MD Anderson Prognostic Scoring Research Articles

Clinical Efficacy of Hypomethylating Agent Therapy in Patients with Chronic Myelomonocytic Leukemia

To observe the clinical efficacy and safety of hypomethylating agent therapy in chronic myelomonocytic leukemia (CMML). From February 2014 to June 2021, the clinical data, efficacy, survival time and safety of CMML patients diagnosed in the Second Hospital of Hebei Medical University and treated with hypomethylating agent therapy were retrospectively analyzed. A total of 25 CMML patients received hypomethylating agent therapy, including 18 cases treated with decitabine (DEC) and 7 cases treated with azacytidine (AZA) as the basic treatment. Among them, 20 patients responded, and 7 patients got complete remission (CR). All patients with CR were treated with DEC as the basic treatment. Five cases of CR occurred in the first 4 courses of treatment. After a median follow-up of 16.4 (9.4-20.5) months, 4 patients with CR progressed to acute myeloid leukemia (AML). The median overall survival (OS) time of 25 CMML patients was 17.4 months (95%CI: 12.437-22.363). According to MD Anderson prognostic scoring system (MDAPS), CMML-specific prognostic scoring system (CPSS), CPSS molecular (CPSS-mol), Mayo molecular model (MMM), risk stratification of patients was performed, and the difference only between different risk stratification of MDAPS and survival time was statistically significant. Common adverse reactions of hypomethylating agent therapy in CMML patients included infection, gastrointestinal reaction, hematological toxicity, skin allergy and liver function damage. All patients' symptoms were improved after corresponding treatment. Hypomethylating agent therapy is effective and safe for CMML patients. CR mostly occurs in the first 4 courses of treatment, and hypomethylating agent therapy combined with low-dose chemotherapy can be used for patients who do not respond. Hypomethylating agent therapy can delay the disease, but can't prevent progression.

An Assessment of the Three Popular Prognostic Scoring Systems for Chronic Myelomonocytic Leukemia (CMML) in an Indian Context

Abstract Introduction: Chronic myelomonocytic leukemia (CMML) is a rare clonal hematopoietic neoplasm with a prevalence of 1.05 to 1.94 cases per 1,00,000 population. There are multiple prognostic scoring system used in practice for CMML, which include both cytogenetic and next-generation sequencing based. Objective This study assesses the clinicohematological profile of CMML patients, along with comparison of three widely used prognostic scoring systems for CMML (CMML-specific prognostic scoring system, MD Anderson prognostic score, Mayo prognostic model). Materials and Methods: This study is an 8-year retrospective study. All relevant data had been retrieved and reviewed by the authors. Inclusion and exclusion criteria: All the cases that were diagnosed before 2016 as per 2008 criteria were reclassified, (2) all the cases that were positive for the mutations associated with myeloproliferative neoplasms were excluded, and (3) cases with more than or equal to 20% blast/blast equivalents were excluded. A univariate analysis was done followed by a multivariate analysis for all the parameters constituting each scoring system. Lastly, a receiver operating characteristic curve was plotted for all the three scoring systems. Result: There were total 23 patients, with a median age of 63 years and a male to female ratio of 2.3:1. Cytogenetic aberration and genetic mutation were observed in 6 and 3 cases, respectively. The median overall survival (OS) was 48 months and the median leukemia-free survival was 12 months. Post-multivariate analysis, the parameters with significant impact on OS were absolute monocyte count more than 10 × 10^9/L, myeloid precursors in peripheral blood, hemoglobin less than 10g/dL, platelet less than 100 × 10^9/L, hemoglobin less than 12g/dL, and absolute lymphocyte count more than 2.5 × 10^9/L. Conclusion: To summarize, we discovered CPSS to be a better prognostic tool for a setup like ours, since molecular investigations are not always readily available for each case. More such researches are needed in the near future so that we can design better prognostic tools and see for their usefulness in real life.

BMT for Myelodysplastic Syndrome: When and Where and How.

Myelodysplastic syndromes (MDS) are a diverse group of hematological malignancies distinguished by a combination of dysplasia in the bone marrow, cytopenias and the risk of leukemic transformation. The hallmark of MDS is bone marrow failure which occurs due to selective growth of somatically mutated clonal hematopoietic stem cells. Multiple prognostic models have been developed to help predict survival and leukemic transformation, including the international prognostic scoring system (IPSS), revised international prognostic scoring system (IPSS-R), WHO prognostic scoring system (WPSS) and MD Anderson prognostic scoring system (MDAPSS). This risk stratification informs management as low risk (LR)-MDS treatment focuses on improving quality of life and cytopenias, while the treatment of high risk (HR)-MDS focuses on delaying disease progression and improving survival. While therapies such as erythropoiesis stimulating agents (ESAs), erythroid maturation agents (EMAs), immunomodulatory imide drugs (IMIDs), and hypomethylating agents (HMAs) may provide benefit, allogeneic blood or marrow transplant (alloBMT) is the only treatment that can offer cure for MDS. However, this therapy is marred, historically, by high rates of toxicity and transplant related mortality (TRM). Because of this, alloBMT is considered in a minority of MDS patients. With modern techniques, alloBMT has become a suitable option even for patients of advanced age or with significant comorbidities, many of whom who would not have been considered for transplant in prior years. Hence, a formal transplant evaluation to weigh the complex balance of patient and disease related factors and determine the potential benefit of transplant should be considered early in the disease course for most MDS patients. Once alloBMT is recommended, timing is a crucial consideration since delaying transplant can lead to disease progression and development of other comorbidities that may preclude transplant. Despite the success of alloBMT, relapse remains a major barrier to success and novel approaches are necessary to mitigate this risk and improve long term cure rates. This review describes various factors that should be considered when choosing patients with MDS who should pursue transplant, approaches and timing of transplant, and future directions of the field.

