CMML-specific Prognostic Scoring System Research Articles

Long-Term Experience with Hypomethylating Agents in Patients with Chronic Myelomonocytic Leukemia

▪INTRODUCTION: Despite the limited number of patients with chronic myelomonocytic leukemia (CMML) included in the clinical trials that resulted in the approval of hypomethylating agents (HMA) in patients with myelodysplastic syndromes (MDS), HMA (azacitidine and decitabine) remain the most commonly used therapeutic intervention for patients with CMML. We present our experience with HMA in the treatment of CMML.METHODS: We retrospectively reviewed 153 patients diagnosed with CMML following the 2006 WHO classification and treated with frontline HMA between 2004 and 2015 at a single institution. Clinical and demographic data were obtained from our electronic database. Response was assessed by modified 2006 International Working Group (IWG) criteria. Statistical analyses were performed with the IBM SPSS Statistics 23.0 software. Overall survival (OS) and leukemia free survival were defined as the time between treatment onset and death or leukemia (or last contact), respectively. Data were summarized using median, range, and percentage. Censored endpoints were estimated by the nonparametric Kaplan-Meier method and compared using the log-rank test. All tests were 2-sided with significance set at p<0.05.RESULTS: Baseline characteristics are shown in Table 1. 45 (30%) patients were female. Median age at diagnosis was 69 years (range 50-88). According to the CMML-specific prognostic scoring system (CPSS), 17 patients (11%) belonged to the low risk group, 45 (29%) to the intermediate-1 risk group, 45 (29%) to the intermediate-2 risk group, and 11 (7%) to the high risk group. Following the FAB criteria, 66 of the patients (43%) had CMML-MD and 87 (57%) had CMML-MP. By WHO classification, 99 patients (65%) were CMML-1 and 54 patients (35%) were CMML-2. Karyotype was available in 150 patients (abnormal in 50 [33%]), and according to the Spanish Haematological Cytogenetics Working Group, 106 (69%) belonged to the good-risk category, 24 (16%) to the intermediate-risk category, and 19 (12%) to the poor-risk category. 35 (23%) patients received azacitidine in monotherapy (AZA), 74 (48%) decitabine in monotherapy (DAC), and 44 (29%) were treated with combinations.The overall response rate (ORR) was 71% (108/153), with 56% (86/153) of the patients achieving complete response (CR). The median duration of response was 10 months (range 1-86 months). No differences were observed in ORR or CR between CMML-MD and CMML-MP (73% vs 69%, p=0.613, for ORR and 61% vs 53%, p=0.340, for CR), CMML-1 and CMML-2 (68% vs 76%, p=0.285; 56% vs 57%, p=0.825) or CPSS score (p=0.133). Median OS was 23 months (Fig.1A), and the cumulative probability of AML transformation was 30% at 5 years. There were statistically significant OS differences between responders and non-responders: 35 vs. 18 months, respectively (p<0.01) (Fig.1B); CMML-MD and CMML-MP: 37 months vs. 25 (p=0.008) (Fig.1C); and good, intermediate, and poor risk cytogenetics: 34, 19, and 17 months, respectively (p=0.001) (Fig.1D). No differences were observed in terms of OS between CMML-1 and CMML-2: 30 and 29 months (p=0.974).Considering only the patients treated with AZA or DAC in monotherapy, CR was significantly higher in those patients treated with DAC (74.3%) when compared with patients treated with AZA (37.1%) (p < 0.001). Despite the fact that DAC shows a trend toward be better than AZA in terms of ORR (79.7% and 62.9%, respectively; p=0.06), leukemia free survival (LFS) (median 22 and 12 months, p=0.367) and OS (median 34 and 24 months, p=0.231), no statistical differences were observed. The only difference observed between groups was hemoglobin level (11.4 g/dl vs 10.4 g/dl, p=0.027). No other significant differences in terms of white blood cells, platelets, neutrophils, number of bone marrow blast, CMML-1 vs CMML-2, CMML-MD vs CMML-MP, CPSS and cytogenetic risk groups were observed between patients treated with AZA vs DAC.CONCLUSION: Here, we present the largest series of CMML treated with HMA. As previously published, HMA are clinically effective in the treatment of patients with CMML, providing ORR of 71% with 56% of CR. Better OS was observed in responders compared with non-responders, in CMML-MD compared with CMML-MP, and in those with low risk cytogenetics. In our cohort, CR was significantly higher in those patients treated with DAC when compared with patients treated with AZA. These results need to be confirmed in larger numbers of patients. [Display omitted] [Display omitted] DisclosuresJabbour:ARIAD: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Research Funding; BMS: Consultancy. Cortes:ARIAD: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Teva: Research Funding. DiNardo:Celgene: Research Funding; Novartis: Research Funding; Agios: Research Funding; Abbvie: Research Funding; Daiichi Sankyo: Research Funding. Konopleva:Cellectis: Research Funding; Calithera: Research Funding.

