Germline Genetic Variation of ASXL1 and BIM Predicts Response to Imatinib and Identifies a Subset of High Sokal Risk Patients with the Greatest Risk of Treatment Failure and Disease Progression

Abstract Background: Scoring systems at CML diagnosis, such as Sokal risk, provide important response prediction for imatinib (IM) treated patients (pts). Specific treatment policies have been suggested for high risk pts to optimize otherwise inferior outcomes. However, responses among pts with high risk are heterogeneous and new biomarkers are required to facilitate rational selection of optimal therapy. Biological factors, such as germline genetic variation, may play a role in therapy response dynamics. We aimed to identify predictive biomarkers of response to IM at CML diagnosis to aid selection of front line therapy for optimal treatment outcomes. Methods: Targeted amplicon sequencing using a custom Ion AmpliSeq panel and the Ion Proton was performed for 35 genes: 10 BCL2 family genes involved in TKI initiated apoptosis (including BIM, BAD and BCL2); 5 drug metabolism genes; and 20 genes implicated in hematologic malignancies (including ASXL1 and TET2). Genotypes were determined for 200 candidate single nucleotide variants (SNPs) for 528 front line IM and 83 front line NIL treated pts. For the IM pts, baseline variables were assessed for association with outcome: Sokal risk, age, gender, assigned IM dose (400, 600 or 800 mg); and genotype. Results: SNPs significantly associated with outcome in univariate analyses were assessed in multivariate models with the other baseline variables. The Sokal risk, ASXL1 rs4911231 and BIM rs686952 SNPs were independent predictors of 12 mo MMR, 48 mo MR4, MR4.5 and failure free survival (FFS, loss of any response, death, progression to AP/BC). For the ASXL1 SNP, the homozygous T genotype (155/508 evaluable pts, 30%), and for the BIM SNP, the A allele (249/507 evaluable pts, 49%) were associated with superior outcomes. We explored the additive effect of combining the genotypes of the ASXL1 and BIM SNPs on outcome. Three risk groups were readily identified (defined in Fig): Good (16% of evaluable pts), Average (46%) and Poor (37%). There were significant differences in the cumulative incidence of 3 mo EMR, 12 mo MMR, and 48 mo MR4, MR4.5 and FFS, as stratified by these SNP risk groups in IM treated pts (Table and Fig A). No significant association was found for progression to AP/BC or survival for any baseline variable. To examine the predictive power of SNP genotype within the high Sokal risk group, high risk pts were stratified by SNP genotype group. Significant differences were observed for EMR, MMR, MR4, MR4.5 and FFS (Table and Figure B), demonstrating the ability of the SNP genotype within high Sokal risk pts to predict response. Moreover, high Sokal risk pts harboring a poor risk SNP genotype had a significantly higher risk of progression to AP/BC vs high Sokal risk pts with an average/good risk genotype, 12% vs 2% (P =.03). The impact of SNP genotype risk on achieving 12 mo MMR was examined in the 83 pts treated with frontline NIL (median 24 mo follow up). In contrast to the significant difference observed for IM pts, there was no significant difference for NIL pts: 75% vs 73% vs 64% for good, average and poor risk, respectively, P =.34, suggesting the poor risk conferred by genotype may be abrogated by more potent TKI. Conclusion: Our data suggest inherent genetic variation contributes to the heterogeneity of response to IM. An intronic SNP in BIM, a key initiator of TKI induced apoptosis, and a synonymous SNP in ASXL1 exon 12, a region commonly mutated in hematologic cancers, were strong biomarkers of IM response. The mechanism by which these SNPs affect response awaits further clinical and experimental evaluation. Among pts with high Sokal risk, the genotype of these 2 SNPs delineated response and identified a good risk subgroup where more potent TKI may not be required for optimal outcomes. Assessment of genetic variation at diagnosis may contribute to a prognostic score that will allow for optimization of therapy. Disclosures Yeung: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel grant international meeting, Research Funding. Hughes:Bristol-Myers Squibb: Honoraria, Research Funding; ARIAD: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Branford:BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Ariad: Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Qiagen: Membership on an entity's Board of Directors or advisory committees.

