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.

scholarly journals The development and validation of prognostic models for overall survival in the presence of missing data in the training dataset: a strategy with a detailed example

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Kara-Louise Royle ◽  
David A. Cairns
Keyword(s):  
Overall Survival ◽  
Missing Data ◽  
Prognostic Model ◽  
Prognostic Index ◽  
Risk Groups ◽  
Prognostic Models ◽  
Training Dataset ◽  
Validation Process ◽  
Test Dataset ◽  
Development And Validation

Abstract Background The United Kingdom Myeloma Research Alliance (UK-MRA) Myeloma Risk Profile is a prognostic model for overall survival. It was trained and tested on clinical trial data, aiming to improve the stratification of transplant ineligible (TNE) patients with newly diagnosed multiple myeloma. Missing data is a common problem which affects the development and validation of prognostic models, where decisions on how to address missingness have implications on the choice of methodology. Methods Model building The training and test datasets were the TNE pathways from two large randomised multicentre, phase III clinical trials. Potential prognostic factors were identified by expert opinion. Missing data in the training dataset was imputed using multiple imputation by chained equations. Univariate analysis fitted Cox proportional hazards models in each imputed dataset with the estimates combined by Rubin’s rules. Multivariable analysis applied penalised Cox regression models, with a fixed penalty term across the imputed datasets. The estimates from each imputed dataset and bootstrap standard errors were combined by Rubin’s rules to define the prognostic model. Model assessment Calibration was assessed by visualising the observed and predicted probabilities across the imputed datasets. Discrimination was assessed by combining the prognostic separation D-statistic from each imputed dataset by Rubin’s rules. Model validation The D-statistic was applied in a bootstrap internal validation process in the training dataset and an external validation process in the test dataset, where acceptable performance was pre-specified. Development of risk groups Risk groups were defined using the tertiles of the combined prognostic index, obtained by combining the prognostic index from each imputed dataset by Rubin’s rules. Results The training dataset included 1852 patients, 1268 (68.47%) with complete case data. Ten imputed datasets were generated. Five hundred twenty patients were included in the test dataset. The D-statistic for the prognostic model was 0.840 (95% CI 0.716–0.964) in the training dataset and 0.654 (95% CI 0.497–0.811) in the test dataset and the corrected D-Statistic was 0.801. Conclusion The decision to impute missing covariate data in the training dataset influenced the methods implemented to train and test the model. To extend current literature and aid future researchers, we have presented a detailed example of one approach. Whilst our example is not without limitations, a benefit is that all of the patient information available in the training dataset was utilised to develop the model. Trial registration Both trials were registered; Myeloma IX-ISRCTN68454111, registered 21 September 2000. Myeloma XI-ISRCTN49407852, registered 24 June 2009.

A moncentric review of targeted therapy on overall survival in metastatic renal clear cell carcinoma.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e15593-e15593
Author(s):  
Melanie Tadj ◽  
Valentin Arnoux ◽  
Mireille Mousseau ◽  
Jean Luc Descotes ◽  
Jean-Louis Quesada ◽  
...  
Keyword(s):  
Overall Survival ◽  
Targeted Therapy ◽  
Cell Carcinoma ◽  
Risk Groups ◽  
Renal Clear Cell Carcinoma ◽  
Rank Test ◽  
First Line ◽  
Log Rank Test ◽  
Targeted Treatments ◽  
Practice Methods