Time-to-Treatment in Chronic Myelomonocytic Leukemia - a Novel Prediction Model

IntroductionFor chronic myelomonocytic leukemia (CMML) several scores exist which prognosticate overall survival (OS) based on different clinical and genetic parameters. The time-to-treatment (TTT) among CMML patients is highly variable, and a predictive model to specifically estimate TTT in CMML has not been described so far. The aims of this single-center retrospective study were (a) to test and validate established myelodysplastic syndrome (MDS)-specific and CMML-specific prognostic scores in our patient cohort, (b) to evaluate which baseline factors were relevant to the time point of treatment initiation with either hydroxyurea or azacitidine, and (c) to propose a prediction model for TTT in CMML.MethodsThis retrospective analysis was based on the data of 55 unselected, consecutive CMML patients diagnosed and/or treated at our tertiary center between 2004 and 2015. We applied the following published prognostic models to our CMML cohort, using both OS and TTT as endpoints: the MD Anderson Prognostic Score (MDAPS), the modified MDAPS (MDAPS M1), the CMML-specific Prognostic Scoring System (CPSS), the Mayo Prognostic Model, the Düsseldorf Score, the International Prognostic Scoring System (IPSS), and the Revised International Prognostic Scoring System (IPSS-R).ResultsAccording to the CMML-specific MDAPS, 27% of our patients were classified as "higher-risk" (23% intermediate-2, 4% high-risk) (Figure 1). At the time of data analysis, 38% and 24% of patients had received azacitidine and hydroxyurea as first-line treatment. A total of 40 (73%) patients had died at the time point of data analysis. The median time of follow-up was 24.8 months (range 1.7-74.8 months).All applied MDS-specific (Düsseldorf Score, IPSS, IPSS-R) and CMML-specific (MDAPS, MDAPS M1, CPSS, Mayo Prognostic Model) prediction scores were able to significantly discriminate patient cohorts with different OS probabilities. The following variables were associated with a shorter TTT in the univariate analysis: the presence of immature myeloid cells in the peripheral blood, white blood cell count ≥14.5 G/L, platelet count <55 G/L, absolute neutrophil count ≥6 G/L, absolute lymphocyte count ≥2.3 G/L, absolute monocyte count ≥2.8 G/L, serum lactate dehydrogenase ≥223 G/L, peripheral blood blasts >0%, bone marrow blast percentage ≥7.5%, red blood cell transfusion-dependence, palpable spleen and/or symptomatic splenomegaly, and the presence of B-symptoms at the time of initial diagnosis. In multivariate analysis, the following factors remained independently associated with TTT: lactate dehydrogenase (HR 5.428; p = 0.008), bone marrow blast count (HR 4.570; p = 0.001), and platelet count (HR 2.660; p = 0.027).These three clinical parameters were included in the TTT prediction model and CMML patients were stratified into three subgroups: low-risk, intermediate-risk and high-risk. Median TTT was not reached for low-risk patients, 16.5 months for intermediate-risk patients, and almost immediate treatment initiation (0.6 months) was observed in the high-risk group (Figure 2).ConclusionsWe validated seven existing MDS-specific and CMML-specific prognostic scores in 55 CMML patients treated at the center in Salzburg. We were able to demonstrate that lactate dehydrogenase, bone marrow blast percentage and platelet count at initial diagnosis were the most relevant parameters for predicting time to treatment initiation in our CMML cohort. Based on these three parameters, we propose the first TTT prediction score for treatment-naïve CMML patients. Clinical implications of this score include the identification of CMML patients for early investigational trials, as well as the tailoring of individual follow-up intervals. [Display omitted] [Display omitted] DisclosuresHuemer:Roche: Other: Travel funding; Merck: Other: Travel funding. Egle:Gilead: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Other: travel support; Celgene: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Other: travel support. Greil:Pfizer: Honoraria, Research Funding; Boehringer-Ingelheim: Honoraria; Eisai: Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Mundipharma: Honoraria, Research Funding; Merck: Honoraria; Janssen-Cilag: Honoraria; Genentech: Honoraria, Research Funding; Novartis: Honoraria; AstraZeneca: Honoraria; Roche: Honoraria, Research Funding; Sanofi Aventis: Honoraria; GSK: Research Funding; Ratiopharm: Research Funding; Cephalon: Consultancy, Honoraria, Research Funding; Bristol-Myers-Squibb: Consultancy, Honoraria. Pleyer:Celgene: Consultancy, Honoraria; Bristol-Myers-Squibb: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; AOP Orphan Pharmaceuticals: Honoraria.