Model Heterogeneity in Predicting Outcomes in Patients with Chronic Myelomonocytic Leukemia (CMML): An Overestimation of Survival in Lower-Risk Group

Model Heterogeneity in Predicting Outcomes in Patients with Chronic Myelomonocytic Leukemia (CMML): An Overestimation of Survival in Lower-Risk Group

Model Heterogeneity in Predicting Outcomes of Patients with Myelodysplastic Syndromes (MDS)

BackgroundThe outcome of MDS patients (pts) is heterogeneous, with some pts living for years, while others die within a few months of diagnosis. Several prognostic models have been developed to risk stratify pts with MDS including: the International Prognostic Scoring System (IPSS), Revised IPSS (IPSS-R), World Health Organization classification-based Prognostic Scoring System (WPSS), and MD Anderson Prognostic Scoring System (MDPSS). When applying these models to clinical practice, considerable heterogeneity in their prediction of outcomes is observed. Understanding such heterogeneity can impact disease expectations and treatment recommendations, as these can differ considerably based on the model used.MethodsClinical data from pts who were diagnosed with MDS according to 2008 WHO criteria and treated at our institution between 1/2000 and 1/2017 were analyzed. All prognostic models were calculated at the time of MDS diagnosis. Overall survival (OS) was calculated from the time of diagnosis to time of last follow up or death. Descriptive statistics were used to study the changes in risk categories across models.ResultsOf 687 pts included in the final analysis, the median age at diagnosis was 68 (11-99) years with a male (63%) predominance. Cytogenetic analysis per IPSS-R: very good 19 (3%), good 441(64%), intermediate (INT) 117 (17%), poor 47 (7%), and very poor 63 (9%). Risk categories by IPSS included: 204 (30%) with low risk, 319 (46%) intermediate-1 (INT-1), 124 (18%) intermediate-2 (INT-2), and 40 (6%) high risk. Risk categories by IPSS-R included: 114 pts (17%) with very low risk, 264 (38%) low, 128 (19%) intermediate, 118 (17%) high, and 63 (9%) very high.Significant heterogeneity was observed when comparing all models to IPSS-R risk categories. Among 378 pts with lower-risk disease (Very Low / Low) per IPSS-R, 3 pts (1%) were re-classified INT-2 per IPSS, 73 (19%) as INT and 28 (7%) as high/very high per WPSS, and 11 (29%) as higher-risk per MDAPSS, Table 1. Among 128 pts with intermediate risk by IPSS-R, 102 (20%) were reclassified as lower-risk per IPSS, 44 (34%) as lower-risk and 47 (37%) as higher-risk per WPSS, and 65 (50%) as lower-risk per MDAPSS, Table 1. Among 181 pts with high/very high-risk by IPSS-R, 44 (25%) were reclassified as lower-risk by IPSS, 54 (30%) per WPSS, and 58 (32%) per MDAPSS, Table1. Among 523 pts with lower-risk (low / INT-1) by IPSS, 102 (20%) were reclassified as INT risk and 46 (9%) as higher-risk per IPSS-R, 113 (22%) as INT and 62 (12%) as higher-risk per WPSS, and 186 (36%) as higher risk per MDAPSS, Table 2. Among 164 pts with higher-risk (INT-2/High) per IPSS, 26 (16%) were reclassified as INT per IPSS-R, 24 (15%) per WPSS, and 53 (32%) per MDAPSS, Table 2.The predicted OS per IPSS-R was overestimated when compared to the actual OS (evaluable in 429 pts) for pts in lower-risk categories. The difference between the median predicted IPSS-R OS and median actual OS was 70.6 months (m) for very low risk, 54 m for low, 9.5 m for INT, 6.7 m for high, and -2.4 m for very high risk (pts lived longer than their predicted OS). The IPSS, on the other hand, underestimated the OS, as the difference between the median predicted OS and median actual OS was -23.3 m for low risk, -16.5 m for INT1, -11.8 m for INT2, and -11.1 m for high risk.ConclusionsSignificant intra-patient (difference of outcome in the same pt based on the model used) and intra-group (difference in outcome among pts who have similar risk category by a given model) variability is observed when applying commonly used models in MDS. More importantly, IPSS-R overestimate OS for lower-risk disease and IPSS underestimate OS across all risk categories. This heterogeneity can impact survival expectations, treatment strategies, and clinical trial eligibility criteria based on the model used. A personalized prediction model that can precisely forecast the actual outcome of a pt is needed. [Display omitted] DisclosuresGerds:Incyte: Consultancy; CTI BioPharma: Consultancy. Advani:Pfizer: Consultancy; Takeda/ Millenium: Research Funding. Maciejewski:Alexion Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Speaker Fees; Apellis Pharmaceuticals: Consultancy; Ra Pharma: Consultancy. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees.

