The Efficacy of Current Prognostic Models in Predicting Outcome of Patients with Myelodysplastic Syndromes (MDS) at the Time of Hypomethylating Agent Failure

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3275-3275
Author(s):  
Aziz Nazha ◽  
Rami S Komrokji ◽  
Guillermo Garcia-Manero ◽  
John Barnard ◽  
Cassie Zimmerman ◽  
...  
Keyword(s):  
Overall Survival ◽  
Scoring System ◽  
Scoring Systems ◽  
Prognostic Models ◽  
Cancer Center ◽  
Md Anderson ◽  
Prognostic Scoring Systems ◽  
Very High ◽  
Time Of Failure

Abstract Background: Several validated prognostic models exist for patients (pts) with MDS, including the International Prognostic Scoring System (IPSS), the Revised IPSS (IPSS-R), and the MD Anderson Prognostic Scoring System (MDAPSS). All were developed in pts with newly diagnosed MDS, and their prognostic value in subsequent stages of disease, such as at the time of failure of hypomethylating agents (HMAs, azacitidine (AZA) and decitabine (DAC), has not been established. Despite this, the IPSS is often used to determine clinical trial eligibility for pts who fail HMAs and is being considered for drug labeling for this indication. Methods Clinical data were combined from the MDS Clinical Research Consortium institutions (Moffitt Cancer Center n=259, Cleveland Clinic n=221, MD Anderson Cancer Center n=192, Cornell University n=100, Dana-Farber Cancer Institute n=45, and Johns Hopkins n=29). The IPSS, IPSS-R, and MDAPSS were calculated at the time of diagnosis and HMA failure. HMA failure was defined as no response to AZA or DAC following ≥ 4 cycles, loss of response, or progression to acute myeloid leukemia (AML). Responses were defined per International Working Group criteria (IWG 2006). Overall survival was calculated from the time of HMA failure to time of death or last follow up (OSHF). Survival curves were compared using stratified log-rank tests. Akaike information criterion (AIC) was used to compare fits from Cox proportional hazards models. Results A total of 488 pts who failed HMAs and had clinical data available at the time of failure were included in the final analyses. Overall, 406 (83%) were treated with AZA and 82 (17%) with DAC. At diagnosis: median age was 70 years (26-91), median absolute neutrophil count 1.06 k/mL (0.06-36.41), hemoglobin 9.3 g/dL (3.4-38.6), platelets 75 X 103/mL (2-969), and bone marrow blasts 7% (0-28). Prognostic scoring systems at diagnosis included, IPSS: 6 (2%) low, 46 (14%) intermediate-1, 206 (60%) intermediate-2, 83 (24%) high; IPSS-R: 3 (1%) very low, 12 (4%) low, 49 (16%) intermediate, 114 (37%) high, 129 (42%) very high; and MDAPSS: 11 (4%) low, 36 (13%) intermediate-1, 89 (31%) intermediate-2, 149 (52%) high. With median follow up from diagnosis of 18.2 months (mo) (0.7-224.6), median time from diagnosis to HMA start was 1.3 mo (0-162.4). Median number of HMA cycles received was (6, range 4-51): AZA (6, range 4-51), and DAC (4, range 4-21). Median OS from time of diagnosis was 19.5 mo (95% CI, 18.3-22.0). At the time of HMA failure, the median OSHF was 7.1 mo (95% CI, 6.2-7.9). Median OSHF by IPSS (n=311, low 10.9, intermediate-1 11.0, intermediate-2 7.1, high 5.1, p=.005), IPSS-R (n=285, very low 22.4, low 10.3, intermediate 5.6, high 9.4, very high 5.7, p<.0001) and MDAPSS (n=215, low 11.0, intermediate-1 11.3, intermediate-2 9.7, high 5.2, p=.01), Figure 1. Prognostic scoring system comparisons using the subset with all three scores gave AIC values of 1401 (IPSS), 1391 (IPSS-R) and 1393 (MDAPSS), with lower scores indicating a better fit. Conclusion When applying three of the most widely used prognostic scoring systems in MDS to pts at the time of HMA failure, the IPSS-R performed the best, followed by the MDAPSS and the IPSS. No system was ideal, though, and should be used with caution for clinical trial eligibility or drug labeling in MDS pts failing HMAs. Figure 1A. Overall survival by scoring systems: (A) IPSS, (B) IPSS-R, (C) MDAPSS Figure 1A. Overall survival by scoring systems: (A) IPSS, (B) IPSS-R, (C) MDAPSS Figure 1B Figure 1B. Figure 1C Figure 1C. Disclosures Roboz: Novartis: Consultancy; Agios: Consultancy; Celgene: Consultancy; Glaxo SmithKline: Consultancy; Astra Zeneca: Consultancy; Sunesis: Consultancy; Teva Oncology: Consultancy; Astex: Consultancy.

