Health-Related Quality of Life as Assessed by the EQ-5D-5L Predicts Outcomes of Patients Treated with Azacitidine—A Prospective Cohort Study by the AGMT
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Lisa Pleyer
1,2,3,*,
Sonja Heibl
1,4,
Christoph Tinchon
1,5,
Sonia Vallet
1,6, 
Martin Schreder
1,7,
Thomas Melchardt
1,2,3,
Norbert Stute
1,2,3,
Kim Tamara Föhrenbach Quiroz
2,
Michael Leisch
1,2,3,
Alexander Egle
1,2,3,
Lukas Scagnetti
1,4,
Dominik Wolf
1,8,
Richard Beswick
9,
Manuel Drost
10,
Julian Larcher-Senn
10,
Thomas Grochtdreis
11
,
Marc Vaisband
1,2,12,
Jan Hasenauer
12,
Nadja Zaborsky
2,3,13,
Richard Greil
1,2,3,† and
Reinhard Stauder
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1
Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
2
Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), Austria and Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
3
3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
4
4th Medical Department of Internal Medicine, Hematology, Internistic Oncology and Palliative Medicine, Klinikum Wels-Grieskirchen GmbH, 4600 Wels, Austria
5
Department for Hemato-Oncology, LKH Hochsteiermark, 8700 Leoben, Austria
6
Department of Internal Medicine 2, University Hospital Krems, Karl Landsteiner Private University of Health Sciences, 3500 Krems, Austria
7
1st Department of Internal Medicine, Center for Oncology and Hematology, Klinik Ottakring, Wiener Gesundheitsverbund, 1030 Vienna, Austria
8
Department of Internal Medicine V, Innsbruck Medical University, 6020 Innsbruck, Austria
9
International Marketing, Swiss Business School, 8302 Zurich, Switzerland
10
Assign Data Management and Biostatistics GmbH, 6020 Innsbruck, Austria
11
Department of Health Economics and Health Services Research, Hamburg Center for Health Economics, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
12
Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
13
Laboratory of Immunological and Molecular Cancer Research (LIMCR), 5020 Salzburg, Austria
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Cancers 2023, 15(5), 1388; https://doi.org/10.3390/cancers15051388
Submission received: 24 January 2023
/
Revised: 10 February 2023
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Accepted: 17 February 2023
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Published: 22 February 2023
(This article belongs to the Collection Acute Myeloid Leukemia (AML))
Abstract
:Simple Summary
The EuroQol 5-Dimension 5-level (EQ-5D-5L) questionnaire is a globally used and multiply validated tool to assess health-related quality of life (HRQoL), but data on its use for patients with myeloid neoplasias is scarce. The aim of this prospective cohort study was to alleviate this knowledge gap. Our data show in a homogenous population of azacitidine-treated patients for the first time that (1) myeloid patients have significantly worse HRQoL than a population norm (i.e., a representative sample of the German general adult population) from a similar geographic region, matched by age, sex and number of comorbidities; (2) The EQ-5D-5L questionnaire response provides added prognostic value to the International Prognostic Scoring System (IPSS) and the revised IPSS (R-IPSS), which are longstanding gold standards of prognostication in these diseases; (3) the multivariate-adjusted significant predictive value of the EQ-5D-5L response parameters on patient outcomes including response to azacitidine, time to next treatment and overall survival; (4) longitudinal assessment of the EQ-5D-5L response/clinical parameter pairs revealed significant additional, independent associations.
Abstract
In this prospective study (NCT01595295), 272 patients treated with azacitidine completed 1456 EuroQol 5-Dimension (EQ-5D) questionnaires. Linear mixed-effect modelling was used to incorporate longitudinal data. When compared with a matched reference population, myeloid patients reported more pronounced restrictions in usual activities (+28%, p < 0.0001), anxiety/depression (+21%, p < 0.0001), selfcare (+18%, p < 0.0001) and mobility (+15%, p < 0.0001), as well as lower mean EQ-5D-5L indices (0.81 vs. 0.88, p < 0.0001), and lower self-rated health on the EuroQol Visual Analogue Scale (EQ-VAS) (64 vs. 72%, p < 0.0001). After multivariate-adjustment, (i) the EQ-5D-5L index assessed at azacitidine start the predicted time with clinical benefit (TCB) (9.6 vs. 6.6 months; p = 0.0258; HR = 1.43), time to next treatment (TTNT) (12.8 vs. 9.8 months; p = 0.0332; HR = 1.42) and overall survival (OS) (17.9 vs. 12.9 months; p = 0.0143; HR = 1.52); (ii) Level Sum Score (LSS) predicted azacitidine response (p = 0.0160; OR = 0.451) and the EQ-5D-5L index showed a trend (p = 0.0627; OR = 0.522); (iii) up to 1432 longitudinally assessed EQ-5D-5L response/clinical parameter pairs revealed significant associations of EQ-5D-5L response parameters with haemoglobin level, transfusion dependence and hematologic improvement. Significant increases of the likelihood ratios were observed after addition of LSS, EQ-VAS or EQ-5D-5L-index to the International Prognostic Scoring System (IPSS) or the revised IPSS (R-IPSS), indicating that they provide added value to these scores.
Keywords:
health-related quality of life (HRQoL); patient-reported outcome (PRO); EuroQol 5-Dimension 5-Level questionnaire (EQ-5D-5L); azacitidine; Austrian Registry of Hypomethylating Agents; prognosis; mixed-effects linear models; acute myeloid leukaemia; myelodysplastic syndromes; chronic myelomonocytic leukaemia1. Introduction
Azacitidine is the first treatment to be associated with improved overall survival (OS), and to be approved by both US and European regulatory authorities for the treatment of patient subgroups with myeloid neoplasms. In patients with myelodysplastic syndromes (MDS) [1,2] and chronic myelomonocytic leukaemia (CMML) [3], it remains the only approved disease-modifying therapeutic substance, whereas several new drugs have recently been approved for certain patient subgroups with acute myeloid leukaemia (AML).
Globally, there has been a distinctive shift towards taking patient perspectives into account when making (regulatory) healthcare and treatment decisions. Traditional clinical ways of measuring health and the effects of treatment are thus increasingly being accompanied by patient-reported outcome measures. In the broad field of the latter, the generic EuroQol 5-Dimension (EQ-5D) questionnaire is multiply validated and globally has been the most used tool in many areas of medicine, including oncology, for over three decades.
Although regulatory agencies offered guidance for the use of patient-reported outcome measures to support labelling claims as early as 2005 [4,5,6,7], the European LeukemiaNet pointed to the importance of assessing HRQoL in the clinical management of patients with MDS in 2013 [8], and the EQ-5D has been the preferred measure of HRQoL for the UK National Institute for Health and Care Excellence since 2008, published reports on HRQoL data in MDS, CMML and AML are scarce. There are 4 publications in MDS, and 10 in AML, 13 of which only report on the mean EQ-VAS and/or the mean or median EQ-5D-5L index value. Only one report assessed the impact of the EQ-5D-5L index on a time-to-event endpoint [9], and only one publication provided details on non-composite results [10], both in patients with lower-risk MDS (Table 1). Publications correlating EQ-5D-5L measures with treatment outcomes in general, and with azacitidine-related outcomes in particular, are lacking to date. The only detailed EQ-5D-5L data on this topic stem from this report.
In this prospective study, we compared EQ-5D-5L responses between patients with MDS, CMML and AML and a population norm (i.e., a representative sample of the German general adult population without myeloid (or other) neoplasias) from a similar geographic region, matched by age, sex and number of comorbidities. In myeloid patients treated with azacytidine within the Austrian Registry of Hypomethylating Agents, we performed more detailed analyses and assessed (1) whether EQ-5D-5L composite variables provided added value to the (R)-IPSS; (2) there might be a predictive value of EQ-5D-5L composite variables (including LSS, EQ-VAS and EQ-5D-5L index value) on the response to azacitidine and several time-to-event endpoints; and (3) performed longitudinal assessments of EQ-5D-5L response/clinical parameter pairs.
2. Materials and Methods
2.1. Study Design and Participants
In this prospective cohort study, data from non-selected, consecutive patients were provided by seven Austrian centres (Supplementary p. 1) participating in the Austrian Registry of Hypomethylating Agents of the Austrian Group for Medical Tumour Therapy (AGMT) Study Group (NCT01595295; ethics committee approval 415-EP/39/Feb-2009; details published previously [23,24]; Figure 1).
The EQ-5D consists of five questions (also known as dimensions (5D): mobility, selfcare, usual activities, pain/discomfort, anxiety/depression) with 5 levels (5L) of problem severity in the responses, as well as a Visual Analogue Scale (EQ-VAS) aiming to capture a respondents’ rating of their ‘health today’ on a scale from 0–100. The composite scores Level Sum Score (LSS) and EQ-5D-5L index are explained in Supplementary p. 2. The EQ-5D questionnaires were assessed at the start of azacitidine treatment cycles. The EQ-5D-5L results of patients diagnosed with MDS, CMML or AML were compared with those of a German population norm (i.e., a representative sample of the German general adult population without myeloid (or other) neoplasias) [28]. The EQ-5D-5L German value set [29] and the reverse crosswalk tool provided by EuroQol on November 16, 2020 were used for calculation of the EQ-5D-5L indices (Supplementary p. 3).
Patients with an EQ-5D available at azacitidine treatment start were stratified according to their LSS, EQ-VAS or EQ-5D-5L index being </≥ the respective group median.
2.2. Statistical Analyses
Only observed values were analysed. Baseline and treatment-related factors were compared using the χ2 test for categorical variables and the Wilcoxon test for continuous variables. Patient subgroups were compared using the log-rank test. All p-values and 95% CIs are two-sided. The threshold for statistical significance was 0.05. Time-to-event endpoints were analysed using the Kaplan–Meier method.
Proceeding in analogy to Efficace et al. [30] who demonstrated that self-reported fatigue provided added value to the IPSS and R-IPSS in patients with MDS, the likelihood ratio (LHR) test was used to determine whether EQ-5D-5L response parameters provided added value to the IPSS or R-IPSS.
The prognostic information provided by LSS, EQ-VAS and EQ-5D-5L index, with regards to whether a patient is likely to respond to azacitidine or not was assessed by univariate and multivariate-adjusted logistic regression analyses. Cox regression models for time-to-event endpoints were applied.