Hypomethylating Agent Therapy for Chronic Myelomonocytic Leukemia Does Not Impact Acute Myeloid Leukemia Transformation or Survival

Background: Chronic myelomonocytic leukemia (CMML) is a clonal hematopoietic stem cell disorder with features of both myeloproliferative neoplasm and myelodysplastic syndrome (MDS). CMML is characterized by persistent blood monocytosis >1 x 109/L, bone marrow dysplasia in one or more hematopoietic cell lines, and increased risk of transformation to acute myeloid leukemia (AML). Our review of SEER Medicare data (Haematologica 2013;98:584) demonstrated that, compared to MDS, CMML has shorter overall survival (OS) and more frequent progression to AML. Hypomethylating agents (HMAs) have become standard therapy for CMML, with reported response rates of 37-69%, but their impact on AML transformation and OS is unclear. Methods: We retrospectively reviewed CMML patients treated at the University of Maryland Greenebaum Comprehensive Cancer Center between January 2000 and December 2019. Clinical characteristics, treatments, AML progression, time to AML progression (TTP), and OS were recorded and analyzed. Descriptive statistics were used for baseline characteristics and Kaplan-Meier analysis was performed for time-to-event data. Statistical analyses were performed using GraphPad Prism 8®. Results: We identified 71 patients with CMML, 82% male and 73% white, with a median age of 69 (range 25 - 96) years; 51% had <10% bone marrow (BM) blasts and 45% had low-risk cytogenetic findings (normal karyotype or -Y). Most patients treated prior to 2005 received hydroxyurea and/or erythropoiesis-stimulating agents or were enrolled on clinical trials, while patients treated since 2005 received HMAs as primary therapy. Median follow-up was 41.1 months. The median OS of the entire cohort was 20 months, with 46% of patients progressing to AML with a median TTP of 11.5 months. By the MD Anderson Prognostic Scoring System at time of diagnosis, CMML was low-risk in 24 patients, intermediate-1 in 16, intermediate-2 in 14, and high-risk in 17. Forty-six patients received HMAs, with an overall response rate (ORR) of 54% (complete response or partial response), while 25 patients did not receive HMAs. Patient and disease characteristics were similar in HMA- and non-HMA-treated patients (Table 1). The estimated OS of HMA-treated patients was 20 months, compared to 14 months for non-HMA-treated patients (p =0.43) (Figure 1). AML transformation occurred in 52% of patients treated with HMAs, with TTP ranging from 3 to 65 months, and in 33% patients not treated with HMAs, with TTP ranging from 5 to 47 months. Most patients receiving HMAs (63%) received ≥ 6 cycles; 46% transformed to AML despite initial response, often in a sudden and unpredictable manner. HMAs were azacitidine in 13 patients, decitabine in 24, azacitidine followed by decitabine in 4, and decitabine followed by azacitidine in 5. Five CMML patients in our cohort underwent allogenic stem cell transplantation. Four of the five relapsed with transformation to AML post transplant, and only one patient remains in remission, 9 months post transplant. Conclusions: Despite a 54% ORR, HMA treatment did not have a significant impact on frequency of AML transformation, or OS in our cohort. Based on our data, favorable response rates previously reported with HMAs and also seen in our patients do not appear to translate into decreased frequency of AML transformation or prolonged OS. Though our study is a retrospective study with inherent selection bias, our results underscore the ongoing need for novel therapies and for clinical trials for CMML patients. Disclosures Niyongere: Kartos Therapeutics: Other: Received clinical trial research support with Kartos Therapeutics ; Forty Seven: Other: Received clinical trial research support with Forty Seven. Emadi:Amgen: Membership on an entity's Board of Directors or advisory committees; KinaRx: Other: co-founder and scientific advisor; NewLink Genetics: Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Research Funding. Doung:Pfizer: Membership on an entity's Board of Directors or advisory committees, Other: clinical trial research support; Incyte: Other: clinical trial research support; Astex: Other: clinical trial research support; MedPacto: Other: clinical trial research support. Baer:Takeda: Other: Institutional research funding; Oscotec: Other: Institutional research funding; Kite: Other: Institutional research funding; Incyte: Other: Institutional research funding; Forma: Other: Institutional research funding; Astellas: Other: Institutional research funding; AbbVie: Other: Institutional research funding.

Validation of the 2017 revision of the WHO chronic myelomonocytic leukemia categories

AbstractThe 2017 revision of the World Health Organization (WHO) classification includes substantial changes to the subclassification of chronic myelomonocytic leukemia (CMML): (1) a 3-tiered blast-based scheme including a novel “CMML-0” category replacing a 2-tiered system in place since 2001 and (2) 2 CMML subtypes, myelodysplastic (MDS-CMML) and myeloproliferative (MP-CMML), based on a white blood cell count cutoff of 13 × 109/L. The clinical utility of this subclassification scheme, particularly the expansion of blast-based subgroups, has not been validated. In this study, a large single-institution CMML patient cohort (n = 629) was used to assess the prognostic impact of the newly proposed categories. Patients were risk stratified according to the CMML-specific Prognostic Scoring System (CPSS) and the MD Anderson Prognostic Scoring System. MP-CMML patients had significantly shorter overall survival (OS; P < .0001; hazard ratio: 0.53, 95% confidence interval: 0.42-0.65) and median duration to acute myeloid leukemia (AML) transformation (P < .0001; 15.2 vs 22.0 months) compared with MDS-CMML patients. The CMML-0 group included 36.4% patients with higher risk CPSS categories and 11.2% of patients with high-risk cytogenetics. Among treatment-naïve patients (n = 499), there was a marginal difference in OS between the CMML-0 and CMML-12017 subgroups (P = .0552). The WHO 2017 blast-based categories were not associated with AML-free survival. Incorporation of the WHO 2017 blast-based subgroups in a modified CPSS scheme had a neutral effect and did not improve its prognostic strength. Our data support the inclusion of MP-CMML and MDS-CMML subtypes in the WHO 2017 revision. Although of some utility in MP-CMML, the 3-tiered blast-based system is not well supported in this study.