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

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3278-3278
Author(s):  
Priyanka Priyanka ◽  
Janhavi Raut ◽  
Patricia S Fox ◽  
Francesco Stingo ◽  
Tariq Muzzafar
Keyword(s):  
Overall Survival ◽  
Scoring System ◽  
Risk Groups ◽  
Risk Classification ◽  
Chronic Myelomonocytic Leukemia ◽  
Cancer Center ◽  
Newly Diagnosed ◽  
Md Anderson ◽  
Myelomonocytic Leukemia

Abstract INTRODUCTION: Chronic 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. AIM: The aim of the study is to validate the alternative CPSS scoring system on the CMML patient cohort at UT MD Anderson Cancer Center (UTMDACC). METHODS: The 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. RESULTS: Two 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. CONCLUSIONS: These data reinforce the validity of the alternative CPSS and serve as an additional validation cohort. Table 1. Alternative CMML-specific prognostic scoring system (CPSS) score criteria Variable Each level assigned the following value(sum to get the composite CPSS score): 0 1 2 WHO subtype CMML-1 blasts (including promonocytes) <5% in the PB and <10% in the BM CMML-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 subtype CMML-MD (WBC <13 × 109/L) CMML-MP (WBC ≥13 × 109/L) — CMML-specific cytogenetic risk classification* Low Intermediate High Hemoglobin ≥10 g/dL <10/dL WBC: white 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 abnormalities Table 2. Alternative CPSS: scores used for predicting likelihood of survival and leukemic evolution in individual patient with CMML Risk group Overall CPSS score Low 0 Intermediate-1 1 Intermediate-2 2-3 High 4-5 Figure 1 Overall Survival by alternative CPSS Score Figure 1. Overall Survival by alternative CPSS Score Figure 2 Time to AML Progression by alternative CPSS Score Figure 2. Time to AML Progression by alternative CPSS Score Disclosures No relevant conflicts of interest to declare.

A Novel Model to Predict Outcome of Patients with Myelodysplastic Syndromes (MDS) at the Time of Hypomethylating Agent Failure

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2888-2888
Author(s):  
Aziz Nazha ◽  
Rami S. Komrokji ◽  
Guillermo Garcia-Manero ◽  
John Barnard ◽  
Katrina Zell ◽  
...  
Keyword(s):  
Overall Survival ◽  
Board Of Directors ◽  
Scoring System ◽  
Research Funding ◽  
Prognostic Model ◽  
Scoring Systems ◽  
Prognostic Models ◽  
Advisory Committees ◽  
New Model

