scholarly journals Comprehensive Clinical-Molecular Transplant Risk Model for Myelofibrosis Undergoing Allogeneic Stem Cell Transplantation

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 689-689 ◽  
Author(s):  
Nico Gagelmann ◽  
Markus Ditschkowski ◽  
Rashit Bogdanov ◽  
Marie Robin ◽  
Bruno Cassinat ◽  
...  
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Research Funding ◽  
Triple Negative ◽  
Cox Regression ◽  
Univariate Analysis ◽  
Risk Groups ◽  
Karnofsky Performance Score ◽  
Very High ◽  
Reduced Intensity

Abstract Background The dynamic International Prognostic Scoring System (DIPSS) is commonly applied to predict survival among patients with primary myelofibrosis (PMF) but has been shown to perform less precisely in secondary myelofibrosis (SMF) and after transplantation. Furthermore, the prognostic relevance of mutation profile resulted in the mutation-enhanced IPSS (MIPSS) in PMF, as well as in a model specific to SMF (MYSEC-PM) after essential thrombocythemia (ET) or polycythemia vera (PV). The aim of the current study was to develop a comprehensive prognostic system including clinical and molecular information, specifically in myelofibrosis undergoing transplantation. Methods Previously published methods were used to sequence myelofibrosis-associated genes (i.a. CALR1/2, JAK2, MPL,ASXL1, SRSF2, EZH2, IDH1/2, DNMT3A, TET2, TP53). Outcome was calculated from date of transplant (95% confidence interval). Variables associated with overall survival (OS) constructed a Cox regression with a stepwise selection procedure. Hazard ratios (HR) were used as weights for model development. Validation was done using repeated random subsampling. Performance of the model was verified via Harrel's concordance index C and was also tested in predefined cohorts: disease (PMF, SMF), conditioning, and ruxolitinib pretreatment. Results Population. The total cohort consisted of 361 patients from four different centers in Germany and France (260 PMF, 101 SMF). Median age at transplant was 57 years (range, 22-75), 58% were male and 42% had a Karnofsky performance score (KPS) <90. The median follow-up was 62 months and was similar between PMF and SMF (p=0.50). Overall 5-year OS was 60% (54-67) being similar in PMF (63%) and SMF after ET (59%) and slightly lower after PV (45%). Most frequent mutations were: JAK2 V617F (57%), CALR (20%; types 1/2/other 66%/23%/11%), MPL (5%), ASXL1 (31%), TET2 (19%), SRSF2 (9%), DNMT3A (6%), TP53 (6%). Two or more mutations were present in 60%. Most transplants were received from matched unrelated (46%), mismatched unrelated donors (MMUD, 27%), identical siblings (27%), and mismatched siblings (1%). Reduced intensity was given more frequently (64%) than myeloablative conditioning (36%). Frequencies at transplant were 9% (low), 29% (intermediate-1), 48% (intermediate-2), 14% (high) according to DIPSS and 3% (low), 40% (intermediate), and 57% (high) for MIPSS. Factors on outcome. In univariate analysis, mutations in CALR and MPL showed better OS (79% and 76%) vs. JAK2 (53%) and triple negative (50%; p=0.001). Outcome was similar according to CALR type (p=0.99). ASXL1 and DNMT3A mutations also entered the multivariate model. The following eight clinical, molecular and transplant-related variables were identified (corresponding HR): leukocytes >25x109/l (1.71), platelets <150x109/l (1.53), KPS <90 (1.63), age >57 years (1.69), recipient/donor CMV serostatus (+/- vs. other, 1.68), ASXL1 (1.74), JAK2/triple negative (2.10), and MMUD (2.11). Myelofibrosis Transplant Scoring System (MTSS). A weighted score of 1 was assigned to leukocytosis, thrombocytopenia, KPS <90, age >57, recipient/donor CMV serostatus (+/-), and ASXL1 mutation, whereas 2 points were assigned to JAK2/triple negative and MMUD. Four risk groups constructed the MTSS: low (score 0-2), intermediate (score 3-4), high (score 5-6), and very high (score 7-9). The 5-year OS according to risk groups was 88%, 71%, 50%, and 20% (Figure 1). The hazard for death (with low-risk as reference) was 2.36 for intermediate-risk, 4.65 for high-risk, and 9.72 for very high-risk. The score was predictive of OS overall as well as for PMF and SMF (p<0.001, respectively). The MTSS showed overall C statistics of 0.718 (0.707-0.730) after cross-validation yielding a median of 0.727 in PMF and 0.708 in SMF indicating improved performance and replicability vs. DIPSS (0.572), MIPSS (0.577), and MYSEC-PM (0.601). The system was also predictive of OS in different conditioning settings (reduced intensity and myeloablative) and in patients with ruxolitinib pretreatment (p<0.001, respectively). Conclusions The new MTSS includes modern disease- and transplant-associated risk variables pertinent to both PMF and SMF. This proposed system consistently predicts outcome facilitating posttransplant decision-making and can be applied to different conditioning settings and to patients receiving ruxolitinib pretreatment. Figure 1. Figure 1. Disclosures Beelen: Medac: Consultancy, Other: Travel Support. Kroeger:Novartis: Honoraria, Research Funding; Riemser: Honoraria, Research Funding; Neovii: Honoraria, Research Funding; Sanofi: Honoraria; JAZZ: Honoraria; Celgene: Honoraria, Research Funding.

