In myelodysplastic syndromes (MDS), health-related quality of life (HRQoL) represents a relevant patient-reported outcome, which is essential in individualized therapy planning. Prospective data on HRQoL in lower-risk MDS remain rare. We assessed HRQOL by EQ-5D questionnaire at initial diagnosis in 1690 consecutive IPSS-Low/Int-1 MDS patients from the European LeukemiaNet Registry. Impairments were compared with age- and sex-matched EuroQol Group norms. A signiﬁcant proportion of MDS patients reported moderate/severe problems in the dimensions pain/discomfort (49.5%), mobility (41.0%), anxiety/depression (37.9%), and usual activities (36.1%). Limitations in mobility, self-care, usual activities, pain/discomfort, and EQ-VAS were signiﬁcantly more frequent in the old, in females, and in those with high co- morbidity burden, low haemoglobin levels, or red blood cells transfusion need (p < 0.001). In comparison to age- and sex- matched peers, the proportion of problems in usual activities and anxiety/depression was signiﬁcantly higher in MDS patients (p < 0.001). MDS-related restrictions in the dimension mobility were most prominent in males, and in older people (p < 0.001); in anxiety/depression in females and in younger people (p < 0.001); and in EQ-VAS in women and in persons older than 75 years (p < 0.05). Patients newly diagnosed with IPSS lower-risk MDS experience a pronounced reduction in HRQoL and a clustering of restrictions in distinct dimensions of HRQoL as compared with reference populations. Introduction survival (OS) and the risk of AML transformation. The international prognostic scoring system (IPSS)  and more Myelodysplastic syndromes (MDS) represent challenging recently, the revised IPSS (IPSS-R)  represent the gold hematopoietic disorders characterized by cytopenias, func- standard in prognostication of MDS. Based on these scoring tional blood defects, and clonal hematopoiesis. The clinical systems, IPSS low/intermediate-1 risk and IPSS-R (very) course is characterized by an impaired health-related quality low/intermediate risk are classiﬁed as lower-risk MDS with of life (HRQoL), the risk of transformation to acute myeloid a low propensity to transform to AML [2, 3]. The treatment leukaemia (AML) and reduced survival in the majority of goals in this cohort of patients are an improvement in patients . Based on biological parameters, the patients are cytopenias, prolongation of survival, and improvement and classiﬁed into different risk groups to predict overall maintenance of HRQoL and functional capacities. IPSS intermediate-2/high and IPSS-R high/very high risk are classiﬁed as higher-risk MDS, which are characterized by Electronic supplementary material The online version of this article an increased risk of AML transformation and a short (https://doi.org/10.1038/s41375-018-0089-x) contains supplementary median survival of less than 2 years . material, which is available to authorized users. Patients with MDS often suffer from a high symptom * Reinhard Stauder burden, resulting in restrictions in HRQoL. Assesssment of firstname.lastname@example.org HRQoL provides information on the patient´s perspective Extended author information available on the last page of the article and perception, thus representing a relevant patient-reported 1234567890();,: Health-related quality of life in lower-risk MDS patients compared with age- and sex-matched reference. . . 1381 outcome (PRO) [1, 4, 5]. The study of HRQoL has become included in this analysis. EUMDS (ClinicalTrials.gov: an increasingly critical area of research , as limitations in NCT00600860) has been approved by the ethics commit- HRQoL are frequently observed in MDS and are only tees of all participating centres and is performed in accor- partially explained by anaemia [7, 8]. Moreover, restrictions dance with the Declaration of Helsinki. Written informed in HRQoL may predict an unfavourable clinical outcome consent was obtained from all patients. [9–12]. In addition HRQoL represents a parameter of response evaluation [1, 13, 14]. Thus, the integration of HRQoL measurement assessment of HRQoL in MDS has been propagated by clinicians, stakeholders, and authorities [1, 13–15]. How- Patient-reported HRQoL was measured by EQ-5D, at the ever, deﬁnitive data on HRQoL in low-risk MDS at initial time of study enrolment. EQ-5D is a validated, generic, diagnosis are limited by small sample size [16, 17], selec- HRQoL questionnaire , consisting of the EQ-5D tion bias [7, 16, 17], and assessment later after initial descriptive system with ﬁve dimensions related to daily diagnosis [7, 11, 16, 18, 19]. In addition, most studies have activities (mobility, self-care, usual activities, pain/dis- included patients with higher-risk MDS [9–12, 16, 18–20], comfort, anxiety/depression), with three-level answers (no AML [10, 11], or CMML [11, 16], which precludes precise problem, some problems, severe problems), and a visual interpretation. Lower-risk patients with MDS are typically analogue scale (EQ-VAS). The ﬁve dimensions were con- of advanced age with a median of 74 years at diagnosis verted into a single summary index (EQ-5D index) by . The dissection between age-associated restrictions in applying the European value set (EVS) . EQ-VAS  HRQoL and the incremental impact of MDS in these is a global evaluation of ‘own health today’ using a health patients is relevant, yet has not been analyzed at all. state scale ranging from 0 (worst imaginable) to 100 (best The main objective of this international prospective cohort imaginable). observational study is to investigate the HRQoL proﬁle of patients with lower-risk