Abstract
Abstract 2776
Poster Board II-752
We wondered whether prognostic factors have similar relevance in different subpopulations of MDS patients.
Our analysis was based on patients with primary, untreated MDS, including 181 RA, 169 RARS, 649 RCMD, 322 RSCMD, 79 5q-syndromes, 290 RAEB I, 324 RAEB II, 266 CMML I, 64 CMML II, and 209 RAEB-T. The impact of prognostic variables in univariate analysis was compared in subpopulations of patients defined by medullary blast count, namely <5%, ≥5% (table), ≥10%, and ≥20% (not shown), as well as 3 subpopulations defined by the cytogenetic risk groups according to IPSS (table). Multivariate analysis of prognostic factors was performed for cytogenetically defined subgroups and WHO-subtypes.
/ . | <5% blasts . | ≥5% blasts . | Cytogenetic risk group . | good . | intermediate . | poor . | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
Log-Rank . | p . | Log-Rank . | p . | / . | Log-Rank . | p . | Log-Rank . | p . | Log-Rank . | p . | |
Hemoglobin </≥10g/dl | 76 | <0,0001 | 90 | <0,0001 | / | 24,1 | <0,0001 | 0,74 | 0,38 | 2,6 | 0,1 |
Sex m/w | 14 | 0,0002 | 0,4 | 0,52 | / | 31 | <0,0001 | 3 | 0,08 | 0 | 0,9 |
Age </≥60years | 64 | <0,0001 | 10,5 | 0,001 | / | 42 | <0,0001 | 4,1 | 0,04 | 1 | 0,3 |
LDH </≥200U/l | 55 | <0,0001 | 33 | <0,0001 | / | 30 | <0,0001 | 10,2 | 0,001 | 4 | 0,04 |
Platelets </≥50000/μl | 29 | <0,0001 | 35 | <0,0001 | / | 4,8 | 0,027 | 6,8 | 0,0091 | 13 | 0,0003 |
ANC </≥1000/μl | 4 | 0,04 | 3 | 0,08 | / | 0,8 | 0,8 | 0,8 | 0,37 | 2,9 | 0,08 |
WBC </≥20000/μl | 21 | <0,0001 | 3,8 | 0,051 | / | 17,9 | <0,0001 | 15,2 | 0,0001 | 4,4 | 0,03 |
Transfusion y/n | 72 | <0,0001 | 68 | <0,0001 | / | 11,7 | 0,0006 | 0,3 | 0,5 | 3 | 0,08 |
Fibrosis y/n | 10 | 0,001 | 10,2 | 0,001 | / | 4,9 | 0,02 | 1,5 | 0,2 | 0,4 | 0,5 |
Karyotype-risk | 51 | <0,0001 | 45 | <0,0001 | / | / | / | / | / | / | / |
Blast count </≥ 5% | / | / | / | / | / | 36,6 | <0,0001 | 9,8 | 0,001 | 8,9 | 0,02 |
Blast count </≥ 10% | / | / | / | / | / | 54,7 | <0,0001 | 6,2 | 0,01 | 12,4 | 0,0004 |
Blast count </≥ 20% | / | / | / | / | / | 58,4 | <0,0001 | 3,1 | 0,08 | 9 | 0,0026 |
/ . | <5% blasts . | ≥5% blasts . | Cytogenetic risk group . | good . | intermediate . | poor . | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
Log-Rank . | p . | Log-Rank . | p . | / . | Log-Rank . | p . | Log-Rank . | p . | Log-Rank . | p . | |
Hemoglobin </≥10g/dl | 76 | <0,0001 | 90 | <0,0001 | / | 24,1 | <0,0001 | 0,74 | 0,38 | 2,6 | 0,1 |
Sex m/w | 14 | 0,0002 | 0,4 | 0,52 | / | 31 | <0,0001 | 3 | 0,08 | 0 | 0,9 |
Age </≥60years | 64 | <0,0001 | 10,5 | 0,001 | / | 42 | <0,0001 | 4,1 | 0,04 | 1 | 0,3 |
LDH </≥200U/l | 55 | <0,0001 | 33 | <0,0001 | / | 30 | <0,0001 | 10,2 | 0,001 | 4 | 0,04 |
Platelets </≥50000/μl | 29 | <0,0001 | 35 | <0,0001 | / | 4,8 | 0,027 | 6,8 | 0,0091 | 13 | 0,0003 |
ANC </≥1000/μl | 4 | 0,04 | 3 | 0,08 | / | 0,8 | 0,8 | 0,8 | 0,37 | 2,9 | 0,08 |
WBC </≥20000/μl | 21 | <0,0001 | 3,8 | 0,051 | / | 17,9 | <0,0001 | 15,2 | 0,0001 | 4,4 | 0,03 |
Transfusion y/n | 72 | <0,0001 | 68 | <0,0001 | / | 11,7 | 0,0006 | 0,3 | 0,5 | 3 | 0,08 |
Fibrosis y/n | 10 | 0,001 | 10,2 | 0,001 | / | 4,9 | 0,02 | 1,5 | 0,2 | 0,4 | 0,5 |
Karyotype-risk | 51 | <0,0001 | 45 | <0,0001 | / | / | / | / | / | / | / |