The Utility Of Newer Risk Models In Predicting Outcomes Of Patients (pts) With Higher-Risk (HR) Myelodysplastic Syndromes (MDS) Treated With Azactidine (aza)

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2771-2771
Author(s):  
Amer M. Zeidan ◽  
Najla H Al Ali ◽  
Mohamed A. Kharfan-Dabaja ◽  
Eric Padron ◽  
Ling Zhang ◽  
...  
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Research Funding ◽  
Goodness Of Fit ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Information Criteria ◽  
Prognostic Groups ◽  
Very High

Abstract Background While aza is the only drug shown to prolong survival in MDS, only half of aza-treated pts achieve objective responses (10-20% complete remission), and 4-6 months might be needed before a response is seen. Therefore the ability to select pts with high and low likelihoods of benefit from aza therapy is a clinical and a research priority. No clinical or laboratory parameter consistently predicts response or survival with aza therapy. A French prognostic scoring system (FPSS) was proposed to predict survival among aza-treated pts with HR-MDS. We sought to compare the relative prognostic discriminatory power of the FPSS with that of the revised IPSS (IPSS-R) and the global MD Anderson prognostic scoring system (MDAPSS) in a large cohort of aza-treated pts with IPSS HR-MDS. Methods The MDS database at Moffitt Cancer Center (MCC) was used to identify patients with HR-MDS (International Prognostic Scoring System [IPSS] intermediate-2 [INT-2] and high-risk) who received aza therapy. Kaplan-Meier curves were used to depict survivals, and the log-rank test was used to compare median overall survival (OS). Akaike information criteria (AIC) were used to assess the relative goodness of fit of the models. Results We identified 259 patients HR-MDS (74.1% with INT-2 and 25.9% with high IPSS) treated with aza at the MCC. The median duration of follow up since diagnosis was 53 months (M) (95% confidence interval [CI], 49-59 M). The median number of aza cycles was 5 (range 1-72), with 75% of pts receiving 4 cycles of therapy or more. The median time from diagnosis to aza initiation was 1.5 M. The median OS for the entire cohort was 19 M (95%CI, 16-22 M), 64% of pts were males, 91% were white, 80% were older than 60 years, and 25% had therapy-related MDS. For the IPSS, the median OS was 23.5 M (CI, 18.4-28.6 M) for INT-2 and 15.9 M (CI, 13.6-18.2 M) for high-risk group (P=0.004). For the FPSS, the median OS was 29.5 M (CI, 14.1-44.9 M) for low risk (LR), 21.1 M (CI, 16.4-26.0 M) for intermediate risk (IR), and 14.1 M (CI, 8.7-19.5 M) for HR (P=0.001). For the MDAPSS the median OS was not reached (NR) for low, 53.5 M (CI, 37.5-69.4 M) for INT-1, 29.5 M (CI, 18.3-40.6 M) for INT-2, and 16.1 M (CI, 14.5-17.7 M) for high risk groups (P<0.0001). For the IPSS-R, the median OS 40.6 M (CI, 22.8-58.4 M) for low, 44.7 M (CI, 25.0-64.4 M) for INT, 23.5 M (CI, 20.3-26.8 M) for high, and 15.2 M (CI, 13.7-16.8 M) for very-high risk groups (P<0.0001). Scores generated using AIC to assess the relative goodness of fit (lower is better) were 1453 (IPSS-R), 1480 (MDAPSS), 1512 (FPSS), and 1522 (IPSS). The IPSS could not refine any of the other models. All three newer models refined IPSS INT-2 but not IPSS high-risk. The IPSS did not refine any of the newer models. The MDAPSS refined the FPSS LR and IR and the IPSS-R high and very-high groups. The FPSS refined IPSS-R very high risk group but not the not the MDAPSS. The R-IPSS did not refine the MDAPSS or the FPSS. Response rates were not statically significantly different within the prognostic groups in any of the scoring systems. Conclusions The IPSS-R, MDAPSS, and the FPSS all functioned well to separate aza-treated pts with IPSS HR-MDS into prognostic groups with different survivals, but the IPSS-R and MDAPSS appear superior to the FPSS. None of the prognostic systems predicted response to aza therapy. HR-MDS patients with poor projected survival with aza therapy might be considered for experimental approaches. Disclosures: Off Label Use: entinostat for MDS. Lancet:Celgene: Research Funding. List:Celgene: Research Funding. Komrokji:Celgene: Research Funding, Speakers Bureau.

MD Anderson Scoring System (MDACC) Predicts Outcomes After Hematopoietic Stem Cell Transplantation (HSCT) Better Than Other Prognostic Classifications In MDS

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3340-3340
Author(s):  
Piyanuch Kongtim ◽  
Uday R Popat ◽  
Marcos de Lima ◽  
Guillermo Garcia-Manero ◽  
Elias J. Jabbour ◽  
...  
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Risk Group ◽  
Univariate Analysis ◽  
Scoring Systems ◽  
Risk Groups ◽  
High Risk Group ◽  
Risk Scores ◽  
Hematopoietic Stem ◽  
Very High

