Age-Associated Differences in Fatigue Among Patients with Cancer

Vol. 40 No. 2 August 2010 Journal of Pain and Symptom Management 217 Original Article Age-Associated Differences in Fatigue Among Patients with Cancer Zeeshan Butt, PhD, Arati V. Rao, MD, Jin-Shei Lai, PhD, Amy P. Abernethy, MD, Sarah K. Rosenbloom, PhD, and David Cella, PhD Department of Medical Social Sciences (Z.B., J.-S.L., S.K.R., D.C.), Comprehensive Transplant Center (Z.B.), Institute for Healthcare Studies (Z.B., J.-S.L., D.C.), Department of Pediatrics (J.-S.L.), and Department of Psychiatry and Behavioral Sciences (S.K.R., D.C.), Northwestern University Feinberg School of Medicine, Chicago, Illinois; and Division of Medical Oncology (A.V.R., A.P.A.), Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA Abstract Context. There has been some suggestion that the fatigue experienced by older cancer patients is more severe than that of younger cohorts; however, there is little empirical evidence to support this claim. Objectives. The goal of the present study was to determine the differential impact of age and cancer diagnosis on ratings of fatigue using a validated selfreport instrument. Methods. The Functional Assessment of Chronic Illness Therapy-Fatigue subscale consists of 13 items measuring fatigue experience and its impact on daily life, with scores ranging from 0 (severe fatigue) to 52 (no fatigue). Fatigue data were available from the U.S. general population (n ¼ 1075; 51.3% female, 45.9 16.5 years) and a sample of mixed-diagnosis cancer patients (n ¼ 738; 64.3% female, 58.7 13.6 years). General population participants were recruited using an Internet-based survey panel; patients with cancer were recruited from Chicago-area oncology clinics. Results. On average, the cancer patient group reported more severe fatigue than the general population group (36.9 vs. 46.6; F[1,1797] ¼ 271.95, P < 0.001). There was evidence for increased fatigue with age (F[6,719] ¼ 2.56, P < 0.02) among patients with cancer, but not in the general population (P ¼ 0.06). Furthermore, the group age interaction was not significant (P ¼ 0.44). Hemoglobin (Hgb) was treated as a covariate for 430 patients with available data; there was no main effect for age in this analysis. Portions of these findings were presented at the 2008 meeting of the Society for Behavioral Medicine. Funding source: A subset of the data analyzed for this study was collected as part of National Institutes of Health (NIH) R01 CA60068 (Principal Investigator: David Cella, PhD). Manuscript preparation supported in part by grant UL1RR025741 from the National Center for Research Resources, NIH. Disclosures: Dr. Butt has received grant support from and served as a consultant for Ortho Biotech Ó 2010 U.S. Cancer Pain Relief Committee Published by Elsevier Inc. All rights reserved. and has served as a consultant for Johnson & Johnson. Dr. Cella has received grant support from Ortho Biotech. The other authors have no disclosures. Address correspondence to: Zeeshan Butt, PhD, Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, 750 N. Lake Shore Drive, 10th Floor, Chicago, IL 60611, USA. E-mail: z-butt@northwestern.edu Accepted for publication: January 19, 2010. 0885-3924/$esee front matter doi:10.1016/j.jpainsymman.2009.12.016

218 Butt et al. Vol. 40 No. 2 August 2010 Conclusion. Older adults, whether they had a cancer diagnosis, reported more fatigue than younger adults. These differences may be explained, in part, by Hgb level. Future research would be helpful to explore longitudinal changes in fatigue in the general population and guide fatigue management for the older cancer patient. J Pain Symptom Manage 2010;40:217e223. Ó 2010 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved. Key Words Fatigue, cancer, assessment, patient-reported outcome, hemoglobin Introduction Fatigue is the most prevalent symptom among individuals with cancer and may be because of the disease itself, its treatment, and/ or psychosocial variables. 1 Depending on the patient population and means of measuring fatigue, prevalence estimates among cancer patients are generally high, ranging from 60% to more than 90%. 