Skip to main content
Erschienen in: Wiener Medizinische Wochenschrift 1-2/2023

Open Access 29.11.2022 | main topic

Significance of hypergammaglobulinemia in patients with chronic myelomonocytic leukemia

verfasst von: Marie-Therese Zack, Univ. Prof. Dr. Klaus Geissler

Erschienen in: Wiener Medizinische Wochenschrift | Ausgabe 1-2/2023

Summary

Chronic inflammation is often indicated by a relative increase in the gamma globulin fraction in the serum electrophoresis. In a retrospective study, we analyzed the prevalence of relative hypergammaglobulinemia in 60 patients with chronic myelomonocytic leukemia (CMML), its potential prognostic impact, and potential correlations with laboratory and molecular features. Relative hypergammaglobulinemia (> 20%) was found in 25/60 (42%) patients. The median survival of patients with relative hypergammaglobulinemia was significantly shorter than in patients without hypergammaglobulinemia (10 vs. 24 months, p = 0.018). There was no difference between the groups regarding leukocyte count, hemoglobin value, and platelet count, but a higher prevalence of NRAS mutations and a lower prevalence of ZRSR2 mutations in patients with hypergammaglobulinemia. Our results show that hypergammaglobulinemia is present in a proportion of CMML patients and that this abnormality is associated with poor overall survival. The role of chronic inflammation in the pathophysiology of CMML needs to be further investigated.
Hinweise

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Introduction

Chronic myelomonocytic leukemia (CMML) is a rare, genotypically and phenotypically heterogenous hematologic malignancy of elderly people with an intrinsic risk to progress and transform into secondary acute myeloid leukemia (AML). With regard to the presence of myeloproliferation, CMML was originally subdivided into myeloproliferative disorder (MP-CMML; white blood cell count [WBC] count > 13 × 109/L) versus myelodysplastic syndrome (MD-CMML; WBC count ≤ 13 × 109/L MD-CMML) by the FAB criteria [1, 2]. Since CMML is characterized by features of both MDS and MPN, the World Health Organization (WHO) classification of 2002 assigned CMML to the mixed category, MDS/MPN [3]. CMML is further subclassified by WHO into three groups based on blast equivalents (blasts plus promonocytes) in peripheral blood (PB) and bone marrow (BM) as follows: CMML‑0 if PB < 2% and BM < 5% blast equivalents; CMML‑1 if PB 2–4% or BM 5–9% blast equivalents; and CMML‑2 if PB 5–19% or BM 10–19% blast equivalent, and/or Auer rods are present [4]. CMML patients may have a highly variable outcome, suggesting that several factors can determine the course of disease and the cause of death in these patients [59]. There are a number of established prognostic parameters that have been incorporated into several prognostic models [1021]. In clinical practice, chronic inflammation is often indicated by a relative increase in the gamma globulin fraction of the electrophoresis. The potential contribution of chronic inflammation to the clinical outcome of CMML patients is poorly investigated. Using the database of the Austrian Biodatabase for Chronic Myelomonocytic Leukemia (ABCMML), we analyzed 60 CMML patients in whom serum electrophoresis was available in patient records.

Patients and methods

Patients

Recently, we have shown that the ABCMML may be used as a representative and useful real-life data source for biomedical research [22]. In this database, we retrospectively collected epidemiologic, hematologic, biochemical, clinical, immunophenotypic, cytogenetic, molecular, and biologic data of patients with CMML from different centers. The diagnosis of CMML and leukemic transformation was according to the WHO criteria [2, 3]. Clinical and laboratory routine parameters were obtained from patient records. A detailed central manual retrospective chart review was carried out to ensure data quality before analysis of data from institutions. Due to the fact that CMML may be considered as an evolutionary process from clonal hematopoiesis of indeterminate potential (CHIP) to CMML-related AML [23], and the fact that the distinction between mature and immature monocytic cells, which is required to determine the time of transformation into AML, is notoriously difficult due to the lack of reliable immunophenotypic markers, we found it more appropriate not to exclude the few CMML patients with transformation from our analysis [24].
In 60 CMML patients collected between 01.01.1990 and 31.03.2019, serum electrophoreses was available for analysis. This research was approved by the ethics committee of the City of Vienna on 10 June 2015 (ethics code: 15-059-VK).