Abstract Background: Several validated prognostic models exist for patients (pts) with myelodysplastic syndromes (MDS), including the International Prognostic Scoring System (IPSS), the Revised IPSS (IPSS-R), the World Health Organization (WHO) classification-based Prognostic Scoring System (WPSS), and the MD Anderson Prognostic Scoring System (MDAPSS). All were developed in pts with newly diagnosed MDS, and their prognostic value in subsequent stages of disease, such as at the time of hypomethylating agents failure (HMAs, azacitidine (AZA) and decitabine (DAC), has not been established. Despite this, the IPSS and IPSS-R is often used to determine clinical trial eligibility for pts who fail HMA and has been used by the FDA for drug labeling in this setting. Here in we developed a new prognostic model that predicts outcome post HMAs failure (HMAF). Methods Included patients were diagnosed with higher-risk MDS (per 2008 WHO criteria, higher-risk defined as IPSS Intermediate-2/High) with clinical and pathologic data entered into the MDS Clinical Research Consortium database. The IPSS, IPSS-R, WPSS and MDAPSS were calculated at the time of diagnosis and HMAF. HMAF was defined as no response to AZA or DAC following >4 cycles, loss of response, or progression to acute myeloid leukemia (AML) at any time after starting therapy. Responses were defined per International Working Group criteria (IWG 2006). Overall survival (OS) was calculated from the time of diagnosis to time of death or last follow up when the models were applied at diagnosis and from HMAF date to time of death or last follows up when the models were applied at the time of HMAF. Cox proportional hazard analysis within the multivariable model-building with fractional polynomials (MFP) approach, which automatically select from all factors at the time of HMAF, was used to build the new model. Akaike information criterion (AIC) was used to compare fits from Cox proportional hazards models. Results Of 450 higher-risk MDS pts who failed HMAs, 311 (69.1%) were treated with AZA and 139 (30.9%) with DAC. The median age at diagnosis was 70 years (range: 35-91). Best responses (BR) to HMA were: 96 (21.3%) with complete remission, 40 (8.9%) partial remission, 46 (10.2%) hematologic improvement, 180 (40.0%) stable disease, and 88 (19.6%) with progressive disease. The median number of cycles received during treatment was 6 (range, 2-51). With a median follow up of 17.4 months (IQ range, 16.1, 18.7), the median OS from diagnosis for the entire group was 18.5 months (IQ range, 17.2, 19.8). Median OS from diagnosis was similar for patients treated with AZA compared to DAC (18.0 months vs. 20.3 months, p = .36). The median OS after HMAF was 7.3 months (IQ range, 6.3, 8.4). Survival plots for each prognostic scoring system at diagnosis and HMAF are shown in Figure 1. Comparing the predictive power of these scoring systems at the time of HMAF, the AICc for each model was: MDASS (3541.1); IPSS-R (3562.0), IPSS (3570.0), and WPSS with AICc of (3572.2) (lower AICc indicates better fit of the model). Given the lower predictive power of the current prognostic models at the time of HMAF, we developed a new prognostic model specific for this patient population. Our MFP modeling approach selected 6 factors that have significant association with OS at the time of HMAF in the final Cox multivariate model (Table 1). The new model identified two risk groups: Low: score < 2.25, median OS 11.0 months (95% CI 8.8-13.6) and a high risk group with score of > 2.25 and median OS 4.5 months (95% CI 3.9-5.3). Using the internal model validation assessment, the estimated AICc for the new model was 3520.4 (lowest AICc). When the new model was applied at time of diagnosis, the AICc decreased to 3515.1, a much smaller decrease compared to the existing prognostic systems built at diagnosis: MDASS (3515.7), IPSS-R (3528.2), WPSS (3537.5) and IPSS (3537.7). Conclusion Currently available MDS prognostic scoring systems should be used cautiously in pts at the time of HMAF and, given their inconsistent reliability, should be avoided for clinical trial eligibility or drug labeling. A new prognostic model was developed specific for this patient population. Table 1. The Post-HMA model Table 1. The Post-HMA model Figure 1. Overall survival by scoring systems at diagnosis and at the time of HMA failure Figure 1. Overall survival by scoring systems at diagnosis and at the time of HMA failure Disclosures Komrokji: Celgene: Consultancy, Research Funding; Incite: Consultancy; Novartis: Speakers Bureau; GSK: Research Funding. Steensma:Celgene: Consultancy; Amgen: Consultancy; Incyte: Consultancy; Onconova: Consultancy. Padron:Novartis: Speakers Bureau; Incyte: Research Funding. List:Celgene Corporation: Honoraria, Research Funding. Sekeres:TetraLogic: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees.