Abstract 3291: Development of a novel prognostic scoring system for patient selection in immune checkpoint inhibitor phase 1 clinical trials

Abstract Purpose: To develop a prognostic scoring system for selecting patients for immune checkpoint inhibitor (ICI) phase 1 clinical trials. Background: The Royal Marsden Hospital (RMH) and MD Anderson (MDA) prognostic scoring systems have been validated for patients in phase 1 clinical trials treated with cytotoxic chemotherapy and targeted therapy, but no such scoring system has been validated to help select patients entering ICI clinical trials. Methods: We analyzed clinical data from patients treated in phase 1 ICI clinical trials (with anti-CTLA4 and anti-PD1 antibody therapy) at the MD Anderson Center for Targeted Therapy. Sixteen clinical factors were studied. Recursive partitioning analysis identified cut-points for each clinical factor and a Cox proportional hazards regression model was used to identify factors independently affecting overall survival. Results: Among 172 patients treated with ICI therapy (105 CTLA4-based and 67 PD1-based) between January 2013 and November 2015, the median age was 60 years (range: 19-86 years) and 87 (51%) were male. The most common tumor types treated included renal cell carcinoma (n = 25; 15%), non-small cell lung cancer (n = 21; 12%), melanoma (n = 17; 10%), sarcoma (n = 14; 8%), gastrointestinal stromal tumors (n = 10; 6%), prostate cancer (n = 6; 3%), and colorectal cancer (n = 6; 3%). Seven factors were independently associated with significantly worse overall survival: age &amp;gt;52 years (hazard ratio [HR] 1.59, 95% confidence interval [CI] 1.1-2.4), Eastern Cooperative Oncology Group performance status &amp;gt;1 (HR 2.81, 95% CI 1.3-6.3), lactate dehydrogenase &amp;gt;466 U/L (HR 2.1, 95% CI 1.4-3.2), platelet count &amp;gt;300 × 109/L (HR 1.8, 95% CI 1.2-2.8), absolute neutrophil count &amp;gt;4.9 × 109/L (HR 2.3, 95% CI 1.5-3.5), absolute lymphocyte count &amp;lt;1.8 × 109/L (HR 3.3, 95% CI 1.9-5.7), and liver metastases (HR 1.8, 95% CI 1.2-2.6). An index was created whereby the cohort was divided into four risk groups based on the number of factors present: 0-2, 3, 4, or 5-6. Median overall survival was 24.2 months (0-2), 11.6 months (3), 8.0 months (4), and 3.8 months (5-6); log rank test, p &amp;lt; 0.0001. The Harrell c-index of this scoring system was 0.72, indicating significant predictability. Conclusion: We have developed a novel “MDA ICI” prognostic scoring system incorporating seven clinical parameters with prognostic significance for patients in phase 1 clinical trials treated with immune checkpoint inhibitors. Unlike in the RMH and MDA prognostic scoring systems, albumin level and number of metastatic sites did not independently correlate with overall survival. Prospective evaluation and external validation of our novel prognostic scoring system is warranted and may help better select patients for future clinical trials of checkpoint inhibitors. Citation Format: Shiraj Sen, Kenneth Hess, David Hong, Aung Naing, Sarina Piha-Paul, Filip Janku, Siqing Fu, Holly Liu, Yunfang Jiang, Rahil Khanji, Daniel Karp, Apostolia Tsimberidou, Nizar Tannir, Funda Meric-Bernstam, Vivek Subbiah. Development of a novel prognostic scoring system for patient selection in immune checkpoint inhibitor phase 1 clinical trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3291. doi:10.1158/1538-7445.AM2017-3291

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.

Incorporation of Molecular Data into the Current Prognostic Models in Treated Patients with Myelodysplastic Syndromes: Which Model Is the Best