Integrating clinical features and genetic lesions in the risk assessment of patients with chronic myelomonocytic leukemia

AbstractChronic myelomonocytic leukemia (CMML) is a myelodysplastic/myeloproliferative neoplasm with variable clinical course. To predict the clinical outcome, we previously developed a CMML-specific prognostic scoring system (CPSS) based on clinical parameters and cytogenetics. In this work, we tested the hypothesis that accounting for gene mutations would further improve risk stratification of CMML patients. We therefore sequenced 38 genes to explore the role of somatic mutations in disease phenotype and clinical outcome. Overall, 199 of 214 (93%) CMML patients carried at least 1 somatic mutation. Stepwise linear regression models showed that these mutations accounted for 15% to 24% of variability of clinical phenotype. Based on multivariable Cox regression analyses, cytogenetic abnormalities and mutations in RUNX1, NRAS, SETBP1, and ASXL1 were independently associated with overall survival (OS). Using these parameters, we defined a genetic score that identified 4 categories with significantly different OS and cumulative incidence of leukemic evolution. In multivariable analyses, genetic score, red blood cell transfusion dependency, white blood cell count, and marrow blasts retained independent prognostic value. These parameters were included into a clinical/molecular CPSS (CPSS-Mol) model that identified 4 risk groups with markedly different median OS (from >144 to 18 months, hazard ratio [HR] = 2.69) and cumulative incidence of leukemic evolution (from 0% to 48% at 4 years, HR = 3.84) (P < .001). The CPSS-Mol fully retained its ability to risk stratify in an independent validation cohort of 260 CMML patients. In conclusion, integrating conventional parameters and gene mutations significantly improves risk stratification of CMML patients, providing a robust basis for clinical decision-making and a reliable tool for clinical trials.

Comparison of three prognostic scoring systems in a series of 146 cases of chronic myelomonocytic leukemia (CMML): MD Anderson prognostic score (MDAPS), CMML-specific prognostic scoring system (CPSS) and Mayo prognostic model. A detailed review of prognostic factors in CMML

Although specific prognostic models for chronic myelomonocytic leukemia (CMML) exist, few are based on large series of patients. MD Anderson prognostic score (MDAPS) has been the most useful for CMML risk assessment. Due to recent emergence of CMML-specific prognostic scoring system (CPSS) and Mayo prognostic model, we compared the three scores.One hundred forty-six CMML patients diagnosed between 1998 and 2014 were retrospectively analyzed. Univariate analysis was performed to assess prognostic impact on overall survival (OS) and leukemia-free survival (LFS) of the variables composing the scores and all items showed prognostic value on OS with the exception of the presence of circulating immature myeloid cells. Regarding LFS, only CPSS variables, bone marrow blast ≥10% and an absolute monocyte count >10×109/L had an impact. When the scores were applied, all showed an impact on OS and retained their significance in multivariate analysis. By using ROC curves and C-index, CPSS showed a slightly better predictive value for mortality and leukemia transformation. Variables composing the three indexes were compared in multivariate analysis and only CPSS parameters and platelets<100×109/L retained their significance. Based on these findings, by adding platelet count to CPSS, a new score was implemented (CPSS-P) showing the best risk prediction capability in our series. This study reinforces the validity of the tested scores.