e15593 Background: Anti-angiogenic treatment had radically modified therapeutic strategy in metastatic renal cell carcinoma (mRCC). This study is aimed to determine the overall survival (OS) improvement in clinical practice. Methods: Retrospective, monocentric and non-interventional study in mRCC diagnosed since 2000 with 2 cohorts of patients determined according to the first line treatment (targeted therapy or others treatment). Results: Between 1 January 2000 and 31 December 2010, 98 patients were included. The 2 cohorts were balanced with regard to baseline disease and demographic characteristics in particular for prognosis profiles distribution. As first line, 58 patients received targeted therapy whose 21% were treated by bevacizumab, 71% by sunitinib and 8% by temsirolimus. In non-targeted therapy cohort (n=40), 37.5% were treated by cytokines, 15% by cytotoxic chemotherapy or hormonal therapy. Patients treated with targeted therapy had a significantly longer median OS (30 months versus 13 months; p<.003, log-rank test). The Hazard Ratio (HR) of death at 3 years was 0.53 (95% Confidence Interval, 0.33-0.85; p=.008, log-rank test). When adjusted to the prognosis profile, the HR of death was 0.43 (95%CI, 0.27-0.71). Conclusions: This retrospective study demonstrated the improvement of OS due to targeted treatments, for all prognostic risk groups. This result supported the complete change of care of mRCC patients with extension of therapeutic indications and efficient therapeutic lines.

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.

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.

Combining Measurements of Plasma Cell Apoptosis and Proliferation in Multiple Myeloma Identifies Patients with Poor Survival.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3410-3410 ◽  
Author(s):  
Shaji Kumar ◽  
Michael Timm ◽  
Martha Q. Lacy ◽  
Angela Dispenzieri ◽  
Suzanne R. Hayman ◽  
...  
Keyword(s):  
Overall Survival ◽  
Plasma Cell ◽  
Cell Apoptosis ◽  
Prognostic Value ◽  
Median Overall Survival ◽  
Plasma Cells ◽  
Annexin V ◽  
Rank Test ◽  
Poor Survival ◽  
Log Rank Test

Abstract Background: Multiple Myeloma (MM) is characterized by accumulation of malignant plasma cells with relatively low proliferative and apoptotic rates. The proliferative rate of plasma cells, measured in terms of % plasma cells labeled by bromodeoxyuridine (BrdU) using slide based fluorescence microscopy (plasma cell labeling index or PCLI) has been shown to be a powerful prognostic factor in MM. We have previously shown that the % bone marrow plasma cells in apoptosis (PCAP) determined by a flow cytometry method that uses Annexin V staining or 7-amino Actinomycin D (7-AAD) correlates with disease stage in MM. The goal of this study was to examine the prognostic value of the PCAP. Methods: We studied 145 patients with MM including 74 with newly diagnosed MM, 40 with relapsed MM, and 31 with MM on treatment in whom simultaneous measurements of % plasma cell apoptosis and PCLI were available. The PCLI is expressed as the percentage of cytoplasmic immunoglobulin positive plasma cells that have taken up BrdU. The PCLI was characterized as high when &gt;= 1%. Mononuclear cells isolated from bone marrow aspirate, following red cell lysis with ACK solution, are incubated with CD38-PE and either CD138-FITC or CD45-FITC. This is followed by incubation with 7-AAD and the plasma cells are gated using the CD38/CD45 staining pattern. The Annexin method used a similar strategy, with Annexin V in place of 7-AAD. The percentage of plasma cells in apoptosis (PCAP) was categorized as high when &gt;5%, the median value. Results: The median follow up for the entire group was 34 months (range, 0.1 mo to 9 years) and 112 (77%) had died at the time of analysis. Forty seven patients (32%) had a high PCLI (&gt;=1%). The median overall survival for the patients with high PCLI was 14.6 months versus 42.3 months for those with a low PCLI; P = 0.0005 (log rank test). Seventy-five (51.7%) patients had a high PCAP. The median overall survival for those patients was 28.9 months versus 40.2 months for those with a low PCAP; P = 0.078. We next examined if there was any correlation between a high PCAP and high PCLI and found none; P = NS by (Fisher’s exact test). Additionally in a multivariate Cox model using both PCLI and PCAP, both were independently prognostic for overall survival. We then developed an index by adding PCLI to log transformed PCAP (PCLI + log PCAP). Using a cutoff of 1.5 for the new index we were able identify a group of patients with poor survival. The 59 patients with a high value for the new index had a median survival of 19.3 months vs 46.1 months for the rest (P &lt; 0.0001, log rank test). Conclusion: The measurement of plasma cell apoptosis has prognostic value in patients with MM. More importantly, we have shown that by combining measures of two important biological characteristics of the plasma cell, namely proliferation and apoptosis, patients with a poor prognosis can be identified. Such a prognostication strategy can help stratify patients in clinical trials as well as shed light on the disease biology.

