Chronic fatigue is the most important factor limiting health-related quality of life of chronic myeloid leukemia patients treated with imatinib

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1 Leukemia (2013) 27, & 2013 Macmillan Publishers Limited All rights reserved /13 ORIGINAL ARTICLE Chronic fatigue is the most important factor limiting health-related quality of life of chronic myeloid leukemia patients treated with imatinib F Efficace 1, M Baccarani 2, M Breccia 3, F Cottone 1, G Alimena 3, GL Deliliers 4, C Baratè 5, G Specchia 6, R Di Lorenzo 7, L Luciano 8, D Turri 9, B Martino 10, F Stagno 11, M Dabusti 12, M Bergamaschi 13, P Leoni 14, MP Simula 15, L Levato 16,CFava 17, D Veneri 18, S Sica 19, A Rambaldi 20, G Rosti 2, M Vignetti 1 and F Mandelli 1 Health-related quality of life (HRQOL) is an important goal of therapy for chronic myeloid leukemia (CML) patients treated with current molecular-targeted therapies. The main objective of this study was to investigate factors associated with long-term HRQOL outcomes of CML patients receiving imatinib. Analysis was performed on 422 CML patients recruited in an observational multicenter study. HRQOL was assessed with the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). Key sociodemographic and clinical data were investigated for their association with HRQOL outcomes. Chronic fatigue and social support were also investigated. Univariate and multivariate linear regression analyses were used to identify independent factors associated with HRQOL outcomes. Fatigue was the only variable showing an independent and consistent association across all physical and mental HRQOL outcomes (Po0.01). Differences between patients reporting low versus high fatigue levels were more than eight and seven times the magnitude of a clinically meaningful difference, respectively, for the role physical (D ¼ 70 points) and emotional scale (D ¼ 63 points) of the SF-36. Fatigue did not occur as an isolated symptom and was most highly correlated with musculoskeletal pain (r ¼ 0.511; Pp0.001) and muscular cramps (r ¼ 0.448; Pp0.001). Chronic fatigue is the major factor limiting HRQOL of CML patients receiving imatinib. Leukemia (2013) 27, ; doi: /leu Keywords: quality of life; chronic myeloid leukemia; adverse effects; fatigue INTRODUCTION Five-year relative survival rates of chronic myeloid leukemia (CML) patients have increased from 23, for those diagnosed during , to 80% for those diagnosed between 2001 and This reflects the major advances made in the treatment of this disease due to the advent of tyrosine kinase inhibitors (TKI), with imatinib being the first TKI approved for the treatment of CML patients. 2 The number of people living with this disease has doubled since 2001, and this trend is expected to continue. The prevalence of CML in 20 years might become 1 in 1000 inhabitants in countries using TKI for all new patients. 3 Although recent data indicates that survival of CML patients, who are in complete cytogenetic response (CCyR) with imatinib therapy, is not statistically significantly different from that of the general population, 4 health-related quality of life (HRQOL) differences do exist. 5 Also, the proportion of patients reporting at least one nonserious adverse event, has been shown to increase over the time with up to 52.6% of patients reporting at least one nonserious adverse event after 8 years of treatment. 4 Although these are of mild severity, it is likely that chronic toxicities in CML might significantly interfere with patients daily life and function, and compromise their HRQOL. 6 We have previously investigated the HRQOL of patients treated with long-term imatinib therapy, by comparing their HRQOL profile with that of their peers, without cancer, in the general population. 5 A key finding was that younger patients (that is, those aged between 18 and 59 years) were those with the greatest limitations compared with their peers. 