MDS at the time of diagnosis, as Measures of population norms compared with the general population matched on age and sex. The incremental impact of MDS on symptom burden is The main objective of this paper was to compare the QoL of dissected by comparing features in MDS with the general patients with MDS with general population with a similar population. A secondary objective is to examine clinical age and gender distribution. Therefore, population norms factors associated with HRQoL of these patients. were used as reference values to assess the relative HRQoL of patients in comparison to that of an average person . Population norms are based on descriptions of current Materials/methods health status from population surveys. Nine European countries in this study (Denmark, France, Germany, Greece, Participants Italy, Netherlands, Spain, Sweden, and the UK) have reported a series of tables of age/sex population norms for The EUMDS Registry is a prospective, non-interventional the EQ-5D for both, proﬁle data and VAS scores . For longitudinal study, enroling newly diagnosed patients with the ﬁve European countries and Israel for which there are no IPSS low or intermediate-1 MDS from 145 haematology published EQ-5D population norms, we replaced the centres in 17 European countries and Israel. Patients with an missing data on the probabilities of being in a given level IPSS risk intermediate-2 or high, or with therapy-related for each EQ-5D dimension with the mean of the available MDS were excluded. Patients without cytogenetic infor- European countries by matching the combination of age mation were only included if the diagnosis of MDS was group and gender. morphologically proven, with <5% bone marrow blasts and at most a single cytopenia according to the IPSS. Based on Demographic and clinical parameters these criteria, exclusively IPPS low or intermediate-1 patients were included in EUMDS. Information on patients’ demographics (age and gender), Therapy is given according to local guidelines . IPSS-R, co-morbidity index (MDS-CI), haemoglobin (Hb) Enrolment was within 100 days of the diagnostic bone marrow level at the time of diagnosis, and red blood cell transfu- aspirate. The average time from date of diagnosis to inclusion sions (RBCT) in the year prior to the diagnosis were was 44 days (standard deviation 28 days). Details on design recorded [3, 21, 26]. Due to the small number of young and data collection have been published elsewhere . adult patients, age was categorized into three groups (<60, As the European Quality of Life ﬁve Dimensions (EQ- 60–75, and 75+ years) to compare HRQoL of different age 5D) was not licensed in two countries, 15 countries were groups. 1382 R. Stauder et al. Statistical analysis Patients with MDS reveal profound impairments in HRQoL Differences in response between the ﬁve EQ-5D dimensions in patients with MDS and European norms were evaluated The MDS cohort was characterized by a mean EQ-5D using χ tests. For both EQ-5D index and EQ-VAS, the index-score of 0.74 and a mean EQ-VAS of 69.6. A sig- mean score with standard deviation was calculated. Wil- niﬁcant proportion of MDS patients reported moderate or coxon’s signed ranks tests were conducted to identify any severe problems in the dimensions pain/discomfort (49.5%), major difference between the MDS patient baseline values mobility (41.0%), anxiety/depression (37.9%), and usual and European norms. The relationship between HRQoL and activities (36.1%), respectively. The dimension with the demographic/clinical factors was examined using multilevel lowest proportion of restrictions was self-care (13.3%) linear regression (additional information is available (Table 2). Clinically meaningful restrictions in the dimen- in Supplementary Materials); univariate analysis was per- sions mobility, self-care, usual activities, and pain/dis- formed for age at diagnosis, gender, IPSS-R, MDS-CI, Hb, comfort as well as in EQ-VAS and EQ-5D index were and RBCT status, and a multivariate analysis was per- observed signiﬁcantly more often in older patients and in formed adjusting for all other variables. We assessed the those with a high co-morbidity burden, low Hb-levels, or discriminative ability of HRQoL not only by a signiﬁcant RBCT need (p < 0.001). Increased problems with anxiety/ difference, but also by a minimally important difference depression were signiﬁcantly more frequent in women (p < (MID) . The MID is viewed as the smallest difference in 0.001) and in patients with lower Hb-levels (p < 0.01). The score in the domain of interest that is perceived by patients impact of both of IPSS and IPSS-R on EQ-5D scoring was as beneﬁcial or that would result in a change in treatment. only marginal. In general, restrictions in all parameters of See Supplementary Materials for more detail. EQ-5D were signiﬁcantly more often reported in female All analyses were undertaken in Stata 14 (StataCorp, patients (p < 0.05, Table 2). College Station, TX). Association of restrictions in HRQoL and demographic and disease factors Results To assess possible associations between clinical parameters Characteristics of patients and HRQoL, univariate and multivariate linear analyses were performed. It was estimated that patients in the Based on IPSS-scoring, i.e., the gold-standard in classiﬁca- reference group of each of demographic and clinical para- tion at the time of start of the registry, 1985 patients were meters would have a mean score of 0.85 on the EQ-5D included between December 2007 and January 2016, among index, and 80.85 on the EQ-VAS (Table 3). Relative to which 961 (48.4%) were IPSS low-risk and 912 (45.9%) these scores, there was a signiﬁcant loss in HRQL for were IPSS Int-1. IPSS score could not be calculated in 5.6% groups who were older (e.g., 75+ vs. <60 years; index: of patients where cytogenetic testing was not available or had −0.08; VAS: −7.33), female, or had increased comorbid- failed. Based on inclusion criteria, exclusively IPSS low or ities, low Hb-levels, or transfusion dependence (Table 3). int-1 patients were included. Retrospective classiﬁcation by These differences exceeded the MID on each of the two IPSS-R revealed a (very) low risk in 24.8% and 37.6%, an HRQL measures (>0.03 on the EQ-5D index and >3.0 on intermediate risk in 21.2%, high/very high risk in 6.1%, and the EQ-VAS). In summary, HRQoL as deﬁned by EQ-5D classiﬁcation was unknown in 10.3% of patients. In total, index and EQ-VAS was more often signiﬁcantly impaired 1690 patients (85.1%) completed both EQ-5D descriptive in older and in female patients and in persons with advanced system and EQ-VAS. Thirty-three patients (1.7%) completed comorbidities, low Hb levels, and increased transfusion EQ-5D description only, and seven patients (0.3%) com- need both in uni- and in multivariate analyses. pleted EQ-VAS only (Table 1.). The majority of patients had advanced age (median age: 74 years), and a male pre- Comparison of HRQoL in MDS and in age- and sex- ponderance was observed. Nearly half of patients were matched reference populations characterized by Hb levels <10 g/dL at baseline, and more than 30% of patients had received RBCT within 1 year prior We compared subgroups of MDS patients with age- and to diagnosis. Demographic characteristics of the patients who sex-matched reference norms. Overall, patients with MDS completed EQ-5D did not differ substantially from the total were characterized by a small, but signiﬁcantly lower EQ- cohort, showing a similar age distribution and a slightly 5D index (0.74 vs. 0.76) and lower EQ-VAS (69.6 vs. 71.8) higher proportion of men. Overall, the HRQoL data in our than European norms (p < 0.05) (Table 4). However, these sample were likely missing at random (Table 1). differences were too small to fulﬁl the criteria of MID. In Health-related quality of life in lower-risk MDS patients compared with age- and sex-matched. . . 1383 Table 1 Demographic and clinical characteristics of MDS-patients—entire cohort and EQ-5D respondents Total EQ-5D Completed EQ-5D not completed Characteristic No. of Patients % No. of patients % No. of patients % Entire cohort 1 985 100.0 1 690 85.1 295 14.9 Age, years <60 214 10.8 187 11.1 27 9.2 60–75 818 41.2 707 41.8 111 37.6 75+ 953 48.0 796 47.1 157 53.2 Gender Male 1 202 60.6 1 039 61.5 163 55.3 Female 783 39.4 651 38.5 132 44.7 Diagnosis (WHO 2001) RA 355 17.9 283 16.7 72 24.4 RARS 310 15.6 276 16.3 34 11.5 RCMD 755 38.0 651 38.5 104 35.3 RCMD-RS 118 5.9 102 6.0 16 5.4 RAEB-1 239 12.0 207 12.2 32 10.8 RAEB-2 9 0.5 8 0.5 1 0.3 MDS-U 81 4.1 68 4.0 13 4.4 5q-Syndrome 118 5.9 95 5.6 23 7.8 IPSS Low risk 961 48.4 813 48.1 148 50.3 Intermediate-1 912 45.9 782 46.3 130 43.9 Low/int-1 no cytogenetics 112 5.6 95 5.6 17 5.7 IPSS-R Very low risk 493 24.8 433 25.6 60 20.3 Low risk 746 37.6 646 38.2 100 33.9 Intermediate risk 420 21.2 341 20.2 79 26.8 High/very high risk 121 6.1 110 6.5 11 3.7 Unknown 205 10.3 160 9.5 45 15.3 MDS-CI Low risk 1 276 64.3 1 076 63.7 200 67.8 Intermediate risk 606 30.5 525 31.1 81 27.5 High risk 103 5.2 89 5.3 14 4.7 Haemoglobin (g/dL) ≥10 1 076 54.2 913 54.0 163 55.3 <10 884 44.5 768 45.4 116 39.3 Unknown 25 1.3 9 0.5 16 5.4 Red blood cell transfusion No 1 390 70.0 1 163 68.8 227 76.9 Yes 595 30.0 527 31.2 68 23.1 WHO World Health Organization, IPSS International Prognostic Scoring System, IPSS-R Revised International Prognostic Scoring System, MDS- CI Myelodysplastic Syndrome-Comorbidity Index, HCT-CI Hematopoietic Cell Transplant-Comorbidity Index Includes EQ-5D completed only, EQ-VAS completed only, and both completed Patients with cytogenetics failed or not available were included if the diagnosis of MDS was morphologically proven, with <5% bone marrow blasts and at most a single cytopenia according to the IPSS. Based on these criteria, exclusively IPPS low or int-1 patients were included in this cohort As assessed in the year prior to initial diagnosis 1384 R. Stauder et al. Table 2 Prevalence of problems in distinct dimensions of EQ-5D, EQ-5D index, and EQ-VAS in MDS patients Mobility Self-care Usual Pain/ Anxiety/ EQ-5D: index EQ-5D: VAS a a problem problem activities discomfort depression a a a problem problem problem % p % p % p % p % p Mean SD Np Mean SD Np Total 41.0 13.3 36.1 49.5 37.9 0.74 0.23 1683 69.6 20.1 1657 Sex 0.007 0.030 0.021 <0.001 <0.001 <0.001 0.005 Male 39.1 11.6 33.6 45.5 30.1 0.77 0.22 1035 70.70 20.02 1022 Female 44.0 16.0 40.0 55.9 50.3 0.69 0.23 648 67.83 20.19 635 Age group (years) <0.001 <0.001 <0.001 <0.001 0.581 <0.001 <0.001 <60 18.5 2.7 26.6 31.5 40.8 0.80 0.22 184 76.65 19.35 185 60–75 33.0 8.5 29.1 43.5 35.9 0.78 0.21 705 72.72 19.95 694 75+ 53.3 20.0 44.5 58.9 39.0 0.69 0.23 794 65.14 19.48 778 IPSS 0.083 0.057 0.899 0.005 0.884 0.845 0.298 Low risk 42.4 13.2 49.6 53.1 39.2 0.74 0.23 809 70.20 19.84 798 Intermediate risk 38.2 13.1 47.7 49.3 36.8 0.75 0.22 780 68.98 20.27 764 Low/int-1 no cytogenetics 51.6 16.1 64.5 44.7 36.6 0.70 0.23 93 69.34 21.40 94 IPSS-R 0.656 0.907 0.899 0.023 0.119 0.769 0.044 Very low risk 40.6 11.9 32.4 53.1 33.8 0.75 0.23 429 71.40 19.46 422 Low risk 40.8 13.0 36.6 49.3 38.9 0.73 0.23 645 69.05 20.38 637 Intermediate risk 42.4 14.4 36.5 44.7 42.9 0.73 0.22 340 68.29 20.76 333 High/very high risk 40.4 14.7 35.8 52.3 36.7 0.76 