▪BackgroundSeveral prognostic models have been developed to risk stratify patients (pts) with MDS including: the International Prognostic Scoring System (IPSS), Revised IPSS (IPSS-R), World Health Organization classification-based Prognostic Scoring System (WPSS), and MD Anderson Prognostic Scoring System (MDPSS). All except for the MDPSS were developed in treatment-naive pts and, if validated in treated pts, were done so primarily in those receiving one line of therapy. Incorporation of molecular data into the IPSS-R improves its predictive power, and adding molecular data to the IPSS can upstage or downstage some pts. In this study, we compared the prognostic utility of each prognostic model, after adding molecular data, in treated MDS pts.MethodClinical and mutational data from MDS pts diagnosed between 1/2000-1/2013 were analyzed. A panel of 60 gene mutations that were described as commonly mutated in myeloid malignancies was included. Patients who underwent hematopoietic cell transplant (HCT) were censored at the time of transplant. Univariable and multivariable analyses on the training cohort were performed by applying Cox proportional hazards regression analyses that included age, model score, and molecular mutations with an outcome of overall survival (OS). All molecular models were then applied to the validation cohort. The fit of the proposed models to the data was assessed by using Akaike's information criterion (AIC, lower values imply better fit) and concordance (c-) index.ResultsA total of 610 pts were included and divided into two cohorts, training (404 pts), and validation (206 pts). Median age of the training cohort was 67 years (range, 19-88); 83 pts (20%) had MDS/MPN including chronic myelomonocytic leukemia (CMML). Pts received a median of 2 lines of therapies (range, 0-7) and 15% of pts underwent HCT. First line therapies included: supportive care (22%), growth factors (22%), azacitidine +/- combinations (30%), decitabine +/- combinations (6%), lenalidomide (5%), induction chemotherapy (3%), immunosuppressive therapy (3%), and other therapies /clinical trials (9%). The median OS in the training and validation cohorts per scoring system (SS), i.e. IPSS, WPSS, MDPSS, and IPSS-R, is summarized in Table 1. The most common mutations in the training cohort were: TET2 (19%), ASXL1 (16%), SF3B1 (13%), DNMT3A (9%), STAG2 (9%), RUNX1 (8%), and U2AF1 (7%). In univariate analyses, mutations in EZH2 (HR1.8, p = .02), TP53 (HR2.3, p < .001), RUNX1 (HR 1.5, p = .05), and NPM1 (HR1.49, p = .001) had a negative impact on OS while SF3B1 (HR .34, p < .001) mutations were associated with favorable outcome. In multivariate analyses that included SS, mutations (from the list above), and age (except for the MDPSS, which already includes age), the following independent prognostic factors for OS were identified: age, EZH2, SF3B1, TP53, and each SS. Based on the fitted coefficients of each prognostic factor, a molecular version of each model including IPSSm, WPSSm, MDPSSm, and IPSS-Rm was proposed with median OS in the training and validation cohorts as summarized in Table 1. The addition of molecular data improved (reduced) the AIC and (raised) the C-index for the IPSS (2332.6, .69 vs. 2365.8, .64), WPSS (2322.3, .68 vs. 2356.2, .65), MDPSS (2308.4, .71 vs. 2323.4, .69), and IPSS-R (2305.2, .70 vs. 2330.5, .66), respectively. Further, the addition of molecular data to the IPSS upstaged 37% of pts from lower- to higher-risk disease and downstaged 5% of intermediate-1 to low risk disease. In the WPSS, it upstaged 21% of pts and downstaged 24%; in the MDPSS it upstaged 19% and dowstaged 22% of pts from intermediate-1 to low risk; and in the IPSS-R it upstaged 26% to higher-risk disease and 59% of pts with intermediate risk to a higher risk category.ConclusionsThe addition of molecular data to established MDS prognostic models can improve their predictive power, even in treated MDS patients. More importantly, adding molecular information can upstage or downstage pts into different risk categories. This study highlights the importance of incorporating molecular data into clinical prognostic systems. [Display omitted] DisclosuresMukherjee:Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Ariad: Consultancy, Honoraria, Research Funding.

Comparison of Myelodysplastic Syndrome Prognostic Scoring Systems.

Objective:Myelodysplastic syndrome (MDS) is a clonal hematopoietic stem cell disease. Patients are at risk of developing cytopenias or progression to acute myeloid leukemia. Different classifications and prognostic scoring systems have been developed. The aim of this study was to compare the different prognostic scoring systems.Materials and Methods:One hundred and one patients who were diagnosed with primary MDS in 2003-2011 in a tertiary care university hospital’s hematology department were included in the study.Results:As the International Prognostic Scoring System (IPSS), World Health Organization Classification-Based Prognostic Scoring System (WPSS), MD Anderson Prognostic Scoring System (MPSS), and revised IPSS (IPSS-R) risk categories increased, leukemia-free survival and overall survival decreased (p<0.001). When the IPSS, WPSS, MPSS, and IPSS-R prognostic systems were compared by Cox regression analysis, the WPSS was the best in predicting leukemia-free survival (p<0.001), and the WPSS (p<0.001) and IPSS-R (p=0.037) were better in predicting overall survival.Conclusion:All 4 prognostic systems were successful in predicting overall survival and leukemia-free survival (p<0.001). The WPSS was found to be the best predictor for leukemia-free survival, while the WPSS and IPSS-R were found to be the best predictors for overall survival.

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

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).MethodsIncluded 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.ResultsOf 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).ConclusionCurrently 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. [Display omitted] [Display omitted] DisclosuresKomrokji: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.

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.

Validation of the Lower-Risk MD Anderson Prognostic Scoring System for Patients With Myelodysplastic Syndrome.

The International Prognostic Scoring System (IPSS) is the most widely used tool for risk assessment and treatment decisions for myelodysplastic syndrome (MDS). Several new models have been proposed to identify a subset of lower-risk patients with MDS who are experiencing inferior than expected outcomes. We validated the Lower-Risk MD Anderson Risk Model (LR-MDAS) in 1288 lower-risk patients with MDS by the IPSS. On the basis of the LR-MDAS, 228 patients (17%) were in category 1, 730 patients (57%) were in category 2, 315 patients (25%) were in category 3, and 15 patients (1%) were in an unknown category. The median overall survival for the corresponding LR-MDAS categories was (1) 109 months (95% confidence interval [CI], 82-137), (2) 56 months (95% CI, 58-73), and (3) 29 months (95% CI, 24-35) (P < .005). Overall, 25% of patients were upstaged to category 3. LR-MDAS refined prognostic value among very low-, low-, and intermediate-risk Revised IPSS. The rate of acute myeloid leukemia transformation according to LR-MDAS was 15%, 18%, and 29% for categories 1, 2, and 3, respectively (P < .005). Our data validate the prognostic value of the LR-MDAS model, but the utility of it as a treatment decision tool should be studied prospectively.