Molecular studies

Genomic DNA was isolated from mononuclear cell (MNC) fractions of the blood samples according to standard procedures. The mutational status of CMML-related protein-coding genes was determined by targeted amplicon sequencing using the MiSeq platform (Illumina, San Diego, CA, USA). Details of the gene panel, library preparation, and data processing have been reported previously [22]. Only variants with strong clinical significance according to the Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer and VAF ≥ 5% were used for statistical analysis regarding a potential predictive value in various treatment options.

Statistical analysis

The log-rank test was used to determine whether individual parameters were associated with overall survival (OS). OS was defined as the time from sampling to death (uncensored) or last follow-up (censored). Dichotomous variables were compared between different groups with the chi-square test. The Mann–Whitney U test was used to compare two unmatched groups when continuous variables were nonnormally distributed.
To measure the degree of relationship between protein fractions of serum electrophoresis, Pearson correlation was performed. All results were considered significant at p < 0.05. Statistical analyses were performed with SPSS v. 27 (IBM Corp., Armonk, NY, USA); the reported p-values were two-sided. The normal upper limits for gamma globulin, α1, and α2 fractions were 20%, 6%, and 12%, respectively. The normal lower limit for the albumin fraction was 50%.

Results

Characteristics of patients

The baseline characteristics of the 60 patients with CMML are shown in Table 1. In order to make comparisons with other published CMML cohorts possible, the percentages of patients regarding established prognostic parameters are given [17]. As seen in other CMML series, there was a male predominance in study patients and more than half of the patients were aged 70 years or older [17]. More than half (51%) of the study patients had leukocytosis > 13 G/L, which is more frequent as compared to other cohorts, where this proportion is usually below 50%. Two patients in this cohort have already transformed into CMML-related acute myeloid leukemia (AML).
Table 1
Characteristics of chronic myelomonocytic leukemia patients
 
Cases
N = 60
Percent
(%)
Age
Evaluable=60
< 70 years
27
45
≥ 70 years
33
55
Sex
Evaluable=60
Male
35
58
Female
25
42
Leukocytes
Evaluable=59
> 13 G/L
32
54
≤ 13 G/L
27
46
Hemoglobin
Evaluable=59
< 10 g/dL
12
20
≥ 10 g/dL
47
80
Platelets
Evaluable=59
< 100 G/L
28
47
≥ 100 G/L
31
53
Peripheral blood blasts
Evaluable=55
Absent
42
76
Present
13
24

Prevalence of hypergammaglobulinemia and other changes in serum electrophoresis in CMML patients

Relative hypergammaglobulinemia (> 20%) was found in 25/60 (42%) patients. A relative decrease of albumin < 50% was seen in 11/58 (19%) patients. The α1 and α2 fractions were increased in 18/60 (30%) and 9/60 (15%) CMML patients, respectively. There was a significant strong negative correlation between gammaglobulinemia and albuminemia (−0.821; p = 0.000), indicating the opposite behavior of these parameters. There was a significant weak negative correlation between gamma globulins and α2 fraction (−0.319; p = 0.017), whereas no significant correlation was observed between gamma globulins and the α1 fraction in the serum electrophoresis (−0.032; p = 0.815).

Impact of relative hypergammaglobulinemia on survival

As shown in Fig. 1, the median survival of patients with relative hypergammaglobulinemia was significantly shorter than in patients without hypergammaglobulinemia (10 vs. 24 months, p = 0.018). Among established prognostic parameters including leukocytosis > 13 G/L, anemia < 10 g/dL, thrombocytopenia < 100 G/L, and the presence of blast cells in peripheral blood, only thrombocytopenia had an adverse impact on survival in the univariate analysis in the study cohort (Table 2). The significant effect of hypergammaglobulinemia in univariate analysis remained in the multivariate analysis in the presence of thrombocytopenia (Table 3).
Table 2
Univariate analysis of established single prognostic parameters in patients with chronic myelomonocytic leukemia
Factors
Factor present
Median OS (months)
Factor absent
Median OS (months)
P-value
(Log-rank)
Gamma fraction > 20%
10.0
24.0
0.018
WBC > 13 × G/L
12.0
23.0
0.505
Hb < 10 g/dL
10.0
23.0
0.396
PLT < 100 × G/L
10.0
24.0
0.005
PB blasts present
12.0
12.0
0.633
The log-rank test was used to determine if individual parameters were associated with OS
OS overall survival, WBC white blood cell count, Hb hemoglobin, PLT platelet count, PB peripheral blood
Table 3
Hazard ratios, confidence intervals, and p-values of Cox regression analyses for survival including hypergammaglobulinemia and thrombocytopenia
Parameter
Hazard ratio
95% confidence interval
P-value
Gamma fraction > 20%
2.735
1.162–6.440
0.021
PLT < 100 G/L
3.365
1.376–8.229
0.008
PLT platelet count