Allogeneic Hematopoietic Cell Transplantation for Adult Chronic Myelomonocytic Leukemia

Allogeneic hematopoietic cell transplantation (HCT) is the only potentially curative treatment for patients with chronic myelomonocytic leukemia (CMML), however there little data regarding prognostic factors and transplant outcomes. Recently a CMML-specific prognostic scoring system (CPSS) was validated in the non-transplant setting [1Such E. Germing U. Malcovati L. et al.Development and validation of a prognostic scoring system for patients with chronic myelomonocytic leukemia.Blood. 2013 Apr 11; 121: 3005-3015Crossref PubMed Scopus (227) Google Scholar]. We sought to validate this scoring system in the HCT setting. We identified 209 adult patients undergoing HCT for CMML reported to the Center for International Blood and Marrow Transplant Research (CIBMTR) from 2001 through 2012. The median age at transplant was 57 years (range 23-74), with a majority being male (70%). Most had Karnofsky Performance Score of 90-100% (61%). Eighty eight (42%) patients had low/intermediate-1, while 79 (38%) had intermediate-2/high, and 42 (20%) had missing CPSS scores. Based on CPSS definition, 50% had favorable, 19% had intermediate, 17% had poor risk, and cytogenetic data were missing for 14%. Median time from diagnosis to transplant was 8 months (range 2-170). HCT were performed with HLA identical siblings (35%), matched unrelated donors (45%), partially matched unrelated donors (15%), or mismatched/indeterminate matched unrelated donors (4%). Patients received bone marrow (16%) or peripheral blood (84%). Patients received myeloablative (51%), reduced-intensity (41%), non-myeloablative (< 5%) or other (<4%) conditioning regimens. GVHD prophylaxis was cyclosporine-based (37%), FK-506-based (61%), methotrexate alone (<1%) or missing (<1%). Median follow up was 51 months (range of 3-122). On multivariate analyses, CPSS scores, KPS, and graft source were significant predictors of overall survival (p=0.004, p=0.01, p=0.01 respectively; CPSS and OS figure below). Higher CPSS scores were not associated with disease free survival (DFS), relapse, or transplant related mortality (TRM) (p=0.2, p=0.1, p=0.08, respectively). To investigate why higher CPSS scores were associated with higher mortality, we performed analysis restricted to patients with relapse following HCT. Those with intermediate-2/high risk had nearly two-fold increase in risk of death after relapse compared to those with low/intermediate-1 CPSS scores. Corresponding rates for low/intermediate-1 risk groups, OS at 1 year, 3 years, and 5 years were 61%, 48%, and 44% respectively and for intermediate-2/high risk groups were 38%, 32%, and 19% respectively. OS of patients who received pre-HCT treatment with hypomethylating agents, chemotherapy, or both was not different compared to those who received no therapy prior (p=0.96). In summary, CPSS scores, lower KPS scores, and bone marrow as graft source were associated with poorer outcomes following HCT.

Comparison of Three Prognostic Scoring Systems in a Series of 146 Cases of Chronic Myelomonocytic Leukemia (CMML): MD Anderson Prognostic Score (MDAPS), CMML-Specific Prognostic Scoring System (CPSS) and Mayo Prognostic Model