To identify variables that might be associated with patient-reported outcomes, linear mixed-effect modelling was utilised, with patient identity as the grouping variable. p-values were visualised using heatmaps.
Sensitivity analyses were performed to check the general conclusions by assessing different endpoints (response subtypes, OS, TCB, TTNT), and assessing both continuous and dichotomised variables. The definition of outcomes and further statistical details are given in Supplementary pp. 4–7.
Assign Data Management and Biostatistics GmbH performed statistical analyses with SAS® 9.4. The Life & Medical Sciences Institute, University of Bonn performed statistical analyses including mixed-effect linear modelling with Python 3.8.12.
3. Results
3.1. Myeloid Patient Characteristics
Data from 272 patients diagnosed with MDS, CMML or AML who were treated with azacitidine between 21 May 2007 and 21 December 2020 were prospectively analysed (Figure 1). Of these, 205 had filled out an EQ-5D at azacitidine treatment start (Figure 1). This subset was used for time-to-event endpoint analyses.
Myeloid patient characteristics at azacitidine treatment start by EQ-5D group are shown in Supplementary p. 8. In the group, 129 (47%), 33 (12%) and 110 (40%) of 272 patients had MDS, CMML or AML, respectively. A total of 168 (62%) of 272 patients were male, the median age was 74.0 (IQR 69.0–79.0) years, 33 (12%) had treatment-related disease, 51 (19%) had an ECOG performance score of ≥2 and median bone marrow blasts were 12% (IQR 5–35%). Differential blood count and other lab values of the EQ-5D group are shown in Supplementary pp. 9–10. A further 86 (32%) and 35 (13%) of 272 patients were red blood cell and/or platelet transfusion dependent, respectively (Supplementary pp. 9–10). Finally, 205 (75%) of 272 patients had at least one additional comorbidity (Supplementary p. 11).
Azacitidine treatment and response characteristics are shown in Supplementary pp. 12–13. Median follow-up duration from diagnosis was 23.4 months (IQR 12.3–40.9) and from azacitidine treatment start 14.7 months (7.8–26.7).
3.2. Patients Treated with Azacitidine Reveal Profound Impairments in HRQoL
Supplementary pp. 14–15 show the most frequent response patterns for questionnaires filed out at azacitidine treatment start and for all EQ-5D questionnaires. Supplementary p. 16 gives an overview of the EQ-5D responses by patient group, response status and number of azacitidine treatment cycles. The mean number of filled-out EQ-5D questionnaires per patient was 5.4 (SD 6.2), the median number was 3.0 (IQR 1.0–3.0).
The myeloid cohort (n = 272) was characterised by mean (SD) LSS, EQ-5D-5L index value and EQ-VAS of 9.1 (3.9), 0.807 (0.232) and 63.9 (21.7), respectively, in their first available EQ-5D-5L questionnaire; results were similar when focusing on patients who had filled out an EQ-5D at azacitidine treatment start (n = 205) (Table 2). In this subgroup, problems (slight, moderate, severe or extreme) were self-reported in the dimensions of mobility (104 (51%) of 205), selfcare (46 (22%)), usual activities (120 (59%)), pain/discomfort (102 (50%)) and anxiety/depression (100 (49%)).
The following parameters at azacitidine treatment start significantly correlated with adverse EQ-5D-5L responses: monocytes ≥10%, haemoglobin levels <10 g/dL, >3 red blood cell transfusions prior to azacitidine start, Eastern Cooperative Oncology Group Performance Status (ECOG-PS) of ≥2, high risk Hematopoietic Cell Transplantation-specific Comorbidity Index (HCT-CI) (Table 2). For example, patients with an ECOG-PS ≥2 experienced more significantly problems in the dimensions of mobility (+30%, p = 0.0008), selfcare (+34%, p < 0.0001), usual activities (+28%, p = 0.0012) and anxiety/depression (+32%, p = 0.0003), and had significantly reduced EQ-VAS (−10%, p = 0.0092) (Figure 2).
3.3. Comparison of HRQoL with a Reference Population Matched by Age, Sex and Number of Comorbidities
We compared HRQoL of the myeloid cohort with that of a German population norm (i.e., a representative sample of the German general adult population without myeloid (or other) neoplasias) [28] with a similar ethnical and socioeconomic background (Figure 1). Myeloid patients reported more pronounced restrictions in mobility (51 vs. 35%, p < 0.0001), selfcare (25 vs. 7%, p < 0.0001), usual activities (56 vs. 28%, p < 0.0001) and anxiety/depression (+15%, p < 0.0001), as well as lower mean EQ-5D-5L indices (0.81 vs. 0.88, p < 0.0001) and lower self-rated health on EQ-VAS (64 vs. 72%, p < 0.0001) than the German population norm (Table 3). These significant differences could also be observed after stratification by age group, sex or number of comorbidities (Table 3).
3.4. IPSS and R-IPSS Prognosticate OS and TTNT
Myeloid patients with lower-risk IPSS had significantly longer unadjusted survival than patients with higher-risk IPSS (21.0 months [95% CI 14.6–30.3] vs. 12.8 months [10.2–16.9]; HR = 0.62 [0.44–0.88]; LHR 7.32; p = 0.0068). Similarly, patients with lower-risk R-IPSS had significantly longer unadjusted survival than patients with higher-risk R-IPSS (30.3 months [11.2–39.3] vs. 14.6 months [11.9–17.8]; HR = 0.561 [0.3320.949]; LHR 5.37; p = 0.0205) (Table 4, first four columns).
Patients with lower-risk IPSS showed a trend towards longer TTNT (p = 0.0578), and patients with lower-risk R-IPSS showed significantly longer TTNT than their higher-risk counterparts (17.6 months [6.9–37.7] vs. 10.8 months [9.3–12.6]; HR = 0.615 [0.379–1.000]; LHR 4.31; p = 0.0379) (Table 4, first 4 columns).
3.5. EQ-5D-5L Composite Scores at Azacitidine Start Provide Added Value to the (R)-IPSS
For the endpoint OS, significant increases of the likelihood ratio (LHR) were observed after addition of (i) the LSS to the IPSS (LHR increased from 7.32 to 10.69; p = 0.0048) or the R-IPSS (LHR increased from 5.37 to 9.05; p = 0.0108); (ii) the EQ-VAS to the IPSS (LHR increased from 7.32 to 11.56; p = 0.0031) or the R-IPSS (LHR increased from 5.37 to 10.28; p = 0.0058); (iii) the EQ-5D-5L index to the IPSS (LHR increased from 7.32 to 13.02; p = 0.0015) or the R-IPSS (LHR increased from 5.37 to 13.48; p = 0.0012), indicating that they provided added value to the IPSS and R-IPSS (Table 4, grey shaded columns).
For the endpoint TTNT, significant increases of the LHR were observed after addition of (i) the LSS to the R-IPSS (LHR increased from 4.31 to 7.74; p = 0.0209); (ii) the EQ-VAS to the R-IPSS (LHR increased from 4.31 to 6.85; p = 0.0327); (iii) the EQ-5D-5L index to the IPSS (LHR increased from 3.60 to 6.38; p = 0.0411) or the R-IPSS (LHR increased from 4.31 to 6.55; p = 0.0378), indicating that they provided added value to the IPSS and R-IPSS (Table 4, grey shaded columns).
3.6. EQ-5D-5L Composite Scores at Azacitidine Start Impact Time-to-Event Endpoints
Myeloid patients with an EQ-5D available at azacitidine treatment start (n = 205) were stratified according to their LSS, EQ-VAS or EQ-5D-5L index being </≥ the respective group median. In unadjusted analyses, patients with (i) an LSS < 8.0 at azacitidine treatment start had significantly longer OS and showed a trend for longer TCB and TTNT; (ii) an EQ-VAS < 65 at azacitidine treatment start had significantly longer OS; (iii) an EQ-5D-5L index ≥0.8845 had significantly longer OS, longer TCB and longer TTNT (Table 5, first four columns) (Figure 3A,C,E).
After multivariate adjustment (for ECOG-PS, number of comorbidities, platelet count ≤30 G/L or transfusion dependence, peripheral blood blasts, azacitidine treatment line and azacitidine dose in cycle one) patients with an EQ-5D-5L index above the group median (i.e., ≥0.8845) had significantly longer OS (17.9 months [95% CI 14.0–21.0] vs. 12.9 months [10.3–16.8]; HR 1.52 [1.09–2.13]; p = 0.0143), longer TCB (9.6 months [95% CI 6.8–12.1] vs. 6.6 months [4.9–8.5]; HR 1.43 [1.04–1.95]; p = 0.0258) and longer TTNT (12.8 months [95% CI 10.5–20.2] vs. 9.8 months [8.5–11.9]; HR 1.42 [1.03–1.96]; p = 0.0332) (Table 5, last three columns) (Figure 3B,D,F).
3.7. EQ-5D-5L Composite Scores at Azacitidine Start Prognosticate the Likelihood of Response to Azacitidine
In univariate logistic regression, the LSS (p = 0.0009), EQ-VAS (p = 0.0237) and EQ-5D-5L index (p = 0.0110) were significantly correlated with response to azacitidine. After multivariate adjustment, LSS remained significantly predictive of response to azacitidine (p = 0.0160; OR 0.451 [95% CI 0.235–0.852]), and the EQ-5D-5L index showed a trend (p = 0.0627; OR 0.522 [0.296–1.032]) (Table 6). An LSS of ≥8 at azacitidine treatment start thus indicates a significantly lower chance of responding to azacitidine as expressed by the OR of 0.45.
3.8. Longitudinal Assessment of EQ-5D-5L Responses and Clinical Parameters
Multivariate-adjusted mixed-effect linear models of up to 1432 longitudinally assessed EQ-5D-5L response/dichotomised clinical parameter pairs revealed significant associations for haemoglobin level, red blood cell transfusion dependence, platelet count, platelet transfusion dependence, levels of ferritin, bilirubin, albumin, cholinesterase, the occurrence of adverse events, number of days with azacitidine treatment, and haematologic improvement (HI-any, HI-E, HI-P) with at least two EQ-5D dimensions, and at least one of the EQ-5D composite variables (LSS, EQ-VAS, EQ-5D-5L index) (Figure 4, Table 7). Sensitivity analyses for continuous clinical parameters yielded similar results (Supplementary pp. 17–18).