Laboratory and molecular features in the presence or absence of hypergammaglobulinemia

As shown in Table 4, there was no difference in the groups regarding laboratory parameters including leukocyte counts, hemoglobin values, platelet counts, and circulating blasts. Regarding molecular aberrations, mutations in the NRAS gene were more common in patients with hypergammaglobulinemia, whereas mutations in the ZRSR2 gene were more common in patients without hypergammaglobulinemia (Table 5).
Table 4
Laboratory features stratified by the presence or absence of hypergammaglobulinemia
 
All patients
(n = 60)
Hypergamma+
(n = 25)
Hypergamma−
(n = 35)
P-value
Age in years; median (range)
Evaluable = 58
71 (36–91)
72 (36–84)
71 (44–91)
0.970
Sex (Male); n
Evaluable = 58
35 (58%)
14 (56%)
21 (60%)
0.757
Leukocytes G/L; median (range)
Evaluable = 57
14.9 (3–238)
20.8 (3–238)
14.1 (3.8–74)
0.212
Hemoglobin g/dL; median (range)
Evaluable = 57
11.9 (7.6–15.0)
11.9 (7.5–14.8)
11.8 (7.6–15.0)
0.580
Platelets G/L; median (range)
Evaluable = 57
102 (5–1148)
93 (12–695)
107 (5–1148)
0.800
PB blasts %; median (range)
Evaluable = 55
0 (0–57)
0 (0–57)
0 (0–18)
0.330
PB peripheral blood, Hypergamma hypergammaglobulinemia
Table 5
Molecular features stratified by the presence or absence of hypergammaglobulinemia
Mutated gene
VAF (≥ 5%)
With hypergammaglobulinemia
Without hypergammaglobulinemia
P-value
NRAS
4/14 (29%)
1/23 (4%)
0.037
KRAS
2/14 (14%)
3/23 (13%)
0.915
CBL
3/14 (21%)
3/23 (13%)
0.502
NF1
0/11 (0%)
4/17 (24%)
0.082
PTPN11
1/14 (7%)
3/23 (13%)
0.575
TET2
8/14 (57%)
20/24 (83%)
0.077
IDH1/2
2/14 (14%)
0/24 (0%)
0.057
ASXL1
4/14 (29%)
10/23 (43%)
0.365
EZH2
0/14 (0%)
4/24 (17%)
0.106
DNMT3A
0/14 (0%)
3/24 (13%)
0.168
SRSF2
5/14 (36%)
8/24 (33%)
0.881
ZRSR2
0/14 (0%)
6/24 (25%)
0.041
U2AF1
1/14 (7%)
2/23 (13%)
0.867
SF3B1
0/14 (0%)
2/24 (8%)
0.267
RUNX1
0/14 (0%)
5/24 (21%)
0.067
TP53
5/14 (36%)
5/20 (25%)
0.500
VAF variant allele frequency