5 However, factors that are associated with long-term HRQOL outcomes of CML patients are not known, 7,8 and in the current analysis we examine a wide range of potentially relevant variables. Such information would have important clinical implications, for example, to lay the 1 Italian Group for Adult Hematologic Diseases (GIMEMA), Data Center and Health Outcomes Research Unit, Rome, Italy; 2 Department of Hematology, Oncology and Laboratory Medicine, Institute of Hematology L. and A. Seràgnoli, University Hospital S.Orsola-Malpighi, Bologna, Italy; 3 Department of Biotechnologies and Hematology, University of Rome Sapienza, Rome, Italy; 4 Department of Hematology, IRCCS Ospedale Maggiore Policlinico, Milan, Italy; 5 Department of Hematology, University of Pisa, Pisa, Italy; 6 Department of Hematology, University of Bari, Bari, Italy; 7 Local Health Unit of Pescara, Hematology, Pescara, Italy; 8 Department of Hematology, University of Naples Federico II, Naples, Italy; 9 Department of Hematology, Hospital Cervello, Palermo, Italy; 10 Department of Hematology, Ospedali Riuniti, Reggio Calabria, Italy; 11 Department of Hematology, Hospital Ferrarotto, Catania, Italy; 12 Department of Hematology, Arcispedale Sant Anna, Ferrara, Italy; 13 Department of Hematology, Clinica Ematologica S. Martino Hospital, University of Genova, Genova, Italy; 14 Department of Hematology, Hospital Torrette, Ancona, Italy; 15 Ospedale Oncologico di Riferimento Regionale Armando Businco, Struttura Complessa di Ematologia e Centro Trapianti, Cagliari, Italy; 16 Department of Hematology, Azienda Ospedaliera Pugliese Ciaccio, Catanzaro, Italy; 17 Department of Hematology, University of Turin, Orbassano, Italy; 18 Department of Hematology, University of Verona, Verona, Italy; 19 Department of Hematology, University of Rome Cattolica S. Cuore, Rome, Italy and 20 Department of Hematology, Ospedali Riuniti di Bergamo, Bergamo, Italy. Correspondence: Dr F Efficace, Italian Group for Adult Hematologic Diseases (GIMEMA), Data Center and Health Outcomes Research Unit, Rome 00161, Italy. f.efficace@gimema.it Presented in part at the 54th Annual Meeting of the American Society of Hematology (ASH), 8 11 December 2012, Atlanta, GA, USA. Received 17 January 2013; revised 8 February 2013; accepted 12 February 2013; accepted article preview online 18 February 2013; advance online publication, 15 March 2013

2 1512 groundwork for developing targeted supportive care programs for CML survivors. In addition to key socio-demographic and clinical data, and considering the chronic nature of the treatment, we hypothesized that also fatigue and social support could be important factors associated with patient outcomes. The impact of fatigue on patients HRQOL might be substantial, 9 and in our previous report we found that fatigue is the most prevalent symptom, being reported by 82% of CML patients treated with imatinib. 5 Fatigue is also often associated with other symptoms in cancer patients. 10 Also, social support has been shown to be a key issue in enhancing HRQOL of cancer survivors, 11 and research has suggested that support from family members may have a key role in the adjustment to the disease and treatment. 12 The main objective of this study was thus to investigate factors associated with long-term HRQOL outcomes of patients in CCyR treated with imatinib therapy. A secondary objective was to investigate the relationships between fatigue and other treatment-related symptoms. PATIENTS AND METHODS Study sample and design This was a multicenter cross-sectional study involving 26 GIMEMA affiliated centers. Eligibility criteria included patients in treatment with imatinib, as first-line therapy, in the early chronic phase of the disease, and having received imatinib for at least 3 years. Patients had to be, at least, in CCyR at the time of study entry. Freedom from psychiatric conditions hampering a HRQOL evaluation was also an inclusion criterion. Patients with a secondary malignancy or those who had received any kind of therapy prior imatinib (except for hydroxyurea and/or anagrelide) were not eligible. Ethic Committees of each participating center approved the study and all patients provided written informed consent. Data collection and variables examined Eligible patients were approached in the hospital and invited to participate by their own treating physician, and those consenting were given a survey booklet to be completed at home. Additional details on study logistic of this study are provided in our previous report. 