3.9. Minimally Clinically Important Differences
Of the statistically significant associations found in the dichotomised analyses, the following exhibited an effect size equal to or larger than the minimally clinically important difference: platelet transfusion dependence (LSS), ferritin ≥1000 µg/L (LSS), albumin ≥3.4 mg/dL (LSS), adverse events grade 3–4 (LSS, EQ-5D-5L index) and cholinesterase ≥2.5 U/L (EQ-VAS). These findings were corroborated in sensitivity analyses using continuous parameters.
4. Discussion
To our knowledge, our group is the first to compare EQ-5D-5L data of patients with MDS, CMML or AML with data from a reference population from a similar ethnic, socioeconomic and geographic background. In this prospective cohort analysis, we found that patients treated with azacitidine had significantly worse HRQoL than the German population norm (i.e., a representative sample of the German general adult population) [28,29] matched by sex, age group and number of comorbidities. In contrast to observations by Stauder et al. [10] who used the EQ-5D-3L, all significant differences observed for the EQ-5D-5L index and the EQ-VAS fulfilled the definitions of the minimally clinically important difference used by that group (>0.03 on the index and >3.0 on the EQ-VAS).
The current gold standards of prognostication in patients with MDS/CMML and low blast count AML are the International Prognostic Scoring System (IPSS) [26] and the revised IPSS (R-IPSS) [27]. The clinical relevance of these scores is underscored by the fact that approval of azacitidine for MDS patients in Europe is restricted to those with higher-risk IPSS (i.e., intermediate-2 and high risk categories). To our knowledge, our data are the first to indicate that LSS, EQ-VAS and EQ-5D-5L index at azacitidine treatment start provided added value to the IPSS and R-IPSS for the endpoints OS and TTNT. Other groups have prominently shown that patient-reported outcomes (other than EQ-5D) may predict OS and/or add value to the (R)-IPSS in elderly patients with MDS [30,31,32] or AML [21]. However, these questionnaires/indices incorporate 30 [30,32], 42 [31] and 44 items [21], many of which are not routinely assessed in patients with myeloid neoplasms, thus hampering the clinical everyday utility outside of clinical trials.
Our data are the only information on the impact of HRQoL, as assessed by the EQ-5D-5L, on time-to-event endpoints of patients treated with azacitidine. After multivariate adjustment (for ECOG-PS, number of comorbidities, platelet count ≤30 G/L or transfusion dependence, peripheral blood blasts, azacitidine treatment line and azacitidine dose in cycle one) an EQ-5D-5L index <0.8845 at azacitidine start indicated a significantly shorter median survival (−5.0 months), an increased risk of death (+52%), significantly shorter azacitidine treatment duration (−3.0 months), shorter TTNT or death (−3.0 months) and a significantly higher risk of requiring a next treatment or dying (+42%). Our data further show that an LSS of ≥8 at azacitidine start indicates a significantly lower chance of responding to the drug (OR 0.45).
This is the first report on the longitudinal assessment of EQ-5D-5L responses with clinical parameters. Multivariate adjusted mixed-effect linear modelling revealed significant associations for EQ-5D-5L response parameters with clinical parameters associated with haematologic improvement, disease progression, or the occurrence of adverse events. Thus, these data show that quality of life ameliorated in responding patients and deteriorates in patients experiencing disease progression or grade 3–4 adverse events. It is difficult to interpret these findings compared with the wider literature as longitudinal analyses of HRQoL data on patients with MDS, CMML or AML are scarce, performed with questionnaires other than EQ-5D-5L and are often without multivariate adjustment. Efficace et al. found no association between ferritin levels and HRQoL as assessed by EORTC QLQC30 both at baseline and during the study period in heavily transfused patients with MDS treated with iron chelation therapy using linear mixed-effect models [33]. We observed significant associations of ferritin, bilirubin and albumin levels with problems in six of eight EQ-5D-5L dimensions/composite variables. This is the first indication that these clinical variables, two of which (hypalbuminaemia and hyperferritinaemia) have been shown to be associated with adverse prognosis in patients with MDS [34,35,36], CMML [37] or AML [38,39] correlate with HRQoL.
Little is known of the longitudinal effect of azacitidine on patients’ HRQoL, but recent publications demonstrating significant improvements of EQ-VAS and/or EQ-5D-5L index in patients responding to treatment in other malignancies [40,41] highlight the contemporality and clinical relevance of the topic.
The mean (SD) EQ-VAS and EQ-5D-5L index values of our cohort were similar to those previously reported in patients with MDS/CMML or AML. Problems (slight, moderate, severe or extreme) were most commonly self-reported in the dimensions of usual activities (59%), mobility (51%), pain/discomfort (50%), anxiety/depression (49%) and selfcare (22%). Similar to the lower-risk MDS population reported by Stauder et al. [10], (i) MDS, CMML and AML patients in our cohort had the least problems in the dimension of selfcare, (ii) no correlation could be found between IPSS or R-IPSS risk group at azacitidine treatment start and EQ-5D responses, and (iii) patient-related factors such as haemoglobin <10 g/dL, red blood cell transfusion dependence, ECOG-PS ≥ 2 and high-risk HCT-CI were found to be associated with significantly more problems in several dimensions and/or significantly worse EQ-5D-5L composite variables. We could, however, not find a significant difference in EQ-5D-5L response by sex or age group.
A limitation of this study is that we cannot speculate what the HRQoL would have been without azacitidine therapy. Furthermore, this question cannot be addressed by real-world evidence or by future randomised clinical trials due to ethical reasons. A further limitation is that we do not have EQ-5D-5L questionnaires for all patients for all treatment cycles. However, to impose mandatory pre-specified required time-points for filling out EQ-5D-5L questionnaires would be against the non-interventional nature of non-interventional studies in general, and of the Austrian Registry of Hypomethylating Agents in particular. Furthermore, these results cannot, eo ipso, be generalised to other treatments of patients with MDS, CMML or AML, as we exclusively studied HRQoL of patients treated with azacitidine. In the future, we aim to analyse EQ-5D-5L responses in myeloid patients irrespective of treatment type within the Austrian Myeloid Registry (NCT04438889; Ethics committee approval was provided by the Ethikkommission für das Bundesland Salzburg (415-E/2581/Feb-2020)), which is a disease-specific (rather than a drug-specific) registry, once sufficient data have been accumulated, and are open for collaborations with other study groups in this regard.
The strengths of this study are that we report the first evidence-based data on all of the above; the prospective nature of data collection; the proven quality of our database in direct patient-level comparison with randomised phase-3 clinical trial data [23]; few missing data; calculation and validation of diagnosis, cytogenetic risk groups, and prognostic scores; response to reduce human errors; multivariate adjustment; longitudinal analyses; correction for multiple testing; and that additional sensitivity analyses confirmed the robustness of our results.
5. Conclusions
In conclusion, the current findings support the use of EQ-5D-5L instruments in future clinical trials and real-world evidence databases, in order to fully consider all factors that can be potentially associated with treatment outcomes. They also extend knowledge on the safety and efficacy of azacitidine by showing that clinical benefits such as improvement of laboratory values associated with haematologic improvement, as well as haematologic improvement itself, correlate with improved HRQoL.
Supplementary Materials
The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/cancers15051388/s1, Supplemental Table S1. Contributions of participating centres; Supplemental Table S2. Information on EQ-5D composite scores; Supplemental Table S3; Choice of appropriate value set region, value set and population norm; Supplemental Table S4. Further statistical details; Supplemental Table S5. Missing data; Supplemental Table S6. Univariate Cox regression analyses of baseline parameters present at azacitidine treatment start in patients with an available EQ-5D in cycle 1 or 2; Supplemental Table S7. Variables remaining in the final multivariate Cox model; Supplemental Table S8. Patient characteristics at azacitidine start; Supplemental Table S9. Lab values assessed at azacitidine start; Supplemental Table S10. Comorbidities assessed at azacitidine start; Supplemental Table S11. Azacitidine treatment and response characteristics; Supplemental Table S12. Most frequent response patterns of EQ-5D questionnaires at azacitidine treatment start; Supplemental Table S13. Most frequent response patterns of all EQ-5D questionnaires; Supplemental Table S14. Overview of EQ-5D responses by patient group and responder status; Supplemental Table S15. Multivariate-adjusted longitudinal analyses of EQ-5D-5L results and continuous parameters per azacitidine treatment cycle using mixed-effects linear models; Supplemental Figure S1. Heatmap of p-values resulting from multivariate-adjusted mixed-effect linear models of longitudinally assessed EQ-5D-5L responses and concomitantly assessed continuous clinical parameters; The Ethics Commottee Approval statement; The protocoll of the Austrian Registry of Hypomethylating Agents; The signed sponsor approval page; The informed consent of the Austrian Registry of Hypomethylating Agents. (References [42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64] are cited in the Supplementary Materials).
Author Contributions
Conceptualisation: L.P., M.D., J.L.-S., M.V., T.G., J.H. and R.S.; formal analysis: L.P., M.D., J.L.-S., M.V., T.G. and J.H.; funding acquisition: R.G.; investigation: all co-authors; methodology: L.P., M.D., J.L.-S., M.V., T.G. and J.H.; project administration: L.P., N.Z. and R.G.; resources: L.P., S.H., C.T., S.V., M.S., T.M., N.S., K.T.F.Q., M.L., A.E., L.S., D.W., T.G., N.Z., R.G. and R.S.; software: L.P., M.D., J.L.-S., M.V., T.G. and J.H.; supervision: L.P.; validation: L.P., M.D., J.L.-S., M.V., T.G. and J.H.; visualisation: L.P., M.D., J.L.-S. and M.V.; writing—original draft preparation: L.P.; writing—review and editing: all co-authors. All authors have read and agreed to the published version of the manuscript.
Funding
The Austrian Group for Medical Tumor Therapy (AGMT) is the sponsor for the Austrian Registry of Hypomethylating Agents and received funding from Celgene/BMS, AbbVie, and Janssen Cilag. The AGMT is a non-for-profit organisation and an academic study group. The group performed administrative and legal management, as well as funding acquisition. No pharmaceutical company and no other funding source were involved in any way and had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. No medical writer or editor was involved.