Validation of the Lower Risk MD Anderson Prognostic Scoring System for Patients with Myelodysplastic Syndromes (MDS)

The International Prognostic Scoring System (IPSS) is the most widely used clinical tool for risk stratification and tailoring treatment in MDS. A subset of pts labeled lower risk MDS by IPSS experience inferior outcomes. The Lower Risk MD Anderson Risk Model (LR-MDAS) was developed to refine IPSS prognostic value. We validated LR-MDAS in large cohort of pts.

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.

An International Data Set for the Study of Chronic Myelomonocytic Leukemia (CMML) Validates Modern Prognostic Scoring Systems and Demonstrates a Critical Need for Novel Prognostication Strategies

Introduction: CMML is a heterogeneous malignancy characterized by peripheral monocytosis and a propensity for AML transformation. Given the low incidence of CMML and its broad range complexity, a large disease-specific data set is necessary to discern independent co-variates predictive of disease behavior. Several prognostic models derived from smaller data sets have been developed to stratify CMML patients into distinct groups that are predictive for OS. However, the validity of these models in a large international data set has never been investigated. Here, we present the largest International CMML data base established to date and report key baseline characteristics predictive for disease outcome. We externally validate and perform a detailed statistical comparison between the International Prognostic Scoring System (IPSS), Revised (R)-IPSS, Global MD Anderson Scoring System (MDASC), MD Anderson Prognostic Score (MDAPS), Dusseldorf Score (DS), Mayo, and Spanish Scoring Systems (CPSS).Methods: Data were abstracted by each contributing institution and deposited for central data review at the Moffitt Cancer Center. Manual review of cases was performed to ensure data quality prior to analysis. Only WHO defined CMML was included. The primary objective of this study was to establish an international CMML data set and validate the above models calculated at the time of presentation to each center. All prognostic models were calculated as previously described. The Kaplan–Meier (KM) method was used to estimate median OS and the log rank test was used to compare KM survival estimates with SPSS version 21.0. Random Forest Survival (RSF) and ROC analysis was done with R.Results: Between July 1981 and June 2014, 1832 CMML patients were captured in the International CMML database. Median age at diagnosis was 70 (16-93) years with a male (67%) predominance. By the WHO classification, the majority of patients had CMML-1 (79.9% vs. 20.1%) and most patients were evenly subcategorized as MPN-CMML (49.8%) versus MDS-CMML (50.2%) by FAB criteria. Splenomegaly was demonstrable in 25%. Most patients had favorable cytogenetics by both IPSS (70%) and CPSS (67.6%) classification schemas. Mean BM blast % was 5.6 and mean monocyte count was 4.85x103/dL. Median OS of the entire data set was 31.6 months. All tested prognostic models were valid and able to predict OS (p<0.0001). To compare relative model performance, 1013 complete cases with sufficient data to calculate all risk models were compared using time dependent receiver operator characteristic (ROC) curves and their area under the curves (AUC). ROC curves were calculated for OS at 36 months. The R-IPSS model had the highest AUC (0.694) while the DS model had the lowest (0.635). The difference in AUC between the R-IPSS and DS models was statistically significant (p = 0.003) whereas there was no significant difference from other models tested. To determine which models were most vulnerable to reclassification from low-risk to higher risk, we calculated a vulnerability score defined by the number of models able to up-stage low-risk disease in more than 15% of cases. Using this metric, the Mayo and MDASC scores were least vulnerable to up-staging by other models. Lastly, we used an orthogonal method for determination of variable importance (RSF for OS at 36 months). RSF is an ensemble method of classification and regression tree methodology. Ranking of variables by their weighted importance determined by this procedure identified the top five variables were hemoglobin, circulating blasts, platelet count, number of cytopenias, and karyotype. A new risk model was developed using the results of the RSF with an AUC of 0.720, which was comparable but not significantly different than other modern scoring systems.Conclusions: This represents the largest international CMML-specific data set derived from eight unique centers of excellence. All modern prognostic models were valid and performed comparably. Despite novel strategies for variable importance discovery, an improved model could not be constructed. This data suggest that the power of clinical variables has reached an asymptote and highlights the need for incorporation of molecular and other novel biological features. This data set is currently being populated with molecular data and is being leveraged to test published CMML molecular prognostic models which will be disclosed at the time of presentation. DisclosuresGarcia-Manero:Epizyme, Inc: Research Funding. Fenaux:Celgene, Janssenm, Novartis: Research Funding. Kantarjian:ARIAD, Pfizer, Amgen: Research Funding. Sekeres:Celgene: Membership on an entity’s Board of Directors or advisory committees; Amgen Corp: Membership on an entity’s Board of Directors or advisory committees; Boehringer-Ingelheim Corp: Membership on an entity’s Board of Directors or advisory committees.