5 The survey included standardized patient-reported questionnaires and other questions related to patients experience of the disease, including job problems (that is, changes in work situation owing to the CML diagnosis and the related treatment). The following socio-demographic variables were examined for their possible association with HRQOL outcomes: age, gender, education (compulsory school versus high school or higher) and marital status (married versus other). Because of their clinical relevance, the following baseline (that is, at diagnosis) variables were also investigated: Sokal risk (low versus medium/ high), comorbidity (0 versus X1) and Eastern Co-operative Oncology Group performance status (0 versus X1). Also, time in responding to therapy (that is, from treatment start to first CCyR) was considered. Patients were defined as early and late responders, respectively, if they obtained a CCyR within 1 year of treatment or after 12 months. 13 Duration of therapy and dose of imatinib (400 mg/day versus other doses) at the time of study inclusion were also investigated. Patient-reported outcome measures HRQOL physical and mental health dimensions, as measured with the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) (version 1), were the primary outcomes investigated in this analysis. The SF-36 is a well-established generic HRQOL measure used in several studies with cancer survivors. 14,15 This questionnaire consists of 36 items yielding eight scales: physical functioning (PF), role limitations due to physical problems (RP), bodily pain (BP), general health perceptions (GH), vitality (VT), social functioning (SF), role limitations due to emotional problems (RE) and mental health (MH). The eight scales provide a score ranging between 0 and 100 with higher scores representing better health outcomes. The following scales: PF, RP, BP and GH are regarded as mainly related to the physical health, while VT, SF, RE and MH are mainly related to mental health of patients. Fatigue was evaluated with the Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue scale. This is a simple 13-item psychometrically robust questionnaire that assesses self-reported tiredness, weakness and difficulty conducting usual activities due to fatigue. It has undertaken a rigorous validation process showing excellent psychometric properties. 16 This scale has been used in several studies of patients with hematological malignancies, demonstrating the sensitivity of this measure when compared with the general population and other cancer patients with different grades of anemia. 17 Additional symptoms were measured with an ad hoc CML symptom survey. 18 The following symptoms were examined for their possible association with fatigue: abdominal discomfort, diarrhea, edema, headache, muscle cramps, musculoskeletal pain, nausea and skin problems. Patients indicated on a four-point Likert scale the extent, to which they had been bothered: not at all, a little (that is, mild), quite a bit (that is, moderate) and very much (that is, severe). Social support was assessed with the multidimensional scale of perceived social support (MSPSS). The MSPSS is a 12-item validated scale, evaluating the perception of the adequacy of social support from friends, family and significant others. 19 In this study, we considered the global social support MSPSS summary scale. This is a psychometrically sound measure previously used in other cancer studies. 12 Statistical methods SF-36 scales were scored according to standard guidelines. 15,20 Considering the paucity of HRQOL data on CML patients, 7 based on which to make a thoughtful selection of specific scales to be investigated, all physical and MH-related aspects were examined in this study. First, univariate linear regression analyses were performed to select candidates for the multivariate models (Po0.2). After having checked for possible high correlations among variables to be included in the analyses, multiple linear regression 21 was used to identify a set of independent factors associated with SF-36 scales, via a stepwise selection procedure. Variables were included in the model based on an entry criterion of 0.05 and removed according to a stay criterion of Bootstrapping was used as additional supportive analysis to investigate the importance of each single variable being included in the selected multivariate model. 