Institutional Review Board Statement
Ethics committee approval was provided by the Ethikkommission für das Bundesland Salzburg (415-EP/39/Feb-2009). The Ethics Committee Approval, the study protocol, the signed Sponsor Approval Page, and the Informed Consent form of the AGMT and the Austrian Registry of Hypomethylating Agents have been made available in the Supplementary pp. 19–30.
Informed Consent Statement
The Informed Consent form of the Austrian Registry of Hypomethylating Agents have been made available in the Supplementary pp. 31–32.
Data Availability Statement
The datasets supporting the conclusions of this article are included within the article and the Supplementary Materials. Data sharing of patient level data collected for the study is not planned. However, we are open to research questions asked by other researchers, and we are also open to data contributions by others. Participation requests or potential joint research proposals can be made at any timepoint to the corresponding author via email ([email protected]) and are subject to approval by the AGMT and its collaborators.
Acknowledgments
We would like to express our gratitude to EurQol for granting us the permission to use both the 3L and the 5L versions of the EuroQol 5-Dimension (EQ-5D) questionnaire, for the provision of the reverse crosswalk and for answering questions pertaining to the analyses and the presentation of EQ-5D-related results. Special thanks to Thomas Grochtdreis et al. for providing additional, non-published EQ-5D-5L data of the German population norm for cohort comparisons.
Conflicts of Interest
L.P.: Honoraria from AbbVie, BMS and Novartis; S.H.: Honoraria from AbbVie, AOP, BMS, Janssen Cilag, Novartis and Roche; CT: No potential conflicts of interest; S.V.: Honoraria from Bristol Myers Squibb, Merck, MSD and Pfizer; consultancy fees from Roche, MSD, EUSA Pharma and Merck; Travel support from Pfizer, Roche, Pierre Fabre and Angelini; M.S.: Honoraria and consultancy BMS/Celgene; T.M.: Honoraria from AbbVie and Celgene/BMS; NS: No potential conflicts of interest; K.T.F.Q.: No potential conflicts of interest; M.L.: Honoraria from BMS, Celgene, Gilead, Takeda and Novartis; Travel support: Celgene and Novartis; AE: Honoraria, consultancy and travel support from AbbVie and BMS/Celgene; L.S.: No potential conflicts of interest; D.W.: Research Funding: BMS/Celgene, MSD, Novartis, Pfizer and Roche; Honoraria: BMS/Celgene, GEMOAB, Gilead, Incyte, MSD, Novartis, Pfizer and Roche; R.B.: No potential conflicts of interest; M.D.: No potential conflicts of interest; J.L.-S.: No potential conflicts of interest; T.G.: No potential conflicts of interest; M.V.: No potential conflicts of interest; J.H:. Research Funding: Böhringer-Ingelheim; N.Z.: No potential conflicts of interest; R.G.: Honoraria from AbbVie, Amgen, AstraZeneca, BMS/Celgene, Daiichi Sankyo, Gilead, Merck, Novartis, Roche, Takeda, BMS, MSD, Sandoz and Gilead; Research funding from Celgene, Roche, Merck, Novartis, MSD, Sandoz and Takeda; Consulting: AbbVie, Astra Zeneca, BMS/Celgene, Novartis, Roche, Takeda, Janssen, MSD, Merck, Gilead and Daiichi Sankyo; Travel support from AbbVie, Amgen, Astra Zeneca, BMS/Celgene, Daiichi Sankyo, Gilead, Janssen Cilag, MSD, Novartis and Roche; R.S.: Honoraria from BMS/Celgene. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
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Figure 1.
Consort diagram. The data collection and cleaning period was from 2 February 2012 to 3 March 2022. Database lock (last patient in) was on 13 December 2020. The inclusion criteria were (1) the diagnosis of MDS, CMML or AML, which was independently and centrally verified on the basis of submitted data; (2) treatment with azacitidine; (3) inclusion in the Austrian Registry of Hypomethylating agents; (4) the presence of a written informed consent for all patients alive at the time of data entry; (5) age ≥ 18 years; (6) the completion of at least one EQ-5D questionnaire. No data from patients <18 years were received. No patients fulfilling these criteria were excluded from the analyses. A total of 6 of 1456 (0.4%) of EQ-5D questionnaires were excluded (empty questionnaire). Permissions to use the German version of EQ-5D questionnaires was obtained from EuroQol. All data for this study were collected prospectively. This study has been reported according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement. To ensure uniformity, composite variables based on provided data were allocated for each individual patient at the start of azacitidine treatment, including diagnosis of MDS, CMML or AML according to the WHO 2016 diagnostic criteria [25], cytogenetic risk group according to the International Prognostic Scoring System (IPSS) [26] and the revised IPSS (R-IPSS) [27] and the IPSS and R-IPSS risk categories themselves.
Figure 1.
Consort diagram. The data collection and cleaning period was from 2 February 2012 to 3 March 2022. Database lock (last patient in) was on 13 December 2020. The inclusion criteria were (1) the diagnosis of MDS, CMML or AML, which was independently and centrally verified on the basis of submitted data; (2) treatment with azacitidine; (3) inclusion in the Austrian Registry of Hypomethylating agents; (4) the presence of a written informed consent for all patients alive at the time of data entry; (5) age ≥ 18 years; (6) the completion of at least one EQ-5D questionnaire. No data from patients <18 years were received. No patients fulfilling these criteria were excluded from the analyses. A total of 6 of 1456 (0.4%) of EQ-5D questionnaires were excluded (empty questionnaire). Permissions to use the German version of EQ-5D questionnaires was obtained from EuroQol. All data for this study were collected prospectively. This study has been reported according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement. To ensure uniformity, composite variables based on provided data were allocated for each individual patient at the start of azacitidine treatment, including diagnosis of MDS, CMML or AML according to the WHO 2016 diagnostic criteria [25], cytogenetic risk group according to the International Prognostic Scoring System (IPSS) [26] and the revised IPSS (R-IPSS) [27] and the IPSS and R-IPSS risk categories themselves.
Figure 2.
EQ-5D-5L responses available at azacitidine treatment start (n = 205), stratified by ECOG-PS.
Figure 2.
EQ-5D-5L responses available at azacitidine treatment start (n = 205), stratified by ECOG-PS.
Figure 3.
Impact of the EQ-5D-5L index at azacitidine treatment start on time-to-event endpoints. (A) Endpoint overall survival (OS), unadjusted. (B) Endpoint OS, adjusted 1. (C) Endpoint time with clinical benefit (TCB), unadjusted. (D) Endpoint TCB, adjusted 1. (E) Endpoint time to next treatment (TTNT), unadjusted. (F) Endpoint TTNT, adjusted 1. (1 Adjusted for the following characteristics at azacitidine treatment start: ECOG-PS, number of comorbidities, platelet count ≤30 G/L or platelet transfusion dependence, peripheral blood blasts, azacitidine treatment line and azacitidine dose in cycle 1).
Figure 3.
Impact of the EQ-5D-5L index at azacitidine treatment start on time-to-event endpoints. (A) Endpoint overall survival (OS), unadjusted. (B) Endpoint OS, adjusted 1. (C) Endpoint time with clinical benefit (TCB), unadjusted. (D) Endpoint TCB, adjusted 1. (E) Endpoint time to next treatment (TTNT), unadjusted. (F) Endpoint TTNT, adjusted 1. (1 Adjusted for the following characteristics at azacitidine treatment start: ECOG-PS, number of comorbidities, platelet count ≤30 G/L or platelet transfusion dependence, peripheral blood blasts, azacitidine treatment line and azacitidine dose in cycle 1).
Figure 4.
Heatmap of p-values from multivariate-adjusted mixed-effect linear models of longitudinally assessed EQ-5D-5L response/clinical parameter pairs. The individual boxes contain the p-values (red coloured p-values denote significant values ≤0.05, orange denotes a trend and is used for p-values between >0.05 and ≤0.065) of the corresponding multivariate-adjusted mixed-effect linear models using EQ-5D-5L responses as endogenous variables (x-axis), and various clinical measurements as exogenous variables (y-axis). Multivariate adjustment was performed by admitting the following variables remaining in the final Cox model as covariates: ECOG-PS, number of comorbidities, platelet count/platelet transfusion dependence, peripheral blood blasts, azacitidine treatment line and azacitidine dose in cycle one.
Figure 4.
Heatmap of p-values from multivariate-adjusted mixed-effect linear models of longitudinally assessed EQ-5D-5L response/clinical parameter pairs. The individual boxes contain the p-values (red coloured p-values denote significant values ≤0.05, orange denotes a trend and is used for p-values between >0.05 and ≤0.065) of the corresponding multivariate-adjusted mixed-effect linear models using EQ-5D-5L responses as endogenous variables (x-axis), and various clinical measurements as exogenous variables (y-axis). Multivariate adjustment was performed by admitting the following variables remaining in the final Cox model as covariates: ECOG-PS, number of comorbidities, platelet count/platelet transfusion dependence, peripheral blood blasts, azacitidine treatment line and azacitidine dose in cycle one.
Table 1.