The Prognostic Utility of the Current Risk Models in Predicting Outcomes of Patients (pts) with Higher-Risk Myelodysplastic Syndromes (HR-MDS) Treated with Hypomethylating Agents (HMA)

Background: Although HMA (azacitidine [aza] or decitabine [dac]) are standard of care therapies for HR-MDS pts, responses may not be seen for 4-6 months and occur in <50% of treated pts. Moreover, curative hematopoietic cell transplantation (HCT), which is recommended as up-front therapy for HR-MDS, is used in <5% of pts. The ability to identify pts with a low likelihood of benefiting from HMA who instead should receive immediate HCT or experimental treatment approaches is a clinical and research priority. Established MDS prognostic systems include the International Prognostic Scoring System (IPSS) and the revised IPSS (IPSS-R) [derived from untreated pt cohorts] and the MD Anderson Prognostic Scoring System (MDAPSS) [derived from treated and untreated pt cohort]. A French Prognostic Scoring System (FPSS) was developed to predict survival among aza-treated HR-MDS pts. We compared the relative prognostic discriminatory power of these models in a large cohort of HMA-treated pts with HR-MDS.Methods: The combined MDS database obtained from six institutions in the MDS Clinical Research Consortium (Moffitt Cancer Center, Cleveland Clinic, MD Anderson Cancer Center, Dana Farber Cancer Institute, Weill Medical College of Cornell University, and the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins) was used to identify patients with HR-MDS (IPSS intermediate-2 [INT-2] and high) who received HMA therapy (aza or dac). Responses were defined per International Working Group 2006 criteria. Overall response rate (ORR) was defined as the sum of rates of complete response (CR), partial response (PR), hematologic improvement (HI), and marrow CR. Pts with stable disease (SD) and progressive disease (PD) were considered non-responders. Logistic regression models were fitted and tested for association of response with prognostic risk categories using chi-square deviance tests. Overall survival (OS) was calculated from the time of diagnosis to time of death or last follow-up. Kaplan-Meier (KM) curves were generated for OS and the log-rank test was used to compare median OS. Akaike information criteria (AIC) were used to assess the relative goodness of fit of the models.Results: We identified 595 pts with HR-MDS (70.3% with INT-2 and 29.7% with high IPSS) who received HMA as upfront therapy (83% aza, 17% dac). Median follow-up from diagnosis was 13.1 months (M), 95% confidence interval (CI): 11.5-15.1 M. 66% of pts were male, 88% white, 85% were >60 years, and 18% had therapy-related MDS. Median number of HMA cycles was 5.7 (range, 0.7-51) with 75% of pts receiving ≥3 cycles of therapy. Median time from diagnosis to start of HMA therapy was 1.5 M. ORR was 42.1% (CR 25.8%, PR 6.7%, HI-E 3.3%, HI-P 2.3%, HI-N 4.0%) while 57.2% were non-responders (SD 28.6% and PD 28.6%) and 0.7 were un-evaluable. None of the prognostic systems predicted overall response to HMA. Median OS for the entire cohort was 16.3 M (CI, 15.0-17.8 M). Figure 1 shows the KM survival curves and Table 1 shows the median OS, the corresponding CI and associated p-value for the risk categories in each prognostic model. Scores generated using the AIC (n=294) to assess the relative goodness of fit (lower is better) were 2139 (MDAPSS), 2148 (FPSS), 2155 (IPSS-R), and 2174 (IPSS).Conclusions: We report the largest direct comparison of the major MDS prognostic models among HMA-treated patients. None of the models predicted overall response to HMA therapy. Nonetheless, the IPSS-R, MDAPSS, and the FPSS all functioned well to separate HMA-treated pts with HR-MDS into different prognostic groups in terms of survival. The MDAPSS and FPSS appear superior to the IPSS-R and IPSS for survival prediction. HR-MDS pts with poor projected survival with HMA therapy should be considered for up-front HCT or for experimental approaches. [Display omitted] Abstract 1935. Table 1IPSS (n=595)IPSS-R (n=555)FPSS (n=296)MDAPSS (n=508)Risk Group (n)Median OS in months (CI)Risk Group (n)Median OS in months (CI)Risk Group (n)Median OS in months (CI)Risk Group (n)Median OS in months (CI)Low (0)NAVery low (1)NALow (19)38.4 (23.1-NR)Low (4)Not reached (NA)INT-1 (0)NALow (3)28.1 (27.0-NR)INT (241)17.8 (15.9-19.6)INT-1 (55)26.2 (18.8-40.4)INT-2 (418)16.8 (15.3-18.3)INT (59)39.1 (23.9-49.6)High (36)10.6 (7.2-13.4)INT-2 (143)18.6 (17.4-24.1)High (177)15.2 (13.4-17.8)High (197)18.8 (16.8-22.2)High (306)13.4 (11.8-15.0)Very High (295)12.2 (11.0-14.1)P-valueP=0.014P<0.0001P<0.0001P<0.0001 DisclosuresSekeres:Celgene: Membership on an entity’s Board of Directors or advisory committees; Amgen Corp: Membership on an entity’s Board of Directors or advisory committees; Boehringer-Ingelheim Corp: Membership on an entity’s Board of Directors or advisory committees. Garcia-Manero:Novartis Pharma: Research Funding. Steensma:Amgen: Consultancy; Ariad: Equity Ownership; Celgene: Consultancy; Novartis: Consultancy. List:Celgene Corporation: Consultancy.