0.21 109 68.61 21.16 109 Unknown 40.6 15.0 43.1 48.8 35.0 0.74 0.22 160 70.49 18.57 156 MDS-CI <0.001 <0.001 <0.001 <0.001 0.493 <0.001 <0.001 Low risk 33.9 10.1 31.6 44.5 37.3 0.76 0.22 1072 72.59 19.38 1053 Intermediate risk 51.8 18.4 42.8 57.2 38.4 0.70 0.23 523 64.92 20.09 518 High risk 63.6 22.7 50.0 64.8 42.0 0.67 0.25 88 61.26 21.76 86 Haemoglobin (g/dL) <0.001 <0.001 <0.001 0.026 0.002 <0.001 <0.001 ≥10 34.5 9.2 28.9 46.9 34.3 0.77 0.22 909 72.71 19.44 893 <10 49.2 18.3 45.0 53.2 42.4 0.70 0.23 765 65.79 20.31 755 Unknown 0.0 0.0 0.0 0.0 22.2 0.95 0.10 9 80.56 15.30 9 Red blood cell transfusion <0.001 <0.001 <0.001 0.049 0.070 <0.001 <0.001 No 35.9 9.8 30.9 47.5 36.2 0.76 0.22 1160 71.74 19.56 1137 Yes 52.2 21.0 47.4 53.9 41.7 0.69 0.24 523 64.94 20.57 520 IPSS-R Revised International Prognostic Scoring System, MDS-CI myelodysplastic syndrome-comorbidity index. Bold numbers emphasize signiﬁcant differences (p<0.05). Problem: moderate or severe problems Patients with cytogenetics failed or not available were included if the diagnosis of MDS was morphologically proven, with <5% bone marrow blasts and at most a single cytopenia according to the IPSS. Based on these criteria, exclusively IPPS low or int-1 patients were included in EUMDS As assessed in the year prior to initial diagnosis Health-related quality of life in lower-risk MDS patients compared with age- and sex-matched. . . 1385 Table 3 Association of HRQL and demographic and disease characteristics in MDS patients based on univariate and multivariate multilevel linear regression analyses EQ-5D index (n = 1683 patients) EQ-VAS (n = 1657 patients) a a Univariate Multivariate Univariate Multivariate Variable Coef. 95% CI p Coef. 95% CI p Coef. 95% CI p Coef. 95% CI p Constant 0.74 0.73 0.76 <0.001 0.85 0.81 0.89 <0.001 70.71 67.98 73.44 <0.001 80.85 76.88 84.82 <0.001 Age group <60 60–75 −0.03 −0.06 0.01 0.144 −0.02 −0.05 0.02 0.287 −3.12 −6.23 −0.01 0.050 −1.85 −4.88 1.18 0.231 75+ −0.11 −0.14 −0.07 <0.001 −0.08 −0.12 −0.05 <0.001 −10.06 −13.19 −6.93 <0.001 −7.33 −10.42 −4.24 <0.001 Sex Male Female −0.07 −0.09 −0.05 <0.001 −0.08 −0.10 −0.06 <0.001 −3.24 −5.17 −1.32 <0.001 −3.65 −5.51 −1.78 <0.001 IPSS-R Very low risk Low risk −0.01 −0.04 0.02 0.414 0.03 0.00 0.06 0.045 −2.19 −4.59 0.21 0.073 1.41 −1.04 3.87 0.260 Intermediate/high risk −0.01 −0.04 0.03 0.750 0.04 0.01 0.07 0.022 −2.68 −5.42 0.06 0.055 1.62 −1.28 4.52 0.274 Unknown 0.00 −0.04 0.04 0.909 0.02 −0.02 0.07 0.254 −0.01 −3.69 3.67 0.997 3.12 −0.55 6.79 0.095 MDS-CI Low risk Intermediate/high risk −0.07 −0.09 −0.04 <0.001 −0.06 −0.08 −0.04 <0.001 −7.33 −9.26 −5.39 <0.001 −6.22 −8.15 −4.28 <0.001 Haemoglobin (g/dL) ≥10 <10 −0.07 −0.09 −0.04 <0.001 −0.05 −0.08 −0.03 <0.001 −7.12 −8.99 −5.24 <0.001 −5.56 −7.77 −3.35 <0.001 Red blood cell transfusion No Yes −0.07 −0.10 −0.05 <0.001 −0.04 −0.07 −0.02 <0.001 −7.14 −9.14 −5.13 <0.001 −4.03 −6.18 −1.87 <0.001 IPSS-R Revised International Prognostic Scoring System, MDS-CI Myelodysplastic Syndrome-Comorbidity Index syndrome-comorbidity index. Bold numbers emphasize signiﬁcant differences (p<0.05). Adjusted for all other variables As assessed in the year prior to initial diagnosis 1386 R. Stauder et al. Table 4 Comparison of HRQL in MDS patients and age- and sex-matched European reference cohorts Mobility Self-care Usual activities Pain/ Anxiety/ EQ-5D: index EQ-5D: VAS a a a problem problem problem discomfort depression a a problem problem % p % p % p % p % p Mean SD Np Mean SD Np Entire cohort <0.001 0.438 <0.001 0.919 <0.001 0.019 0.029 European Norm 33.5 12.4 26.0 48.8 14.9 0.76 0.18 1683 71.8 3.1 1657 EUMDS 41.0 13.3 36.1 49.5 37.9 0.74 0.23 1683 69.6 20.1 1657 Male <0.001 0.409 <0.001 0.371 <0.001 0.059 0.268 European Norm 29.4 10.7 23.4 43.9 13.7 0.79 0.16 1035 72.6 2.8 1022 EUMDS 39.1 11.6 33.6 45.5 30.1 0.77 0.22 1035 70.7 20.0 1022 Female 0.142 0.820 <0.001 0.355 <0.001 0.164 0.039 European Norm 40.0 15.0 30.1 56.8 16.7 0.72 0.19 648 70.5 3.1 635 EUMDS 44.0 16.0 40.0 55.9 50.3 0.69 0.23 648 67.8 20.2 635 Age group, <60 0.202 0.288 <0.001 0.645 <0.001 0.019 0.508 European Norm 13.6 4.9 11.4 28.3 9.8 0.86 0.15 184 77.3 2.9 185 EUMDS 18.5 2.7 26.6 31.5 40.8 0.80 0.22 184 76.7 19.3 185 Age group, 60–75 0.002 0.179 <0.001 0.606 <0.001 0.261 0.086 European Norm 25.4 6.7 20.0 44.5 14.9 0.79 0.17 705 73.1 1.7 694 EUMDS 33.0 8.5 29.1 43.5 35.9 0.78 0.21 705 72.7 20.0 694 Age group, 75+ <0.001 0.711 <0.001 0.671 <0.001 0.207 <0.001 European Norm 45.2 19.1 34.6 57.4 16.0 0.71 0.17 794 69.3 1.1 778 EUMDS 53.3 20.0 44.5 58.9 39.0 0.69 0.23 794 65.1 19.5 778 Problem: moderate or severe problems. Bold numbers emphasize signiﬁcant differences (p<0.05). Health-related quality of life in lower-risk MDS patients compared with age- and sex-matched. . . 1387 Fig. 1 Proportion of moderate/severe problems in male (a) and female as lines. Differences (Δ) of patients with MDS to sex-matched refer- (b) patients with MDS (blue bars) as compared to European age- and ence group shown when signiﬁcant (*** p < 0.001; **p < 0.01; *p < sex-matched standard population (dark grey). Standard errors indicated 0.05; as assessed by Wilcoxon signed rank tests) contrast, distinct differences which fulﬁlled the criteria of a older patients (60+ years; p < 0.01; Fig. 2c). The dimen- MID were seen in individual components of EQ-5D: a sions self-care and pain/discomfort were not different signiﬁcantly higher proportion of MDS patients reported between the cohorts (Table 2; Figs. 1 and 2). Differences in moderate/severe problems in the dimensions mobility, usual EQ-5D index were most pronounced in younger MDS activities, and anxiety/depression