Towards a Comprehensive Prognostic Score in CLL Based On a Combination of Genetic Parameters.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 1234-1234
Author(s):  
Claudia Haferlach ◽  
Frank Dicker ◽  
Tamara Weiss ◽  
Susanne Schnittger ◽  
Christian Beck ◽  
...  
Keyword(s):  
Overall Survival ◽  
Chromosome Aberrations ◽  
Prognostic Score ◽  
Prognostic Significance ◽  
Rank Test ◽  
Prognostic Impact ◽  
Time To Treatment ◽  
Log Rank Test ◽  
Equity Ownership ◽  
The Impact

Abstract Abstract 1234 Poster Board I-256 CLL is a heterogeneous disease with a variable clinical course. In this study the prognostic power of chromosome banding analysis (CBA), interphase FISH and IgVH status was evaluated. In total 399 untreated cases were analyzed. First, we could confirm the prognostic significance of established parameters such as age (≥65 yrs), white blood cell count (≥20.000/μl), IgVH status, TP53 deletion and 11q deletion in our cohort. In addition, a negative prognostic impact of translocations involving the IgH locus, especially t(14;18)(q32;q21) and of the complexity of the karyotype measured by the number of clonal chromosome aberrations in CBA was observed. Furthermore it became obvious that some parameters discriminated better for overall survival and other for time to treatment. While the impact of the IgVH status on overall survival was low within the first 5 years after diagnosis (mutated 88.5% surviving vs unmutated 82.0% surviving, log rank test p=0.022), an unmutated IgVH status was strongly correlated with a shorter median time to treatment (18.3 months unmutated vs 110.7 months mutated, log rank test p<0.0001). On the other hand the impact of TP53 deletion was more pronounced on overall survival as compared to time to treatment. Age was associated with a shorter overall survival but was not significantly associated with time to treatment. Based on these results we propose a score for overall survival (OS) based on: age ≥65 yrs, WBC ≥20.000/μl, unmutated IgVH status, TP53 deletion, t(IgH), and the number of chromosome aberrations observed in CBA. Three respective risk groups showed considerable differences in OS (94.5% vs 64.3% vs 41.1% surviving at 5 yrs, p<0.0001). In contrast, time to treatment (TTT) was predicted best by unmutated IgVH status, ATM deletion, t(IgH) and number of chromosome aberrations. Four subgroups could be separated with median TTT of 110.7 months, 39.8 months, 19.5 months, and 3.8 months, respectively (p<0.0001). In conclusion, our data show that in combination with established prognostic markers such as an unmutated IgVH status, TP53/17p deletions or 11q deletions also the newly defined complexity of the karyotype measured by the number of chromosome aberrations has an important impact both on overall survival and also on time to treatment in CLL. These newly combined parameters translate into a more distinct separation of prognostic subgroups within the first years after diagnosis as compared to other prognostic systems using FISH data only or based on FISH data in combination with IgVH status. Prospective studies should evaluate the power for early stage CLL patients. Disclosures Haferlach: MLL Munich Leukemia Laboratory: Equity Ownership. Dicker:MLL Munich Leukemia Laboratory: Employment. Weiss:MLL Munich Leukemia Laboratory: Employment. Schnittger:MLL Munich Leukemia Laboratory: Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Equity Ownership.

Validation of a Prognostic Model and the Impact of SF3B1, DNMT3A, and Other Mutations in 289 Genetically Characterized Lower Risk MDS Patient Samples

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 969-969 ◽  
Author(s):  
Rafael Bejar ◽  
Kristen Stevenson ◽  
Bennett Caughey ◽  
Omar Abdel-Wahab ◽  
Naomi Galili ◽  
...  
Keyword(s):  
Scoring System ◽  
Lower Risk ◽  
Prognostic Model ◽  
Point Mutations ◽  
Gene Mutations ◽  
Risk Groups ◽  
Appropriate Therapy ◽  
Md Anderson ◽  
Risk Categories ◽  
Independent Cohort