Abstract MDS is a heterogeneous group of hematopoietic stem cell disorders. Various prognostic models have been established to categorize patients with MDS including the International Prognostic Scoring System (IPSS), the Revised-IPSS (r-IPSS) and MDACC Scoring System. In this analysis, we compared those three classification schemas for their outcome predictability after HSCT. We analyzed 291 MDS patients with a median age of 55 (interquartile range (IQR) 47-60.7 years) who underwent HSCT between January 2001 and December 2011. Histology by WHO classification included RA/RARS 48 (16.5%), RCMD 28 (9.6%), RAEB-1 59 (20.2%), RAEB-2 63 (21.7%), MDS unclassified 67 (23%), and CMML 26 (9%). Of 291, 117 patients (40.2%) had therapy related MDS (t-MDS). Conditioning regimen was myeloablative in 201 patients (69.1%) and reduced intensity in 90 patients (30.9%). Donors were matched related (MRD), matched unrelated (MUD), mismatched (MMD) in 131 (45%), 114 (39.2%) and 46 (15.8%) patients respectively. Risk categorization was performed by IPSS, r-IPSS and MDACC scoring systems at the time of diagnosis. IPSS, r-IPSS and MDACC scoring systems could be assessed in 239 (82.1%), 241 (82.8%) and 231 (79.4%) patients respectively. The median follow up time of 109 survivors was 45 months. The median time from diagnosis to HSCT was 7.3 months (IQR 4.6-12.4 months). Three-year overall survival (OS) was 38.1% (95%CI 32.3-43.9) with 3-year event free survival (EFS) of 34.2% (95%CI 28.4-40). Cumulative relapse incidence (RI) at 3-year was 28.8% (95%CI 23.3-34.5). Cumulative incidence of treatment related mortality (TRM) at 3 year post-transplant was 27.9% (95%CI 22.6-33.6). In univariate analysis, IPSS and r-IPSS were able to differentiate 2 risk groups for OS and EFS. High risk group per IPSS and very high risk group per r-IPSS had lower OS with hazard ratio (HR) of 2.4 to 3.1, lower EFS with HR of 2.2 to 2.7. While IPSS could not predict RI, very high risk group by r-IPSS had higher RI with HR of 3.6 compared with lower risk groups. Both IPSS and r-IPSS did not identify different risk groups for TRM. On the other hand, MDACC scoring system was able to identify 4 different risk groups for EFS and OS in univariate analysis. Three-year OS was 68%, 46.1%, 30.3% and 11.4% for patients with MDACC risk score of 0-4, 5-6, 7-8 and ≥9 respectively (p<0.001) (figure1). Three-year EFS with MDACC risk score of 0-4, 5-6, 7-8 and ≥9 was 61.7%, 40.8%, 28.1% and 7.4% respectively (p<0.001). For RI and TRM, only MDACC risk scores of ≥9 was associated with poor outcomes with 3-year RI of 38.9% and 3-year TRM of 41.7% compared with 13.3% and 15.5% in risk scores of 0-4 (p=0.01 and p=0.01 respectively). In multivariate analysis, MDACC score, matched unrelated and mismatched donors were associated with inferior OS (table1). As a summary, MDACC risk scoring system for MDS better differentiates prognostic groups than IPSS or r-IPSS. Considering the high frequency of t-MDS among transplanted MDS patients, we propose that MDACC scoring system should be used for prognostic classification for hematopoietic transplantation. Disclosures: No relevant conflicts of interest to declare.

scholarly journals A Laboratory Based Scoring System Predicts Early Treatment in Rai 0/Binet a CLL

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4399-4399
Author(s):  
Jared A Cohen ◽  
Francesca Maria Rossi ◽  
Riccardo Bomben ◽  
Lodovico Terzi-di-Bergamo ◽  
Pietro Bulian ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Scoring System ◽  
Research Funding ◽  
Early Stage ◽  
Recursive Partitioning ◽  
Risk Groups ◽  
Advisory Committees ◽  
Early Stage Disease ◽  
Training Cohort

Abstract Introduction: Observation is the standard of care for asymptomatic early stage chronic lymphocytic leukemia (CLL) however these cases follow a heterogenous course. Recent studies show novel biomarkers can delineate indolent from aggressive early stage disease and current clinical trials are exploring the role of early intervention in high risk cases. Although several scoring systems have been established in CLL, most are designed for overall survival, do not circumscribe early stage disease, and require cumbersome calculations relying on extensive laboratory and clinical information. Aim: We propose a novel laboratory-based prognostic calculator to risk stratify time to first treatment (TTFT) in early stage CLL and guide candidate selection for early intervention. Methods: We included 1574 cases of early stage CLL in an international cohort from Italy, the United Kingdom and the United States using a training-validation model. Patient information was obtained from participating centers in accordance with the Declaration of Helsinki. The training cohort included 478 Rai 0 cases from a multicenter Italian cohort, all referred to a single center (Clinical and Experimental Onco-Hematology Unit of the Centro Riferimento Oncologico in Aviano, IT) for immunocytogenetic lab analyses. Considering TTFT as an endpoint, we evaluated 8 variables (age>65, WBC>32K, 17p-, 11q-, +12, IGHV status, CD49d+, gender) with univariate and multivariate Cox regression internally validated using bootstrapping procedures. FISH thresholds were 5% for 11q-, and +12 and 10% for 17p-. Cases were categorized according to the hierarchical model proposed by Dohner. IGHV status was considered unmutated at ≥98%. CD49d+ was set at >30%. WBC cutoff of >32K was established by maximally selected log rank analysis. Variables were weighted based on the proportion of their normalized hazard ratios rounded to the nearest whole integer. We used recursive partitioning for risk-category determination and Kaplan-Meier analysis to generate survival curves. We compared the concordance index (C-index) of our model with the CLL international prognostic index (CLL-IPI) for 381/478 cases in the training cohort with available beta-2-microglobulin data and for all validation cohorts. We used 3 independent single-center cohorts for external validation. Results: The training cohort had 478 cases of Rai 0 CLL with a median (95% CI) TTFT of 124 months (m) (104-183m). Five prognostic variables emerged with respect to TTFT, and each assigned a point value of 1 or 2 according to their respective normalized HR values as follows: 17p-, and UM IGHV (2 pts); 11q-, +12, and WBC>32K (1 pt). We identified three risk groups, based on point cut-offs of 0, 1-2, and 3-5 established by recursive partitioning analysis with a median (95% CI) TTFT of 216m (216-216m), 104m (93-140m) and 58m (44-68m) (p<0.0001, C-index 0.75) for the low, intermediate, and high-risk groups, respectively (figure 1). A comparison with the CLL-IPI was possible in 381 cases with available beta-2-microglobulin data. In this subset, the C-index was 0.75 compared to 0.68 when patient risk groups were split according to the CLL-IPI. The scoring system was then validated in 3 independent cohorts of early stage CLL: i) Gemelli Hospital in Rome, IT provided 144 Rai 0 cases. Median (95% CI) TTFT was 86m (80-94m, 95% CI). Median (95% CI) TTFT for the low, intermediate and high-risk groups was 239m (239-239m), 98m (92-132m) and 85m (60-109m) respectively (p=0.002 between low and intermediate groups, p=0.09 between intermediate and high groups; C-index 0.64 v 0.60 for CLL-IPI). ii) Cardiff University Hospital in Wales, UK provided 395 Binet A cases. Median (95% CI) TTFT was 74 m (67-81m) overall and NR, 111m (97-146m) and 70m (29-114m) for the low, intermediate and high-risk groups respectively (p<0.001 between low and intermediate groups, p=0.009 between intermediate and high groups; C-index 0.63 v 0.63 for CLL-IPI). iii) Mayo Clinic in Rochester, MN provided 557 Rai 0 cases. Median (95% CI) TTFT was 127m (96m-NR) overall and NR, 76m (64m-NR) and 36m (31-59m) for the low, intermediate and high-risk groups respectively (p<0.0001; C-index 0.72 v 0.68 for CLL-IPI). Conclusion: We present a novel laboratory-based scoring system for Rai 0/Binet A CLL to aid case selection in risk-adapted treatment for early disease. Further comparison to existing indices is needed to verify its utility in the clinical setting. Disclosures Zaja: Novartis: Honoraria, Research Funding; Takeda: Honoraria; Abbvie: Honoraria; Celgene: Honoraria, Research Funding; Amgen: Honoraria; Janssen: Honoraria; Sandoz: Honoraria. Fegan:Roche: Honoraria; Napp: Honoraria; Janssen: Honoraria; Gilead Sciences, Inc.: Honoraria; Abbvie: Honoraria. Pepper:Cardiff University: Patents & Royalties: Telomere measurement patents. Parikh:AstraZeneca: Honoraria, Research Funding; Janssen: Research Funding; MorphoSys: Research Funding; Abbvie: Honoraria, Research Funding; Gilead: Honoraria; Pharmacyclics: Honoraria, Research Funding. Kay:Janssen: Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees.