INTRODUCTION: Although specific prognostic models for Chronic Myelomonocytic Leukemia (CMML) exist, few are based on large series of patients. Since its publication in 2002, the MD Anderson prognostic score (MDAPS) has been the most powerful prognostic tool for CMML. Due to the recent emergence of the CMML-specific prognostic scoring system (CPSS) and the Mayo prognostic model, we compared the three scores to assess their usefulness in our series. These three indexes, and not those based on clinical and molecular variables (Mayo Molecular Model and GFM prognostic score), were selected as the most easy-to-apply in normal clinical practice.AIM: 1) To assess the prognostic impact on overall survival (OS) and leukemia-free survival (LFS) of the variables composing the scores: MDAPS, CPSS and Mayo prognostic model; 2) To test the capability of the scores to detect the high-risk CMML patients; 3) To detect the index with the best predictive value for mortality and leukemia transformation, and 4) To implement a new score after selecting the best variables of the three indexes in terms of OS prognostic information.PATIENTS AND METHODS: From January 1997 to August 2013 a retrospective analysis including 146 patients diagnosed with CMML was performed in Hospital Clínic of Barcelona (n=134) and Hospital Germans Trias i Pujol (n=12). The median age was 76 years (range 27-96 years) and 63% were males. One-hundred and twenty-nine (88%) had a CMML-1, 17 (12%) a CMML-2, 102 (70%) a CMML-MD and 44 (30%) a CMML-MP. The median follow-up for surviving patients was 24.5 months and the median OS was 20 months (range 0-159 months). The prognostic impact in terms of OS and LFS of each of the variables that compose the indexes were studied by a univariate survival analysis (Kaplan-Meier; Log-Rank). A multivariate analysis (Cox model) was performed to assess the independent impact of the variables that showed significance in the univariate analysis in order to select the ones with the best prognostic information. The global prognostic scores were analyzed by univariate and multivariate analyses. In addition, ROC curves and the concordance index (C-index) were implemented to select the score with the best predictive power for mortality or leukemia transformation.RESULTS: All the variables that compose the MDAPS (hemoglobin level < 12 g/dl, absolute lymphocyte count > 2.5 x 109/L, presence of circulating immature myeloid cells (IMCs) and BM blasts ≥ 10%), the CPSS (CMML-MD vs. CMML-MP, CMML-1 vs. CMML-2, RBC transfusion dependency and the Spanish cytogenetic risk classification) and the Mayo prognostic model (absolute monocyte count > 10x109/L, presence of IMCs, hemoglobin < 10 g/dl and platelet count < 100 x 109/L) showed prognostic value on OS with the exception of circulating IMCs. Regarding LFS, only CPSS variables, BM blast ≥ 10% and an absolute monocyte count > 10x109/L had an impact. When the scores were applied, all showed an impact on OS and retained their significance in multivariate analysis. By using ROC curves and C-index, CPSS (ROC area: 0.80, CI 95%: 0.72-0.88; C-index: 0.73) showed a slightly better predictive value for mortality. Variables composing the three indexes were compared in a multivariate analysis and only CPSS parameters and platelets < 100 x 109/L retained their significance. Based on these findings, by adding platelet count information to CPSS, a new score was implemented (CPSS-P) showing the best risk stratification in our series (Figure 1).CONCLUSIONS: The present study reinforces the validity of CPSS, the MDAPS and the Mayo prognostic model for the assessment of CMML patients. Moreover, by including the platelet count information to the CPSS improved the prediction capacity for OS and LFS in our series. It is of importance to remark that platelet count information could help to better stratify CMML patients, being of special value in the subset of patients with normal karyotype. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Somatic Mutations of ASXL1, RUNX1 and SETBP1 Improve Prognostic Stratification of Patients with Chronic Myelomonocytic Leukemia