A Comparison of Prognostic Models for Chronic Myelomonocytic Leukemia (CMML) in the Era of Hypomethylating Agents

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 1695-1695 ◽  
Author(s):  
Eric Padron ◽  
Najla H Al Ali ◽  
Deniz Peker ◽  
Jeffrey E Lancet ◽  
Pearlie K Epling-Burnette ◽  
...  
Keyword(s):  
Overall Survival ◽  
Scoring System ◽  
Prognostic Model ◽  
Median Overall Survival ◽  
Prognostic Score ◽  
Risk Groups ◽  
Prognostic Models ◽  
Rank Test ◽  
Log Rank Test ◽  
Md Anderson

Abstract Abstract 1695 Introduction: CMML is a genetically and clinically heterogeneous malignancy characterized by peripheral monocytosis, cytopenias, and a propensity for AML transformation. Several prognostic models attempt to stratify patients into subcategories that are predictive for overall survival (OS), six models of which are specific to CMML. However, these models have either never been externally validated in the context of CMML or were externally validated prior to the use of hypomethylating agents. We externally validate and perform a detailed statistical comparison between the International Prognostic Scoring System (IPSS), MD Anderson Scoring System (MDASC), MD Anderson Prognostic Score (MDAPS), Dusseldorf Score (DS), and Spanish Scoring Systems (SS) in a large, single institution cohort. Methods: Data were collected retrospectively from the Moffitt Cancer Center (MCC) CMML database and charts were reviewed of patients that satisfied the WHO criteria for the diagnosis of CMML. The primary objective of the study was to validate the above prognostic models calculated at the time of initial presentation to MCC. All prognostic models were calculated as previously published. All analyses were conducted using SPSS version 15.0 (SPSS Inc, Chicago, IL). The Kaplan–Meier (KM) method was used to estimate median overall survival and the log rank test was used to compare KM survival estimates between two groups. Results: Between January 2000 and February 2012, 123 patients were captured by the MCC CMML database. The median age at diagnosis was 69 (30–90) years and the majority of patients were male (69%). By the WHO classification, the majority of patients had CMML-1 (84% vs. 16%) and most patients were subcategorized as MPN-CMML (59%) versus MDS-CMML (39%) by the FAB CMML criteria. The median overall survival of the entire cohort was 30 months and the rate of AML transformation was 44% (54). Twenty-two patients (18%) were treated with decitabine and 66 (54%) patients were treated with 5-azacitidine. Risk group stratification according to specific prognostic model is summarized in Table 1. The IPSS, MDASC, DS, and SS all predicted OS (p<0.05) while the MDASP could not be validated (p=0.924). When only patients who were treated with 5-azacitadine were considered, the MDASC, DS, and SS continued to predict OS (p<0.05) while the IPSS (p=0.15) and MDASP (p=0.239) did not. Previous reports have demonstrated that the MDASC provides further discrimination to refine stratification by the IPSS in Myelodysplastic Syndromes (MDS). Except for the low-risk DS patients, we grouped patients in our CMML cohort into lower and higher risk disease with each prognostic score and attempted to further stratify patients by the MDASC using KM and the log rank test. The MDASC was able to further risk stratify patients in each group for all prognostic models except those in the higher risk groups by the SS (p=0.07) and DS (P=0.45). When a similar statistical analysis was applied to each prognostic scoring system, only the MDASC was consistently able to further stratify the majority of risk groups as described in Table 2. The Dusseldorf scoring system was able to further stratify all lower risk groups regardless of model but was not able to do so in higher risk disease. Conclusions: This represents the first external validation of existing CMML prognostic models in the era of hypomethylating agent therapy. Except for the MDASP, we were able to validate the prognostic value all models tested. The MDASC represents the most robust model as it consistently refined the stratification of other models tested and remained predictive of OS in 5-azacitidine treated patients. Multi-institution collaboration is needed to construct a robust CMML specific prognostic model. Comparison to the IPSS-R is in progress. Disclosures: No relevant conflicts of interest to declare.