Discussion

Serum electrophoresis is an excellent tool for analyzing the inflammation status in patients. In the early phase of acute inflammation, the α1 and α2 fractions are increased, whereas changes in albumin and the γ fraction are not regularly seen [25]. In the late phase of acute inflammation, the serum albumin starts to decrease and the γ fraction to increase. Chronic inflammatory disorders are characterized by increased gamma globulins and by decreased serum albumin, whereas the α1 and α2 fractions are not altered anymore.
Since serum electrophoresis is not routinely performed in myeloid disorders, it was available in only a subgroup of patients in our ABCMML database. In these patients, we have seen relative polyclonal hypergammaglobulinemia in 42%. There was a clear inverse correlation to albumin levels, indicating opposite changes of gamma globulins and albumin in chronic inflammation. In a subgroup of patients, α1 and/or α2 fractions were increased in the electrophoresis, suggesting a persistent acute-phase pattern in these patients.
The mechanism behind hypergammaglobulinemia in CMML patients remains to be determined. Polyclonal hypergammaglobulinemia has already been described in previous series of patients with CMML [26]. We have looked for possible correlations of hypergammaglobulinemia with phenotypic and molecular features. Regarding laboratory features including leukocyte count, hemoglobin value, platelet value, and circulating blasts, we could not find any differences in patients with or without hypergammaglobulinemia, indicating that the mechanisms leading to changes in these parameters are different from the mechanism leading to hypergammaglobulinemia. Regarding molecular parameters, we observed an association of hypergammaglobulinemia and molecular aberrations of the NRAS and ZRSFR genes. These findings are unexpected, but have to be considered with caution due to the small number of CMML patients who had molecular analysis. However, in this context, it has to be mentioned that recently, a functional link between molecular aberrations and activation of the inflammasome was reported in a preclinical model [27]. In this mouse model, Kras-driven myeloproliferation was reversed by functional inactivation of NLRP1, a major component of the inflammasome. A similar phenotypic improvement was seen with therapeutic IL‑1 receptor blockade.
Most strikingly, patients with hypergammaglobulinemia had inferior survival as compared to CMML patients without hypergammaglobulinemia. This adverse impact on survival was found in univariate analysis and was retained in the multivariate analysis in the presence of thrombocytopenia, which was the only adverse blood parameter, indicating that the pathophysiologic basis for the two alterations are different. In larger series, all parameters including leukocytosis, anemia, thrombocytopenia, and circulating blast cells are established prognostic parameters. The lack of prognostic impact of these parameters, except thrombocytopenia, is most likely the result of the small patient cohort in this study. Therefore, the prognostic impact of hypergammaglobulinemia in this study deserves even more attention. There is clear evidence in the literature that IL‑6 is one of the main stimulatory factors of IgG production [28, 29]. On the other hand, it has been shown that CMML cells can produce IL‑6 in vitro and stimulate CMML cell growth in an autocrine manner [30]. One attractive hypothesis of our exploratory findings could be that IL‑6 may provide a common basis for hypergammaglobulinemia and the adverse outcome in these patients. This hypothesis must be further explored in future studies.
We are aware of the limitations of our study. For example, most of the information used in this study was derived from retrospective real-world data that were not collected systematically or prospectively. Thus, not every parameter was available in all patients. In addition, data from patient records were obtained over many years and from many different centers. Moreover, the patients included in this study were a relatively heterogenous population regarding the blast cell counts, and there was a lack of molecular data in a significant number of patients. However, real-world data have recently been recognized as an important way to get insights into the routine management and natural history of rare diseases [31]. CMML is a rare disease and adequate patient numbers for a systematic and prospective study are not easy to collect within a limited timeframe. Moreover, the ABCMML provides information derived from molecular as well as from functional studies and therefore allows a more comprehensive view and deeper insight into the complex pathophysiology of this hematologic malignancy [22].

Funding

This study was supported by the Gesellschaft zur Erforschung der Biologie und Therapie von Tumorkrankheiten—ABCMML-112015

Conflict of interest

M.-T. Zack and K. Geissler declare that they have no competing interests.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creativecommons.​org/​licenses/​by/​4.​0/​.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Unsere Produktempfehlungen