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Somatic Mutations Improve Risk Classification By Cytogenetic Abnormalities in Patients with Myelodysplastic Syndrome after Hematopoietic Stem Cell Transplantation

Blood ◽

10.1182/blood-2019-125937 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 512-512

Author(s):

Fevzi F. Yalniz ◽

Rima M. Saliba ◽

Orhan K. Yucel ◽

Guillermo Garcia-Manero ◽

Jeremy Ramdial ◽

...

Keyword(s):

High Risk ◽

Disease Progression ◽

Board Of Directors ◽

Research Funding ◽

Risk Groups ◽

Advisory Committees ◽

Hematopoietic Stem ◽

Ras Pathway ◽

Cart Analysis ◽

Poor Risk

Background: Hematopoietic stem cell transplantation (HSCT) offers potentially curative therapy for patients with myelodysplastic syndrome (MDS) but disease progression after HSCT remains a major reason for failure after transplant. Identification of risk factors for progression of MDS after HSCT would allow to identify target population for early initiation of preventive treatments to improve outcomes. Methods: Patients with a diagnosis of MDS who received first HSCT between 2013 and 2018 with available pre-transplant genetic profile obtained from next generation sequencing of genes were included for the retrospective analysis. Cytogenetic findings were categorized by the revised International Prognostic Scoring System (R-IPSS). Primary outcome of interest was risk of disease progression. Classification and regression tree (CART) analysis was performed to evaluate independent predictors on multivariate analysis using standard methods. Results: Of 378 MDS patients transplanted within the study period, 225 were eligible to be included in this analyses. As shown in the table 1, the study cohort was high risk; cytogenetic risk groups were very-poor and poor in 50 (23%) and 32 (15%) patients, respectively. At least one pathogenic mutation was identified in 215 (91%) of patients prior to transplant. Most frequently mutated genes included, TP53 (24%, 54/225), RAS pathway genes (NRAS, KRAS, FLT3, PTPN11 and KIT) (20%, 44/225), TET2 (16%, 37/172), ASXL1 (12%, 27/172) and DNMT3A (11%, 25/200). In our cohort, patients with very-poor cytogenetics had a high frequency of TP53 mutations (73%), and TP53 mutations occurred almost exclusively in patients with very-poor cytogenetics (76% v 7%; P < .001). That makes those two groups almost inseparable from each other. The median follow-up in 121 (54%) survivors was 24 months (range, 1.8 to 74 months). Of the 225 patients, 65 (29%) had disease progression after HSCT, with a median of 154 days to progression (range, 28 to 1196). By univariate analyses, presence of TP53 (HR, 3.2; CI, 1.9-5.4; P<.001), DNMT3A (HR, 2.6; CI, 1.5-4.7; P=.001), RAS pathway mutations (HR, 2.01; CI, 1.2-3.4; P=.01), therapy related MDS (HR, 2.05; CI, 1.2-3.5; P=.008), very poor risk cytogenetics (HR, 3.4; CI, 1.9-6.3; P<.002), and use of post-transplant cyclophosphamide (PTCy) (HR, 0.5; CI, 0.3-0.96; P=.003) were