Chronic myelomonocytic leukemia (CMML) is a myelodysplastic/myeloproliferative neoplasm characterized by a highly variable clinical course. Based on clinical, hematologic and cytogenetic parameters, we previously developed a CMML-specific Prognostic Scoring System (CPSS) that stratifies patients into 4 different risk groups [Blood 2013;121:3005-15]. Recently, recurrent somatic mutations have been identified in CMML, and preliminary evidence suggests that selected mutated genes may provide useful prognostic information.In this study, we performed a comprehensive mutation analysis of genes implicated in myeloid malignancies in a large and well characterized cohort of CMML patients with the aim to dissect relationships between genotype and disease phenotype and to integrate somatic mutations into a clinical/molecular prognostic model.Thirty-eight genes were analyzed by high throughput sequencing (Illumina MiSeq, San Diego, CA) in a cohort of 199 CMML patients (pts) diagnosed according to WHO classification, and in 12 pts with monocytosis not fulfilling WHO diagnostic criteria. Myelodysplastic and myeloproliferative subtypes (CMML-MD and CMML-MP, respectively) were defined according to FAB criteria. Least absolute shrinkage and selection operator (Lasso) and Cox proportional hazards methods were adopted to select and weight variables for prognostic scoring.Ninety-three percent of pts showed at least one somatic mutation (median number per patient: 2, range 0-6). The most frequently mutated genes were TET2 (44%), SRSF2 (43%), ASXL1 (34%), KRAS (11%), NRAS (10%), CUX1 (10%), CBL (9%), RUNX1 (7%), SETBP1 (7%), JAK2 (6%), SF3B1 (6%), and U2AF1 (5%). A significant association was found between mutations in TET2 and RNA splicing factors (P=.037), 42 of 199 CMML pts (21%) showing co-occurrence of TET2 and SRSF2 mutations. Mutations in genes involved in signaling were significantly associated with CMML-MP (P=.002), whereas SF3B1 mutations were associated with CMML-MD (P=.024).The number of mutations per patient inversely correlated with overall survival (OS) (HR=1.32, P=.021). In univariate analysis, mutations in ASXL1 (HR=2.31, P=.026) , RUNX1 (HR=3.53, P=.02) and SETBP1 (HR=3.85, P=.005) significantly affected OS. Focusing the analysis on disease subtype, ASXL1 mutations significantly affected survival in CMML-MD (HR=3.45, P=.025), whereas CUX1 and SETBP1 had a significant prognostic value in CMML-MP (HR=4.33, P=.013 and HR=4.4, P=.025, respectively).In order to investigate the additive value of somatic mutations to current prognostic assessment, we first fitted a Lasso Cox regression model for genetic variable selection. The selected variables were then included in an unpenalized Cox regression in order to obtain unbiased coefficients. The statistically significant variables were CPSS-specific cytogenetic risk groups (HR=2.49, P=.001), mutations in ASXL1 (HR=2.77, P=.018), RUNX1 (HR=5.39, P=.009) and SETBP1 (HR=3.96, P=.013). Based on regression coefficients, we defined a CMML-specific genetic risk score that was able to identify three different groups (Low risk: normal karyotype and –Y; Intermediate: other abnormalities, mutations in ASXL1; High: trisomy 8, complex karyotype, mutations in RUNX1 or SETBP1), with significantly different OS (HR=2.24, P<.001). The Akaike information criterion showed that this genetic risk score performed better than the original CPSS cytogenetic risk classification (AIC 274 vs. 282, respectively). According to the CMML-specific genetic risk score, 36% of patients had a shift toward a higher risk category compared with cytogenetic risk classification. Then, the new genetic risk categories were integrated in the CPSS (CPSS-Mol), which was able to identify 4 risk groups with different OS (HR=2.29, P<.001) and risk of disease progression (HR=2.62, P<.001). As a robustness analysis, we also fitted a Lasso Cox regression model including clinical and genetic variables, and all variables included in the clinical/molecular score were confirmed. The Akaike information criterion showed that the CPSS-Mol performed better than the original CPSS (AIC 251 vs. 253, respectively).In conclusion, this study showed that mutation pattern in CMML significantly correlates with disease phenotype. The integration of somatic mutations in current scoring systems significantly improves prognostic stratification of patients. DisclosuresNo relevant conflicts of interest to declare.

Validation of Alternative Chronic Myelomonocytic Leukemia (CMML)-Specific Prognostic Scoring (CPSS) System in UT MD Anderson Cancer Center Cohort