Abstract Abstract 969 Selection of the appropriate therapy for patients with myelodysplastic syndromes (MDS) depends heavily on the predicted prognosis of each afflicted individual. Prognostic scoring systems help stratify patients into risk groups, but outcomes can be highly variable even within these groups. Of particular concern are patients predicted to have lower risk disease that go on to progress more rapidly than expected. Such patients may not be offered risk-appropriate therapy at a time when it might be of greatest benefit. A prognostic model that better predicts survival in patients believed to have lower risk disease has been proposed by investigators at the MD Anderson Cancer Center, but not yet validated in an independent cohort. Acquired genetic mutations can also identify patients with higher-than-predicted disease risk. We have previously demonstrated that mutations in any of five genes (TP53, EZH2, ETV6, RUNX1, and ASXL1) predict a poorer prognosis independently of the International Prognostic Scoring System (IPSS). In this study, we examined 289 MDS patients with Low or Intermediate-1 IPSS risk for mutations in 21 genes, including two genes that have recently been reported to be frequently mutated in MDS: DNMT3A and SF3B1. We validate the ability of the Lower-Risk MD Anderson Prognostic Scoring System (LR-PSS) to more finely risk-stratify patients using an independent cohort and identify gene mutations independently associated with clinical features and overall survival. Patients were stratified into one of three risk categories using the LR-PSS shown in the Table. The 58 patients (20%) assigned to Category 1 had a median survival of 5.19 years (95% confidence interval in years [CI] 3.05–10.34), compared to 2.65 years (CI 2.18–3.30) for the 160 patients (55%) in Category 2, and 1.11 (CI 0.82–1.51) for the 71 patients (25%) in Category 3. Differences in survival were significant between all three categories (p < 0.001 for all comparisons). Point mutations were identified in 63% of samples, including 64% of those with a normal karyotype. The 10 most frequently mutated genes were TET2 (23% of cases), SF3B1 (21%), ASXL1 (15%), DNMT3A (14%), RUNX1 (9%), EZH2 (8%), JAK2 (3%), NRAS (3%), TP53 (2%), and ETV6 (2%). Mutations of SF3B1 were highly enriched in cases of refractory anemia with ring sideroblasts (RARS; 32 out of 43, 74%), associated with normal blast percentages (p = 0.04) and neutrophil counts (p = 0.002), and more likely to be present in cases with platelet counts greater than 450,000/μl (p < 0.001). We extended our analysis of SF3B1 mutations by adding a separate cohort of 98 RARS patients with Low or Intermediate-1 IPSS risk for a total of 141 cases. In this extended RARS set, SF3B1 mutations were associated with improved survival even after adjustment for IPSS risk group or LR-PSS category (hazard ratio [HR]=0.49; CI 0.29–0.81, HR=0.35; CI 0.21–0.58, respectively). SF3B1 is the first gene mutation independently associated with a favorable prognosis in non-CMML MDS. In contrast, DNMT3A mutations were not associated with differences in overall survival in the 289 patients with lower IPSS risk MDS. In a model generated from stepwise Cox regression analysis that considered LR-PSS risk categories and the mutation status of the 13 most frequently mutated genes as candidates, only EZH2 mutations emerged as a LR-PSS-independent risk factor associated with a poor prognosis (HR=2.90; CI 1.86–4.53). In a similar model using IPSS risk groups, EZH2 (HR=2.85; CI 1.78–4.57), NRAS (HR=2.78; CI 1.35–5.72), and ASXL1 (HR=1.60; CI 1.09–2.34) were significant IPSS-independent risk factors. Mutations in genes such as ASXL1, RUNX1, NRAS, and ETV6, which are associated with poor survival in unselected MDS patients, were most common in patients assigned to the LR-PSS risk Category 3, indicating that this prognostic model may capture more clinically relevant information associated with adverse gene mutations. In conclusion, this study validates the LR-PSS 's ability to identify higher risk MDS patients among those with lower IPSS risk and demonstrates that point mutations are common in this cohort, associate with specific clinical features, and independently provide both favorable and adverse prognostic information.Table:Table:. The Lower-Risk MD Anderson Prognostic Scoring System (LR-PSS) Disclosures: No relevant conflicts of interest to declare.