scholarly journals Estimated Glomerular Filtration Rate Is an Independent Predictor of Outcome in High-Risk Myelodysplastic Syndrome (MDS) and Low Blast Count Acute Myeloid Leukaemia (AML) Patients Treated with Azacytidine (AZA). a Retrospective Study from the MDS Registry of the Hellenic MDS Study Group

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 5423-5423
Author(s):  
Sotirios Papageorgiou ◽  
Vasileios Papadopoulos ◽  
Papoutselis Menelaos ◽  
Anthi Bouhla ◽  
Argiris Symeonidis ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Cox Regression ◽  
Performance Status ◽  
Univariate Analysis ◽  
Advisory Committees ◽  
Landmark Analysis ◽  
Kaplan Meier ◽  
Blast Count

Introduction. Myelodysplastic Syndrome (MDS) is a disease of the elderly. Apart from IPSS, IPSS-R and WPSS, several indexes incorporating patient comorbidities (such as the MDS CI index- Della Porta et al Haematologica 2011, the HCT-CI index - Sorror et al Blood 2005) and performance status (the GFM index- Itzykson et al Blood 2011) have been used to predict outcome in MDS patients treated with azacytidine (AZA). We sought to investigate the effect of comorbidities on the outcome after AZA in a large group of patients from the MDS registry of the Hellenic MDS Study Group. Methods. The present study has been conducted as a retrospective observational cohort one. It included high-risk MDS and low blast count AML patients treated with AZA from 26 centers in Greece from 2007 to 2018. T-test and ANOVA were used to compare scale variables between two or more groups respectively. Univariate analysis of nominal and scale survival data was performed using Kaplan-Meier survival curves and Cox regression respectively. All variables achieving p<0.05 at univariate analysis were considered eligible for multivariate analysis; the latter was based on Cox regression method. Results. We analyzed 536 consecutive patients. Patient characteristics are depicted in Table 1. The median follow-up period was 27.5±4.8 months. 371 patients received at least four cycles of AZA and 165 patients received less than 4 cycles of AZA. Patients who received ≥4 cycles of AZA did not differ from those who received <4 cycles regarding gender, age, estimated Glomerular Filtration Rate (eGFR), cardiovascular, renal, and tumor comorbidities. Significantly higher IPSS-R and GFM scores at baseline were found in the group of patients receiving < 4 cycles of AZA compared to patients who received ≥ 4 cycles of AZA (p=0.042 and 0.05 respectively), while transfusion dependence at baseline occurred more often in patients who received ≥ 4 cycles of AZA (p=0.039). To assess the prognostic significance of risk factors on leukemia free survival (LFS) and overall survival (OS), univariate and multivariate analysis for the whole population was performed, as well as a landmark analysis for patients who were treated with at least 4 cycles of AZA. ECOG performance status and the presence of peripheral blasts were independent prognostic factors for LFS and OS for the whole cohort analysis while response to AZA and the presence of peripheral blasts were independent prognosticators for LFS and OS in the landmark analysis. In addition, prior low dose cytarabine was an independent adverse prognostic factor for LFS in the landmark analysis. As regards comorbidities, neither of MDS-CI, HCT-CI and GFM systems independently predicted LFS or OS in either analysis, but eGFR with a cut-off of 45 ml/min was a strong and independent prognosticator for LFS and OS in both the standard and the landmark analysis. Kaplan-Meier survival curves regarding LFS and OS at AZA initiation and landmark analysis after 4th cycle of AZA in relation with eGFR are shown in Figure 1. Conclusion. This is the first study to demonstrate the importance of eGFR at baseline as a prognostic marker for LFS and OS in high-risk MDS and low-blast AML patients treated with AZA. The role of comorbidities and PS needs to be further evaluated in this patient group. Disclosures Symeonidis: Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Tekeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Vassilakopoulos:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; WinMedica: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene / GenesisPharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Panayiotidis:Bayer: Other: Support of clinical trial. Pappa:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Research Funding; Gilead: Honoraria, Research Funding; Novartis: Honoraria, Research Funding, Speakers Bureau; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene / GenesisPharma: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kotsianidis:Celgene: Research Funding.

scholarly journals Outcome of Patients Younger Than 50 Years Old Diagnosed with Myelodysplastic Syndromes (MDS): Single Institution Experience