significant predictors of progression rate. As previously mentioned, we used CART analysis to evaluate independent predictors of progression. The results demonstrated that given the significant overlap with TP53 and very poor cytogenetics, when both variables were forced into the model, only very poor cytogenetics remained significant for progression. Based on CART analysis, 4 mutually exclusive risk groups for progression were identified (Figure 1): high risk (very poor risk cytogenetics or DNMT3Amut), intermediate risk (good, intermediate or poor risk cytogenetics/RAS-pathmut/DNMT3Awt), low risk (poor risk cytogenetics/RAS-pathwt /DNMT3Awt) and a very low risk group (very good, good or intermediate risk cytogenetics/RAS-pathwt /DNMT3Awt). The correlation between R-IPSS based cytogenetic risk and our identified risk groups is shown in table 2. This illustrates how the addition of molecular data upstaged 25% of the patients to a higher risk category as well as downstaged 23% of the patients to a lower risk category for disease progression when compared to the original R-IPSS classification. The cumulative incidence of disease progression at 2 years was 6% (reference), 26% (P=.005), 42% (P<.001) and 56% (P<.001) in very-low, low, intermediate and high risk groups, respectively (Figure 2). Within the risk groups identified, progression incidence was comparable by conditioning intensity and the use of PTCy. The actuarial 2-year progression-free survival for the defined 4 risk groups was, 69% (reference), 48% (HR, 2; P=.04), 38% (HR, 2.2; P=.009), 22% (HR, 3.2; P<.001) and 14% (HR, 4.8; P<.001), in very-low, low, intermediate and high-risk groups, respectively. Non-relapse mortality was similar across the identified risk groups. Conclusion: The proposed model, by incorporating DNMT3A and RAS pathway molecular mutation status to cytogenetic risk per R-IPSS, improves upon the classification of risk groups and enables the physician to better risk stratify and predict likelihood of progression after transplantation. Disclosures Garcia-Manero: Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding. Popat:Bayer: Research Funding; Incyte: Research Funding; Jazz: Consultancy. Ciurea:Kiadis Pharma: Membership on an entity's Board of Directors or advisory committees, Other: stock holder; Spectrum: Membership on an entity's Board of Directors or advisory committees; Miltenyi: Research Funding; MolMed: Membership on an entity's Board of Directors or advisory committees. Kebriaei:Jazz: Consultancy; Pfizer: Honoraria; Kite: Honoraria; Amgen: Research Funding. Bashir:Imbrium: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Spectrum: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; StemLine: Research Funding; Acrotech: Research Funding; Celgene: Research Funding. Champlin:Actinium: Consultancy; Johnson and Johnson: Consultancy; Sanofi-Genzyme: Research Funding. Oran:Astex pharmaceuticals: Research Funding; AROG pharmaceuticals: Research Funding.