Refined MD Anderson Prognostic Scoring System (MDAPS-R) for Chronic Myelomonocytic Leukemia (CMML)

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3797-3797
Author(s):  
Koichi Takahashi ◽  
Naveen Pemmaraju ◽  
Miloslav Beran ◽  
Alfonso Quintás-Cardama ◽  
Jorge E. Cortes ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Scoring System ◽  
Relative Strength ◽  
Rank Test ◽  
Proportional Hazard ◽  
Cytogenetic Abnormalities ◽  
Cox Proportional Hazard ◽  
Log Rank Test ◽  
Cox Proportional Hazard Regression ◽  
Md Anderson

Abstract Abstract 3797 Background: Since the time of initial proposal of the MD Anderson Prognostic Score (MDAPS) in 2000, there has been substantial development in diagnosis and treatment for patients (pts) with CMML. MDAPS did not incorporate cytogenetic abnormalities, which is one of the most important factors of prognostication in other myeloid malignancies. Therefore, we analyzed a large cohort of patients with CMML and developed new prognostic scoring system that also incorporates cytogenetic abnormalities (named MDAPS-R). Methods: From 2003 and 2012, we identified 358 pts with diagnosis of CMML, using standards strictly defined by World Health Organization (WHO) criteria. Potential prognostic factors were identified by log-rank test. Of those, independent prognostic factors were extracted after Cox proportional hazard regression. Based on the relative strength of hazard ratio (HR), MDAPS-R was developed and was verified by log-rank test. Result: Median age of the analyzed group was 68 years (range:23–89);113 (32%) pts were female. Two hundred twenty one (62%) pts were classified as CMML-1 and 104 (29%) were CMML-2 (unknown in 33 pts). Thirty nine (11%) pts had prior exposure to chemotherapy and/or radiation therapy. Mean (± SE) white blood cell count (WBC) was 24.5 ± 1.5 (x103/μL), hemoglobin (Hb) was 10.8 ± 0.1(g/dL), platelet count (Plt) was 132 ± 7.0 (x103/μL) and bone marrow blast count (BMBL) was 6.9 ± 0.3 (%), respectively. Cytogenetics was diploid in 224 (63%) pts. Trisomy 8 was detected in 14 (4%) pts, del 20q in 12 (3.4%), -Y in 13 (3.6%), del 7q/-7 in 25 (7%), and del 5q/-5 in 10 (2.8%) pts, respectively. Complex cytogenetic abnormality was detected in 16 (4.5%) pts. Two hundred eighty (78%) pts had RAS mutation analysis and 49 (18%) had NRAS mutation while 16 (5.7%) had KRAS mutation. FLT3 alteration was tested in 297 pts (83%):3 (1%) had D835 mutation while 10 (3.4%) had ITD. JAK2 mutation was tested in 161 (45%) pts of which 19 (12%) had V617F mutation. Less commonly occurring mutations included: NPM1 (5/88 tested), c-kit (3/156), CEBPA (6/83), IDH1 (1/59), IDH2 (3/58), and DNMT3a (1/4). During the median follow up duration of 15 months (range; 1–145), 53 (15%) pts transformed to acute leukemia and 182 (51%) pts died. Median transformation free survival (TFS) and overall survival (OS) of the analyzed group was 24.9 months (range; 1–145) and 26.8 months (range; 1–145), respectively. Log-rank test identified significant covariates in association with OS that include: BMBL (<10 vs. ≥10; P = 0.024), WBC (≤10 vs. >10; P = 0.01), Hb (<12 vs. ≥12; P < 0.001), CMML subtype (CMML-1 vs. 2; P = 0.007), prior exposure to chemo and/or radiation (Yes vs. No; P < 0.001), cytogenetics (diploid vs. complex or del7q/-7 vs. others; P < 0.001), serum β2 microglobulin (β2MG) (≤4.0 vs >4.0; P < 0.001), serum LDH (≤700 vs. >700; P < 0.001), peripheral absolute lymphocyte count (ALC) (≤2.5 vs. >2.5; P < 0.001), and peripheral absolute monocyte count (≤4.0 vs. >4.0; P = 0.012). None of the molecular mutations had impact on OS. After being fitted into Cox proportional hazard regression, following covariates remained independently significant: BMBL ≥10 % (vs. <10; HR = 1.6), Hb < 12 g/dL (vs. ≥12; HR = 1.9), LDH > 700 IU/L (vs. ≤700; HR = 1.5), ALC > 2.5 × 103/μL (vs. <2.5; HR = 1.7), β2MG > 4.0 mg/L (vs. ≤ 4.0; HR = 1.6), and complex cytogenetics or del 7q/-7 (vs. diploid; HR = 2.3 and others vs. diploid; HR = 1.5). We developed MDAPS-R based on relative strength of HR in each of these above factors (1 point assigned to each of the following: BM BL '10 %, Hb<12 g/dL, LDH 700 IU/L, ALC .2.5 × 103/μL, and β2MG > 4.0 mg/L; 0 points for diploid cytogenetics, 2 points for −7/del 7q or complex cytogenetics, and 1 point for all other abnormal karyotype). Among 358 pts, 282 (79%) were evaluable for analysis via MDAPS-R. MDAPS-R stratified pts into 4 distinct prognostic groups: score 0–1 = low risk (N = 70, median OS 56 months), 2–3 = intermediate-1 risk (N = 133, median OS 28 months), 4–5 = intermediate-2 risk (N = 68, median OS 18 months), and 6–7 = high risk (N = 11, median OS 7.5 months) (P < 0.001, Figure 1A). MDAPS-R also predicted TFS in the same cohort (median TFS: low = 54, int-1 = 26, int-2 = 15, and high = 7 months, P < 0.001, Figure 1B). Conclusion: We propose a refined version of MDAPS (MDAPS-R) specifically for pts with CMML that incorporates cytogenetic abnormalities. This model may help risk-stratified decision making in CMML pts. 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.