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5541-5541
Author(s):  
Aref Al-Kali ◽  
Rong He ◽  
Mrinal M Patnaik ◽  
David S Viswanatha ◽  
Patricia T. Greipp ◽  
...  
Keyword(s):  
High Risk ◽  
Myelodysplastic Syndromes ◽  
Older Patients ◽  
Research Funding ◽  
Multivariate Analyses ◽  
Statistical Significance ◽  
Young Patients ◽  
Risk Groups ◽  
World Health ◽  
Very High

Abstract Background: Myelodysplastic syndromes (MDS) are rare hematological neoplasms that are more typically seen in elderly patients. Young patients (< 50 years old) have been reported to comprise between 3-6% in the Surveillance, Epidemiology and End Results (SEER) (Ma X et al, Cancer 2007; Rollison R et al, Blood 2008) with a better overall survival (OS). We hereby report the characteristics of young MDS patients with long survival follow-up. Methods: A total of 1012 MDS patients' data from Oct 1993 to Dec 2015 at Mayo Clinic were reviewed after appropriate IRB approval was obtained. All cases had their bone marrow slides reviewed at our institution. Patients youngers than 50 years old (yMDS) were included as cohort 1, while the rest was included as control group (cohort 2). Prognostic factors were analyzed by univariate and multivariate analyses. Survival estimates were calculated using Kaplan-Meier curves and univariate and multivariate analyses was based on log-rank testing using JMP software version 10. Results: Characteristics: We identified 68 (7%) yMDS patients with a median age of 42 years (range, 18-49). Female gender was more common in yMDS (43% vs 31%, p= 0.05). Upon comparison between cohort 1 and 2, only platelets were significantly lower in yMDS (61 vs 102, p <0.0001), but not white blood cells, hemoglobin or degree of marrow fibrosis. MDS subtyping according to World Health Organization 2016 showed single lineage dysplasia in 15% vs 2%, multilineage dysplasia 24% vs 36% , ring sideroblasts 9% vs 15%, isolated del (5q) 1% vs 3%, excess blasts 44% vs 31%, and unclassifiable in 6% vs 5%. As expected, therapy related MDS (t-MDS) was more frequent in yMDS (33% vs 17%, p= 0.005). Transformation to acute myeloid leukemia (AML) was also more frequent in yMDS (28 % vs 11%, p= 0.0004). Compared to cohort 2, yMDS IPSS-R scores were very high, high, intermediate, low, and very low in 24% vs 13%, 29% vs 16%, 21% vs 20%, 19% vs 35%, and 7% vs 17%, respectively. Allogenic hematopoietic cell transplantation (HCT) was more frequent in yMDS (42% vs 4%, p< 0.0001). Survival outcome: Median OS was longer for cohort 1 vs cohort 2 but did not reach statistical significance (43 vs 21 months, p= 0.1). Median progression free survival (PFS) was shorter for cohort 1 vs cohort 2 but did not reach statistical significance (8 vs 12 months, p= 0.3). Median OS for cohort 1 based on R-IPSS was 44, 105, 40, 18, and 12 months for very low, low, intermediate, high and high risk groups, respectively (p= 0.09). Median OS was shorter in t-MDS vs de novo MDS in cohort 1 (13 vs 47 months, p = 0.04). Young patients who had transformed to AML had a worse median OS (18 vs 93 months, p=0.001). On multivariate analysis neither t-MDS nor R-IPSS had a statistically significant impact on OS. Conclusions: MDS is rarely diagnosed under the age of 50. IPSS-R was less powerful in detecting differences between its risk groups for this patient population, although more than half of the patients with yMDS had either high or very high risk. Among this cohort of yMDS patients, there was a significantly higher proportion with therapy-related myeloid neoplasms compared to older patients (one third of patients), with subsequent higher rates of transformation to AML and higher allogeneic HCT. In our study, we did not find an improved OS for yMDS patients compared to older patients. Disclosures Al-Kali: Celgene: Research Funding; Onconova Therapeutics, Inc.: Research Funding.

Immunological nomograms predicting prognosis and guiding adjuvant chemotherapy in stage II colorectal cancer.

2019 ◽  
Vol 37 (4_suppl) ◽  
pp. 499-499
Author(s):  
Junjie Peng ◽  
Yaqi Li ◽  
Yang Feng
Keyword(s):  
Colorectal Cancer ◽  
High Risk ◽  
Adjuvant Chemotherapy ◽  
Cox Regression ◽  
Univariate Analysis ◽  
Tumor Infiltrating Lymphocytes ◽  
Risk Groups ◽  
High Risk Group ◽  
Stage Ii ◽  
Stage Ii Colorectal Cancer

499 Background: The type, abundance, and location of tumor-infiltrating lymphocytes (TILs) have been associated with prognosis in colorectal cancer. The objective of this study was to assess the prognostic role of TILs and develop a nomogram for accurate prognostication of stage II colorectal cancer. Methods: Immunohistochemistry was conducted to assess the densities of intraepithelial and stromal CD3+, CD8+, CD45RO+ and FOXP3+ TILs, and to estimate PD-L1 expression in tumor cells for 168 patients with stage II colorectal cancer. The prognostic roles of these features were evaluated using COX regression model, and nomograms were established to stratify patients into low and high-risk groups and compare the benefit from adjuvant chemotherapy. Results: In univariate analysis, patients with high intraepithelial or stromal CD3+, CD8+, CD45RO+ and FOXP3+ TILs were associated significantly with better relapse-free survival (RFS) and overall survival (OS), except for stromal CD45RO+ TILs, whereas PD-L1 expression wasn't associated with RFS or OS. In multivariate analysis, patients with high intraepithelial CD3+ and stromal FOXP3+ TILs were associated with better RFS (p < 0.001 and p = 0.032, respectively), while only stromal FOXP3+ TILs was an independent prognostic factor for OS (p = 0.031). The nomograms were well calibrated and showed a c-index of 0.751 and 0.757 for RFS and OS, respectively. After stratifying into low and high-risk groups, the high-risk group exhibited a better OS from adjuvant chemotherapy (3-year OS of 81.9% v 34.3%, p = 0.006). Conclusions: These results may help improve the prognostication of stage II colorectal cancer and identify a high-risk subset of patients who appeared to benefit from adjuvant chemotherapy.