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Outcomes of Patients with Relapsed or Refractory Acute Myeloid Leukemia Receiving Hypomethylating Agent and Venetoclax

Blood ◽

10.1182/blood-2019-128958 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1357-1357 ◽

Cited By ~ 2

Author(s):

Hannah Asghari ◽

Dasom Lee ◽

Yehuda E. Deutsch ◽

Onyee Chan ◽

Najla Al Ali ◽

...

Keyword(s):

Board Of Directors ◽

Myeloid Leukemia ◽

Research Funding ◽

Risk Groups ◽

Initial Therapy ◽

Intermediate Risk ◽

Advisory Committees ◽

Significant Difference ◽

Frontline Therapy ◽

Refractory Aml

Background: Patients with acute myeloid leukemia (AML) have dismal overall outcomes and survival is exceptionally poor in patients who experience relapse or are refractory (R/R) to frontline therapy. Since December 2018, combination therapy with hypomethylating agents (HMA) and venetoclax (HMA+Ven) has become standard frontline therapy for older patients or younger unfit patients. Moreover, it has been routinely utilized in patients experiencing relapsed or refractory AML yet response and outcome data is limited in patients with R/R disease. Thus, we investigated outcomes after HMA+Ven in patients with relapsed or refractory AML. Methods: We retrospectively annotated 72 patients who received treatment with HMA+Ven at Moffitt Cancer Center and Memorial Healthcare System between 2017 and 2019. Patients were divided into two subgroups: 1) initial remission therapy and 2) salvage therapy. Clinical and molecular data were abstracted in accordance with the Institutional Review Board approved protocol. Overall response rate (ORR) included patients achieving complete remission (CR), CR with incomplete count recovery (CRi), and morphologic leukemia free state (MLFS). Patients achieving CR, CRi, or MLFS were termed as responders (RES) and patients without CR, CRi, or MLFS were nonresponders (NRES). Fisher's Exact method was used to determine significance for categorical variables. Kaplan-Meier analysis was performed to determine median overall survival (mOS) and log-rank test was utilized to determine significance. All p-values are two-sided. Results: Out of 72 patients, 41 received HMA+Ven as initial therapy and 31 received it in the R/R setting. Baseline characteristics are outlined in Table 1. Median age was 63 years for patients with R/R AML with 58% female. In the R/R cohort, ORR was 34.5% with 0 (0%) patients achieving CR, 8 (27.6%) patients achieving CRi, and 2 (6.9%) achieving MLFS (Table 2). When compared to patients receiving HMA+Ven as initial therapy, ORR was significantly lower in the R/R cohort (64.1% vs. 34.5%, p=0.03). Among 31 patients in the R/R cohort, 6.5% (n=2) proceeded to allogeneic stem cell transplant (allo-SCT) after achieving CRi. European LeukemiaNet (ELN) risk stratification was known in 22 patients in the R/R cohort and ORR were similar in patients in the favorable/intermediate risk group (n=8) compared to adverse risk group (n=14) (37.5% vs. 28.6%, p=1.0). When compared to HMA+Ven used as initial therapy, ORR among the R/R cohort were not different among adverse risk groups (58.3% vs. 28.6%, p=0.10); however, ORR