The Impact of Comorbidity in Myelodysplastic Syndromes

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 4940-4940
Author(s):  
Yu-Chung Huang ◽  
Kuo-Wei Chen ◽  
Ying-Chung Hong ◽  
Chia-Jen Liu ◽  
Yuan-Bin Yu ◽  
...  
Keyword(s):  
Scoring System ◽  
Proportional Hazards ◽  
Conflicts Of Interest ◽  
Prognostic Score ◽  
Risk Groups ◽  
Cox Proportional Hazards ◽  
Prognostic Models ◽  
International Prognostic Scoring System ◽  
The Impact ◽  
Cell Disorder

Abstract Abstract 4940 Introduction Myelodysplastic syndrome (MDS) is a heterogeneous clonal hematopoietic cell disorder. The prognostic implication of comorbidities at diagnosis of MDS is emerging. Objective We aimed to investigate the impact of comorbidity on the patients with MDS. Method Totally 263 MDS patients during a 15-year period in single institute were collected. The clinical characteristics and the extra-hematological systemic diseases at diagnosis were all registered in this database. Well established prognostic models, including original International Prognostic Scoring System (IPSS), WHO classification-based Prognostic Scoring System (WPSS), and total MDACC scores were evaluated in our cohort. Results Comorbidity was present in 76. 4% of patients. In univariate and multivariate analysis, HCT-CI ≥ 3 was significantly associated with poor outcome. IPSS, WPSS and MDACC were informative to discriminate between risk groups of patients with MDS. By comparing AIC values in the Cox proportional hazards analysis, MDACC had superior prognostic value followed by IPSS and WPSS. A modified score incorporating HCT-CI and MDACC divided patients into four risk groups. The 3 year-survival rate was 72%, 40%, 31%, 4%, respectively. Conclusion Building new models incorporating comorbidities to current prognostic score help to predict survival in patients with MDS. Disclosures: No relevant conflicts of interest to declare.

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