1 Furthermore, in a large sample of patients with advanced cancer who have received chemotherapy, fatigue was spontaneously endorsed and ranked as the most important symptom that should be monitored. 2 Although common, cancer-related fatigue (CRF) remains poorly understood. 3 Patients may describe their experience of fatigue in terms of being exhausted, tired, weak, or slowed. In clinical practice, fatigue may be neglected or underdetected because of the fact that it is a subjective experience that is assessed by patient self-report. Treatment of CRF is further complicated by its multifactorial clinical manifestations, involving both psychological and physical components. One common cause of fatigue in the context of cancer is anemia. The decrease in hemoglobin (Hgb) leads to patient weakness, pallor, dyspnea, and fatigue. Given their nonspecific nature, symptoms of anemia are often difficult to attribute directly to anemia itself. However, the impact of low Hgb can be far reaching. 4,5 Important heath-related outcomes such as quality of life (QOL) can be enhanced with proper evaluation and treatment of fatigue and other anemia-related symptoms, 6 especially for the older adult. 7 There has been some suggestion that the fatigue experienced by older cancer patients is more severe than that of younger cohorts; however, there is little empirical evidence to support this claim. This is especially relevant in the case of the elderly, who may be more likely to consider fatigue as a normal part of the disease course with which they must suffer. In fact, our group has found no effect of age on CRF, when comparing patients older than 50 with those younger. 3 That said, few data are available to guide the assessment and treatment of CRF in older cancer patients. This lack of information is of considerable concern given that CRF can seriously compromise patients QOL and ability to function on a daily basis. 8 Given the general aging of the cancer population, and the importance of addressing fatigue in this population, we conducted a closer examination of the potential impact of age on CRF. Specifically, available cross-sectional data sets were used to investigate whether fatigue varied systematically as a function of both age and diagnosis. We hypothesized that cancer patients would report more fatigue than the general population and that this difference would be more pronounced for the older sample. That is, a statistical interaction between age and diagnosis was expected with respect to fatigue. Hgb values were available for a subset of patients, and it was hypothesized that differences in fatigue may be at least partly explained by this important clinical variable. Patient and Methods Sample Two existing data sets for this cross-sectional secondary data analysis were used. Full details on recruitment of the samples are found in the original publications. 3,9e12 Briefly, the first data set consisted of a large sample (n ¼ 1075) of individuals from the general population, randomly drawn to complete a series of

Vol. 40 No. 2 August 2010 Age-Associated Differences in Fatigue 219 questionnaires from more than 100,000 individuals enrolled in an Internet-based survey panel. 9 Data from several mixed-diagnosis cancer samples 3,10e12 comprised the second data set (n ¼ 738). In this second data set, patients were recruited from Chicago-area oncology clinics for studies on health-related QOL. All patients received some treatment for their cancer. Ethics Participants provided informed consent before data collection. Original data collection and informed consent procedures were approved by the appropriate institutional review board. Assessments All participants completed the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) subscale. 