compared to the reference patients (<60 years). EQ-VAS was more often diminished at populations (p < 0.001) (Table 4). advanced age (75+ years) as compared to peers Analyses stratiﬁed by sex and age depicted most pro- (p < 0.001; Table 2). These differences fulﬁlled the criteria nounced differences in the dimensions anxiety/depression, of a MID. and usual activities, in all age groups, and in both sexes (p < 0.001). Compared to peers, prevalence of problems in anxiety/depression was most prominent in female Discussion (16.7% vs. 50.3%; Fig. 1b) and in younger patients (9.8% vs. 40.8%, p < 0.001; Fig. 2a). Restrictions in This prospective cohort observational study adds substantial mobility were most pronounced in male (Fig. 1a) and in information on the prevalence and clustering of restrictions 1388 R. Stauder et al. Fig. 2 Proportion of moderate/ severe problems by age group (<60 (a), 60–75 (b), or >75 (c) years old) in patients with MDS (blue bars) as compared to European age- and sex-matched standard population (dark grey). Standard errors indicated as lines. Differences (Δ) of patients with MDS to sex-matched reference group shown when signiﬁcant (***p < 0.001; **p < 0.01; *p < 0.05; as assessed by Wilcoxon signed rank tests) in HRQoL in lower-risk patients with MDS at diagnosis. In with European reference populations. Moreover, we iden- a cross-sectional analysis, we observed profound restric- tiﬁed demographic and clinical factors, which are associated tions in distinct dimensions of the EQ-5D when compared with restrictions in HRQoL. Health-related quality of life in lower-risk MDS patients compared with age- and sex-matched. . . 1389 Prevalence of restrictions in HRQoL in MDS at initial populations is possible. This study reveals an incremental diagnosis / Factors associated with decreased symptom burden in MDS characterized by pronounced age- HRQoL and sex-dependent differences in the distinct EQ-5D dimensions. Both young and old patients suffer from trou- Data on symptom burden in lower-risk MDS at initial blesome MDS-related symptoms. Data from the literature presentation are rare, and limited by small sample size [16, are rare and have been characterized by a small sample size 17], selection bias [7, 16, 17], and analyses performed later and were restricted to one country [16, 17]. The study of after initial diagnosis [7, 11, 16, 18, 19]. In addition, most Hellstrom evaluated HRQoL at later time points after studies have included patients with higher risk MDS [9–11, diagnosis, and was focused on selecting anaemic patients 16, 18–20], AML [10, 11] or CMML [11, 16], which pre- with a high probability for response to ESAs for a clinical cludes precise interpretation. The strength of our study is study . The study of Jansen  reported exclusively the large number of observations at initial diagnosis and the EQ-5D VAS but lacked a presentation of EQ-5D daily parallel analysis of the different parameters of the validated activities for which we show strong differences. Moreover, score EQ-5D including EQ-5D VAS, EQ-5D index as well patients in Jansen's study were entered at variable time as the different EQ-5D dimensions in a homogenous cohort points after diagnosis, and included patients with higher risk of lower-risk patients. This is the ﬁrst report to present MDS and CMML . details on restrictions in the distinct domains of EQ-5D in The high prevalence of anxiety/depression and of MDS, which reveals huge differences in HRQoL-proﬁle in limitations in usual activities is more pronounced in women daily activities. These ﬁndings are particularly relevant, as in our study. These observations form the basis to studies from the literature reported exclusively EQ-5D appreciate the relevance of MDS on individual health in a summary scores and EQ-5D VAS [16, 20], but lacked a given patient and the opportunity to assist health care pro- presentation of EQ-5D daily activities. viders in managing the relevant symptoms . Thus, Our study shows a pronounced symptom burden in many patient-centred care will be improved by special attention to patients with MDS, predominantly in the dimensions pain/ patient subgroups [29, 30]. The ﬁnding of the difference of discomfort, mobility, anxiety/depression, and usual activities. depression between our MDS patients and the general Moreover, a clustering of symptoms in distinct subgroups of population is corroborated by similar evidence in other patients is revealed. The low percentage of self-reported haematologic conditions. For example, Efﬁcace et al.  problems in the dimension self-care, particularly in elderly is observed that depression was one of the most impaired remarkable. This phenomenon has been observed across psychological domains in a sample of chronic myeloid different cancer types  and may be explained by focusing leukaemia patients as compared to their peers in the general on “washing and dressing” in the deﬁnition of self-care, population; and, similar to our ﬁndings, this impairment whereas functional capacities like “work, housework, family was most pronounced in female patients. In agreement with or leisure activities” are assessed in the dimension “usual other studies [8, 32, 33], differences by gender were activities”. observed with lower HRQoL being more pronounced in We demonstrated that advanced age, pronounced females. Although the discussion of causes of disparity in co-morbidities, low Hb-levels, RBCT need, and female sex gender-based distribution is beyond the scope of this were signiﬁcantly associated both with a decreased EQ-5D manuscript, gender-speciﬁc evaluations and interventions index, and