INTRODUCTIONChronic myelomonocytic leukemia (CMML) is a myeloid neoplasm that belongs to the category of myelodysplastic syndrome / myeloproliferative neoplasms (MDS / MPN). The International Prognostic Scoring System for Myelodysplastic Syndromes (IPSS) classification and its revised version (IPSS-R) addressed patients with newly diagnosed, untreated MDS and excluded CMML. While numerous investigators have attempted to devise a prognostic risk scoring system for CMML, no system has been generally accepted for this entity. A CMML-specific prognostic scoring (CPSS) system proposed by Such, et al [Blood. 2013; 11;121(15):3005-15] defines 4 different prognostic risk categories for estimating both overall survival (OS) and risk for AML transformation; the alternative version replaces RBC transfusion dependency with hemoglobin levels. AIMThe aim of the study is to validate the alternative CPSS scoring system on the CMML patient cohort at UT MD Anderson Cancer Center (UTMDACC). METHODSThe databases of the Department of Hematopathology at UTMDACC were searched for patients diagnosed with CMML presenting from 2005 to 2012. Cases were classified by WHO 2008 criteria. Inclusion criteria were: confirmed diagnosis of CMML, age > 18 years, persistent absolute monocyte count >1 × 109/L, marrow blasts < 20%, peripheral blood blasts < 20%. The alternative CPSS score was calculated as a function of WHO subtype, FAB subtype, CMML-specific cytogenetic risk classification, and hemoglobin score. Cox proportional hazards regression was used to model overall survival and time to AML progression from date of diagnosis. For time to AML progression, patients who did not experience AML progression were censored at their date of death or last follow-up. Kaplan-Meier curves were used to estimate survival and the log-rank test was used to test for significant differences by CPSS score. All statistical analyses were performed using SAS 9.3 for Windows. RESULTSTwo hundred and three patients with newly diagnosed, untreated CMML were identified in the clinical databases. These included 132 males and 71 females; median age was 70 (range 55-80) years. 149 had CMML-1 and 54 had CMML-2. A total of 107 deaths and 38 progressions were observed. The median (range) follow-up time for all patients was 1.9 (2 days-10.8) years. The variables that compose the alternative CPSS (WHO subtype, FAB subtype, CMML-specific cytogenetic risk classification, hemoglobin) as well as a description of how the score is calculated are given in Tables 1-2. In univariate Cox models, the alternative CPSS score was a significant predictor of both OS and time to AML progression (Type III p-values <.0001 and 0.0037, respectively). Median survival times for OS were 4.07, 3.32, 2.14, and 1.23 years in the low, intermediate-1, intermediate-2, and high risk groups, respectively. Since less than half the patients progressed, the median time to AML progression could not be estimated for all groups but was 6.40 and 1.60 in the intermediate-2 and high risk groups, respectively. Overall, the alternative CPSS score was highly predictive of both OS and progression free survival (PFS) and clearly delineated the patient risk groups in this sample. CONCLUSIONSThese data reinforce the validity of the alternative CPSS and serve as an additional validation cohort.Table 1Alternative CMML-specific prognostic scoring system (CPSS) score criteriaVariableEach level assigned the following value(sum to get the composite CPSS score):012WHO subtypeCMML-1 blasts (including promonocytes) <5% in the PB and <10% in the BMCMML-2 blasts (including promonocytes) from 5% to 19% in the PB and from 10% to 19% in the BM, or when Auer rods are present irrespective of blast count—FAB subtypeCMML-MD (WBC <13 × 109/L)CMML-MP (WBC ≥13 × 109/L)—CMML-specific cytogenetic risk classification*LowIntermediateHighHemoglobin≥10 g/dL<10/dL WBCwhite blood cell* CMML-specific cytogenetic risk classification; low: normal and isolated –Y; intermediate: other abnormalities; and high: trisomy 8, complex karyotype (≥3 abnormalities), chromosome 7 abnormalitiesTable 2Alternative CPSS: scores used for predicting likelihood of survival and leukemic evolution in individual patient with CMMLRisk groupOverall CPSS scoreLow0Intermediate-11Intermediate-22-3High4-5 [Display omitted] [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Evaluation Of Two Prognostic Scoring Systems For Chronic Myelomonocytic Leukemia (CMML): CMML-Specific Prognostic Scoring System (CPSS) and MD Anderson Prognostic Score (MDAPS) In A Series Of 122 Cases Of De Novo CMML