10 The FACIT-F is a 13-item scale that asks respondents to rate statements regarding their fatigue experience and its impact on their daily lives. Sample items include I feel fatigued, I feel weak all over, and I feel listless (washed out). All items are rated on a 0 (not at all) to 4 (very much) scale. By scoring convention, after appropriate reverse scoring of 11 items, lower scores on the FACIT-F subscale indicate greater levels of fatigue. (A scoring template is available at www.facit.org.) Originally developed for use with cancer patients, 9,13 the scale has been successfully tested for use in the general population 3,9 and chronic anemia of aging. 7 To enhance the clinical usefulness of the FACIT-F subscale, Cella et al. 13 estimated a minimum clinically meaningful difference of 3 points by using both anchor- and distributionbased methods. Additionally, Eastern Cooperative Oncology Group (ECOG) performance ratings were available for all cancer patients and Hgb values, obtained within 30 days of fatigue ratings, were available for a subset of 430 cancer patients. Data Analysis Sociodemographic and clinical comparisons between the general population and patient groups were conducted using independent samples t-tests or c 2 tests, as appropriate. Analyses of variance (ANOVAs) and analysis of covariance were used to assess differences in fatigue across age categories. Statistical significance was set at P < 0.05. All analyses were conducted using PASW Statistics 17 (SPSS, Chicago, IL). 14 Results Sample Characteristics As summarized in Table 1, the general population sample was 45.9 16.6 years, 51% female, and primarily (84%) Caucasian. When asked to rate their health status on a 1 ( good ) to 5 ( bad ) scale, 56% of the sample responded with either a 1 or 2 rating. Cancer patients were 58.7 13.6 years, 64% female, 88% Caucasian, and 79% self-reported ECOG performance status ratings of 0 or 1 (no symptoms to symptomatic, but ambulatory). 15 Breast (33%) and colorectal (12%) were the most common tumor types. Patients were older (t[1802] ¼ 17.3, P < 0.001) and more likely to be female (c 2 [1] ¼ 29.6, P < 0.001), compared with the general population sample. Fatigue As expected, cancer patients reported more fatigue (FACIT-F subscale ¼ 36.9 11.4) than the general population sample (46.6 7.2; F[1,1804] ¼ 329.2, P < 0.001). This finding was not because of the difference in gender ratios between the samples. Females reported more fatigue than males in the general population sample (t[1057] ¼ 3.7, P < 0.001), whereas males and females reported comparable levels of fatigue (t[724] < 1, P > 0.5) in the cancer sample. Additionally, when the entire sample (i.e., patients and general population) was subdivided using a binary age split (<65 vs. $65), older individuals reported more fatigue (40.2 11.0) than those less than 65 years (43.4 10.0; F[1,1797] ¼ 33.9, P < 0.001). Because an age cut off of 65 is arbitrary, the first age analysis was followed up with a mean comparison of fatigue by age, divided by decade. This analysis confirmed the association of age with fatigue (F[6,1797] ¼ 15.5, P < 0.001). Table 2 presents the mean fatigue scores by decade across the entire sample. Considered independently, diagnosis status and age were associated with increased fatigue, but the age trend becomes more consistent when the two subsamples are combined. Given the relatively low representation of the very young and the

220 Butt et al. Vol. 40 No. 2 August 2010 Table 1 Sociodemographic and Clinical Summary of Samples General Population (n ¼ 1075) Cancer Sample (n ¼ 738) Age (mean standard deviation), in years 45.9 16.6 58.7 13.6 % Female 51 64 Ethnicity, % Caucasian 84.1 88.0 African American 10.1 6.0 Hispanic 3.0 3.0 Other 2.8 3.0 Self-reported health status, % 1 ( good ) 19.4 37.6 ECOG PSR 0 2 36.5 41.6 PSR 1 3 31.0 17.0 PSR 2 4 10.7 3.8 PSR 3 5 ( bad ) 2.5 0.0 PSR 4 FACIT-F subscale score 46.6 7.2 36.9 11.4 Hgb d 12.0 1.9 g/dl Tumor type, % d Breast 33.4 Colorectal 11.9 NHL 9.1 Ovarian 7.3 Prostate 5.1 Cancer stage, % I d 10.2 II d 24.6 III d 26.9 IV d 19.8 Note: ECOG Performance Status Rating: 0 ¼ fully active without restriction; 4 ¼ completely disabled, no self-care. Lower scores on the FACIT-F subscale indicate greater levels of fatigue. Cancer patients reported more severe fatigue than the general population (F[1,1804] ¼ 329.2, P < 0.001). NHL ¼ non-hodgkin s