Validation Of The Revised International Prognostic Scoring System (IPSS-R) In 1000 Newly Diagnosed MDS Patients With Low- and Intermediate-1 Risk MDS In The European Leukemianet MDS (EUMDS) Registry

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2770-2770 ◽  
Author(s):  
Louise de Swart ◽  
Alex Smith ◽  
Tom Johnston ◽  
Detlef Haase ◽  
Jackie Droste ◽  
...  
Keyword(s):  
High Risk ◽  
Mortality Rate ◽  
Risk Score ◽  
Scoring System ◽  
Scoring Systems ◽  
International Prognostic Scoring System ◽  
Newly Diagnosed ◽  
High Age ◽  
Very High

Abstract Background The EUMDS registry was initiated to provide an overview of the real-world demographics, diagnostics and disease-management of MDS. The first patient was registered in December 2007 and today 16 countries and 131 centers are participating. In 1997 the International Prognostic Scoring System (IPSS) was developed to predict clinical outcomes for patients with MDS and is still the most widely used prognostic scoring system. Recently, the IPSS has been revised (IPSS-R). Objective To validate the prognostic discrimination of the IPSS and IPSS-R in the first 1000 newly diagnosed lower risk MDS patients. Results The median age of the population at diagnosis was 75 years (range 19-95). WHO 2001 classification was RCMD (35%), RARS (18%), RA (18%), RAEB-1 (12%), RCMD-RS (7%), 5q- syndrome (6%), MDS-U (3%) and RAEB-2 (0.4%). Within the first two years of follow-up 57% of the patients received MDS specific treatment: 48% received erythropoiesis stimulating agents (ESA), 11% granulocyte colony-stimulating factor (G-CSF), 51% received at least one red blood cell transfusion and 8% iron chelation therapy. IPSS risk score was Low in 49%, Intermediate-1 in 45% (0.5=32%, 1=13%) and unknown in 6% (no cytogenetic analysis) of the patients. IPSS-R risk score was Very Low in 25%, Low in 44%, Intermediate in 16%, High/Very high in 4% of the patients, and 10% unknown (Figure 1; Table 1). 77% of IPSS karyotypes were Good, 15% Intermediate, 1% Poor and unknown in 6%. 7% of the IPSS-R cytogenetic groups were Very good, 72% Good, 11% Intermediate, 1% were each Poor or Very poor and 8% unknown. Overall survival (OS) and disease progression (DP) (high risk MDS/Leukaemia) were both evaluated. Median follow-up time was 2.1 years (range 0 - 4.9 years). The mortality rate in patients with IPSS Low was 23% and 38% among those with an Intermediate IPSS (HR 2.09, 95%CI: 1.64-2.66; Figure 2A). The mortality rate in patients according to the IPSS-R was Very Low (21%; HR 0.77, 95%CI: 0.55-1.07), Low (26%; HR 1), Intermediate (51%; HR 2.53, 95%CI: 1.90-3.38) and High/Very high (65%; HR 4.47, 95%CI: 2.94-6.78) (Figure 2B). The prognostic discrimination of the scoring systems was assessed using the Akaike Information Criterion (AIC) from univariate proportional hazards models; the lower the AIC value the more informative the prognostic scoring system. The AIC of the IPSS and IPSS-R models were 3198.77 and 3154.48, respectively for OS and 1323.16 and 1274.19, respectively for DP (Table 1). A similar assessment of the components of the IPSS and IPSS-R scores revealed comparable fits to both OS and DP, regardless of which component was considered (Table 2). Conclusion IPSS and IPSS-R both predict OS and DP very well. IPSS-R was slightly superior in evaluating the clinical outcome, but it identified a subgroup (4.5% of all patients) of High and Very High-risk patients with a very poor prognosis, and another subgroup of good prognosis patients (IPSS-R Very Low) within the IPSS INT-1 cohort (13.6% of IPSS INT-1). Both scoring systems appear to be more strongly associated with predicting the risk of developing DP than OS. This observation may be due to the average high age at diagnosis of MDS reflecting the effect of competing causes of death associated with high age. Disclosures: Guerci-Bresler: Novartis: Honoraria; BMS: Honoraria; Celgene: Honoraria; Amgen: Honoraria.