were significantly lower among patients with favorable/intermediate risk (100% vs. 37.5%, p=0.009). At a median follow-up of 7.6 months (mo), mOS was 4.9mo in the R/R cohort with mOS among RES superior to NRES (not reached vs. 2.4mo, p=0.0009) (Figure 1). Moreover, mOS was inferior in R/R patients compared to initial therapy (4.9mo vs. 13.8mo, p=0.0013) (Figure 2). A total of 15 (48.4%) patients had HMA exposure prior to receiving HMA+Ven without apparent impact on mOS (3.7mo (prior HMA) vs. 4.9mo (no prior HMA), p=0.97). The median duration of CR/CRi was 5.2mo and the median time to CR/CRi was 2.4mo. Based on ELN risk groups, mOS was not statistically different among patients with favorable/intermediate risk disease compared to adverse risk disease (8.6mo (fav/int) vs. 2.8mo (adverse), p=0.07). Responses were also analyzed based upon somatic mutations (Figure 2). In patients with isocitrate dehydrogenase 1 and 2 mutations (IDH1/IDH2) compared to patients without IDH1/2, ORR were 60% vs. 25%, respectively (p=0.28) with no significant difference in mOS (7.2mo (IDHmut) vs. 3.1mo (IDHwt), p=0.38). Comparing patients with TP53 mutation to those without TP53 mutations, no significant difference in ORR (25% vs. 33%, p=1.0) or mOS (4.4mo vs. 6.9mo, p=0.0.84) was noted. Conclusion: Although combination therapy with HMA+Ven has yielded impressive responses as frontline therapy, response rates with this combination in the salvage setting are less encouraging with the possible exception of those patients with IDH1/IDH2 mutations. Nevertheless, responders to salvage HMA+Ven had a significant survival benefit compared to nonresponders, suggesting that this combination is a reasonable salvage option in patients with relapsed or refractory AML. Disclosures Padron: Incyte: Research Funding. Kuykendall:Incyte: Honoraria, Speakers Bureau; Celgene: Honoraria; Janssen: Consultancy; Abbvie: Honoraria. List:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Lancet:Agios, Biopath, Biosight, Boehringer Inglheim, Celator, Celgene, Janssen, Jazz Pharmaceuticals, Karyopharm, Novartis: Consultancy; Pfizer: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Other: fees for non-CME/CE services . Sallman:Celyad: Membership on an entity's Board of Directors or advisory committees. Komrokji:JAZZ: Speakers Bureau; JAZZ: Consultancy; Agios: Consultancy; DSI: Consultancy; pfizer: Consultancy; celgene: Consultancy; Novartis: Speakers Bureau; Incyte: Consultancy. Sweet:Abbvie: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Agios: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Celgene: Speakers Bureau; Jazz: Speakers Bureau; Incyte: Research Funding; Pfizer: Consultancy; Stemline: Consultancy. Talati:Jazz Pharmaceuticals: Honoraria, Speakers Bureau; Daiichi-Sankyo: Honoraria; Astellas: Honoraria, Speakers Bureau; Pfizer: Honoraria; Celgene: Honoraria; Agios: Honoraria. OffLabel Disclosure: Venetoclax is approved in combination with hypomethylating agents (azacitidine or decitabine) or low dose cytarabine for treatment of newly diagnosed AML in adults aged 75 years or older, or those who have comorbidities that preclude the use of induction chemotherapy.