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

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.MethodsClinical 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.ResultsA 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.ConclusionWhen 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. [Display omitted] [Display omitted] [Display omitted] DisclosuresRoboz:Novartis: Consultancy; Agios: Consultancy; Celgene: Consultancy; Glaxo SmithKline: Consultancy; Astra Zeneca: Consultancy; Sunesis: Consultancy; Teva Oncology: Consultancy; Astex: Consultancy.

Acute myeloid leukemia arising from chronic myelomonocytic leukemia during hypomethylating therapy.

TO THE EDITOR: Acute myeloid leukemia (AML) arising from chronic myelomonocytic leukemia (CMML) exhibits a poor prognosis [1, 2] and represents a great challenge during hematological clinical practice. The introduction of hypomethylating therapies, such as azacitidine [3, 4] and decitabine [5], in CMML management has provided some important advances; however, currently the majority of CMML cases progress into AML. We present the characteristics of 2 patients, in whom the atypical and sudden progression from CMML to AML was observed when they were administered azacitidine. Previously, both cases had achieved a very good response to this agent. The first case is a 60-year-old man with a suspected therapy-related CMML, which arose 3 years after receiving chemo-radiotherapy treatment for a solid head and neck tumor. When diagnosed as having CMML, hypercellular bone marrow (BM) with 15% blasts was noted. Furthermore, the JAK2 V617F mutation was identified by quantitative PCR analysis, whereas standard cytogenetic and FISH analysis using BM and peripheral blood showed no abnormalities (normal karyotype). The MD Anderson Prognostic Scoring System (MDAPS) [6] classification was 4 (high risk). The patient received azacitidine at a dosage of 75 mg/m2 for 5+2 days (excluding weekends) every 4 weeks. After the fourth cycle of azacitidine, complete remission (CR) of CMML (BM blasts <5%) was recorded, although the patient continued the treatment during allogeneic hematopoietic stem cell transplantation. However, soon after the sixth cycle of azacitidine, a sudden evolution into AML (myelomonoblastic subtype) occurred. A very rapid transition from near normal peripheral blood counts to a very marked level of blastic leukocytosis was observed within 4 days: the WBC count was 120×109/L and 70% of myelomonoblastic cells were positive for HLA-DR, CD4, CD13, CD15, CD33, CD64, CD45, CD34, CD56, and CD117. Furthermore, an abnormal karyotype, i.e., 46,XY,del(7)(q31)[7]/46, XY[13], was found. FISH analysis confirmed a deletion of the long arm of chromosome 7 in 80% of blastic cells. Molecular studies detected the previously observed JAK2 V617F mutation, as well as the IDH2 R172K mutation; however, no AML-related alterations, such as CBFb/MYH11, DEK/CAN, NPM1, FLT3, and RUNX1/ETO, were identified. The patient received 1 course of chemotherapy for AML but soon died of disease progression. The second case was a 72-year-old-man who was attended to because of pancytopenia with monocytosis. A BM aspirate and trephine biopsy showed hypercellular BM with 18% blasts, resulting in a diagnosis of CMML. The JAK2 V617F mutation was detected and chromosomal analysis revealed an abnormal karyotype, i.e., 46,XY,inv(12)(p13.3q15). The patient was classified by MDAPS as high-risk. He was treated with azacitidine according to the same schedule reported above, achieving a hematological and cytogenetic CR after the sixth cycle. The hypomethylating regimen was continued for additional 7 cycles; however, before starting the fourteenth cycle, the patient complained of a sudden deterioration of his general condition. A marked peripheral blastosis (WBC=140×109/L) was identified and 90% of immature monoblasts were positive for the immunophenotype HLA-DR, CD15, CD33, CD64, CD45, CD34, CD56, and CD117. A diagnosis of AML (French-American-British classification: M5b) was made. The same karyotypic abnormality that had been detected when diagnosed as having CMML was again identified. Molecular studies showed no abnormalities. The patient's condition rapidly worsened, and he died a few days after AML diagnosis because of cardiac and pulmonary complications. He had not been able to receive any chemotherapeutic treatment. In conclusion, we reported 2 atypical cases dealing with a sudden and devastating transformation of high-risk CMML into AML during azacitidine treatment while in CR. Although new effective treatments such hypomethylating agents have been introduced, CMML remains a severe and incurable disease, for which allogeneic hematopoietic stem cell transplantation represents the only potentially curative treatment [1]. The evolution into AML can be delayed, but not avoided, in patients treated with hypomethylators. Moreover, AML can arise from CMML during its natural course [1]. AML transformation during hypomethylating therapy for CMML is quite common because of the lack of response to the hypomethylating agent and/or of disease progression [3, 7, 8, 9]. The present 2 cases did not provide any evidence that hypomethylating therapy is related to leukemic transformation, clonal selection, or evolution into AML. However, what makes these cases unusual is that the evolution into AML occurred within a few days without any prodromal clinical signs or anticipatory hematological features. Although presented with negative prognostic features both patients achieved a good response to the treatment; however, the responses were transient (2 and 7 months, respectively), and the particularly devastating evolution into AML was characterized by a rapid and prominent leukemic spread and a rapidly fatal clinical course. The biological and clinical features of AML transformation in patients who have received hypomethylators is not fully elucidated and understood; hence, further research into this issue is required to optimize the salvage treatment in this very challenging setting.