22,23 For each SF-36 scale, stepwise selection procedure was applied to 5000 bootstrap-generated samples, using the initial set of candidate variables considered in this study. The inclusion frequency of each variable in the final models was inspected to further evaluate its independent association with the corresponding SF-36 scale (that is, the higher the percentage of inclusion, the higher the importance of the variable). 22 Coefficients estimates and 95% confidence intervals are reported. To account for multiple testing, the significance level of the final models was Bonferroni corrected by dividing a ¼ 0.05 by 8, that is, the number of SF-36 scales. Clinical significance of HRQOL outcomes was evaluated and eight points were considered to be a minimally important difference for the SF-36 scales. 24 Minimally important difference can be regarded as the smallest difference in score that patients perceive as beneficial or harmful. Differences in scores smaller than the minimally important difference can be considered as not relevant, independent of their statistical significance, and were used in this study to facilitate interpretation of the magnitude of impact of covariates on HRQOL outcomes. For descriptive purposes, and to ease interpretation of data, the cohort was divided into four groups based on the Functional Assessment of Chronic Illness Therapy-Fatigue scores quartiles, and patients were defined as having low, low medium, medium high and high fatigue levels. SF-36 scales and patient-reported symptom intensity were summarized according to fatigue levels. All analyses were performed with SAS Version 9.2 (SAS Institute Inc., Cary, NC, USA). RESULTS Out of 448 eligible patients enrolled, 422 (94%) returned the survey booklet and were used for this analysis. Median time in treatment with imatinib was 5 years (range: years). The majority of patients (77%) were in treatment with standard imatinib dose of 400 mg/day at the time of study inclusion, and 34% of patients, out of the 344 who were working at the time of diagnosis, reported having had job problems due to their disease and related treatment. Details of the population analyzed are reported in Table 1. Factors associated with physical-related HRQOL outcomes In the multivariate analysis, the following factors were independently associated with a better physical functioning: younger age, Leukemia (2013) & 2013 Macmillan Publishers Limited

3 Table 1. Socio-demographic and clinical characteristics Variable CML patients (N ¼ 422) Gender, N (%) Female 172 (40.8) Male 250 (59.2) Age at study entry, (years) Median 57 Range Education, N (%) Compulsory school 194 (46.0) High school 155 (36.7) University degree or higher 70 (16.6) Unknown 3 (0.7) Marital status, N (%) Married/living together 313 (74.2) Single 42 (10.0) Widow 31 (7.3) Divorced 30 (7.1) Unknown 6 (1.4) Comorbidity at diagnosis, N (%) (63.7) X1 153 (36.3) Sokal risk at diagnosis, N (%) Low 222 (52.6) Medium/high 186 (44.1) Unknown 14 (3.3) Job problems due to disease and therapy, N (%) a No 228 (66.3) Yes 116 (33.7) Time to first CCyR Early responders (o1 year) 342 (81.0) Late responders (X1 year) 80 (19.0) Imatinib dose at the time of HRQOL evaluation 400 mg/day 327 (77.5) Other than 400 mg/day 95 (22.5) Abbreviations: CCyR, complete cytogenetic response; CML, chronic myeloid leukemia; HRQOL, health-related quality of life. a Only for patients who had been working at the time of diagnosis. being male, higher education and less fatigue (Po0.01). A younger age was also an independent factor associated with less bodily pain, and a better general health status (Po0.01). Details are reported in Table 2. Fatigue was the only factor with a statistically significant association, at the multivariate level, with all the physical-related scales (Po0.01). Additional bootstrap analysis