decreased EQ-VAS after adjustment for should be discussed or suggested in patients with MDS. co-variables. These observations extend data from the The relevance of anxiety/depression in patients with MDS literature [7, 8, 18, 20] and deﬁne cohorts of patients which is supported by the fact that 9.5% of EU-MDS patients are at high risk of decreased HRQoL. Hb levels [7, 18, 20] receive antidepressants at baseline , and that impairments and transfusion dependence  are important predictors in depression screening by geriatric depression scale (GDS) of HRQoL, both in this study and in the literature. are observed in 24% of patients with MDS . Likewise Effective treatment for anaemia and reduction of transfusion “emotional health” and “uncertainty/sense of control” have need might thus contribute to improvement and main- been highly ranked by patients and caregivers in a recent tenance of HRQoL . Future studies will focus on the study . To address the individual needs of patients with prediction of deterioration of HRQoL, and focus on early MDS, the novel, disease speciﬁc score for MDS, QUALMS prevention. [18, 35], is currently applied and validated in the A relevant aspect of our work is the signiﬁcant difference EUMDS-cohort. Our study also conﬁrms that age- and in symptom burden in patients with MDS as compared to sex-dependent baseline values in HRQoL should be age- and sex matched European reference populations. considered when interpreting the results of clinical studies Thus, dissection of features which are MDS-speciﬁc from in MDS that use HRQoL as an endpoint, as suggested symptoms which are present in matched general recently [4, 8]. 1390 R. Stauder et al. Strengths of this work are the large number of observa- (TRIAGE-MDS) (TRIAGE-MDS, Austrian Science Found I 1576) within the TRANSCAN - Primary and secondary prevention of cancer tions, the well-deﬁned inclusion criteria in a non- call (ERA Net). interventional registry, the enclosure of newly diagnosed MDS patients within 100 days of the date of the diagnostic Author contributions Explanation of author contributions: conception and design: TdW, DB, SL, ASi, RS, JC, PF, UG, MSH, AG, LM, KM, bone marrow aspirate, and the parallel analysis of the dif- ASa, GS, EH, CvM; collection and assembly of data: all co-authors; ferent parameters of the validated generic score EQ-5D data analysis and/or interpretation: RS, KK, CvM, GY, AS, TDW; . Based on the use of a generic questionnaire, com- manuscript writing: all co-authors; ﬁnal approval of manuscript: all co- parisons with reference populations are possible. authors. Limitations: Disease-speciﬁc scores may more accurately reﬂect the spectrum in a given disease. To address this Compliance with ethical standards aspect, the MDS-speciﬁc score QUALMS has been devel- Conﬂict of interest This study was carried out within the EUMDS oped recently [18, 35]. QUALMS has been integrated in Registry which is supported by Novartis Oncology. T. de Witte is the EUMDS in a recently amended version of the protocol. project leader and C. van Marrewijk is the project manager of the Based on objectives of this study and the EUMDS registry, EUMDS Registry. Outside the funding by Novartis Oncology, the analyses have been restricted to IPSS lower-risk MDS. following co-authors report grants or personal fees: R. Stauder received research funding and honoraria from Celgene, Teva and Therefore, this study does not allow conclusions on MDS in Novartis. T. de Witte reports grants from Celgene, personal fees from general. However, the recently introduced new protocol of Incyte, personal fees from Amgen, personal fees from Incyte outside the registry will register all subtypes of MDS. Other aspects the submitted work. G. Sanz reports personal fees by Celgene. M. of HRQoL, which might be relevant for the outcome of Mittelmann reports personal fees by Oﬁzer, Amgen, research grants by Celgene/Neopharm, and advisory roles for Celgene, Amgen, and patients, e.g., the deterioration of HRQoL over time, have Janssen. A. Savic personal fees by Seattle Genetics, Novo Nordisk, not yet been analyzed. These investigations are currently and Amgen. F. Efﬁcace reports personal fees by Bristol-Myers Squibb, performed in several studies focusing on the impact of Seattle Genetics, TEVA and Incyte; and research funding by Lund- beck, TEVA, and Amgen. The remaining authors declare that they speciﬁc interventions on HRQoL. have no conﬂict of interest. In summary Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, This is the ﬁrst study to analyze prospectively the PRO adaptation, distribution and reproduction in any medium or format, as HRQoL in IPSS lower-risk MDS at diagnosis, and to long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if compare patients with MDS with age- and sex-matched changes were made. The images or other third party material in this healthy populations. Patients experience profound age- and article are included in the article’s Creative Commons license, unless sex-dependent restrictions in different HRQoL dimensions. indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended Distinct demographic and disease parameters are associated use is not permitted by statutory regulation or exceeds the permitted with reduced HRQoL. These observations should form the use, you will need to obtain permission directly from the copyright basis for individualized treatment directed at relief of dis- holder. To view a copy of this license, visit http://creativecommons. tinct symptoms. In addition, these results may provide a org/licenses/by/4.0/. benchmark in the evaluation of new interventional options aimed at improving HRQoL outcomes. References Supplementary Materials is available at Leukaemia (www.nature.com/leu) providing additional information 1. Malcovati L, Hellstrom-Lindberg E, Bowen D, Ades L, Cermak J, Del Canizo C, et al. Diagnosis and treatment of primary myelo- regarding (i) EQ-5D index and EVS; (ii) on the comparison dysplastic syndromes in adults: recommendations from the Eur- of patients with MDS and the reference population; (iii) on opean LeukemiaNet. Blood. 