lymphoma; PSR ¼ performance status rating. very old in our cancer sample, we also tested the association of age separately for each group. In the cancer sample, there was a significant association (F[6,719] ¼ 2.56, P < 0.02) suggesting an increase in fatigue with age. The association of fatigue with age in the general population sample suggested a nonsignificant trend (F[6,1065] ¼ 2.03, P ¼ 0.06). A test of the interaction between sample (i.e., general population vs. cancer sample) and age required a test of both effects simultaneously. Considered conjointly, the main effect for sample (F[1,1797] ¼ 271.9, P < 0.001) and age (F[6,1797] ¼ 3.5, P < 0.01) remained; however, there was no support for a sample-age interaction (F[6,1707] ¼ 0.98, P ¼ 0.44). This lack of statistical interaction suggests that although cancer patients reported more fatigue than the general population, this difference did not increase significantly with age. Across the total sample, results from a regression analysis suggested that, with each additional decade, fatigue scores worsened (mean standard error) by 1.27 0.14 points on the FACIT-F subscale (P < 0.001) (Fig. 1). Hemoglobin The potential impact of Hgb on fatigue ratings by age was investigated in the subset of cancer patients with available data (n ¼ 430). Of note, those patients with available Hgb values were not different from those patients without these data with respect to age (F[1,730] ¼ 0.001, P ¼ 0.98), sex (c 2 [1] ¼ 0.15, P ¼ 0.70), or FACIT-F subscale scores (F[1,730] ¼ 1.65, P ¼ 0.20). For those with available Hgb, the mean standard deviation values were within normal limits (12.0 1.7 g/dl) and ranged from 7.0 to 19.3 g/dl. Hgb values were modestly associated with FACIT-F subscale scores (r ¼ 0.24, P < 0.001), in the expected direction. Men had higher Hgb values (12.4 2.0 g/dl) than women (11.8 1.5 g/dl; t[428] ¼ 3.15, P < 0.005). Interestingly, although there was no direct association of Hgb with age category

Vol. 40 No. 2 August 2010 Age-Associated Differences in Fatigue 221 Table 2 FACIT-F Subscale Scores by Population, Age, and for the Total Sample Population Age Category (Years) n % Mean Standard Deviation Minimum Maximum Cancer population 18e30 18 2.5 35.5 11.7 6 51 30e40 48 6.6 37.8 11.1 11 52 40e50 133 18.3 36.0 11.6 7 52 50e60 181 24.9 37.3 11.3 3 52 60e70 172 23.7 38.5 11.4 3 52 70e80 145 20.0 36.1 10.4 7 52 80þ 29 4.0 30.5 13.3 3 52 Total 726 100.0 36.8 11.4 3 52 General population 18e30 224 20.9 46.2 7.6 15 52 30e40 219 20.4 47.6 5.9 23 52 40e50 218 20.3 46.2 7.8 16 52 50e60 190 17.7 47.1 6.5 19 52 60e70 128 11.9 46.1 7.3 19 52 70e80 72 6.7 46.0 7.9 18 52 80þ 21 2.0 43.4 8.6 19 52 Total 1072 100.0 46.6 7.2 15 52 Total 18e30 242 13.5 45.4 8.5 6 52 30e40 267 14.8 45.8 8.1 11 52 40e50 351 19.5 42.3 10.6 7 52 50e60 371 20.6 42.3 10.4 3 52 60e70 300 16.7 41.8 10.6 3 52 70e80 217 12.1 39.4 10.7 7 52 80þ 50 2.8 35.9 13.1 3 52 Grand total 1798 100.0 42.6 10.3 3 52 Note: Total n does not equal 1813 because of missing data. FACIT-F subscale scores have a possible range of 0e52. Lower scores indicate greater levels of fatigue. A three-point change on the FACIT-F subscale has been shown to indicate clinically significant change in fatigue over time. 13 (F[6,429] ¼ 0.75, P ¼ 0.61), when Hgb was treated as a covariate in an ANOVA of the effect of age on fatigue ratings, Hgb explained significant variance in fatigue ratings (F[1,426] ¼ 24.15, P < 0.001) but age category (i.e., decade) did not (F[6,426] ¼ 1.63, P ¼ 0.14). Discussion The present cross-sectional study is notable in that it is the first to directly assess the statistical interaction between diagnosis and age on fatigue. Based on extant research, one might expect no or limited impact of age on CRF. 16 Cella et al. 3 found that people older than 50 years in the general population reported more fatigue than their younger counterparts on the 13-item FACIT-F subscale, but found no such age effect in the sample of anemic cancer patients. Similar analyses in other cancer clinical trials have failed to find a substantial effect of age on fatigue- and/or anemia-related QOL in cancer patients. 