Abo für kostenpflichtige Inhalte

Literatur
1.
Zurück zum Zitat Bennett JM, Catovsky D, Daniel MT, et al. Proposals for the classification of the myelodysplastic syndromes. Br J Haematol. 1982;51(2):189–99.CrossRef Bennett JM, Catovsky D, Daniel MT, et al. Proposals for the classification of the myelodysplastic syndromes. Br J Haematol. 1982;51(2):189–99.CrossRef
2.
Zurück zum Zitat Vardiman JW, Harris NL, Brunning RD. The World Health Organization (WHO) classification of the myeloid neoplasms. Blood. 2002;100(7):2292–302.CrossRef Vardiman JW, Harris NL, Brunning RD. The World Health Organization (WHO) classification of the myeloid neoplasms. Blood. 2002;100(7):2292–302.CrossRef
3.
Zurück zum Zitat Vardiman JW, Thiele J, Arber DA, et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood. 2009;114(5):937–51.CrossRef Vardiman JW, Thiele J, Arber DA, et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood. 2009;114(5):937–51.CrossRef
4.
Zurück zum Zitat Arber DA, Orazi A, Hasserjian R, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127(20):2391–405.CrossRef Arber DA, Orazi A, Hasserjian R, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127(20):2391–405.CrossRef
5.
Zurück zum Zitat Onida F, Kantarjian HM, Smith TL, et al. Prognostic factors and scoring systems in chronic myelomonocytic leukemia: a retrospective analysis of 213 patients. Blood. 2002;99(3):840–9.CrossRef Onida F, Kantarjian HM, Smith TL, et al. Prognostic factors and scoring systems in chronic myelomonocytic leukemia: a retrospective analysis of 213 patients. Blood. 2002;99(3):840–9.CrossRef
6.
Zurück zum Zitat Patnaik MM, Padron E, LaBorde RR, et al. Mayo prognostic model for WHO-defined chronic myelomonocytic leukemia: ASXL1 and spliceosome component mutations and outcomes. Leukemia. 2013;27(7):1504–10.CrossRef Patnaik MM, Padron E, LaBorde RR, et al. Mayo prognostic model for WHO-defined chronic myelomonocytic leukemia: ASXL1 and spliceosome component mutations and outcomes. Leukemia. 2013;27(7):1504–10.CrossRef
7.
Zurück zum Zitat Itzykson R, Kosmider O, Renneville A, et al. Prognostic score including gene mutations in chronic myelomonocytic leukemia. J Clin Oncol. 2013;31(19):2428–36.CrossRef Itzykson R, Kosmider O, Renneville A, et al. Prognostic score including gene mutations in chronic myelomonocytic leukemia. J Clin Oncol. 2013;31(19):2428–36.CrossRef
8.
Zurück zum Zitat Elena C, Gallì A, Such E, et al. Integrating clinical features and genetic lesions in the risk assessment of patients with chronic myelomonocytic leukemia. Blood. 2016;128(10):1408–17.CrossRef Elena C, Gallì A, Such E, et al. Integrating clinical features and genetic lesions in the risk assessment of patients with chronic myelomonocytic leukemia. Blood. 2016;128(10):1408–17.CrossRef
9.
Zurück zum Zitat Machherndl-Spandl S, Jäger E, Barna A, et al. Impact of age on the cumulative risk of transformation in patients with chronic myelomonocytic leukaemia. Eur J Haematol. 2021;107(2):265–74.CrossRef Machherndl-Spandl S, Jäger E, Barna A, et al. Impact of age on the cumulative risk of transformation in patients with chronic myelomonocytic leukaemia. Eur J Haematol. 2021;107(2):265–74.CrossRef
10.
Zurück zum Zitat Fenaux P, Beuscart R, Lai JL, et al. Prognostic factors in adult chronic myelomonocytic leukemia: an analysis of 107 cases. J Clin Oncol. 1988;6(9):1417–24.CrossRef Fenaux P, Beuscart R, Lai JL, et al. Prognostic factors in adult chronic myelomonocytic leukemia: an analysis of 107 cases. J Clin Oncol. 1988;6(9):1417–24.CrossRef
11.
Zurück zum Zitat Germing U, Strupp C, Aivado M, et al. New prognostic parameters for chronic myelomonocytic leukemia. Blood. 2002;100(2):731–2. author reply 732–733.CrossRef Germing U, Strupp C, Aivado M, et al. New prognostic parameters for chronic myelomonocytic leukemia. Blood. 2002;100(2):731–2. author reply 732–733.CrossRef
12.