confirmed that fatigue had the highest inclusion frequency for all scales. Factors associated with mental-related HRQOL outcomes In the multivariate analysis, older age, greater social support and less fatigue were independently associated with better social functioning (Po0.01). A greater social support was associated with better MH (Po0.01). Additional details are reported in Table 3. Lower levels of fatigue were significantly associated with better outcomes in all scales (Po0.01). As shown for physical-related HRQOL outcomes, fatigue had the highest inclusion frequency for all scales in additional bootstrap analysis. HRQOL and job problems by fatigue severity As fatigue was found to be the main variable associated with all physical and mental HRQOL outcomes in multivariate analyses, for 1513 descriptive purposes in Figure 1, we report mean scores of the SF-36 scales by levels of fatigue. Patients role limitations in daily activities due to RP and RE were found to be the most compromised aspects by fatigue severity. Differences between patients with highest versus those with lowest levels of fatigue were, respectively, more than eight and seven times the magnitude of a clinically meaningful difference for the RP (D ¼ 70 points) and RE scales (D ¼ 63 points) (Figure 1). There was a statistically significant association between fatigue and job problems (Po0.001). To illustrate, medium high to high levels of fatigue were reported by 65% of patients who had job problems and only by 34% of patients who did not report any problem due to their disease and treatment. Fatigue and its relationship with other symptoms Investigation of fatigue levels by other symptoms revealed a greater overall symptom burden in patients reporting higher fatigue. As an example, whilein patients reporting high fatigue there were 60% also reporting severe musculoskeletal pain, in the group with low fatigue there were only 4% of patients with severe musculoskeletal pain. Although with different percentages, this pattern was consistent across all treatment-related symptoms investigated. Details are reported in Figure 2. Additional correlation analyses between fatigue and other symptoms, revealed that musculoskeletal pain (r ¼ 0.511; Po0.001) and muscular cramps (r ¼ 0.448; Po0.001) were the two mostly correlated symptoms with fatigue. To further explore whether fatigue was still the most powerful factor independently associated with HRQOL, compared with musculoskeletal pain and muscular cramps, additional analyses were performed. Multivariate analyses were rerun twice for all SF-36 scales, replacing fatigue with either musculoskeletal pain or with muscular cramps. For all scales, fatigue was the variable contributing the most in explaining all physical and mental HRQOL outcomes. Results are displayed in Table 4. DISCUSSION The main finding of this study was that chronic fatigue is the main factor limiting the HRQOL of CML patients who receive long-term imatinib therapy. Out of all the key socio-demographic and clinical variables examined in this study, only fatigue showed a robust and consistent association across all physical and mental HRQOL dimensions. The magnitude of the HRQOL differences between patients with high versus those with low fatigue levels was very large. Fatigue greatly impacted on the extent, to which the physical health and the emotional problems limited the work or other usual activities of patients in terms of time and performance (RP and RE scales of the SF-36) (Figure 1). Higher levels of fatigue were more common in patients who reported having had job problems, further confirming the limitations imposed by fatigue on patients daily life. We also explored, in multivariate analysis, the potential impact on HRQOL of musculoskeletal pain and muscular cramps, but fatigue was still the main contributing factor in explaining physical and mental HRQOL impairments. Our findings in this CML population receiving a targeted therapy are consistent with data reported for patients with solid tumors treated with conventional anticancer treatments. 25 It is difficult to put our findings in relation to the wider literature as no study has investigated this issue in CML patients. 8 However, the negative impact of fatigue on HRQOL was also documented in patients with acute myeloid leukemia (AML) treated with conventional chemotherapies. 26 Using the same self-reported fatigue measure of our study, Alibhai et al. 26 found that fatigue had a wide ranging negative impact in all domains of HRQOL of older AML patients receiving intensive or non-intensive & 2013 Macmillan Publishers Limited Leukemia (2013)