17,18 In contrast, the present analyses suggest that, as the decades accumulate, ratings of fatigue increase. However, increases in fatigue are not more pronounced for older patients with cancer compared with the general population. To the authors knowledge, this is the first published analysis that addresses this topic by considering cancer diagnosis and age concurrently. Across the overall sample of cancer patients and the general population, there is a statistically significant but somewhat modest increase in fatigue with age (1.27 points per decade on the FACIT-F subscale). Evaluation of the cancer and general population subgroups revealed that the increase in fatigue was more evident in the cancer sample. Hgb level appears to be a meaningful covariate and may be one of many factors that account for the age-associated differences in fatigue within the cancer sample. Low Hgb is common in the elderly, and the incidence increases with age. A recent analysis of U.S. national data using the National Health and Nutrition Examination Survey (1988e1994) suggests that the rate of anemia

222 Butt et al. Vol. 40 No. 2 August 2010 LESS fatigue FACIT-Fatigue Subscale MORE fatigue 52 48 44 40 36 32 28 24 20 16 12 8 4 0 18-30 31-40 41-50 51-60 61-70 71-80 80+ general population cancer sample Age Fig. 1. Fatigue in the general population and among cancer patients with advancing age. Bars represent means þ 95% confidence interval. Across both groups, there was evidence for increased fatigue with age (F[6,1797] ¼ 3.53, P < 0.01) but no group age interaction (P > 0.25). is 10%e11% for individuals older than 65 years and greater than 20% for individuals older than 85 years. 19 Thus, given that both anemia and cancer are common among the elderly, the question of age-associated fatigue changes is important to consider. Of course, CRF is not always because of low Hgb, 1,20,21 as suggested by the modest correlation between Hgb and FACIT-F subscale scores in the present analysis. CRF also may be brought on by the direct effects of the cancer, comorbid medical conditions, psychosocial factors, and/ or other treatment-related side effects 1,22,23 that were not assessed as part of this study. We focused on anemia as a potential explanatory variable in the present analysis because it was available for a significant portion of patients in this secondary data analysis. Additional data are needed to characterize the fatigue of the oldest cancer patients; our own sample was deficient in this age range. It also would be helpful to replicate the present findings in a sample of patients receiving more aggressive treatment regimens, as this would likely have significant impact on patient s reported fatigue. Although we were limited in terms of potential covariates and our cell sizes for the oldest old, our secondary data analysis was successful in generating hypotheses for future studies. Indeed, there is much research to be done to improve our understanding of how ratings of fatigue change with age. There remain questions to be answered with respect to changes in fatigue over time and the consequences of fatigue in aging adults. As individuals age, there may be a shift in their report of fatigue, because of some level of accommodation for or acceptance of reduced activity levels. 24 Fatigue also may impact the ability to participate in important life activities, which may be associated with inactivity, subsequent loss of muscle tone and weakness, and increased disability. 25 A sense of decreased ability to engage in physical activity also may have psychological consequences that should be monitored. 26 Certainly, additional research may be useful to explore longitudinal changes in fatigue to guide fatigue management for the older patient with and without cancer. References 1. Wagner LI, Cella D. Fatigue and cancer: causes, prevalence and treatment approaches. Br J Cancer 2004;91:822e828. 2. Butt Z, Rosenbloom SK, Abernethy AP, et al. Fatigue is the most important symptom for advanced cancer patients who have had chemotherapy. J Natl Compr Canc Netw 2008;6:448e455.