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Proposal of a Novel Latin American International Prognostic Index (LATAM-IPI) for Diffuse Large B-Cell Lymphoma (DLBCL) By the Grupo Para El Estudio De Linfoproliferativos En Latino-America (GELL)

Blood ◽

10.1182/blood-2020-142836 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 25-27

Author(s):

Luis Villela Villela ◽

Ana Ramirez-Ibarguen ◽

Brady E Beltran ◽

Camila Peña ◽

Denisse A. Castro ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Scoring Systems ◽

Risk Groups ◽

Training Set ◽

Extranodal Involvement ◽

Advisory Committees ◽

Internal Validation ◽

Biological Variables

Introduction. There are different scoring systems to differentiate risk groups in patients with DLBCL treated with chemoimmunotherapy. Those systems have used the same 5 variables (age, performance status, LDH, stage, extranodal involvement) for 27 years. However, LATAM data have not been included in the development of previous scoring systems. It is important to mention that novel biological variables, such as albumin, beta-2-microglobulin (B2M) and platelet/lymphocyte ratio (PLR), have been reported and could improve discrimination (Villela et al. Blood 2019; 134Suppl_1: 1613). Therefore, we carried out a large, multinational study to develop and validate a LATAM-IPI score. Methods. This is a retrospective cohort of 1030 patients with a diagnosis of DLBCL treated with standard chemoimmunotherapy with curative intent between 2010 and 2018. Data were obtained from 8 LATAM countries: Argentina, Colombia, Chile, Guatemala, Mexico, Paraguay, Peru, and Venezuela. The five classic IPI variables (age, ECOG, extranodal involvement, LDH, stage) were analyzed and albumin and PLR were added (Villela et al. Blood 2019; 134Suppl_1: 1613). B2M was not included because it was not requested regularly in all countries. Development of LATAM-IPI: The training set consisted of 85% of the sample, randomly selected, and the remaining 15% was reserved for internal validation. Using the training set, the univariate and multivariate association between clinical prognostic factors and OS was analyzed fitting Cox proportional-hazard models. Outcomes. Clinical characteristics of the training (n=878) and internal validation (n=151) cohorts are shown in Table 1. There were no statistical differences in baseline characteristics between the cohorts. The median follow-up for the whole cohort was 36 months (IQR: 11-57). When exploring the classic IPI variables on the training set, all variables were associated with high risk of mortality [age 65-74, Hazard Ratio (HR) 1.24, 95% CI 0.96 to 1.58, p=0.08; age ≥75, HR 1.71, 95% CI 1.28 to 2.28, p=0.0003), ECOG (≥ 2, HR=2, 95% CI 1.61 to 2.53; p<0.0001), EN (≥2, HR=1.53, 95% CI 1.18 to 1.97; p=0.0012), stage (III/IV, HR=2.1, 95% CI 1.64 to 2.69; p<0.0001) and LDH (ratio 1.1-2.9, HR=1.55, 95% CI 1.22 to 1.97; p=0.0003; ratio ≥3, HR= 2.68, 95% CI 1.93 to 3.7, p<0.0001). Similarly, the biological variables Albumin (≤3.5 mg/dL, HR 2.37, 95% CI 1.9 to 2.95, p<0.0001) and PLR (≥273, HR= 1.52, 95% CI 1.23 to 1.87; p=0.0001) were associated with high risk of death. Next, these variables were evaluated by multivariate analysis. The independent variables were albumin (<3.5 mg/dL, HR 1.84, 95% CI 1.45 to 2.3, p<0.0001, 1 point), LDH (ratio 1.1 to 2.9, HR 1.30, 95% CI 1.02 to 1.67, p=0.03, 1 point; ratio ≥3, HR=1.84, 95% CI 1.31 to 2.5, p=0.0004, 2 points), advanced stage (HR 1.65, 95% CI 1.27 to 2.13, p=0.0001, 1 point), age (≥75, HR= 1.51, 95% CI 1.15 to 1.98, p=0.003, 1 point), and ECOG (≥2, HR 1.40, 95% CI 1.10 to 1.77, p=0.005). Now, for the development of LATAM-IPI, the groups were distributed as follows: 0 points, low; 1-3 points, intermediate; 4-6 points, high risk. There were no differences in the distribution of the risk groups between training and validation sets (Table 2). In the learning cohort, the 5-year OS rates for low, intermediate and high risk were 81%, 63% and 33%, respectively (p<0.0001). In the validation cohort, the 5-year OS rates for low, intermediate and high risk were 81%, 63% and 44%, respectively (p=0.02) (Figure 1). Conclusions: Using multinational learning and validation cohorts including over 1,000 DLBCL patients treated with standard chemoimmunotherapy in LATAM, we developed a novel LATAM-IPI score using age ≥75 years, ECOG ≥2, advanced stage, LDH ratio (1.1-29 and ≥3) and albumin <3.5 mg/dl. Next steps are to disseminate our results with other involved researchers in LATAM to prospectively assess and reproduce our results. We expect this score will help to further define the prognosis of DLBCL patients in LATAM. Disclosures Villela: amgen: Speakers Bureau; Roche: Other: advisory board, Speakers Bureau. Idrobo:Janssen: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Abbvie: Honoraria, Speakers Bureau; Tecnofarma: Honoraria, Speakers Bureau; Takeda: Honoraria, Speakers Bureau. Gomez-Almaguer:Amgen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Castillo:Janssen: Consultancy, Research Funding; TG Therapeutics: Research Funding; Kymera: Consultancy; Abbvie: Research Funding; Beigene: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding.