Varying Importance of Prognostic Factors in Subgroups of Myelodysplastic Syndromes Defined by Blast Count, Cytogenetic Risk Group, or WHO Classification.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2776-2776
Author(s):  
Andrea Kuendgen ◽  
Corinna Strupp ◽  
Kathrin Nachtkamp ◽  
Barbara Hildebrandt ◽  
Rainer Haas ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
High Risk ◽  
Research Funding ◽  
Risk Group ◽  
Univariate Analysis ◽  
Risk Groups ◽  
High Risk Group ◽  
Intermediate Risk ◽  
Blast Count

Abstract Abstract 2776 Poster Board II-752 Introduction: We wondered whether prognostic factors have similar relevance in different subpopulations of MDS patients. Methods: Our analysis was based on patients with primary, untreated MDS, including 181 RA, 169 RARS, 649 RCMD, 322 RSCMD, 79 5q-syndromes, 290 RAEB I, 324 RAEB II, 266 CMML I, 64 CMML II, and 209 RAEB-T. The impact of prognostic variables in univariate analysis was compared in subpopulations of patients defined by medullary blast count, namely <5%, ≥5% (table), ≥10%, and ≥20% (not shown), as well as 3 subpopulations defined by the cytogenetic risk groups according to IPSS (table). Multivariate analysis of prognostic factors was performed for cytogenetically defined subgroups and WHO-subtypes. Results: Strong prognostic factors in all blast-defined subgroups were hemoglobin, transfusion dependency, increased WBC, age, and LDH. However, all variables became less important in patients with ≥20% blasts (RAEB-T) and increased WBC was rare. Platelet count and cytogenetic risk groups were relevant in patients with <5%, ≥5%, and ≥10% marrow blasts, but not in RAEB-T. Marrow fibrosis was important in patients with <5% or ≥5% blasts, but not ≥10%. Gender and ANC <1000/μl were significant only in patients with a normal blast count. Furthermore, we looked for the effect of the karyotypes, relevant for IPSS scoring (-Y, del5q, del20q, others, del7q/-7, complex), and found a comparable influence on survival, irrespective whether patients had < or ≥5% marrow blasts. In subpopulations defined by cytogenetic risk groups, several prognostic factors were highly significant in univariate analysis, if patients had a good risk karyotype. These included hemoglobin, sex, age, LDH, increased WBC, transfusion need, and blast count (cut-offs 5%, 10%, and 20%). In the intermediate risk group only LDH, platelets, WBC, and blasts were significant prognostic factors, while in the high risk group only platelets and blast count remained significant. Multivariate analysis was performed for the cytogenetic risk groups and for subgroups defined by WHO subtypes. The analysis considered blast count (</≥5%), hemoglobin, platelets, ANC, cytogenetic risk group, transfusion need, sex, and age. In the subgroup including RA, RARS, and 5q-syndrome, LDH, transfusion, and age in descending order were independent prognostic parameters. In the RCMD+RSCMD group, karyotype, age, transfusion, and platelets were relevant factors. In the RAEB I+II subgroup, the order was hemoglobin, karyotype, age, and platelets, while in CMML I+II only hemoglobin had independent influence. In RAEB-T none of the factors examined was of independent significance. Looking at cytogenetic risk groups, in the favorable group, several variables independently influenced survival, namely transfusion, blasts, age, sex, and LDH (in this order). Interestingly, in the intermediate and high risk group, only blast count and platelets retained a significant impact. Conclusion: Univariate analysis showed prognostic factors (except ANC) included in IPSS and WPSS are relevant in most subgroups defined by marrow blast percentage. However, they all lose their impact if the blast count exceeds 20%. Regarding cytogenetic risk groups, several prognostic factors lose their influence already in the intermediate risk group. This underscores the prognostic importance of MDS cytogenetics. Multivariate analysis showed MDS subpopulations defined by WHO types also differ with regard to prognostic factors. In particular, CMML and RAEB-T stand out against the other MDS types. Disclosures: Kuendgen: Celgene: Honoraria. Hildebrandt:Celgene: Research Funding. Gattermann:Novartis: Honoraria, Participation in Advisory Boards on deferasirox clinical trials. Germing:Novartis, Celgene: Honoraria, Research Funding.

scholarly journals WT1 mRNA Expression in the Peripheral Blood of Patients with MDS Yields Additional Prognostic Information within the IPSS-R Risk Categories "Very Low", "Low" and "Intermediate"

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1827-1827
Author(s):  
Christina Rautenberg ◽  
Sabrina Pechtel ◽  
Norbert Gattermann ◽  
Rainer Haas ◽  
Ulrich Germing ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Peripheral Blood ◽  
Research Funding ◽  
Risk Groups ◽  
Prognostic Information ◽  
Expression Status ◽  
Very High ◽  
Risk Categories ◽  
Who 2008