2013;122:2943–64. multivariate analysis; and (iiii) on minimally important 2. Greenberg P, Cox C, LeBeau MM, Fenaux P, Morel P, Sanz G, difference (MID). et al. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood. 1997;89:2079–88. 3. Greenberg PL, Tuechler H, Schanz J, Sanz G, Garcia-Manero G, Acknowledgements This study was only feasible thanks to the major Sole F, et al. Revised international prognostic scoring system for contributions by all colleagues and patients from participating myelodysplastic syndromes. Blood. 2012;120:2454–65. institutions. 4. Wildiers H, Heeren P, Puts M, Topinkova E, Janssen-Heijnen ML, Extermann M, et al. International Society of Geriatric Oncology Funding This study was carried out within the EUMDS Registry consensus on geriatric assessment in older patients with cancer. J which is supported by an educational grant from Novartis Pharmacy B. Clin Oncol. 2014;32:2595–603. V. Oncology Europe. This study was supported by Horizon 2020 5. Bottomley A, Pe M, Sloan J, Basch E, Bonnetain F, Calvert M, research and innovation program, grant agreement No 634789, MDS- et al. Analysing data from patient-reported outcome and quality of RIGHT, within Personalizing health and care program PHC-2014- life endpoints for cancer clinical trials: a start in setting interna- 634789. Additionally, this study was supported by Translational tional standards. Lancet Oncol. 2016;17:e510–4. Implementation of genetic evidence in the management of MDS Health-related quality of life in lower-risk MDS patients compared with age- and sex-matched. . . 1391 6. Patel SS, Gerds AT. Patient-reported outcomes in myelodysplastic improve the prognostic value of the international prognostic syndromes and MDS/MPN overlap syndromes: stepping onto the scoring system for MDS in older adults. J Geriatr Oncol. stage with changing times. Curr Hematol Malig Rep. 2015;6:288–98. 2017;12:455–60. 20. Oliva EN, Finelli C, Santini V, Poloni A, Liso V, Cilloni D, et al. 7. Steensma DP, Heptinstall KV, Johnson VM, Novotny PJ, Sloan Quality of life and physicians’ perception in myelodysplastic JA, Camoriano JK, et al. Common troublesome symptoms and syndromes. Am J Blood Res. 2012;2:136–47. their impact on quality of life in patients with myelodysplastic 21. de Swart L, Smith A, Johnston TW, Haase D, Droste J, Fenaux P, syndromes (MDS): results of a large internet-based survey. Leuk et al. Validation of the revised international prognostic scoring Res. 2008;32:691–8. system (IPSS-R) in patients with lower-risk myelodysplastic 8. Efﬁcace F, Gaidano G, Breccia M, Criscuolo M, Cottone F, syndromes: a report from the prospective European LeukaemiaNet Caocci G, et al. Prevalence, severity and correlates of fatigue in MDS (EUMDS) registry. Br J Haematol. 2015;170:372–83. newly diagnosed patients with myelodysplastic syndromes. Br J 22. Brooks R. EuroQol: the current state of play. Health Policy. Haematol. 2015;168:361–70. 1996;37:53–72. 9. Efﬁcace F, Gaidano G, Breccia M, Voso MT, Cottone F, Ange- 23. Greiner W, Weijnen T, Nieuwenhuizen M, Oppe S, Badia X, lucci E, et al. Prognostic value of self-reported fatigue on overall Busschbach J, et al. A single European currency for EQ-5D health survival in patients with myelodysplastic syndromes: a multi- states. Results from a six-country study. Eur J Health Econ. centre, prospective, observational, cohort study. Lancet Oncol. 2003;4:222–31. 2015;16:1506–14. 24. Langelaan M, de Boer MR, van Nispen RM, Wouters B, Moll 10. Deschler B, Ihorst G, Platzbecker U, Germing U, Marz E, de AC, van Rens GH. Impact of visual impairment on quality of life: Figuerido M, et al. Parameters detected by geriatric and quality of a comparison with quality of life in the general population and life assessment in 195 older patients with myelodysplastic syn- with other chronic conditions. Ophthalmic Epidemiol. dromes and acute myeloid leukemia are highly predictive for 2007;14:119–26. outcome. Haematol. 2013;98:208–16. 25. Szende A, Williams A. Measuring self-reported population health 11. Buckstein R, Wells RA, Zhu N, Leitch HA, Nevill TJ, Yee KW, —an International Perspective based on EQ-5D. EuroQol Group, et al. Patient-related factors independently impact overall survival 2012. in patients with myelodysplastic syndromes: an MDS-CAN pro- 26. Lubetkin EI, Jia H, Franks P, Gold MR. Relationship among spective study. Br J Haematol. 2016;174:88–101. sociodemographic factors, clinical conditions, and health-related 12. Efﬁcace F, Cottone F, Abel G, Niscola P, Gaidano G, Bonnetain quality of life: examining the EQ-5D in the U.S. general popu- F, et al. Patient-reported outcomes enhance the survival prediction lation. Qual Life Res. 2005;14:2187–96. of traditional disease risk classiﬁcations: an international study in 27. Jaeschke R, Singer J, Guyatt GH. Measurement of health status. patients with myelodysplastic syndromes. Cancer. https://doi.org/ Ascertaining the minimal clinically important difference. Control 10.1002/cncr.3119, 2017. Clin Trials. 1989;10:407–15. 