34 A volunteer bias among the controls could not be excluded among the subjects 60 years or older and especially not among women of that age.⁵ A possible volunteer bias among the oldest controls can enlarge the difference between the HDS and the controls of that particular age.⁵ However, there was only a small and insignificant difference in fatigue between the first and late responders among the normal controls.⁵ This indicates that the "true population values" are not substantially higher than the norms used in the present study.

Second, the data quality among the HDS was poorer than that among the controls. The HDS questionnaire was much more comprehensive than the questionnaire received by the controls, and the FQ was presented at the end. We think these two factors constitute the most probable explanation for the poorer data quality among the HDS. Imputing missing data in questionnaires with four or fewer missing values is a conservative approach, and careful imputation rather than deletion of entire cases is recommended because deletion introduces a bias.³⁵ The imputation did not affect the TF score, and without imputation, more of the oldest subjects would have been excluded from the analysis.

The definition of fatigue as chronic if it lasts for 6 months or longer is based on consensus.⁶ The cut-off (4 or higher) used in the definition of caseness was based on a comparison between the FQ and the question on fatigue in the CIS-R.²⁶ This assumes that the CIS-R is the gold standard and error-free, which is, of course, questionable. Consequently, the results regarding cases must be interpreted cautiously. The FQ, like other screening instruments, gives prevalence estimates of morbidity rather than accurate measures of disorders. Therefore, fatigue caseness is not synonymous with a diagnosis or a disorder but constitutes substantial fatigue of long duration. However, the case definition excludes transient fatigue, which is part of life. Fatigue after curative treatment for HD, therefore, seems to be chronic and stable because we found no effect of time since diagnosis. The fact that a higher proportion of the HDS (61%) than of the normal controls (31%) reported long-lasting fatigue also supports the chronic character of fatigue among the HDS.

Fatigue is a subjective experience, and measures of subjective health are not measures of pathology but independent outcome measures.²⁹ Still, the present study is limited by the uncertainty of what constitutes fatigue. Fatigue may be a symptom of depression,¹⁵ but fatigue has also been shown to increase during radiotherapy in breast cancer patients without an accompanying increase in depressive symptoms.¹³ Therefore, the strong association between fatigue and psychiatric conditions, notably depression, found in the middle-aged general population⁸ may therefore not hold in patient populations, despite the same subjective experience.¹⁶ In the present sample, the correlation between anxiety and depression was much higher than the correlation between fatigue and anxiety/depression. Other psychiatric conditions, such as somatoform disorders, may also be accompanied by fatigue. As suggested in relation to fatigue in general, a multifactorial etiology that includes the combined effects of physical, psychologic, and behavioral influences may provide a more convincing model for chronic fatigue among cancer survivors than models that imply single agents will cause single diseases.⁶ Thus, several factors may therefore contribute the to increased level of fatigue among the HDS. Correlates of persisting fatigue among cancer survivors have barely been addressed,⁹ and in our opinion, both biologic and psychologic correlates should be addressed.

The medical late complications of Hodgkin's disease and its treatment may arise from the tissue damage caused by chemotherapy or radiotherapy, from complications of surgery, or from the persisting immunologic deficits caused by the disease or the therapy.³⁰ Late medical complications, such as hypothyroidism, pericarditis, and pulmonary, are related to specific treatment regimens, ie, mantle field irradiation.^30,36 Except for the higher levels of fatigue and more cases among the stage IB/IIB subjects, we found no associations between disease/treatment characteristics and fatigue. Therefore, it is possible that aspects of the disease itself can be associated with fatigue after curative treatment. This is supported by the finding of higher levels of fatigue among HDS than among testicular cancer survivors.²⁰

To help interpret the clinical significance of our findings, we anchored the level of fatigue to different health states in the general population. The demonstration of functional consequences of fatigue upon the survivors' lives would further support the clinical significance. Fatigued HDS report difficulties at work²² and do so to a greater extent than survivors of testicular cancer do.²⁰ It has also been shown that activity patterns are changed after treatment of HD, and greater changes are found in relation to leisure activities than in relation to work.³⁷ Documentation of the functional consequences of chronic fatigue after curative treatment of HD is also important if rehabilitation programs are to be introduced.

The results of this study have several implications. For example, survivors may interpret fatigue as a possible symptom of disease relapse; therefore, information about the prevalence of fatigue is important. Given the impact fatigue may have on quality of life in general and the subjective burden associated with being fatigued, persisting fatigue among cancer survivors should be addressed in future research. Chronic fatigue is associated with disability at the same level as chronic medical conditions,¹ but the medical community tends to ignore medically unexplained physical symptoms.³⁸ Therapeutic interventions for such symptoms are available,³⁸ and both cognitive behavioral therapy³⁹ and aerobic exercise⁴⁰ may be effective.

	ACKNOWLEDGMENTS

 
We thank Professor Arnstein Finset, PhD, for assisting in the translation of the questionnaire and for helpful comments in the preparation of the manuscript. We also thank Kristin Vembe for producing Fig 1.

	REFERENCES

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
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Submitted April 1, 1998; accepted September 18, 1998.

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