Abstract Introduction: The revised version of the International Prognostic Scoring System, (IPSS-R), is an accepted standard for assessing the prognosis of patients with MDS. Its usefulness may be further improved by integrating molecular findings. However, such efforts are impeded by limited access to molecular diagnostics, lack of standardized methodology, and a relatively low frequency of individual gene mutations in MDS. The Wilms' Tumor-1 (WT1) gene is overexpressed on mRNA level in the peripheral blood (PB) in about 50% of patients with MDS. The aim of this analysis was to determine whether PB WT1 expression status yields additional prognostic information. Methods: For this purpose, PB WT1 mRNA expression was measured in 91 newly diagnosed patients with MDS (WHO: MDS del5q, n=7; RARS, n=1; RCUD, n=4; RCMD, n=37; RAEB-I, n=16; RAEB-II, n=23; MDS/MPN unclassifiable, n=3 / IPSS-R: very low risk, n=3; low risk, n=28; intermediate risk, n=27; high risk, n=13; very high risk, n=20), using the Ipsogen® WT1 ProfileQuant® Kit. This standardized, commercially available assay uses a validated cut-off level of 50 WT1 copies/104ABL copies for discrimination between normal and overexpression of WT1 in PB. MDS patients in our study cohort were stratified accordingly (normal WT1 expression with <50 WT1 copies versus overexpression with >50 WT1 copies). WT1 expression status was correlated with clinical parameters and outcome. Results: Overall, 53 MDS patients (58%) showed WT1 overexpression, which correlated significantly with WHO 2008 disease category and IPSS-R risk groups, as indicated by both the absolute WT1 levels (correlation with WHO 2008 type, p=0.0028, and IPSS-R, p=0.0075) and the frequency of WT1-overexpressing patients within the respective MDS subgroup (correlation with WHO 2008 type, p=0.0029, and IPSS-R, p=0.0027). Regarding the entire cohort, patients with elevated WT1 expression had a significantly lower progression-free survival (PFS) and overall survival (OS) compared to those with normal WT1 expression (p<0.0001 and p=0.0306). Furthermore, within the IPSS-R risk groups 'very low', 'low' and 'intermediate', PFS differed significantly between patients showing normal vs. elevated WT1 expression status (IPSS-R very low/low: median PFS 30.1 months vs. not reached, for WT1 high vs normal, respectively, p=0.0127; IPSS-R intermediate: median PFS 14.4 months vs. 59.5 months, for WT1 high vs. normal, respectively p=0.0240). These differences in PFS retained their prognostic significance in multivariate analysis after adjusting for IPSS-R (HR 0.306; 95% CI 0,156-0,598, p=0.001). However, they did not translate into a difference in overall survival, which was probably due to a relevant number of patients proceeding to allogeneic stem cell transplantation. Given the large proportion of patients displaying WT1 overexpression in the IPSS-R high and very high risk groups, it was not surprising that no significant prognostic subdivision by WT1 expression level was seen in these risk categories. Conclusion: Our results show that PB WT1 expression offers additional prognostic information in patients belonging to the IPSS-R risk groups 'very low', 'low' and 'intermediate'. Assessment of WT1 expression status at diagnosis is a relatively time and cost efficient method that can be performed without patient discomfort and may help to identify MDS IPSS-R low and intermediate patients at risk for early progression. Disclosures Rautenberg: Celgene: Honoraria. Germing:Janssen: Honoraria; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Kobbe:Roche: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Celgene: Honoraria, Other: Travel Support, Research Funding. Schroeder:Celgene: Consultancy, Honoraria, Research Funding.

Revised-IPSS (IPSS-R) Is a Powerful Tool to Evaluate the Outcome of MDS Patient Treated with Azacitidine (AZA): The Groupe Francophone Des Myelodysplasies (GFM) Experience

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 422-422 ◽  
Author(s):  
Lionel Ades ◽  
Mathilde Lamarque ◽  
Sophie Raynaud ◽  
Raphael Itzykson ◽  
Sylvain Thepot ◽  
...  
Keyword(s):  
Platelet Count ◽  
High Risk ◽  
Scoring System ◽  
Prognostic Value ◽  
Conflicts Of Interest ◽  
Performance Status ◽  
Risk Groups ◽  
Predictive Score ◽  
Prognostic Impact ◽  
Very High

Abstract Abstract 422 Background: The IPSS published in 1997, based on cytogenetics, marrow blast % and the number of cytopenias, has played a major role in prognosis assessment in MDS. A provisional revised IPSS had been presented in 2011, which in our experience brought limited additional prognostic value for outcome of AZA treatment (Lamarque, ASH 2011). A final IPSS-R has now been published (Greenberg, Blood 2012), using the same parameters but 5 rather than 3 cytogenetic subgroups (Schanz et al, JCO, 2011), new cut off values for cytopenias and bone marrow blast % and different weighing of parameters. It appears to refine IPSS prognostic value but, like the original IPSS, was established in pts who had received no disease modifying drugs. We assessed the prognostic value of IPSS-R in 264 higher risk MDS treated with AZA, a drug with a survival impact in those pts. Methods: Between Sept 2004 and Jan 2009, before drug approval in EU, we enrolled 282 IPSS high and int 2 (higher) risk MDS in a compassionate patient named program of AZA and established in this cohort a prognostic scoring system (“AZA predictive score” based on Performance status (PS), cytogenetics, presence of circulating blasts, and RBC transfusion dependency) (Itzykson, Blood, 2011). We took advantage of this cohort to evaluate the prognostic impact of IPSS-R in higher risk MDS treated with AZA. Results: Median age was 71 years. WHO diagnosis: 4% RA, RARS or RCMD, 20% RAEB-1, 54%RAEB-2, 22% RAEB-t/AML. Cytogenetics could be reclassified using IPSS-R cytogenetic groups (Shanz, JCO 2011) in 265 pts, in: 1% very good, 37% good, 18% int, 12% poor and 32% very poor. 18%, 48% and 34% pts had Hb<8g/dl, between 8 and 10 and >10 g/dl, respectively. 43%, 32% and 25% had baseline platelet count <50 G/l between 50–100 and >100 G/L, respectively. ANC was <0.8 G/l in 45% pts. Marrow blast % was <=2%, 3–5%, 5–10%, >10 % in 2%, 3%, 18% and 77% pts. Overall IPSS-R could be calculated in 259 patients and was low (1 pt), Intermediate (28 pts, 11%), high (87 pt, 34%) and very high (143 pt, 55% pts). The only pt in the low group was excluded from further analysis. Using the “classical” IPSS, high and Int-2 patients treated with AZA had significantly different Response (37% vs 49%, p=0.05) and OS (median 9.4 vs 16 mo, respectively, p=0.004). Using the IPSS-R, 46%, 47% and 39% responded (CR, PR, or Hematological improvement- HI) to AZA in the int, poor and very poor groups, respectively (p=0.463). Individual IPSS-R parameters, including IPSS-R cytogenetic classification (p= 0.646), Hb level (p= 0.948), platelet count (p=0.10), ANC (p= 0.465) and marrow blast % stratified according to R-IPSS (p=0.287) had no significant impact on AZA response. According to IPSS-R cytogenetic classification, median OS was 21.8 mo, 12.3 mo, 15.1 mo and 7.1 mo in the good, int, poor and very poor risk groups respectively (overall p <10−4). Finally, According to IPSS-R, median OS was 30.7 mo, 17.6 mo, and 10 mo in the Intermediate, High and Very High risk groups, respectively (p <10−4, figure 1). I. The 55% patients with very high risk according to IPSS-R could be further subdivided by our AZA scoring system (Itzykson et al, Blood, 2011) in 3%, 67% and 30% low, int or high risk with a significant different OS across those groups (median not reached (NR), 12.7 and 5.9 mo, p <10−4). Similarly, The 34% patients with high risk according to IPSS-R could be further subdivided by the same AZA scoring system in 6%, 80% and 14% low, int or high risk with a significant different OS across those groups (median NR, 17.3 and 6.1 mo, p <10−4). Conclusion: Contrary to the provisional IPSS-R presented in 2011, the final IPSS-R (Greenberg, Blood 2012) has strong prognostic value for survival in MDS pts treated with AZA.Its prognosic value can be further improved by specific scoring systems established for AZA treatment, like the one published by our group (Itzykson, Blood, 2011). Disclosures: No relevant conflicts of interest to declare.