Blast count </≥ 5% | / | / | / | / | / | 36,6 | <0,0001 | 9,8 | 0,001 | 8,9 | 0,02 |
Blast count </≥ 10% | / | / | / | / | / | 54,7 | <0,0001 | 6,2 | 0,01 | 12,4 | 0,0004 |
Blast count </≥ 20% | / | / | / | / | / | 58,4 | <0,0001 | 3,1 | 0,08 | 9 | 0,0026 |
Strong prognostic factors in all blast-defined subgroups were hemoglobin, transfusion dependency, increased WBC, age, and LDH. However, all variables became less important in patients with ≥20% blasts (RAEB-T) and increased WBC was rare. Platelet count and cytogenetic risk groups were relevant in patients with <5%, ≥5%, and ≥10% marrow blasts, but not in RAEB-T. Marrow fibrosis was important in patients with <5% or ≥5% blasts, but not ≥10%. Gender and ANC <1000/μl were significant only in patients with a normal blast count. Furthermore, we looked for the effect of the karyotypes, relevant for IPSS scoring (-Y, del5q, del20q, others, del7q/-7, complex), and found a comparable influence on survival, irrespective whether patients had < or ≥5% marrow blasts.
In subpopulations defined by cytogenetic risk groups, several prognostic factors were highly significant in univariate analysis, if patients had a good risk karyotype. These included hemoglobin, sex, age, LDH, increased WBC, transfusion need, and blast count (cut-offs 5%, 10%, and 20%). In the intermediate risk group only LDH, platelets, WBC, and blasts were significant prognostic factors, while in the high risk group only platelets and blast count remained significant.
Multivariate analysis was performed for the cytogenetic risk groups and for subgroups defined by WHO subtypes. The analysis considered blast count (</≥5%), hemoglobin, platelets, ANC, cytogenetic risk group, transfusion need, sex, and age. In the subgroup including RA, RARS, and 5q-syndrome, LDH, transfusion, and age in descending order were independent prognostic parameters. In the RCMD+RSCMD group, karyotype, age, transfusion, and platelets were relevant factors. In the RAEB I+II subgroup, the order was hemoglobin, karyotype, age, and platelets, while in CMML I+II only hemoglobin had independent influence. In RAEB-T none of the factors examined was of independent significance. Looking at cytogenetic risk groups, in the favorable group, several variables independently influenced survival, namely transfusion, blasts, age, sex, and LDH (in this order). Interestingly, in the intermediate and high risk group, only blast count and platelets retained a significant impact.
Univariate analysis showed prognostic factors (except ANC) included in IPSS and WPSS are relevant in most subgroups defined by marrow blast percentage. However, they all lose their impact if the blast count exceeds 20%. Regarding cytogenetic risk groups, several prognostic factors lose their influence already in the intermediate risk group. This underscores the prognostic importance of MDS cytogenetics. Multivariate analysis showed MDS subpopulations defined by WHO types also differ with regard to prognostic factors. In particular, CMML and RAEB-T stand out against the other MDS types.
Kuendgen:Celgene: Honoraria. Hildebrandt:Celgene: Research Funding. Gattermann:Novartis: Honoraria, Participation in Advisory Boards on deferasirox clinical trials. Germing:Novartis, Celgene: Honoraria, Research Funding.
Author notes
Asterisk with author names denotes non-ASH members.