Comparison of published EQ-VAS and EQ-5D index values in patients with MDS and AML.
| First Author | Year Published | Patients, n | Disease | EQ-5D, Type | EQ-VAS, Mean (SD) | Index Value, Mean (SD) | Index Value, Median (IQR) | Impact on Time-to-Event Endpoint |
|---|---|---|---|---|---|---|---|---|
| MDS | ||||||||
| Szende A. [11] | 2009 | 47 | MDS | 3L | NR | 0.78 (NR) | NR | NR |
| Oliva E. [12] | 2012 | 148 | MDS | 3L | 60 (20) | NR | 0.74 (0.62–0.85) | NR |
| Stauder R. [10] | 2018 | 1683 | Lower-risk MDS | 3L | 69.6 (20.1) | 0.74 (0.23) | NR | NR |
| de Swart L. [9] | 2020 | NR | Lower-risk MDS | 3L | 70.5 (19.7) | NR | NR | EQ-5D-3L index was significantly associated with progression-free survival in univariate analysis |
| Pleyer L. (this article) | 2023 | 162 | MDS/CMML | 5L | 64.4 (21.2) | 0.79 (0.3) | 0.88 (0.73–0.95) | EQ-5D-5L index, LSS and EQ-VAS were significantly associated with overall survival and the likelihood to respond to azacitidine in univariate analysis; EQ-5D-5L index was significantly associated with overall survival, time with clinical benefit and time to next treatment in multivariate-adjusted analyses. LSS was significantly associated with the likelihood to respond to azacitidine in multivariate analysis. |
| AML | ||||||||
| Uyl-de Groot C.A. [13] | 1998 | NR NR | AML | 3L | 70.6 (NR) 64.8 (NR) | NR NR | NR NR | NR |
| Slovacek L. [14] | 2007 | NR | AML | 3L | 67.5 (NR) | NR | NR | NR |
| Leunis A. [15] | 2014 | 88 | AML | 3L | 74.6 (17.4) | 0.82 (17.4) | NR | NR |
| Kurosowa S. [16] | 2015 | 392 | AML | 3L | NR | NR | NR | NR |
| van Dongen-Leunis, A. [17] | 2016 | 111 | AML | 5L | NR | 0.81 (0.22) | 0.87 (NR-NR) | NR |
| Mamolo C. [18] | 2019 | NR | AML | 3L | 61.2 (NR) | 0.74 (NR) | NR | NR |
| Horvath Walsh L. [19] | 2019 | 75 | AML | 3L | 61.2 (NR) | 0.74 | NR | NR |
| Yu H. [20] | 2020 | NR/168 NR/168 | AML | 3L 5L | 76.9 (15.1) | 0.829 (0.16) 0.786 (0.25) | NR NR | NR |
| Peipert J. [21] | 2020 | 307 | AML | 5L | 61.9 (20.1) | 0.67 (0.26) | NR | NR |
| Pratz K.W. [22] | 2022 | 642 | AML | 5L | NR | NR | NR | NR |
| Pleyer L. (this article) | 2023 | 110 | AML | 5L | 64.7 (21.7) | 0.83 (0.2) | 0.89 (0.76–0.98) | EQ-5D-5L index, LSS and EQ-VAS were significantly associated with overall survival and the likelihood to respond to azacitidine in univariate analysis; EQ-5D-5L index was significantly associated with overall survival, time with clinical benefit and time to next treatment in multivariate-adjusted analyses. LSS was significantly associated with the likelihood to respond to azacitidine in multivariate analysis. |
NR indicates not reported.
Table 2.
Prevalence of problems in patients with myeloid neoplasias (assessed by EQ-5D-5L at azacitidine treatment start (n = 205) 1) by disease-related and patient-related parameters.
Table 2.
Prevalence of problems in patients with myeloid neoplasias (assessed by EQ-5D-5L at azacitidine treatment start (n = 205) 1) by disease-related and patient-related parameters.
| Mobility Problem 2 | Selfcare Problem 2 | Usual Activities Problem 2 | Pain/Discomfort Problem 2 | Anxiety/Depression Problem 2 | Level Sum Score 3 | Index Value 4 | EQ-VAS | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n/n (%) | p 5 | n/n (%) | p 5 | n/n (%) | p 5 | n/n (%) | p 5 | n/n (%) | p 5 | n | Mean (SD) | p 5 | n | Mean (SD) | p 6 | n | Mean (SD) | p 6 | |
| Total cohort | |||||||||||||||||||
| 1st available EQ-5D | 136/272 (50.0) | NA | 68/72 (25.0) | NA | 150/272 (55.1) | NA | 138/272 (50.7) | NA | 125/272 (46.0) | NA | 266 | 9.1 (3.9) | NA | 266 | 0.807 (0.232) | NA | 263 | 63.9 (21.6) | NA |
| EQ-5D in cycle 1 or 2 | 104/205 (50.7) | NA | 46/205 (22.4) | NA | 120/205 (58.5) | NA | 102/205 (49.8) | NA | 100/205 (48.8) | NA | 200 | 9.2 (3.9) | NA | 198 | 0.810 (0.229) | NA | 200 | 64.5 (21.4) | NA |
| Disease-related parameters 1 | |||||||||||||||||||
| Azacitidine ≥2nd line: No Yes | 75/145 (52.1) 29/59 (49.2) | 0.7045 | 35/143 (24.5) 11/59 (18.6) | 0.3688 | 86/141 (61.0) 34/59 (557.6) | 0.6577 | 76/143 (53.1) 26/59 (44.1) | 0.2406 | 72/143 (50.3) 28/59 (47.5) | 0.7085 | 141 59 | 9.3 (4.0) 8.7 (3.5) | 0.3288 | 141 59 | 0.800 (0.243) 0.831 (0.192) | 0.4282 | 141 57 | 63.3 (22.0) 67.5 (19.7) | 0.2136 |
| Diagnosis: MDS or CMML AML | 59/112 (52.7) 45/91 (49.5) | 0.6472 | 28/111 (25.2) 18/91 (19.8) | 0.3585 | 66/109 (60.6) 54/91 (59.3) | 0.8619 | 66/111 (59.5) 36/91 (39.6) | 0.0049 | 53/111 (47.4) 47/91 (51.6) | 0.5812 | 109 91 | 9.4 (4.0) 8.8 (3.6) | 0.2921 | 109 91 | 0.788 (0.256) 0.835 (0.192) | 0.2160 | 110 88 | 64.4 (21.2) 64.7 (21.7) | 0.9440 |
| Treatment-related disease: No Yes | 89/175 (50.9) 12/24 (50.0) | 0.9372 | 39/174 (22.4) 6/24 (25.0) | 0.7769 | 102/172 (59.3) 14/24 (58.3) | 0.9279 | 84/174 (48.3) 15/24 (62.5) | 0.1914 | 79/174 (45.4) 17/24 (70.8) | 0.0194 | 172 24 | 9.1 (3.9) 9.5 (3.7) | 0.4741 | 172 24 | 0.810 (0.238) 0.809 (0.182) | 0.4869 | 170 24 | 64.7 (21.8) 64.4 (19.9) | 0.7998 |
| IPSS: Low or intermediate-1 Intermediate-2 or high | 39/72 (54.2) 62/125 (49.6) | 0.5369 | 17/71 (23.9) 27/125 (21.6) | 0.7055 | 40/69 (58.0) 75/125 (60.0) | 0.7830 | 39/71 (54.9) 58/125 (46.4) | 0.2510 | 32/71 (45.1) 64/125 (51.2) | 0.4093 | 69 125 | 9.3 (4.2) 8.9 (3.5) | 0.7663 | 69 125 | 0.789 (0.274) 0.836 (0.169) | 0.7950 | 70 122 | 65.6 (20.7) 64.6 (21.8) | 0.6783 |
| R-IPSS: Very low or low Intermediate, poor, very poor | 11/26 (42.3) 90/169 (53.3) | 0.2984 | 6/26 (23.1) 39/168 (23.2) | 0.9877 | 13/26 (50.0) 102/166 (61.4) | 0.2682 | 15/26 (57.7) 82/168 (48.8) | 0.3992 | 12/26 (46.2) 84/168 (50.0) | 0.7151 | 26 166 | 9.3 (5.0) 9.1 (3.6) | 0.5927 | 26 166 | 0.758 (0.369) 0.821 (0.188) | 0.7551 | 25 165 | 64.6 (21.8) 64.7 (21.1) | 0.9609 |
| IPSS cytogenetic risk: good Intermediate or poor | 60/125 (48.0) 34/56 (60.7) | 0.1135 | 29/124 (23.4) 14/56 (25.0) | 0.8143 | 67/123 (54.5) 35/55 (63.6) | 0.2534 | 62/124 (50.0) 29/56 (51.8) | 0.8244 | 64/124 (50.0) 27/56 (48.2) | 0.6729 | 123 55 | 9.0 (3.9) 9.5 (3.8) | 0.2706 | 123 55 | 0.814 (0.228) 0.806 (0.216) | 0.3255 | 122 54 | 65.7 (21.4) 64.1 (21.1) | 0.6006 |
| Peripheral blood blasts: <10% ≥10% | 78/156 (50.0) 26/47 (55.3) | 0.5225 | 34/155 (21.9) 12/47 (25.5) | 0.6065 | 94/153 (61.4) 26/47 (55.3) | 0.4539 | 83/155 (53.5) 19/47 (40.4) | 0.1150 | 77/155 (49.7) 23/47 (48.9) | 0.9291 | 153 47 | 9.3 (4.0) 8.8 (3.3) | 0.7245 | 153 47 | 0.798 (0.246) 0.847 (0.162) | 0.4270 | 153 45 | 64.8 (20.9) 63.8 (23.1) | 0.7879 |
| Monocytes: <10% ≥10% | 56/121 (46.3) 44/75 (58.7) | 0.0918 | 23/121 (19.0) 22/74 (29.7) | 0.0846 | 61/119 (51.3) 52/74 (70.3) | 0.0091 | 60/121 (49.6) 41/74 (55.4) | 0.4301 | 52/121 (43.0) 43/74 (58.1) | 0.0402 | 119 74 | 8.5 (3.5) 10.1 (4.3) | 0.0053 | 119 74 | 0.850 (0.193) 0.752 (0.267) | 0.0052 | 118 73 | 67.7 (19.8) 61.5 (22.5) | 0.0626 |
| Haemoglobin: <10.0 g/dL ≥10.0 g/dL | 81/142 (57.0) 23/61 (37.7) | 0.0115 | 37/141 (26.2) 9/61 (14.8) | 0.0739 | 89/139 (64.0) 31/61 (50.8) | 0.0792 | 73/141 (51.8) 29/61 (47.5) | 0.5807 | 71/141 (50.4) 29/61 (47.5) | 0.7135 | 139 61 | 9.5 (4.0) 8.3 (3.5) | 0.0295 | 139 61 | 0.790 (0.242) 0.855 (0.191) | 0.0429 | 137 61 | 62.8 (21.0) 68.5 (21.8) | 0.0545 |
| Red blood cell transfusions: ≤3 >3 | 62/138 (44.9) 22/26 (84.6) | 0.0002 | 31/137 (22.6) 8/26 (30.8) | 0.3724 | 75/135 (55.6) 20/26 (76.9) | 0.0425 | 73/137 (53.3) 16/26 (61.5) | 0.4384 | 64/137 (46.7) 15/26 (57.7) | 0.3045 | 135 26 | 9.0 (4.0) 9.9 (3.2) | 0.0723 | 135 26 | 0.809 (0.247) 0.864 (0.163) | 0.1412 | 134 25 | 65.6 (21.7) 55.2 (17.6) | 0.0147 |
| Platelet count: <100 G/L ≥100 G/L | 36/65 (55.4) 68/138 (49.3) | 0.4165 | 17/65 (26.2) 29/137 (21.2) | 0.4299 | 39/63 (61.9) 81/137 (59.1) | 0.7092 | 34/65 (52.3) 68/137 (49.6) | 0.7226 | 30/65 (46.2) 70/137 (51.1) | 0.5117 | 63 137 | 9.4 (4.0) 9.0 (3.8) | 0.4665 | 61 137 | 0.797 (0.254) 0.815 (0.218) | 0.4980 | 64 134 | 65.8 (19.9) 63.9 (22.1) | 0.6100 |
| Patient-related parameters 1 | |||||||||||||||||||
| Sex male: No Yes | 45/81 (55.6) 59/122 (48.4) | 0.3152 | 21/81 (25.9) 25/121 (20.7) | 0.3819 | 49/79 (62.0) 71/121 (58.7) | 0.6366 | 44/81 (54.3) 58/121 (47.9) | 0.3735 | 47/81 (58.0) 53/121 (43.8) | 0.0475 | 79 121 | 9.6 (4.0) 8.9 (3.7) | 0.1644 | 79 121 | 0.786 (0.261) 0.825 (0.206) | 0.2445 | 77 121 | 66.3 (21.9) 63.4 (21.1) | 0.2408 |
| Age ≥75 yrs: No Yes | 47/105 (44.8) 57/98 (58.2) | 0.0563 | 19/104 (18.3) 27/89 (27.6) | 0.1159 | 64/103 (62.1) 56/97 (57.7) | 0.5252 | 44/104 (42.3) 59/98 (59.2) | 0.0165 | 51/104 (49.0) 49/98 (50.0) | 0.8913 | 103 97 | 8.7 (3.4) 9.6 (4.2) | 0.2478 | 103 97 | 0.832 (0.191) 0.785 (0.263) | 0.2429 | 103 95 | 66.9 (21.0) 60.0 (21.6) | 0.1083 |
| ECOG-PS: 0–1 ≥2 | 74/163 (45.4) 30/40 (75.0) | 0.0008 | 26/162 (16.0) 20/40 (50.0) | <0.0001 | 87/160 (54.4) 33/40 (82.5) | 0.0012 | 79/162 (48.8) 23/40 (57.5) | 0.3224 | 70/162 (43.2) 30/40 (75.0) | 0.0003 | 160 40 | 8.4 (3.4) 12.0 (4.3) | <0.0001 | 160 40 | 0.847 (0.185) 0.659 (0.315) | <0.0001 | 159 39 | 66.5 (20.8) 56.6 (22.3) | 0.0092 |
| HCT-CI: Low risk Intermediate risk High risk | 31/77 (40.3) 33/65 (50.8) 40/61 (65.6) | 0.0127 | 13/77 (16.9) 12/65 (18.5) 21/60 (35.0) | 0.0259 | 40/75 (53.3) 36/65 (55.4) 44/60 (73.3) | 0.0406 | 38/77 (49.4) 26/65 (40.0) 38/60 (63.3) | 0.0324 | 36/77 (46.8) 30/65 (46.2) 34/60 (56.7) | 0.4155 | 75 65 60 | 8.3 (3.3) 8.9 (3.7) 10.4 (4.4) | 0.0133 | 75 65 60 | 0.849 (0.186) 0.822 (0.224) 0.748 (0.271) | 0.0189 | 75 64 59 | 67.8 (20.1) 65.4 (21.0) 59.5 (22.7) | 0.0750 |
| No. of comorbidities: 0–1 ≥2 | 52/116 (44.8) 52/87 (59.8) | 0.0350 | 23/116 (19.8) 23/86 (26.7) | 0.2464 | 66/114 (57.9) 54/86 (62.8) | 0.4841 | 57/116 (49.1) 45/86 (52.3) | 0.6541 | 52/116 (44.8) 48/86 (55.8) | 0.1225 | 114 86 | 8.7 (3.5) 9.8 (4.3) | 0.0689 | 114 86 | 0.839 (0.183) 0.770 (0.276) | 0.0703 | 113 85 | 66.8 (21.0) 61.6 (21.6) | 0.0829 |
IPSS, International Prognostic Scoring System; IPSS-LR, IPSS lower-risk; IPSS-HR, IPSS higher-risk; R-IPSS, revised IPSS; ECOG-PS, Eastern Cooperative Oncology Group Performance Score; HCT-CI, Haematopoietic Stem Cell Comorbidity Index; MRC, Medical research Council. 1 EQ-5D in cycle 1 or 2 with a non-missing value for the respective parameter (hence patient numbers may vary slightly for each parameter analysed). 2 Problems were defined as answer options 2, 3, 4 or 5 for EQ-5D-5L and answer options 2 or 3 for EQ-5D-3L. 3 Represents the numerical sum of all EQ-5D responses. 4 The EQ-5D-5L index is measured on a scale from 0 to 1, whereby 0 indicates death and 1 perfect health. 5 Baseline parameters and EQ-5D-5L results were compared using the Chi-squared test (based on non-missing observations) for EQ-5D-5L problems (=2,3,4,5) vs. EQ-5D-5L no-problems (=1). 6 Baseline parameters and EQ-5D-5L results were compared using the Wilcoxon rank-sum test (also called Mann–Whitney U-test or Mann–Whitney–Wilcoxon Test) for Level Sum Score, EQ-5D-5L index value and EQ-VAS. Font color is red for all significant p-values <0.05.
Table 3.
Comparison of HRQoL (as assessed by first available EQ-5D-5L) 1 between myeloid patients (n = 269) and a German population norm without myeloid neoplasias (n = 5001) 2 matched by age group, sex or number of comorbidities.
Table 3.
Comparison of HRQoL (as assessed by first available EQ-5D-5L) 1 between myeloid patients (n = 269) and a German population norm without myeloid neoplasias (n = 5001) 2 matched by age group, sex or number of comorbidities.
| Mobility Problem 3 | Selfcare Problem 3 | Usual Activities Problem 3 | Pain/Discomfort Problem 3 | Anxiety/Depression Problem 3 | Index Value | EQ-VAS | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n/n (%) | p4 | n/n (%) | p4 | n/n (%) | p4 | n/n (%) | p4 | n/n (%) | p4 | n | Mean (SD) | p5 | n | Mean (SD) | p5 | |
| Total cohort Austrian Registry German Norm | 136/269 (50.6) 1772/5001 (35.4) | <0.0001 | 68/268 (25.4) 360/5001 (7.2) | <0.0001 | 150/266 (56.4) 1417/5001 (28.3) | <0.0001 | 138/268 (51.5) 2847/5001 (56.9) | 0.0802 | 125/269 (46.5) 1256/5001 (25.1) | <0.0001 | 266 5001 | 0.81 (0.23) 0.88 (0.18) | <0.0001 | 260 4997 | 63.9 (21.6) 71.6 (21.4) | <0.0001 |
| ≥75 years Austrian Registry German Norm | 74/130 (56.9) 399/593 (67.3) | 0.0245 | 39/130 (30.0) 111/593 (18.7) | 0.0041 | 71/129 (55.0) 281/593 (47.4) | 0.1151 | 75/130 (57.7) 418/593 (70.5) | 0.0046 | 59/131 (45.0) 160/593 (27.0) | <0.0001 | 129 593 | 0.79 (0.25) 0.80 (0.28) | 0.7547 | 127 590 | 61.7 (22.4) 60.9 (26.2) | 0.7662 |
| 65 < 75 years Austrian Registry German Norm | 50/105 (47.6) 324/654 (46.1) | 0.7146 | 22/105 (21.0) 69/654 (10.6) | 0.0023 | 60/104 (57.7) 198/654 (30.3) | <0.0001 | 49/105 (46.7) 411/654 (62.8) | 0.0016 | 49/105 (46.7) 158/654 (24.2) | <0.0001 | 104 654 | 0.84 (0.19) 0.85 (0.240 | 0.5650 | 102 654 | 66.8 (19.3) 66.1 (25.5) | 0.7777 |
| <65 years Austrian Registry German Norm | 12/34 (35.3) 1049/3754 (27.9) | 0.3420 | 7/33 (21.2) 180/3754 (4.8) | <0.0001 | 19/33 (57.6) 938/3754 (25.0) | <0.0001 | 14/33 (42.4) 2017/3754 (53.7) | 0.1948 | 17/33 (51.5) 938/3754 (25.0) | 0.0005 | 33 3754 | 0.77 (0.26) 0.90 (0.15) | <0.0001 | 34 3753 | 63.5 (24.0) 74.2 (19.1) | 0.0011 |
| Females Austrian Registry German Norm | 59/103 (57.3) 980/2584 (37.9) | <0.0001 | 30/103 (29.1) 203/2584 (7.9) | <0.0001 | 63/101 (62.4) 789/2584 (30.5) | <0.0001 | 60/103 (58.3) 1497/2584 (57.9) | 0.9487 | 56/103 (54.5) 734/2584 (28.4) | <0.0001 | 101 2584 | 0.78 (0.26) 0.86 (0.20) | <0.0001 | 98 2581 | 64.6 (21.8) 71.1 (22.2) | 0.0048 |
| Males Austrian Registry German Norm | 77/166 (46.4) 791/2417 (32.7) | 0.0003 | 38/165 (23.0) 157/2417 (6.5) | <0.0001 | 86/165 (52.7) 628/2417 (26.0) | <0.0001 | 78/165 (47.3) 1350/2417 (55.9) | 0.0319 | 69/166 (41.6) 522/2417 (21.6) | <0.0001 | 165 2417 | 0.83 (0.21) 0.90 (0.16) | <0.0001 | 165 2416 | 63.5 (21.5) 72.1 (20.5) | <0.0001 |
| One comorbidity Austrian Registry German Norm | 24/66 (36.4) 455/1432 (31.8) | 0.4344 | 9/66 (13.6) 74/1432 (5.2) | 0.0033 | 31/64 (48.4) 361/1433 (25.2) | <0.0001 | 32/66 (48.5) 813/1432 (56.8) | 0.1843 | 31/67 (46.3) 317/1432 (22.1) | <0.0001 | 64 1432 | 0.87 (0.17) 0.90 (0.15) | 0.0861 | 64 1432 | 66.3 (22.8) 73.0 (19.2) | 0.0067 |
| Two comorbidities Austrian Registry German Norm | 42/85 (50.6) 378/820 (46.1) | 0.4295 | 23/85 (27.1) 74/821 (9.0) | <0.0001 | 49/85 (57.7) 294/821 (35.8) | <0.0001 | 43/85 (50.6) 570/821 (69.4) | 0.0004 | 31/85 (37.7) 245/821 (29.8) | 0.1370 | 85 821 | 0.82 (0.21) 0.85 (0.18) | 0.1154 | 83 821 | 65.7 (20.6) 65.1 (21.9) | 0.7841 |
| ≥Three comorbidities Austrian Registry German Norm | 69/118 (58.5) 627/870 (72.1) | 0.0024 | 36/117 (30.8) 179/871 (20.6) | 0.0119 | 70/117 (59.8) 536/870 (61.6) | 0.7104 | 63/117 (53.9) 748/871 (85.9) | <0.0001 | 62/117 (53.0) 374/871 (42.9) | 0.0398 | 117 871 | 0.77 (0.27) 0.72 (0.28) | 0.0944 | 116 871 | 61.3 (21.4) 55.2 (24.0) | 0.0093 |
EQ-VAS indicates EuroQol Visual Analogue Scale. 1 First available EQ-5D with a non-missing value for the respective parameter (hence patient numbers may vary slightly for each parameter analysed). 2 Published and unpublished data provided by Grochtdreis et al. [28]. 3 Problems were defined as answer options 2, 3, 4 or 5 for EQ-5D-5L and answer options 2 or 3 for EQ-5D-3L. 4 The prevalence of EQ-5D-5L problems (=2,3,4,5) vs. EQ-5D-5L no-problems (=1) were compared using the Chi-squared test. 5 EQ-5D-Indices and EQ-VAS were compared between the Austrian Registry of Hypomethylating Agents and the German Norm cohorts using Student’s T-test. Font color is red for all significant p-values <0.05.
Table 4.
Prognostic value of the IPSS and R-IPSS with or without baseline Level Sum Score (LSS), EQ Visual Analogue Scale (VAS) or EQ-5D-5l index value, by time-to-event endpoint (patients with EQ-5D-5L responses available at azacitidine treatment start (n = 205)).
Table 4.
Prognostic value of the IPSS and R-IPSS with or without baseline Level Sum Score (LSS), EQ Visual Analogue Scale (VAS) or EQ-5D-5l index value, by time-to-event endpoint (patients with EQ-5D-5L responses available at azacitidine treatment start (n = 205)).
| (R)-IPSS | (R)-IPSS + LSS | (R)-IPSS + EQ-VAS | (R)-IPSS + Index | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Months [95% CI] 1 | LHR | p 6 | LHR | p 6 | LHR | p 6 | LHR | p 6 | |
| Overall survival | |||||||||
|
IPSS: Lower-risk 2 Higher-risk 3 | 21.0 [14.6–30.3] 12.8 [10.2–16.9] | 7.3195 | 0.0068 | 10.6911 | 0.0048 | 11.5552 | 0.0031 | 13.0219 | 0.0015 |
|
R-IPSS: Lower-risk 4 Higher-risk 5 | 30.3 [11.2–39.3] 14.6 [11.9–17.8] | 5.3691 | 0.0205 | 9.0542 | 0.0108 | 10.2840 | 0.0058 | 13.4753 | 0.0012 |
| Time with clinical benefit | |||||||||
|
IPSS: Lower-risk 2 Higher-risk 3 | 8.9 [5.6–13.1] 7.9 [5.2–9.6] | 1.0693 | 0.3011 | 3.6196 | 0.1637 | 1.9171 | 0.3835 | 3.6196 | 0.1637 |
|
R-IPSS: Lower-risk 4 Higher-risk 5 | 7.8 [3.4–14.9] 8.0 [6.4–9.6] | 0.0757 | 0.7832 | 4.0208 | 0.1339 | 1.5603 | 0.4583 | 4.0208 | 0.1339 |
| Time to next treatment | |||||||||
|
IPSS: Lower-risk 2 Higher-risk 3 | 14.6 [9.5–19.3] 11.3 [8.9–12.6] | 3.5998 | 0.0578 | 5.7236 | 0.0572 | 4.7933 | 0.0910 | 6.3834 | 0.0411 |
|
R-IPSS: Lower-risk 4 Higher-risk 5 | 17.6 [6.9–37.7] 10.8 [9.3–12.6] | 4.3114 | 0.0379 | 7.7372 | 0.0209 | 6.8408 | 0.0327 | 6.5489 | 0.0378 |
IPSS, International Prognostic Scoring System; R-IPSS, revised IPSS; LHR, likelihood ratio test. 1 Estimated via univariate Cox proportional hazards regression. 2 IPSS lower-risk comprises IPSS low and intermediate-1 risk categories. 3 IPSS higher-risk comprises IPSS intermediate-2 and high risk categories. 4 R-IPSS lower-risk comprises R-IPSS very low and low risk categories. 5 R-IPSS higher-risk comprises R-IPSS intermediate, high and very high risk categories. 6 Estimated via multivariate Cox proportional hazards regression.
Table 5.
Time-to-endpoint results for patients with EQ-5D-5L results available at azacitidine treatment start (n = 205).
Table 5.
Time-to-endpoint results for patients with EQ-5D-5L results available at azacitidine treatment start (n = 205).
| Univariate (n = 205) | Multivariate 4 (n = 205) | |||||
|---|---|---|---|---|---|---|
| Months [95% CI] | p | HR [95% CI] | Months [95% CI] | p | HR [95% CI] | |
| Overall Survival | ||||||
|
Level Sum Score: <median 1 ≥median | 19.3 [14.6–21.5] 12.4 [8.7–15.0] | 0.0407 | 1.408 [1.013–1.956] | 16.9 [12.9–37.4] 14.2 [11.7–17.8] | 0.2286 | 1.234 [0.876–1.737] |
|
EQ-VAS (health today): ≥median 2 <median | 17.9 [13.8–21.3] 12.8 [8.7–16.8] | 0.0141 | 1.511 [1.084–2.106] | 16.9 [12.9–30.6] 14.0 [11.4–24.7] | 0.2293 | 1.242 [0.872–1.769] |
|
EQ-5D-5L index: ≥median 3 <median | 18.5 [15.0–21.0] 11.9 [8.5–14.9] | 0.0093 | 1.536 [1.109–2.127] | 17.9 [14.0–21.0] 12.9 [10.3–16.8] | 0.0143 | 1.523 [1.088–2.131] |
| Time with Clinical Benefit | ||||||
|
Level Sum Score: <median 1 ≥median | 10.2 [6.6–13.2] 6.1 [4.3–8.2] | 0.0573 | 1.340 [0.989–1.815] | 8.7 [6.5–11.8] 6.8 [5.2–8.8] | 0.2174 | 1.221 [0.889–1.677] |
|
EQ-VAS (health today): ≥median 2 <median | 9.6 [6.6–12.1] 6.7 [4.6–8.5] | 0.1841 | 1.227 [0.906–1.662] | 8.4 [6.4–11.4] 7.7 [5.6–9.6] | 0.5233 | 1.111 [0.998–1.012] |
|
EQ-5D-5L index: ≥median 3 <median | 10.2 [7.2–12.8] 6.1 [4.0–8.2] | 0.0134 | 1.456 [1.078–1.966] | 9.6 [6.8–12.1] 6.6 [4.9–8.5] | 0.0258 | 1.425 [1.044–1.945] |
| Time to Next Treatment | ||||||
|
Level Sum Score: <median 1 ≥median | 13.5 [9.8–17.6] 9.4 [7.6–11.9] | 0.0633 | 1.347 [0.982–1.846] | 12.6 [10.2–16.5] 10.8 [8.9–12.6] | 0.1144 | 1.302 [0.938–1.806] |
|
EQ-VAS (health today): ≥median 2 <median | 12.6 [9.4–16.8] 11.1 [8.5–12.8] | 0.1034 | 1.305 [0.946–1.801] | 11.9 [9.7–14.6] 11.1 [9.0–20.2] | 0.4197 | 1.150 [0.819–1.614] |
|
EQ-5D-5L index: ≥median 3 <median | 13.1 [10.8–17.4] 9.2 [6.7–11.9] | 0.0414 | 1.383 [1.011–1.890] | 12.8 [10.5–20.2] 9.8 [8.5–11.9] | 0.0332 | 1.420 [1.028–1.962] |
EQ-VAS indicates EuroQol Visual Analogue Scale. 1 Median for Level Sum Score: 8.0. 2 Median for EQ-VAS: 65. 3 Median for EQ-5D-5L index: 0.8845. 4 Adjusted for the covariates remaining in the final Cox model: ECOG-PS, number of comorbidities, platelet count/transfusion dependence, peripheral blood blasts, azacitidine treatment line and azacitidine dose in cycle one.
Table 6.
Prognostic value of baseline Level Sum Score, EQ visual analogue scale (VAS) or EQ-5D-5L index value for the likelihood to respond to azacitidine (patients with EQ-5D-5L responses available at azacitidine treatment start (n = 205)).
Table 6.
Prognostic value of baseline Level Sum Score, EQ visual analogue scale (VAS) or EQ-5D-5L index value for the likelihood to respond to azacitidine (patients with EQ-5D-5L responses available at azacitidine treatment start (n = 205)).
| Univariate p | Multivariate 4 p | Multivariate 4 OR [95% CI] | |
|---|---|---|---|
| Level Sum Score: ≥ vs. < median 1 | 0.0009 | 0.0160 | 0.451 [0.235–0.852] |
| EQ-VAS: < vs. ≥ median 2 | 0.0237 | 0.1065 | 0.590 [0.321–1.116] |
| EQ-5D-5L index: < vs. ≥ median 3 | 0.0110 | 0.0627 | 0.522 [0.296–1.032] |
1 Median for Level Sum Score: 8.0. 2 Median for EQ-VAS: 65. 3 Median for EQ-5D-5L index: 0.8845. 4 Adjusted for the covariates remaining in the final Cox model: ECOG-PS, number of comorbidities, platelet count/transfusion dependence, peripheral blood blasts, azacitidine treatment line and azacitidine dose in cycle one.
Table 7.
Multivariate-adjusted 1 longitudinal analyses of EQ-5D results and dichotomised parameters per azacitidine treatment cycle using mixed-effects linear models.