A Novel Prognostic Model Based on Tumor Microenvironment Biology in Relapse Biopsies Predicts Post-Autologous Stem Cell Transplantation Outcomes in Classical Hodgkin Lymphoma

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1093-1093
Author(s):  
Fong Chun Chan ◽  
Anja Mottok ◽  
Alina S Gerrie ◽  
Maryse M Power ◽  
Kerry J Savage ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Research Funding ◽  
Prognostic Model ◽  
Cox Regression ◽  
Inverse Correlation ◽  
Risk Groups ◽  
Low Risk ◽  
Classical Hodgkin Lymphoma ◽  
First Line

Abstract Introduction: Disease progression remains a significant clinical burden in classical Hodgkin lymphoma (CHL) with 25-30% of patients relapsing after first-line treatment. The current standard of care for relapsed CHL is high dose chemotherapy followed by autologous stem cell transplantation (ASCT). This secondary therapy only cures approximately 50% of patients, with virtually no reliable biomarkers to identify the patients in which this salvage treatment regimen fails. The specific aim of this study was to establish the extent of changes in tumor microenvironment (TME) composition between matched primary and relapse samples, and to build and validate a prognostic model for post-ASCT outcomes using relapse samples. Materials & Methods:NanoString digital gene expression profiling was used to ascertain the gene expression of 784 genes of interest from 245 biopsies sampled from 174 CHL patients. This cohort included 90 patients with single biopsies performed at first diagnosis (primary), 13 patients with single biopsies taken at relapse, and 71 patients with paired biopsies taken at first diagnosis and at relapse. All patients received ABVD as first-line treatment, and 151 patients went on to receive ASCT. The 784 genes of interest were selected based on previously reported associations with outcome in CHL and/or components of the TME. Spearman statistics were used for pairwise correlations and log-rank tests were used to assess survival differences. Bootstrap aggregation with concordance statistics (C-stat) was used to calculate the post-ASCT prognostic properties and a two-sample t-test was used to compare primary and relapse samples. Penalized elastic-net multivariate cox regression was used for model construction. An independent, similarly treated, cohort of 31 relapse biopsies was used for model validation. Results: Comparative gene expression analysis revealed that 17 of the 71 patients (24%) exhibited poor correlations between their paired primary and relapse samples (r2 < 0.75) - indicative of significant differences in their TME compositions. Amongst these differences was a striking inverse correlation between macrophage and B-cell gene expression pattern changes (r2 = -0.809). We validated these findings by using CD20 and CD163 immunohistochemistry confirming this inverse correlation of relative changes in macrophage and B cell content in the TME (r2= -0.645). Patients who exhibited poor gene expression correlations had inferior post-ASCT failure-free survival (FFS) (3-year: 38.5%) compared to patients with high gene expression correlations (3-year: 77%; P = 0.005). A comparative C-stat analysis of prognostic properties between primary and relapse samples demonstrated that relapse samples contain superior prognostic features for prediction of post-ASCT outcomes (relapse C-stat 0.785 ± 0.073 vs. primary C-stat 0.594 ± 0.079, P < 0.001). To this end, we developed a gene expression prognostic model using penalized Cox regression that was based on gene expression measurements in relapse samples (RHL30). RHL30 was able to risk stratify patients according to post-ASCT outcomes in the training cohort (5-year post-ASCT FFS: 23.8% in high-risk vs. 77.5% in low-risk; 5-year post-ASCT overall survival [OS]: 30.9% in high-risk vs. 85.4% in low-risk). This was validated in an independent cohort of 31 patients with relapsed CHL with a 5-year post-ASCT FFS of 37.5% in the high-risk vs. 70.1% in the low-risk groups (P = 0.017) and 5-year post-ASCT OS of 37.5% in the high-risk vs. 71.6% in the low-risk groups (P = 0.006). Conclusions: The TME gene expression profile differs significantly between matched primary and relapse CHL samples in a subset of patients with relapsed CHL. Gene expression measurements derived from relapse samples contain superior predictive properties for response to ASCT. To this end, we have developed a novel clinically applicable prognostic model (RHL30), derived from relapse samples, that identifies patients who have a high likelihood to benefit from ASCT (low-risk), and conversely a subgroup of patients who may benefit from additional or alternative therapeutic approaches (high-risk). Disclosures Connors: Seattle Genetics: Research Funding; Bristol Myers Squib: Research Funding; Millennium Takeda: Research Funding; NanoString Technologies: Research Funding; F Hoffmann-La Roche: Research Funding. Scott:NanoString Technologies: Patents & Royalties: named inventor on a patent for molecular subtyping of DLBCL that has been licensed to NanoString Technologies.

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