4 1514 Table 2. Univariate and multivariate regression analyses on physical health-related aspects Variables Physical functioning Role physical Bodily pain General health Univariate a Multivariate b Univariate a Multivariate b Univariate a Multivariate b Univariate a Multivariate b b (95% CI) b (95% CI) b (95% CI) b (95% CI) b (95% CI) b (95% CI) b (95% CI) b (95% CI) Age at study entry (years) Gender (ref. male) Education (ref. high) Marital status (ref. married) Late CCyR responders (X1 year) Duration of therapy (years) Comorbidity at diagnosis (ref. no) ECOG performance status (ref. 0) Sokal risk (ref. low) ( 0.879; 0.578) ( ; ) ( ; ) ( ; 1.729) ( 6.936; 5.360) ( 0.990; 2.249) ( ; 9.775) ( ; 2.292) ( ; 3.413) Current imatinib dose (ref. 400 mg/day) ( 4.790; 6.738) Fatigue c (1.601; 2.001) Social support d (1.007; 4.284) ( 0.541; 0.286) ( ; 5.022) ( 9.074; 2.018) ( 0.897; 0.349) ( ; 9.006) ( ; 8.132) ( 9.771; 9.124) ( ; 8.130) ( 2.975; 2.511) ( ; 5.287) ( ; 3.628) ( ; 1.450) ( 7.551; ) (1.290; 1.670) (2.588; 3.289) (1.117; 6.687) ( 0.601; 0.266) ( ; 7.878) ( ; 0.236) ( ; 6.982) ( 9.291; 2.395) ( 6.581; 6.153) ( 0.388; 2.976) ( ; 6.686) ( 6.959; 3.717) ( 7.878; 2.217) ( 7.469; 4.478) (2.507; 3.220) (1.664; 2.087) (1.621; 5.048) ( 0.345; 0.080) ( 0.524; 0.229) ( ; 4.097) ( 9.143; 0.366) ( 6.616; 3.639) ( 6.034; 5.118) ( 2.052; 0.917) ( ; 5.877) ( ; 1.066) ( 6.579; 2.376) ( 3.118; 7.383) (1.597; 2.023) (1.464; 1.836) (1.141; 4.127) ( 0.290; 0.056) ( 7.670; 0.561) (1.406; 1.778) Abbreviations: CI, confidence intervals; CCyR, complete cytogenetic response; ECOG, Eastern Co-operative Group;, not selected in the multivariate model. a Statistically significant factors (Po0.05) are in bold. b Statistically significant factors after Bonferroni adjustment (adjusted alpha ¼ 0.05/8 ¼ ) are in bold. c On this scale, the higher the score the lower is the level of fatigue. d On this scale, the higher the score the higher is the level of perceived social support. Leukemia (2013) & 2013 Macmillan Publishers Limited

5 1515 Table 3. Univariate and multivariate regression analyses on mental health-related aspects Variables Vitality Social functioning Role emotional Mental health Univariate a Multivariate b Univariate a Multivariate b Univariate a Multivariate b Univariate a Multivariate b b (95% CI) b (95% CI) b (95% CI) b (95% CI) b (95% CI) b (95% CI) b (95% CI) b (95% CI) Age at study entry (years) ( 0.370; 0.091) Gender (ref. male) ( ; 6.691) Education (ref. high) ( 8.204; 0.003) Marital status (ref. married) Late CCyR responders (X1 year) Duration of therapy (years) Comorbidity at diagnosis (ref. no) ECOG performance status (ref. 0) ( 9.799; 0.315) ( 4.864; 5.497) ( 0.765; 1.991) ( ; 3.676) ( 6.187; 2.543) Sokal risk (ref. low) ( 5.678; 2.687) Current imatinib dose (ref. 400 mg/day) ( 3.054; 6.779) Fatigue c (1.733; 2.012) Social support d (1.821; 4.588) ( 0.179; 0.122) ( ; 3.878) ( 6.943; 1.824) ( 7.721; 2.451) ( 4.696; 6.410) ( 1.202; 1.740) ( 9.714; 0.713) ( 6.018; 3.294) ( 4.189; 4.672) (0.189; ) (1.733; 2.012) (1.516; 1.876) (3.231; 6.120) (0.068; 0.293) ( 0.600; 0.064) ( ; 4.048) ( ; 1.528) ( 9.975; 8.236) ( ; 4.961) ( 2.845; 2.440) ( ; 0.115) ( ; 4.355) ( 9.746; 6.261) ( 9.856; 8.811) (1.466; 1.835) (2.296; 2.998) (1.455; 3.680) (2.503; 7.829) ( 0.324; 0.061) ( ; 7.390) ( 6.509; 1.250) ( ; 1.475) ( 5.417; 4.324) ( 1.079; 1.532) ( 9.384; 1.433) ( 3.348; 4.942) ( 3.404; 4.528) ( 2.917; 6.295) (2.296; 2.998) (1.237; 1.567) (2.792; 5.345) ( 7.558; 1.448) (1.099; 1.435) (1.208; 3.240) Abbreviations: CI, confidence intervals; CCyR, complete cytogenetic response; ECOG, Eastern Co-operative Group;, not selected in the multivariate model. a Statistically significant factors (Po0.05) are in bold. b Statistically significant factors after Bonferroni adjustment (adjusted alpha ¼ 0.05/8 ¼ ) are in bold. c On this scale, the higher the score the lower is the level of fatigue. d On this scale, the higher the score the higher is the level of perceived social support. & 2013 Macmillan Publishers Limited Leukemia (2013)