IntroductionDespite the existence of specific prognostic scoring systems, the International Prognostic Scoring System (IPSS) has been the most used for the evaluation of Chronic Myelomonocytic Leukemia (CMML) although it is not applicable for proliferative variants. Since its publication in 2002, the MD Anderson Prognostic Score (MDAPS) has been the most specific and powerful prognostic tool for CMML. Due to the recent emergence of CMML-specific Prognostic Scoring System (CPSS), we sought to determine its usefulness in our series and it was compared with the MDAPS to identify the index with the best capability to discriminate between high and low risk patients. Aim1) To assess the prognostic impact of each of the variables composing the prognostic scoring systems: MDAPS and CPSS and 2) to evaluate the discriminative ability of both scores to detect the highest risk patients. Patients and MethodsOne hundred and twenty-two patients (74M/48F; median age: 76 years, 27-96 years; median follow-up: 1.88 years, 0-11.4 years) diagnosed with CMML (108 CMML-I; 14 CMML-II; 92 dysplastic CMML; 30 proliferative CMML) between 1998 and 2013 from the Hospital Clínic de Barcelona (n=110) and the Hospital Universitari Germans Trias i Pujol (n=12). The prognostic impact in terms of overall survival (OS) and leukemia free survival (LFS) of each of the variables that compose the score systems and both scores were studied by an univariate survival analysis (Kaplan-Meier; Log-Rank). The two prognostic indices were faced in a multivariate analysis (Cox Regression) to assess the discriminative power of each one to detect the highest risk patients. Finally, Receiver Operating Characteristics (ROC) curves were plotted and the area under the ROC curve was calculated as an index for the predictive value of the model. ResultsAll the variables that compose the CPSS (CMML-I vs. II, transfusion requirement, dysplastic vs. proliferative variant and CPSS cytogenetics) had prognostic impact in terms of OS (p <0.001, p <0.001, p <0.001, p =0.001) and LFS (p <0.001, p =0.005, p < 0.001, p =0.004). For the variables composing the MDAPS (Hb <120g/L, total lymphocyte count > 2500/mm3, presence of circulating immature cells and bone marrow blasts ≥ 10%) only the Hb <120g/L and the bone marrow blasts ≥ 10% impacted on OS (p =0.001, p <0.001, respectively) and only the bone marrow blasts ≥ 10% had an impact on the LFS (p <0.001). When the score systems were applied to our series, both had an impact on OS and LFS (OS CPSS p <0.001; LFS CPSS p <0.001; OS MDAPS p <0.001; LFS MDAPS p =0.037). In a multivariate analysis including gender, age, high risk patients defined by the MDAPS (high risk MDAPS) and high risk patients defined by the CPSS (high risk CPSS), only age and high risk CPSS retained its statistical significance for OS (p = 0.023, p =0.001, respectively) and only high risk CPSS for LFS (p =0.001). The greatest area under the curve (AUC), showing the highest predictive value, was observed in the mortality ROC curve of the CPSS (0.77, CI 95%: 0.68-0.86) while the AUC for the MDAPS was smaller (0.58, CI: 0.47-0.69). ConclusionsIn our series, CPSS seems to be a better tool than MDAPS for the prediction of OS and LFS in CMML. These data reinforce the validity of the CPSS and could serve as an additional validation cohort.▪Cox Regression analysis for Overall Survial (OS)PHR95,0% CILowerUpperGender,3961,307,7052,423Age,0231,0361,0051,069MDAPS High Risk,080,437,1731,105CPSS High Risk,001,358,194,659 Disclosures:No relevant conflicts of interest to declare.

Development and validation of a prognostic scoring system for patients with chronic myelomonocytic leukemia

AbstractThe natural course of chronic myelomonocytic leukemia (CMML) is highly variable but a widely accepted prognostic scoring system for patients with CMML is not available. The main aim of this study was to develop a new CMML-specific prognostic scoring system (CPSS) in a large series of 558 patients with CMML (training cohort, Spanish Group of Myelodysplastic Syndromes) and to validate it in an independent series of 274 patients (validation cohort, Heinrich Heine University Hospital, Düsseldorf, Germany, and San Matteo Hospital, Pavia, Italy). The most relevant variables for overall survival (OS) and evolution to acute myeloblastic leukemia (AML) were FAB and WHO CMML subtypes, CMML-specific cytogenetic risk classification, and red blood cell (RBC) transfusion dependency. CPSS was able to segregate patients into 4 clearly different risk groups for OS (P < .001) and risk of AML evolution (P < .001) and its predictive capability was confirmed in the validation cohort. An alternative CPSS with hemoglobin instead of RBC transfusion dependency offered almost identical prognostic capability. This study confirms the prognostic impact of FAB and WHO subtypes, recognizes the importance of RBC transfusion dependency and cytogenetics, and offers a simple and powerful CPSS for accurately assessing prognosis and planning therapy in patients with CMML.