13. Cannella L, Caocci G, Jacobs M, Vignetti M, Mandelli F, Efﬁcace 28. Pickard AS, Jiang R, Lin H-W, Rosenbloom S, Cella D. Using F. Health-related quality of life and symptom assessment in ran- patient-reported outcomes to compare relative burden of cancer: domized controlled trials of patients with leukemia and myelo- EQ-5D and functional assessment of cancer therapy-general in dysplastic syndromes: What have we learned? Crit Rev Oncol eleven types of cancer. Clin Ther. 2016;38:769–77. Hematol. 2015;96:542–54. 29. Frosch ZA, Abel GA. Assessing quality of care for the myelo- 14. Cheson BD, Bennett JM, Kantarjian H, Pinto A, Schiffer CA, dysplastic syndromes. Curr Hematol Malig Rep. 2016;11:402–7. Nimer SD, et al. Report of an international working group to 30. Burgstaller S, Wiesinger P, Stauder R. Myelodysplastic syn- standardize response criteria for myelodysplastic syndromes. dromes in the elderly: treatment options and personalized man- Blood. 2000;96:3671–4. agement. Drugs Aging. 2015;32:891–905. 15. Dueck AC, Mendoza TR, Mitchell SA, Reeve BB, Castro KM, 31. Efﬁcace F, Breccia M, Cottone F, Okumura I, Doro M, Riccardi F, Rogak LJ, et al. Validity and reliability of the US National Cancer et al. Psychological well-being and social support in chronic Institute’s Patient-Reported Outcomes Version of the Common myeloid leukemia patients receiving lifelong targeted therapies. Terminology Criteria for Adverse Events (PRO-CTCAE). JAMA Support Care Cancer. 2016;24:4887–94. Oncol. 2015;1:1051–9. 32. Wang XS, Cleeland CS, Mendoza TR, Yun YH, Wang Y, 16. Jansen AJ, Essink-Bot ML, Beckers EA, Hop WC, Schipperus Okuyama T, et al. Impact of cultural and linguistic factors on MR, Van Rhenen DJ. Quality of life measurement in patients with symptom reporting by patients with cancer. J Natl Cancer Inst. transfusion-dependent myelodysplastic syndromes. Br J Haema- 2010;102:732–8. tol. 2003;121:270–4. 33. Valentiny C, Kemmler G, Stauder R. Age, sex and gender impact 17. Hellstrom-Lindberg E, Gulbrandsen N, Lindberg G, Ahlgren T, multidimensional geriatric assessment in elderly cancer patients. J Dahl IMS, Dybedal I, et al. A validated decision model for Geriatr Oncol. 2012;3:17–23. treating the anaemia of myelodysplastic syndromes with ery- 34. Hamaker ME, Mitrovic M, Stauder R. The G8 screening tool thropoietin plus granulocyte colony-stimulating factor: signiﬁcant detects relevant geriatric impairments and predicts survival in effects on quality of life. Br J Haematol. 2003;120:1037–46. elderly patients with a haematological malignancy. Ann Hematol. 18. Abel GA, Efﬁcace F, Buckstein RJ, Tinsley S, Jurcic JG, Martins 2014;93:1031–40. Y, et al. Prospective international validation of the Quality of Life 35. Abel GA, Klaassen R, Lee SJ, Young NL, Cannella L, Steensma in Myelodysplasia Scale (QUALMS). Haematol. 2016;101: DP, et al. Patient-reported outcomes for the myelodysplastic 781–8. syndromes: a new MDS-speciﬁc measure of quality of life. Blood. 19. Fega KR, Abel GA, Motyckova G, Sherman AE, DeAngelo DJ, 2014;123:451–2. Steensma DP, et al. Non-hematologic predictors of mortality 1392 R. Stauder et al. Afﬁliations 1 2 1 2 3 4 ● ● ● ● ● ● Reinhard Stauder Ge Yu Karin A. Koinig Tim Bagguley Pierre Fenaux Argiris Symeonidis 5,6 7 8 9 10 ● ● ● ● ● Guillermo Sanz Jaroslav Cermak Moshe Mittelman Eva Hellström-Lindberg Saskia Langemeijer 11 12 13 14 15 16 ● ● ● ● ● ● Mette Skov Holm Krzysztof Mądry Luca Malcovati Aurelia Tatic Ulrich Germing Aleksandar Savic 10 17 18 10 19 2 ● ● ● ● ● ● Corine van Marrewijk Agnès Guerci-Bresler Elisa Luño Jackie Droste Fabio Efﬁcace Alex Smith 20 21 David Bowen Theo de Witte Department of Internal Medicine V (Hematology and Oncology), Department of Hematology, Oncology and Internal Medicine, Medical University Innsbruck, Innsbruck, Austria Warszawa Medical University, Warszawa, Poland Epidemiology and Cancer Statistics Group, Department of Health Department of Hematology Oncology, Fondazione IRCCS Sciences, University of York, New York, United Kingdom Policlinico San Matteo, University of Pavia, Pavia, Italy Service d’Hématologie, Hôpital Saint-Louis, Assistance Publique Center of Hematology and Bone Marrow Transplantation, Fundeni des Hôpitaux de Paris (AP-HP) and Université Paris 7, Clinical Institute, Bucharest, Romania Paris, France Department of Hematology, Oncology and Clinical Immunology, Department of Medicine, Division of Hematology, University of Universitätsklinik Düsseldorf, Düsseldorf, Germany Patras Medical School, Patras, Greece Clinic of Hematology - Clinical Center of Vojvodina, University Department of Hematology, Hospital Universitario y Politécnico of Novi Sad, Novi Sad, Serbia La Fe, Valencia, Spain Service d’Hématologie, Center Hospitalier Universitaire Brabois CIBERONC, Instituto Carlos III, Madrid, Spain Vandoeuvre, Nancy, France Department of Clinical Hematology, Institute of Hematology & Servicio d’Hematología, Servicio de Salud del Principado de Blood Transfusion, Praha, Czech Republic Asturias Oviedo, Oviedo, Spain Department of Medicine A, Tel Aviv Sourasky (Ichilov) Medical Fondazione GIMEMA Onlus, Rome, Italy Center and Sackler Medical Faculty, Tel Aviv University, Tel Aviv, Israel St. James’s Institute of Oncology, Leeds Teaching Hospitals, Leeds, United Kingdom Department of Medicine, Division of Hematology, Karolinska Institutet, Stockholm, Sweden Department of Tumor Immunology - Nijmegen Center for Molecular Life Sciences, Radboud University Medical Center, Department of Hematology, Radboud University Medical Center, Nijmegen, Netherlands Nijmegen, Netherlands Department of Hematology, Aarhus University Hospital, Aarhus, Denmark
Leukemia – Springer Journals
Published: Mar 6, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera