1. The real world of 'low-risk' MDS: early lessons from the EUMDS registry
Theo de Witte, Louise de Swart, Alex Smith, Pierre Fenaux, Raphael Itzykson, Guillermo Sanz, Eva Hellström-Lindberg, Argyris Symeonidis, Jaroslav Cermak, Ulrich Germing, Reinhard Stauder, Otilia Georgescu, Marius MacKenzie, Luca Malcovati, Mette Skov Holm, Krzysztof Mądry, Sophie Park, Odile Beyne-Rauzy, Jackie Droste, and David Bowen

2. MDS: median age at presentation
Registry
Median age at diagnosis (years)
Dusseldorf1
69-73
Pavia2
65-71
Spain3 74
SW Thames4
77 (77-78)
SEER5
> 75
≥80y – 38%
≥70y – 33%
Yorkshire Network UK** 75
ELN MDS Registry**
(IPSS Low/INT-1 only)
74 ( )
Germing et al, Leukemia Research, 2000, 24, 983
Malcovati et al, Journal of Clinical Oncology, 2005, 23, 7594
Sanz et al, ASH 2008,
Phekoo et al, Haematologica 2006,91, 1400
Rollison et al, Blood 2008, 112, 45
**unpublished data

3. Why establish a multicentre, multicountry registry for low risk MDS?
To understand the diagnosis and management of MDS as defined by ‘real world’ physicians in small and large hospitals across Europe
Lack of prospective interventional studies
Solution = Longitudinal observational studies linked with translational studies (e.g. whole genome sequencing)
Potential to identify new biomarkers for therapy response IN THE REAL WORLD (stratified / personalised medicine)

4. Clinical effectiveness
Product registration for market authorisation relies on traditional phase 3 clinical trials
This does not reflect the real-world
Target population
Outcome
Clinical registries with good source data validation / quality assurance can demonstrate:
Clinical effectiveness
?cost effectiveness (health technology assessment)
IN THE REAL WORLD

5. Study Design: EU-MDS Registry I
Newly diagnosed MDS patients (<3 months after diagnosis): no selection!
IPSS low- and intermediate-1
Total 1000 patients in 14 countries, 118 sites
Primary objective: to analyze the impact of various disease and patient related factors, including co-morbidity and the impact of disease-management on outcome

6. Study design EU-MDS Registry II
Secondary objectives
Investigate correlation between:
Clinical characteristics at inclusion
Secondary iron overload due to transfusions
Administered treatment
and
Overall survival & progression-free survival
Performance status, quality of life

7. Structure: EU-MDS Registry
An academic programme Sponsor: University of Nijmegen

8. Number of Patients by Country
14 Countries
118 Centres
Recruited:
Jan 2008-Dec 2010
Number of days from diagnosis to inclusion:
42 median (0 to 98)

9. Age at Diagnosis
Median age: 74 (19-95)

10. MDS Classification WHO 2001
Total
Female
Median Age (years) N
1000 (100%)
40% 74 RA
180 (18.0)
36% 75
RARS
184 (18.4)
45% 76
RCMD
354 (35.4)
35%
RCMD-RS
71 (7.1)
37%
RAEB-1
114 (11.4) 72
RAEB-2
4 (0.4)
50%
MDS-U
31 (3.1)
39% 73
5q-Syndrome
62 (6.2)
81%

11. WHO Classification by Country

12. Reproducibility of WHO 2008 classification
Least reproducible:
% erythroid dysplasia
Unilineage vs. multilineage dysplasia
Blast % between 2-10%
Senent et al, Haematologica 2013, 98, 568

13. IPSS & Cytogenetics IPSS Score Total N 1000 (100%) 485 (48.5) 0.5
485 (48.5)
0.5
316 (31.6) 1
133 (13.3) NK
66 (6.6)
Cytogenetics
Total N
1000 (100%)
Good
772 (77.2)
Intermediate
149 (14.9)
Poor
13 (1.3)
Not Done
66 (6.6)

14. IPSS Score by Country

15. Concomitant medication Co-morbidities%
Anti - Hypertensive
45.6
Proton Pump Inhibitors
21.7
Cholesterol Lowering
20.4
Anti – Diabetic
16.8
Diuretics
16.6
Anti – Platelet
15.9
Anti - Coagulant
14.3
Anti – Arrhythmic
11.7
Folic Acid
11.2
Antidepressants 10
Thyroid Drugs
9.5 %
Diabetes mellitus
18.0
Arrhythmia
11.8
Thyroid disease
11.7
Rheumatological Disease
10.7
Dyspnoea on moderate activity
9.7
Malignant Disease
8.5
Heart failure requiring treatment
8.4
Renal Disease
7.9
Previous myocardial infarction
7.8
Angina
7.5

16. Co-morbidity at Baseline
Sorror Score
QoL - EQ5D

17. Co-morbidity MDS Co-morbidity index Total Low 642 (64.2) Intermediate
302 (30.2)
High
56 (5.6)
MD- CI derived from a score of 5 comorbidities namely:
Cardiac disease, moderate to severe hepatic disease, severe pulmonary
disease, renal disease, solid tumor.
Della Porta et al, Haematologica 2011, 96, 441

18. Cause of Death Cause of Death N % Total 198 100 Infection 42 21.2 AML37
18.7
Cardiovascular 19
9.6
Other
Other Malignancy 13
6.6
Pulmonary 12
6.1
Haemorrhage 10
5.1
Myelodysplastic 5
2.5
Hepatic 4
2.0
Accidental 3
1.5
Renal Failure 2
1.0
Not Known 32
16.2

19. Interventional treatment 1

21. Transfusion Status
Baseline
Over Time

22. Proportion of Subjects Transfused (at least 1 RBC unit) and Treated Subjects by Country

23. Prognostic factors for overall survival and disease progression
Multivariate analysis
IPSS score
WPSS score
Red cell transfusion dependence
Univariate analysis (exploratory)
Rate of progression of cytopenias
EQ-5D domains
NB. Follow up is relatively short; median 24 months

24. Overall survival of EUMDS cohort by IPSS and IPSS-R

25. IWG-PM IPSS-R cohort

26. EQ-5D Dimensions and Survival
Mobility
Self-care

27. Ongoing substudies
Clinical effectiveness of erythropoetic stimulating agents (ESA)
Lenalidomide to follow
Clinical significance of red cell transfusion dependence
Biochemical and clinical analysis of iron overload (serum samples collected 6 monthly on >500 patients)
Molecular genotype definition for patients at diagnosis

28. Learning points
Prospective registry data will provide ‘real world’ demographic and outcome data for low risk MDS
MDS has the oldest median age of all haematological malignancies
Reproducibility of morphological diagnosis is far from perfect
Approximately half of low-risk MDS patients do not require active therapy at diagnosis
Only 25-30% patients are transfusion-dependent at any time point in the first 2 years from diagnosis
Registries such as EUMDS will be important datasets for clinical effectiveness and health technology assessment

29. Acknowledgments Chief Investigator: Theo de Witte
Database / statistics: Alex Smith
Project Manager: Jackie Droste
Research Fellow: Louise de Swart
Steering and Operational Committee members
PI, staff and willing patients at each site