Prognosis and Outcomes in MDS-MPN Unclassifiable: Single Institution Experience of a Rare Disorder

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1698-1698 ◽  
Author(s):  
Ateefa Chaudhury ◽  
Rami S. Komrokji ◽  
Najla H. Al Ali ◽  
Ling Zhang ◽  
Pardis Vafaii ◽  
...  
Keyword(s):  
Overall Survival ◽  
Risk Stratification ◽  
Scoring System ◽  
Lower Risk ◽  
Research Funding ◽  
Median Overall Survival ◽  
Scoring Systems ◽  
Rare Disorder ◽  
International Prognostic Scoring System ◽  
Cancer Center

Abstract Introduction: The 2008 World Health Organization (WHO) classification has recognized a unique overlap category that has features of proliferation found in myeloproliferative neoplasms (MPN) and also dysplasia found in myelodysplastic syndrome (MDS). The least well characterized of the 4 MDS/MPN overlap diseases is a rare entity known as MDS/MPN Unclassifiable (MDS/MPN-U), comprising <5% of myeloid disorders. Furthermore, given the rarity of this disorder, there is no validated risk stratification scoring system, although there are several commonly used prognostic models for MDS, including the International Prognostic Scoring System (IPSS), the Revised International Prognostic Scoring System (IPSS-R), and the M.D. Anderson Cancer Center model (MDAS). The objectives of this study were to evaluate the natural history of this very uncommon diagnosis and to determine which of the current scoring symptoms used for MDS best discriminates outcomes. Methods: The Moffitt Cancer Center database of over 3000 MDS patients was used to identify patients with MDS/MPN-U and to subsequently perform a comprehensive chart/pathology review. We then applied IPSS, IPSS-R, and the MDAS scores to each patient in order to compare differences in overall survival (OS) amongst different risk groups within each scoring system. Finally, we compared outcomes in the MDS/MPN-U group with a large number of matched MDS cases from within our database, using the MDAS. Descriptive statistical analyses were utilized. Chi square analysis and t- test were performed to compare categorical and continuous variables. Akaike information criteria (AIC) were used to assess the relative goodness of fit of the models. All data was analyzed using SPSS version 21.0 statistical software. Results: Forty three patients were identified with MDS/MPN-U and were pathologically confirmed to meet WHO criteria. Median age was 71 years (range 55 - 91) and the M:F = 26.17. Median baseline laboratory parameters: WBC 11.2 x 103/dL (range 0.9 - 84.8); Hb 9.7 g/dL (range 5.8-14.4); platelets 137 x 103/uL. Table 1 summarizes risk stratification per current validated MDS scoring systems. The majority of patients had lower risk disease by all the models. Forty of 42 (95%) patients evaluable for prognostic scoring were classified as low/Int-1 by IPSS. However, 11 out of the 40 pts (28%) classified as lower risk by IPSS were upgraded to Int-2 or high risk by MDAS. Twenty-two patients received hypomethylating agents (HMA) as first line treatment after supportive care. Per IWG 2006, 8 of 22, (36%) had complete response, partial remission, or hematologic improvement, 7 (32%) had stable disease, and 6 (27%) had progressive disease. The median OS for all MDS/MPN-U patients was 33 months (95% Confidence Interval 22 - 45). Within each MDS scoring system, statistically significant survival differences were detected between risk stages (table 1). The IPSS-R did not improve the IPSS prognostic value. Patients categorized as lower-risk (low/Int-1) by MDAS had superior survival compared to IPSS. Lastly, we compared outcomes between the 43 MDS/MPN-U patients and 1117 IPSS low/Int-1 matched controls within the MDS database. Median overall survival was inferior in MDS/MPN-U vs. MDS (33.4 mo vs. 57 mo, p = 0.005). In addition, using the MDAS, stage-by-stage, survival was significantly worse in the MDS/MPN-U group. Table 1. Risk Stratification Based on MDS Scoring Systems MDS/MPN-Un (%) Median Overall Survival (mo) P-value IPSS Low Int-1 Int-2 High 15 (35.7)25 (59.5)1 (2.4)1 (2.4) 33.433.312.86.0 < 0.001 IPSS-R Very Low Low Intermediate High Very High 6 (14.3)21 (50)10 (23.8)4 (9.5)1 (2.4) 18.2333.425.112.86.0 0.001 MDAS Low Int-1 Int-2 High 6 (14.3)20 (47.6)13 (31.0)3 (7.1) 52.433.425.16.0 < 0.001 Conclusions: MDS/MPN-U appears to have a variable disease course but with generally poor outcomes, even amongst lower-risk patients classified by MDS scoring systems, and despite a moderate rate of response to treatment. Matched comparisons indicate inferior outcomes compared with similarly staged MDS patients. The MDAS may offer increased discriminatory capacity for determining prognosis based on disease stage. Further work with a larger patient population and cross comparisons to other MDS/MPN diseases will assist further understanding of this rare disorder. Integration of somatic mutations data may compliment the clinical models. Disclosures Komrokji: Novartis: Research Funding, Speakers Bureau; Celgene: Consultancy, Research Funding; Pharmacylics: Speakers Bureau; Incyte: Consultancy. Lancet:Kalo-Bios: Consultancy; Celgene: Consultancy, Research Funding; Pfizer: Research Funding; Amgen: Consultancy; Seattle Genetics: Consultancy; Boehringer-Ingelheim: Consultancy.