6 1516 Figure 1. HRQOL aspects by fatigue severity. Horizontal axis shows CML patients classified into four groups based on their fatigue levels, that is: low, low medium, medium high and high fatigue. These correspond, respectively, to the 4th (75th to 100th percentile), 3rd, 2nd and 1st (0th to 25th percentile) quartile of Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue scale. On this scale, the higher the score the lower is the level of fatigue. Vertical axis shows the score of the SF-36 scales (ranging between 0 and 100), with higher scores indicating better health. The D are calculated as the difference in SF-36 scale mean scores between patients with low medium, medium high and high fatigue versus those with low fatigue levels. A difference exceeding at least 8 points, can be considered as a clinically meaningful difference. (a) Physical health-related aspects; (b) Mental health-related aspects. chemotherapy up to 6 months from diagnosis. Our findings are new and also extend our previous results 5 by showing, for the first time, that fatigue is not only a frequently reported symptom, but it is also by far the most important factor negatively affecting patients daily life. Imatinib has been shown to have a less toxic profile than previous interferon based therapies used to treat CML patients, 27 and one could have expected a lower impact of fatigue on patients HRQOL. However, we found that even small differences in fatigue severity (that is, between patients reporting low versus low medium levels) corresponded to clinically meaningful impairments in all physical and mental HRQOL domains (Figure 1). Activity enhancement, physically based therapies and psychosocial interventions have been recommended to reduce cancerrelated fatigue in patients receiving active treatments 10 and, current data, suggest these should be highly considered in supportive care programs for this population. Given the chronic nature of the disease, we also hypothesized that social support could have had an impact on patients HRQOL. Previous data in patients with solid tumors and leukemia have shown the important role of social support in enhancing HRQOL of cancer survivors, 28,29 and, in this study, we partially supported this evidence. A greater social support was an important aspect associated with better MH-related aspects, but not for physicalrelated aspects. Another important finding was that fatigue in this population does not occur by itself but clusters with other symptoms. Patients who reported higher levels of fatigue also reported a higher symptom burden and this was consistent across all symptoms examined (Figure 2). Although not directly comparable, due to the different study design, our findings confirm recent preliminary data. 30 Nazha et al. 30 in a sample of 148 CML patients receiving various TKI, including imatinib, nilotinib, dasatinib and bosutinib, found that higher levels of fatigue were associated with higher severity of other symptoms, such as muscle soreness, malaise and swelling. In our analysis, fatigue was mainly correlated with musculoskeletal pain and muscular cramps, and a similar association has also been documented in patients with other Leukemia (2013) & 2013 Macmillan Publishers Limited