Table 7.
Multivariate-adjusted 1 longitudinal analyses of EQ-5D results and dichotomised parameters per azacitidine treatment cycle using mixed-effects linear models.
| Mobility | Selfcare | Usual Activities | Pain/Discomfort | Anxiety/Depression | Level Sum Score 2 | EQ-VAS | EQ-5D-5L Index | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Differential blood count | n 3 | p | n | p | n | p | n | p | n | p | n | p | n | p | n | p |
| Peripheral blood blasts< vs. ≥5% | 1425 | 0.9897 | 1417 | 0.2548 | 1417 | 0.1447 | 1421 | 0.9703 | 1416 | 0.8775 | 1395 | 0.2930 | 1365 | 0.0996 | 1395 | 0.3916 |
| White blood cell count< vs. ≥30.0 G/L | 1429 | 0.1502 | 1421 | 0.5278 | 1421 | 0.2869 | 1425 | 0.0801 | 1420 | 0.2674 | 1399 | 0.1371 | 1368 | 0.7712 | 1399 | 0.1272 |
| Absolute neutrophil count< vs. ≥1.0 G/L | 1415 | 0.2206 | 1407 | 0.1586 | 1407 | 0.8529 | 1411 | 0.6784 | 1406 | 0.6362 | 1385 | 0.5171 | 1355 | 0.1329 | 1385 | 0.9389 |
| Monocytes< vs. ≥1.0 G/L | 1417 | 0.2559 | 1409 | 0.9738 | 1409 | 0.4770 | 1413 | 0.5203 | 1408 | 0.8287 | 1387 | 0.6366 | 1357 | 0.2476 | 1387 | 0.9439 |
| Lymphocytes< vs. ≥1.0 G/L | 1402 | 0.4021 | 1394 | 0.5043 | 1394 | 0.6879 | 1398 | 0.5349 | 1393 | 0.0941 | 1372 | 0.8871 | 1343 | 0.5429 | 1372 | 0.6557 |
| Haemoglobin< vs. ≥10.0 g/dL | 1429 | <0.0001 | 1421 | 0.0227 | 1421 | <0.0001 | 1425 | 0.9289 | 1420 | 0.7871 | 1399 | <0.0001 | 1368 | <0.0001 | 1399 | 0.0110 |
| Red blood cell transfusions: Yes vs. No | 1429 | 0.0003 | 1421 | 0.7072 | 1421 | <0.0001 | 1425 | 0.1935 | 1420 | 0.6996 | 1399 | 0.0003 | 1368 | <0.0001 | 1399 | 0.0161 |
| Platelet count< vs. ≥50 G/L | 1429 | 0.0122 | 1421 | 0.0647 | 1421 | 0.0248 | 1425 | 0.3142 | 1420 | 0.9574 | 1399 | 0.0212 | 1368 | 0.0006 | 1399 | 0.0156 |
| Platelet transfusions: Yes vs. No | 1429 | 0.0257 | 1421 | 0.0047 | 1421 | 0.0044 | 1425 | 0.0002 | 1420 | 0.2067 | 1399 | 0.0002 | 1368 | <0.0001 | 1399 | <0.0001 |
| Comorbidity/toxicity | ||||||||||||||||
| Ferritin< vs. ≥1000 µg/L | 723 | 0.0006 | 720 | 0.0598 | 720 | 0.0020 | 722 | 0.0785 | 718 | 0.5635 | 709 | 0.0024 | 703 | 0.0053 | 709 | 0.0163 |
| Creatinine< vs. ≥1.5 mg/dL | 1417 | 0.7976 | 1409 | 0.8133 | 1409 | 0.6386 | 1413 | 0.7286 | 1408 | 0.7550 | 1387 | 0.9162 | 1356 | 0.5338 | 1387 | 0.8874 |
| Lactate dehydrogenase, U/L | 1399 | 0.4066 | 1391 | 0.1095 | 1392 | 0.7977 | 1395 | 0.0642 | 1390 | 0.9778 | 1370 | 0.3834 | 1337 | 0.3343 | 1370 | 0.3673 |
| Glutamate oxaloacetate transaminase, U/L | 1406 | 0.7039 | 1398 | 0.8181 | 1399 | 0.5276 | 1402 | 0.2078 | 1397 | 0.4316 | 1377 | 0.6822 | 1345 | 0.5734 | 1377 | 0.9119 |
| Glutamate pyruvate transaminase, U/L | 1348 | 0.0867 | 1340 | 0.9662 | 1340 | 0.6501 | 1344 | 0.4822 | 1339 | 0.8201 | 1318 | 0.4770 | 1288 | 0.7212 | 1318 | 0.7369 |
| Bilirubin< vs. ≥1.2 mg/dL | 1407 | 0.0149 | 1399 | 0.0066 | 1399 | 0.0451 | 1403 | 0.9600 | 1398 | 0.4338 | 1377 | 0.0158 | 1346 | 0.0494 | 1377 | 0.0170 |
| Albumin< vs. ≥3.4 mg/dL | 583 | 0.0052 | 579 | <0.0001 | 578 | 0.0412 | 580 | 0.0942 | 576 | 0.0454 | 567 | 0.0034 | 565 | 0.2309 | 567 | 0.0355 |
| Cholinesterase< vs. ≥3.7 U/L | 584 | 0.0108 | 581 | 0.0437 | 580 | 0.6728 | 582 | 0.1706 | 580 | 0.5751 | 567 | 0.0992 | 567 | 0.0216 | 567 | 0.7691 |
| Adverse events 4 Grade 0–2 vs. 3–4 | 1429 | 0.0208 | 1421 | 0.0616 | 1421 | 0.0229 | 1425 | 0.0028 | 1420 | 0.0179 | 1399 | 0.0005 | 1368 | 0.0074 | 1399 | <0.0001 |
| Azacitidine dose/regimen | ||||||||||||||||
| Azacitidine< vs. ≥7 days | 1429 | 0.1648 | 1421 | 0.0129 | 1421 | 0.4369 | 1425 | 0.0964 | 1420 | 0.0158 | 1399 | 0.0096 | 1368 | 0.4788 | 1399 | 0.0288 |
| Azacitidine< vs. ≥75 mg/m2/day | 1426 | 0.1485 | 1418 | 0.1155 | 1418 | 0.0249 | 1422 | 0.0168 | 1417 | 0.0001 | 1396 | 0.0003 | 1365 | 0.0040 | 1396 | 0.0013 |
| Haematologic improvement (HI) | ||||||||||||||||
| HI-any 5: Yes vs. No | 1275 | 0.0004 | 1268 | 0.0130 | 1270 | 0.0003 | 1272 | 0.6473 | 1266 | 0.1747 | 1248 | 0.0005 | 1221 | <0.0001 | 1248 | 0.0048 |
| HI-Erythrocytes: Yes vs. No | 1296 | 0.0008 | 1289 | 0.0163 | 1291 | <0.0001 | 1293 | 0.2981 | 1287 | 0.7419 | 1269 | 0.0084 | 1239 | <0.0001 | 1269 | 0.1645 |
| HI-Platelets: Yes vs. No | 1317 | 0.0025 | 1310 | 0.0011 | 1311 | 0.0008 | 1315 | 0.0951 | 1310 | 0.2232 | 1288 | 0.0005 | 1262 | <0.0001 | 1288 | 0.0003 |
| HI-Neutrophils: Yes vs. No | 1362 | 0.4299 | 1355 | 0.7016 | 1354 | 0.2083 | 1358 | 0.1326 | 1353 | 0.4239 | 1333 | 0.2837 | 1303 | 0.0012 | 1333 | 0.6162 |
1 Adjusted for the covariates remaining in the final Cox model: ECOG-PS, number of comorbidities, platelet count/transfusion dependence, peripheral blood blasts, azacitidine treatment line and azacitidine dose in cycle one. 2 Represents the numerical sum of all EQ-5D-5L responses. 3 Number of parameter/EQ-5D-5L response pairs. 4 Assessed according to CTCAEv4.0. 5 Includes HI-Neutrophils and/or HI-Erythrocytes and/or HI-Platelets. Font color is red for all significant p-values <0.05.
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Pleyer, L.; Heibl, S.; Tinchon, C.; Vallet, S.; Schreder, M.; Melchardt, T.; Stute, N.; Föhrenbach Quiroz, K.T.; Leisch, M.; Egle, A.; et al. Health-Related Quality of Life as Assessed by the EQ-5D-5L Predicts Outcomes of Patients Treated with Azacitidine—A Prospective Cohort Study by the AGMT. Cancers 2023, 15, 1388. https://doi.org/10.3390/cancers15051388
AMA Style
Pleyer L, Heibl S, Tinchon C, Vallet S, Schreder M, Melchardt T, Stute N, Föhrenbach Quiroz KT, Leisch M, Egle A, et al. Health-Related Quality of Life as Assessed by the EQ-5D-5L Predicts Outcomes of Patients Treated with Azacitidine—A Prospective Cohort Study by the AGMT. Cancers. 2023; 15(5):1388. https://doi.org/10.3390/cancers15051388
Chicago/Turabian StylePleyer, Lisa, Sonja Heibl, Christoph Tinchon, Sonia Vallet, Martin Schreder, Thomas Melchardt, Norbert Stute, Kim Tamara Föhrenbach Quiroz, Michael Leisch, Alexander Egle, and et al. 2023. "Health-Related Quality of Life as Assessed by the EQ-5D-5L Predicts Outcomes of Patients Treated with Azacitidine—A Prospective Cohort Study by the AGMT" Cancers 15, no. 5: 1388. https://doi.org/10.3390/cancers15051388
APA StylePleyer, L., Heibl, S., Tinchon, C., Vallet, S., Schreder, M., Melchardt, T., Stute, N., Föhrenbach Quiroz, K. T., Leisch, M., Egle, A., Scagnetti, L., Wolf, D., Beswick, R., Drost, M., Larcher-Senn, J., Grochtdreis, T., Vaisband, M., Hasenauer, J., Zaborsky, N., ... Stauder, R. (2023). Health-Related Quality of Life as Assessed by the EQ-5D-5L Predicts Outcomes of Patients Treated with Azacitidine—A Prospective Cohort Study by the AGMT. Cancers, 15(5), 1388. https://doi.org/10.3390/cancers15051388
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