Vol. 40 No. 2 August 2010 Age-Associated Differences in Fatigue 223 3. Cella D, Lai JS, Chang CH, Peterman A, Slavin M. Fatigue in cancer patients compared with fatigue in the general United States population. Cancer 2002;94:528e538. 4. Beghe C, Wilson A, Ershler WB. Prevalence and outcomes of anemia in geriatrics: a systematic review of the literature. Am J Med 2004;116(Suppl 7A):3Se10S. 5. Pujade-Lauraine E, Gascon P. The burden of anaemia in patients with cancer. Oncology 2004; 67(Suppl 1):1e4. 6. Vogelzang NJ, Breitbart W, Cella D, et al. Patient, caregiver, and oncologist perceptions of cancer-related fatigue: results of a tripart assessment survey. The Fatigue Coalition. Semin Hematol 1997; 34:4e12. 7. Agnihotri P, Telfer M, Butt Z, et al. Chronic anemia and fatigue in elderly patients: results of a randomized, double-blind, placebo-controlled, crossover exploratory study with epoetin alfa. J Am Geriatr Soc 2007;55:1557e1565. 8. Cella D, Kallich J, McDermott A, Xu X. The longitudinal relationship of hemoglobin, fatigue and quality of life in anemic cancer patients: results from five randomized clinical trials. Ann Oncol 2004;15:979e986. 9. Cella D, Zagari MJ, Vandoros C, et al. Epoetin alfa treatment results in clinically significant improvements in quality of life in anemic cancer patients when referenced to the general population. J Clin Oncol 2003;21:366e373. 10. Yellen SB, Cella DF, Webster K, Blendowski C, Kaplan E. Measuring fatigue and other anemia-related symptoms with the Functional Assessment of Cancer Therapy (FACT) measurement system. J Pain Symptom Manage 1997;13:63e74. 11. Lai JS, Cella D, Dineen K, et al. An item bank was created to improve the measurement of cancer-related fatigue. J Clin Epidemiol 2005;58:190e197. 12. Lai JS, Crane PK, Cella D. Factor analysis techniques for assessing sufficient unidimensionality of cancer related fatigue. Qual Life Res 2006;15:1179e1190. 13. Cella D, Eton DT, Lai JS, Peterman AH, Merkel DE. Combining anchor and distribution-based methods to derive minimal clinically important differences on the Functional Assessment of Cancer Therapy (FACT) anemia and fatigue scales. J Pain Symptom Manage 2002;24: 547e561. 14. PASW for Windows. Rel 17.02. Chicago, IL: 2009. 15. Oken MM, Creech RH, Tormey DC, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol 1982;5:649e655. 16. Butt Z, Cella D. Relationship of hemoglobin, fatigue, and quality of life in anemic cancer patients. In: Nowrousian MR, ed. Recombinant human erythropoietin (rhepo) in clinical oncology: Scientific and clinical aspects of anemia in cancer. New York: Springer-Verlag, 2008; 369e392. 17. Thome B, Dykes AK, Hallberg IR. Quality of life in old people with and without cancer. Qual Life Res 2004;13:1067e1080. 18. Aapro MS, Cella D, Zagari M. Age, anemia, and fatigue. Semin Oncol 2002;29:55e59. 19. Guralnik JM, Eisenstaedt RS, Ferrucci L, Klein HG, Woodman RC. The prevalence of anemia in persons age 65 years and older in the United States: evidence for a high rate of unexplained anemia. Blood 2004;104:2263e2268. 20. Lipman AJ, Lawrence DP. The management of fatigue in cancer patients. Oncology 2004;18:1527e1534. 21. Jacobsen PB. Assessment of fatigue in cancer patients. J Natl Cancer Inst Monogr 2004;93e97. 22. Mock V, Atkinson A, Barsevick AM, et al. Cancerrelated fatigue. Clinical practice guidelines in oncology. J Natl Compr Canc Netw 2007;5:1054e1078. 23. Levy M. Cancer fatigue: a review for psychiatrists. Gen Hosp Psychiatry 2008;30:233e244. 24. Schwartz CE, Bode R, Repucci N, et al. The clinical significance of adaptation to changing health: a meta-analysis of response shift. Qual Life Res 2006;15:1533e1550. 25. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146eM156. 26. Brown LF, Kroenke K. Cancer-related fatigue and its associations with depression and anxiety: a systematic review. Psychosomatics 2009;50:440e447.