scholarly journals Allogeneic Transplantation for Chronic Myelomonocytic Leukemia (CMML) Is Associated with High Disease-Free Survival Even in the Setting of High-Risk Disease

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2575-2575 ◽  
Author(s):  
Matias Eugenio Sanchez ◽  
Kamal Kant Singh Abbi ◽  
Roni Tamari ◽  
Ann Jakubowsky ◽  
Esperanza B Papadopoulos ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Disease Free Survival ◽  
Scoring Systems ◽  
Prognostic Models ◽  
Free Survival ◽  
High Risk Disease ◽  
Unrelated Donors ◽  
Prognostic Scoring Systems ◽  
Disease Free

Abstract Background: CMML has a poor prognosis with a median overall survival of about 30 months and a 15-20% risk of transformation to acute myeloid leukemia. For high-risk patients the median survival is 9 months. The only curative therapy is allogeneic hematopoietic stem cell transplantation (allo-HSCT). While several prognostic models have been proposed in CMML, their predictive value in allograft recipients is not well established. We report the outcome of allo-HSCT in 28 patients (pts) with CMML, and the relationship between five CMML prognostic scoring systems and post-transplant disease-free survival (DFS). Methods: 28 pts with CMML underwent allo-HSCT at MSKCC between 1/2002 and 2/2014. Pt and transplant characteristics are summarized in Table 1. Of the 28 pts, 6 had progressed to CMML-2 and 7 to AML pre-transplant. Except for 3 pts, all received chemotherapy before cytoreduction to decrease disease burden and all patients had <20% blasts prior to conditioning. Five prognostic scoring systems were used to classify the patients into low and high risk: 2 MDS and 3 CMML-specific models. T-cell depleted pts (n = 16, 60%) received myeloablative conditioning (12 busulphan/ melphalan/ fludarabine/ rabbit ATG and 4 TBI-based) whereas 12 pts (40%) received unmodified grafts with varying conditioning intensity. The source of HSC was 23 PB, 2 BM, and 3 cord blood. Results All pts had sustained donor engraftment. The cumulative incidences of day 100 grade II-IV acute graft-versus-host disease (GVHD) and 1-year chronic GVHD were 18% (95%CI:3-32) and 17% (95%CI:1-33), respectively. The 1-year incidence of transplant-related mortality was 7% (95%CI:0-17) with the most common transplant-related cause of death being infection. Three pts relapsed for a 1-year incidence of 13% (95%CI:0-26). These patients died of their disease. With a median follow-up of survivors of 3.3 years (range 3 months-11.6 years), the 3-year Kaplan-Meier estimate of overall survival is 74% (95%CI: 51-88) and DFS is 71% (95%CI: 47-85). All pts classified as having high-risk disease had similar survival to low risk disease pts (Table 2). Conclusion: This preliminary data suggests that allo-HSCT can achieve a high DFS in pts with CMML, even in the setting of high-risk disease. Thus, allo-HSCT should potentially be considered in all patients with CMML including pts who have a dismal prognosis based on current prognostic scoring systems. Table 