7 1517 Figure 2. Intensity of key treatment-related symptoms by fatigue severity. Low, low medium, medium high and high correspond, respectively, to the 4th (75th to 100th percentile), 3rd, 2nd and 1st (0th to 25th percentile) quartile of FACIT-Fatigue scale. On this scale, the higher the score the lower is the level of fatigue. Symptoms investigated by fatigue severity were rated by patients on a four-point Likert scale (that is, not at all, a little, quite a bit or very much ) and, for descriptive purposes, answers on the categories quite a bit and very much (that is, moderate to severe) were combined. chronic medical conditions, such as those with HIV/AIDS receiving antiretroviral therapy. 31 Current data emphasize the need of studies addressing how treatment-related symptoms interact with one another. This study has a number of strengths. So as recommended by international guidelines, 10 fatigue was reported by patients themselves using a well-validated and solid questionnaire. 32 Also, we could rely on a large sample size, which allowed for adequate powered analyses. Finally, our findings are generalizable to the majority of CML patients currently being treated in the real world setting (that is, those who reach at least a CCyR with imatinib therapy). Our study also has potential limitations. The cross-sectional study design allowed an examination of statistical associations and not of causal relationships. Also, current findings cannot be extended to CML patients who switched from first-line imatinib therapy to other TKI. In summary, our results show that fatigue is the major factor limiting HRQOL of CML patients receiving long-term imatinib therapy. Fatigue is also associated with other symptoms, mainly with musculoskeletal pain and muscular cramps. Future therapeutic strategies, tailored on the individual patient characteristics, could be crucial in reducing chronic fatigue and ultimately improve HRQOL outcomes. & 2013 Macmillan Publishers Limited Leukemia (2013)

8 1518 Table 4. Contribution of fatigue versus musculoskeletal pain or muscular cramps in explaining HRQOL limitations SF-36 Scales CONFLICT OF INTEREST Adjusted R 2 coefficients of alternative multivariate regression models Original multivariate model with fatigue Alternative multivariate model replacing fatigue with musculoskeletal pain Alternative multivariate model replacing fatigue with muscular cramps Physical health-related aspects Physical functioning Role physical Bodily pain General health Mental health-related aspects Vitality Social functioning Role emotional Mental health The table shows adjusted R 2 coefficients of multivariate regression models. For each scale, the set of independent variables is the same as shown in Tables 2 and 3 for multivariate analysis, replacing fatigue with either musculoskeletal pain or muscular cramps. An adjusted R 2 closer to 1 suggests a better model fit. Consultant or advisory role: FE, Mi Ba, MB, GR, CB (Novartis and Bristol Myers Squibb); research funding: FE, GR, PL (Novartis); honoraria: Mi Ba (Novartis, Bristol Myers Squibb, Pfizer and Ariad); expert testimony: DT (Novartis and Bristol Myers Squibb); AR (Novartis); other remuneration: DT (Novartis and Bristol Myers Squibb). ACKNOWLEDGEMENTS We are grateful to all patients who participated in this study and we acknowledge the essential contribution of the Associazione Italiana contro le Leucemie, Linfomi e Mieloma (AIL), which provided logistic and administrative support to this project. This study was supported by Novartis. Novartis had no role in the design and conduct of the study; collection, management, analysis and interpretation of data; and preparation, review or approval of the manuscript. AUTHOR CONTRIBUTIONS: FE was the study co-ordinator and Mi Ba was the study co-coordinator of this project. Details of contribution are as follows: conception and design: FE, Mi Ba, FM; collection and assembly of data: FE, MB, GA, GR, GLD, CB, GS, R Di L, LL, DT, BM, FS, MD, Mi Ba, PL, MPS, LL, CF, DV, SS, AR; data analysis and interpretation: FE, FC, Mi Ba, FM; statistical analysis: FC, FE; manuscript writing: FE, FC, Mi Ba, FM; final approval of manuscript: FE, Mi Ba, MB, GA, GR, FC, LDG, CB, GS, RDL, LL, DT, BM, FS, MD, Mi Ba, PL, MPS, LL, CF, DV, SS, AR, MV, FM; provision of study material or patients: Mi Ba, MB, GA, GR, LDG, CB, GS, GF, LL, DT, BM, FS, MD, Mi Ba, PL, MPS, LL, CF, DV, SS, AR. REFERENCES 1 Bjorkholm M, Ohm L, Eloranta S, Derolf A, Hultcrantz M, Sjoberg J et al. Success story of targeted therapy in chronic myeloid leukemia: a population-based study of patients diagnosed in Sweden from 1973 to J Clin Oncol 2011; 29: Kris MG, Benowitz SI, Adams S, Diller L, Ganz P, Kahlenberg MS et al. 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