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

Blood ◽

10.1182/blood-2018-99-112162 ◽

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.

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Mutation Landscape and Prognostic Correlates of ASXL1 Variants in Primary and Secondary Myelofibrosis

Blood ◽

10.1182/blood-2021-148685 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 2578-2578

Author(s):

Giacomo Coltro ◽

Paola Guglielmelli ◽

Giada Rotunno ◽

Carmela Mannarelli ◽

Chiara Maccari ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Risk Group ◽

Risk Groups ◽

High Risk Group ◽

Prognostic Impact ◽

Driver Genes ◽

Advisory Committees ◽

Risk Of Death ◽

Significant Difference

Abstract Introduction: Myelofibrosis (MF), whether primary (PMF) or secondary (SMF) to polycythemia vera or essential thrombocytemia, is characterized by a complex and partially undeciphered molecular architecture. Besides mutations in driver genes (JAK2, CALR, MPL), somatic mutations in selected myeloid-associated genes have been shown to impact prognosis of MF patients (pts). Among these, ASXL1 mutations (ASXL1MTs) are associated with poor outcomes in myeloid malignancies including PMF, where they are included in the category of "high molecular risk" (HMR) mutations along with EZH2MTs, IDH1/2MTs, and SRSF2MTs (Vannucchi AM, Leukemia 2013). However, a recent study (Luque Paz D, Blood Adv 2021) questioned the value of ASXL1MTs in MF. The current study aimed at further characterizing the prognostic role of ASXL1MTs in MF. Methods: After IRB approval, pts with WHO-defined MF were included in the study. Mutational analysis by targeted NGS was performed as previously described (Guglielmelli P, JCO 2017). All deposited variants were manually curated to assess pathogenicity. In this study, we also used the molecular model proposed by Luque Paz et al. that identifies 4 genetic groups: TP53MT; High-risk (≥1 mutation in EZH2, CBL, U2AF1, SRSF2, IDH1/2); ASXL1MT-only; and "Others". Results: A total of 525 pts were included in the study, including 331 (63%) PMF and 194 (37%) SMF. Median age at diagnosis was 89 (18-90) years, 314 (60%) were male. The median follow-up time was 80 (98% CI, 68-90) months. Overall, 324 (62%) pts were JAK2MT, 126 (24%) CALRMT, 24 (5%) MPLMT, 40 (8%) triple negative (TN), and 11 (2%) double mutated. Among non-driver genes, ASXL1MTs were found in 158 (30%) pts, EZH2MTs in 45 (9%), SRSF2MTs in 37 (7%), NRASMTs in 30 (6%) U2AF1MTs in 27 (5%), TP53MTs and CBLMTs in 25 (5%) each, IDH1/2 MTs in 18 (3%), and KRAS MTs in 15 (3%). Pts in the HMR category were 125 (38%) in PMF and 63 (32%) in SMF. According to the above model, distribution of pts was as follows: TP53MT n=25 (5%), High-risk n=137 (26%), ASXL1MT-only n=64 (12%), and Others n=299 (57%). Pts in the TP53MT and ASXL1MT-only groups were more likely to be diagnosed with SMF compared to pts in the High-risk and Others groups (44% and 48% vs 28% and 38%, respectively). In addition, the High-risk group was enriched in TN pts (16%), while CALRMTs were more common in the ASXL1MT-only and Others compared to the TP53MT and High-risk groups (25% and 27% vs 12% and 18%, respectively). In univariate analysis, the TP53MT and High-risk groups were associated with the worst overall survival (OS), with median values of 38 (14-110) and 55 (45-85) months (P=.0039), respectively (Fig 1A). Albeit remarkably better, the OS of pts in the ASXL1MT-only group was inferior compared to pts in the Others group (median 124 [91-156] vs 193 [142-NR] months; P=.0118) (Fig 1A). We then analyzed separately PMF and SMF cohorts. In the former, the TP53MT and High-risk groups remained associated with the worst OS (median 58 [20-126] vs 55 [36-85] months), although with no significant difference, likely due to the low frequency (4%) of TP53MTs mutations in PMF (Fig 1B). Concurrently, the negative prognostic impact of the ASXL1MT-only group was confirmed in comparison to the Others group (median 103 [78-NR] vs 320 [178-NR] months; P=.0170). In pts with SMF, while the TP53MT group (6%) had by far the worst OS (median 13 [6-NR] months), the OS of the ASXL1MT-only group (median 141 [56-171] months) was comparable to that of the Others group (median 131 [106-NR] months; P=.5188) and not different from the High-risk group (median 58 [45-174] months; P=.3606) (Fig 1C). In a further analysis including only pts in the High-risk group, ASXL1MTs were found in 62% and 63% of patients with PMF and SMF, respectively. In survival analysis, the presence of ASXL1MTs was associated with an increased risk of death only in PMF (median OS 47 [31-73] vs 102 [34-317] months; P=.0240), unlike in SMF (median OS 90 [47-174] vs 25 [16-338] months; P=.3296) (Fig 1D-E). Conclusion: In the current study, we critically re-addressed the prognostic impact of ASXL1MTs by applying a genetic model recently developed by Luque Paz et al. to our cohort of molecularly annotated, WHO-defined MF pts. Overall, our results confirm that ASXL1MTs -even in the absence of other co-occurring high-risk mutations- harbor a negative prognostic impact mainly in PMF. These findings also reinforce the idea that PMF and SMF represent two different biological entities. Figure 1 Figure 1. Disclosures Vannucchi: Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees.