1. Patient and transplant characteristics Characteristics N=28 Age , years (range) 60 (12-69) Gender Male Female - 18 (64%) 10 (36%) BM Blasts at diagnosis (%) <5 5-9 10-19 - 13 (46%) 7 (25%) 8 (29%) Diagnosis karyotype risk group per Spanish Score Good Intermediate/Poor - 17 (60%) 11 (40%) WHO classification at diagnosis CMML-1 ( <10 % BM blasts) CMML-2 (10-20% BM blasts) - 20 (71%) 8 (29%) FAB classification at diagnosis Myelodysplastic subtype (< 13000 WBC) Myeloproliferative subtype (> 13000 WBC) - 14 (50%) 14 (50%) WHO status at progression (highest disease) CMML -1 CMML -2 AML - 12 (43%) 9 (32%) 7 (25%) Pre-transplant therapy No chemotherapy Hypomethylating agent AML type chemotherapy - 5 (18%) 10 (36%) 13 (46%) BM Blasts pre-transplant (%) <5 5-9 10-19 - 21 (75%) 4 (14%) 3 (11%) Transplant conditioning Myeloablative Reduced intensity - 22 (78%) 6 (22%) Donor 8/8 HLA Matched related donor 8/8 HLA Matched unrelated donors HLA-mismatched unrelated donors Cord blood - 13 (46%) 9 (32%) 3 (11%) 3 (11%) GVHD prophylaxis T cell depletion Calcineurin inhibitor - 16 (60%) 12 (40%) Table 2: DFS per risk level defined by different prognostic models *CMML- specific scoring systems Prognostic Score N 3 year DFS IPSS-R 0-1 2-3 - 11 17 - 83% 63% MDASC 0-1 2-3 - 21 7 - 71% 69% MDAPS * 0-1 2-3 - 16 12 - 68% 74% Mayo * 0-1 2 - 10 18 - 56% 76% Spanish Score * 0-1 2-3 - 20 8 - 68% 75% Disclosures Boulad: Genzyme Sanofi: Trials partially funded by Genzyme Sanofi Other.

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

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2810-2810 ◽  
Author(s):  
Xavier Calvo ◽  
Meritxell Nomdedeu ◽  
Dolors Costa ◽  
Arturo Pereira ◽  
Núria Martínez ◽  
...  
Keyword(s):  
Bone Marrow ◽  
High Risk ◽  
Scoring System ◽  
Prognostic Score ◽  
Scoring Systems ◽  
Prognostic Impact ◽  
Risk Patients ◽  
Md Anderson ◽  
Prognostic Scoring Systems ◽  
Bone Marrow Blasts

Abstract Introduction Despite 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. Aim 1) 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 Methods One 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. Results All 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 &lt;0.001, p &lt;0.001, p &lt;0.001, p =0.001) and LFS (p &lt;0.001, p =0.005, p &lt; 0.001, p =0.004). For the variables composing the MDAPS (Hb &lt;120g/L, total lymphocyte count &gt; 2500/mm3, presence of circulating immature cells and bone marrow blasts ≥ 10%) only the Hb &lt;120g/L and the bone marrow blasts ≥ 10% impacted on OS (p =0.001, p &lt;0.001, respectively) and only the bone marrow blasts ≥ 10% had an impact on the LFS (p &lt;0.001). When the score systems were applied to our series, both had an impact on OS and LFS (OS CPSS p &lt;0.001; LFS CPSS p &lt;0.001; OS MDAPS p &lt;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). Conclusions In 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. Disclosures: No relevant conflicts of interest to declare.

Sign in / Sign up

Export Citation Format

Share Document