Zurück zum Zitat Storniolo AM, Moloney WC, Rosenthal DS, et al. Chronic myelomonocytic leukemia. Leukemia. 1990;4(11):766–70. Storniolo AM, Moloney WC, Rosenthal DS, et al. Chronic myelomonocytic leukemia. Leukemia. 1990;4(11):766–70.
13.
Zurück zum Zitat Schuler E, Schroeder M, Neukirchen J, et al. Refined medullary blast and white blood cell count based classification of chronic myelomonocytic leukemias. Leuk Res. 2014;38(12):1413–9.CrossRef Schuler E, Schroeder M, Neukirchen J, et al. Refined medullary blast and white blood cell count based classification of chronic myelomonocytic leukemias. Leuk Res. 2014;38(12):1413–9.CrossRef
14.
Zurück zum Zitat Tefferi A, Hoagland HC, Therneau TM, et al. Chronic myelomonocytic leukemia: natural history and prognostic determinants. Mayo Clin Proc. 1989;64(10):1246–54.CrossRef Tefferi A, Hoagland HC, Therneau TM, et al. Chronic myelomonocytic leukemia: natural history and prognostic determinants. Mayo Clin Proc. 1989;64(10):1246–54.CrossRef
15.
Zurück zum Zitat Worsley A, Oscier DG, Stevens J, et al. Prognostic features of chronic myelomonocytic leukaemia: a modified Bournemouth score gives the best prediction of survival. Br J Haematol. 1988;68(1):17–21.CrossRef Worsley A, Oscier DG, Stevens J, et al. Prognostic features of chronic myelomonocytic leukaemia: a modified Bournemouth score gives the best prediction of survival. Br J Haematol. 1988;68(1):17–21.CrossRef
16.
Zurück zum Zitat Such E, Cervera J, Costa D, et al. Cytogenetic risk stratification in chronic myelomonocytic leukemia. Haematologica. 2011;96(3):375–83.CrossRef Such E, Cervera J, Costa D, et al. Cytogenetic risk stratification in chronic myelomonocytic leukemia. Haematologica. 2011;96(3):375–83.CrossRef
17.
Zurück zum Zitat Such E, Germing U, Malcovati L, et al. Development and validation of a prognostic scoring system for patients with chronic myelomonocytic leukemia. Blood. 2013;121(15):3005–15.CrossRef Such E, Germing U, Malcovati L, et al. Development and validation of a prognostic scoring system for patients with chronic myelomonocytic leukemia. Blood. 2013;121(15):3005–15.CrossRef
18.
Zurück zum Zitat Wassie EA, Itzykson R, Lasho TL, et al. Molecular and prognostic correlates of cytogenetic abnormalities in chronic myelomonocytic leukemia: a Mayo Clinic-French Consortium Study. Am J Hematol. 2014;89(12):1111–5.CrossRef Wassie EA, Itzykson R, Lasho TL, et al. Molecular and prognostic correlates of cytogenetic abnormalities in chronic myelomonocytic leukemia: a Mayo Clinic-French Consortium Study. Am J Hematol. 2014;89(12):1111–5.CrossRef
19.
Zurück zum Zitat Itzykson R, Fenaux P, Bowen D, et al. Diagnosis and treatment of chronic myelomonocytic leukemias in adults: recommendations from the European Hematology Association and the European leukemianet. Hemasphere. 2018;2(6):e150.CrossRef Itzykson R, Fenaux P, Bowen D, et al. Diagnosis and treatment of chronic myelomonocytic leukemias in adults: recommendations from the European Hematology Association and the European leukemianet. Hemasphere. 2018;2(6):e150.CrossRef
20.
Zurück zum Zitat Patnaik MM, Itzykson R, Lasho TL, et al. ASXL1 and SETBP1 mutations and their prognostic contribution in chronic myelomonocytic leukemia: a two-center study of 466 patients. Leukemia. 2014;28(11):2206–12.CrossRef Patnaik MM, Itzykson R, Lasho TL, et al. ASXL1 and SETBP1 mutations and their prognostic contribution in chronic myelomonocytic leukemia: a two-center study of 466 patients. Leukemia. 2014;28(11):2206–12.CrossRef
21.
Zurück zum Zitat Padron E, Garcia-Manero G, Patnaik MM, et al. An international data set for CMML validates prognostic scoring systems and demonstrates a need for novel prognostication strategies. Blood Cancer J. 2015;5(7):e333.CrossRef Padron E, Garcia-Manero G, Patnaik MM, et al. An international data set for CMML validates prognostic scoring systems and demonstrates a need for novel prognostication strategies. Blood Cancer J. 2015;5(7):e333.CrossRef
22.
Zurück zum Zitat Geissler K, Jäger E, Barna A, et al. The Austrian biodatabase for chronic myelomonocytic leukemia (ABCMML): a representative and useful real-life data source for further biomedical research. Wien Klin Wochenschr. 2019;131(17–18):410–8.CrossRef Geissler K, Jäger E, Barna A, et al. The Austrian biodatabase for chronic myelomonocytic leukemia (ABCMML): a representative and useful real-life data source for further biomedical research. Wien Klin Wochenschr. 2019;131(17–18):410–8.CrossRef
23.
Zurück zum Zitat Itzykson R, Solary E. An evolutionary perspective on chronic myelomonocytic leukemia. Leukemia. 2013;27(7):1441–50.CrossRef Itzykson R, Solary E. An evolutionary perspective on chronic myelomonocytic leukemia. Leukemia. 2013;27(7):1441–50.CrossRef
24.
Zurück zum Zitat Foucar K, Hsi ED, Wang SA, et al. Concordance among hematopathologists in classifying blasts plus promonocytes: a bone marrow pathology group study. Int J Lab Hem. 2020;42(4):418–22.CrossRef Foucar K, Hsi ED, Wang SA, et al. Concordance among hematopathologists in classifying blasts plus promonocytes: a bone marrow pathology group study. Int J Lab Hem. 2020;42(4):418–22.CrossRef
25.
Zurück zum Zitat Vavricka SR, Burri E, Beglinger C, et al. Serum protein electrophoresis: an underused but very useful test. Digestion. 2009;79(4):203–10.CrossRef Vavricka SR, Burri E, Beglinger C, et al. Serum protein electrophoresis: an underused but very useful test. Digestion. 2009;79(4):203–10.CrossRef
26.
Zurück zum Zitat Fenaux P, Jouet JP, Zandecki M, et al. Chronic and subacute myelomonocytic leukaemia in the adult: a report of 60 cases with special reference to prognostic factors. Br J Haematol. 1987;65(1):101–6.CrossRef Fenaux P, Jouet JP, Zandecki M, et al. Chronic and subacute myelomonocytic leukaemia in the adult: a report of 60 cases with special reference to prognostic factors. Br J Haematol. 1987;65(1):101–6.CrossRef
27.
Zurück zum Zitat Hamarsheh S, Osswald L, Saller BS, et al. Oncogenic KrasG12D causes myeloproliferation via NLRP3 inflammasome activation. Nat Commun. 2020;11(1):1659.CrossRef Hamarsheh S, Osswald L, Saller BS, et al. Oncogenic KrasG12D causes myeloproliferation via NLRP3 inflammasome activation. Nat Commun. 2020;11(1):1659.CrossRef
28.
Zurück zum Zitat Brandt SJ, Bodine DM, Dunbar CE, et al. Dysregulated interleukin 6 expression produces a syndrome resembling Castleman’s disease in mice. J Clin Invest. 1990;86(2):592–9.CrossRef Brandt SJ, Bodine DM, Dunbar CE, et al. Dysregulated interleukin 6 expression produces a syndrome resembling Castleman’s disease in mice. J Clin Invest. 1990;86(2):592–9.CrossRef
29.
Zurück zum Zitat Zhao EJ, Cheng CV, Mattman A, et al. Polyclonal hypergammaglobulinaemia: assessment, clinical interpretation, and management. Lancet Haematol. 2021;8(5):e365–75.CrossRef Zhao EJ, Cheng CV, Mattman A, et al. Polyclonal hypergammaglobulinaemia: assessment, clinical interpretation, and management. Lancet Haematol. 2021;8(5):e365–75.CrossRef
30.
Zurück zum Zitat Everson MP, Brown CB, Lilly MB. Interleukin‑6 and granulocyte-macrophage colony-stimulating factor are candidate growth factors for chronic myelomonocytic leukemia cells. Blood. 1989;74(5):1472–6.CrossRef Everson MP, Brown CB, Lilly MB. Interleukin‑6 and granulocyte-macrophage colony-stimulating factor are candidate growth factors for chronic myelomonocytic leukemia cells. Blood. 1989;74(5):1472–6.CrossRef
Metadaten
Titel
Significance of hypergammaglobulinemia in patients with chronic myelomonocytic leukemia
verfasst von
Marie-Therese Zack
Univ. Prof. Dr. Klaus Geissler
Publikationsdatum
29.11.2022
Verlag
Springer Vienna
Erschienen in
Wiener Medizinische Wochenschrift / Ausgabe 1-2/2023
Print ISSN: 0043-5341
Elektronische ISSN: 1563-258X
DOI
https://doi.org/10.1007/s10354-022-00983-6

Weitere Artikel der Ausgabe 1-2/2023

Wiener Medizinische Wochenschrift 1-2/2023 Zur Ausgabe