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Combining Information Regarding Chromosomal Aberrations t(4;14), Del(17p13) and the Copy Number of 1q21 with the International Staging System Classification Allows Stratification of Myeloma Patients Undergoing Autologous Stem Cell Transplantation: Results From the HOVON-65/GMMG HD4 Trial

Blood ◽

10.1182/blood.v118.21.332.332 ◽

2011 ◽

Vol 118 (21) ◽

pp. 332-332

Author(s):

Kai Neben ◽

Henk M. Lokhorst ◽

Anna Jauch ◽

Uta Bertsch ◽

Thomas Hielscher ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Prognostic Value ◽

Risk Group ◽

Staging System ◽

Risk Groups ◽

Low Risk ◽

Advisory Committees ◽

International Staging System

Abstract Abstract 332 PURPOSE : In Multiple Myeloma (MM), the combination of serum beta-2-microglobulin level with serum albumin concentration has been proposed as an outcome predictor in the International Staging System (ISS). More recently, subgroups of MM defined by genetic and cytogenetic abnormalities have been associated with unique biologic, clinical, and prognostic features. PATIENTS AND METHODS: We analyzed the prognostic value of 12 chromosomal abnormalities by fluorescent in situ hybridization (FISH) in a series of 354 MM patients treated within the HOVON-65/GMMG-HD4 trial. Patients with newly diagnosed MM were randomized to receive either three cycles of VAD (arm A; vincristine, adriamycin, dexamethasone) or PAD (arm B; bortezomib, adriamycin, dexamethasone). All patients underwent autologous stem cell transplantation (ASCT) followed by maintenance therapy with thalidomide 50 mg daily (arm A) or bortezomib 1.3 mg/m2 once every 2 weeks (arm B), respectively. In addition, a second cohort of patients was analyzed as a control group (n=462), undergoing ASCT at the University of Heidelberg between September 1994 and December 2010. RESULTS: For the entire group of patients treated within the HOVON-65/GMMG-HD4 trial, we identified 233 patients with 2 copies (67.7%), 95 patients with 3 copies (27.6%) and 16 patients (4.7%) with more than three copies of the chromosomal region 1q21. In addition to del(17p13) and t(4;14), we added +1q21 (>3 copies) to the group of high-risk aberrations, since the outcome of these patients was almost as poor as it was observed for patients with del(17p13). Subsequently, we analyzed whether combining the ISS score with information on the presence of high-risk aberrations could improve the prognostic value with regard to patients' outcome. A combination of the presence or absence of del(17p13), t(4;14), or +1q21 (>3 copies) with the ISS score allowed patients to be stratified into three distinct groups: low-risk [absence of del(17p13)/t(4;14)/+1q21 (>3 copies) and ISS I], high-risk [presence of del(17p13)/t(4;14)/+1q21 (>3 copies) and ISS II/III], and intermediate-risk (all remaining patients). Most of the patients belonged to the low- (33%) and intermediate-risk (49%) groups, whereas 18% were allocated to the high-risk group. The median PFS times for the low-, intermediate-, and high-risk groups were 41.9 months, 31.1 months (HR=1.7; p=0.0018) and 18.7 months (HR=3.6; p<0.0001), respectively. The 3yr-overall survival (OS) decreased from 94% in the low-risk group to 80% (HR=4.6; p=0.0001) and 43% (HR=12.8; p<0.0001) in the intermediate- and high-risk groups, respectively. These results were confirmed in the independent cohort of patients: From date of first ASCT, the median PFS times for the low-, intermediate-, and high-risk groups were 43.3 months, 23.0 months (HR=1.5; p=0.015) and 13.8 months (HR=2.4; p=0.0003), respectively. The 4yr-OS decreased from 84% in the low-risk group to 71% (HR=2.1; p=0.0043) and 49% (HR=3.84; p<0.0001) in the intermediate- and high-risk groups, respectively. CONCLUSION: In our series, the ISS/FISH-based score/algorithm predicted PFS and OS much better than the ISS alone. Our results with molecular cytogenetic techniques may already have implications for the risk-adapted clinical management of patients with MM particularly in younger patients. Disclosures: van de Velde: Ortho Biotech Oncology Research & Development: Employment. Sonneveld:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen-Cilag: Membership on an entity's Board of Directors or advisory committees, Research Funding; Onyx: Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: Membership on an entity's Board of Directors or advisory committees.

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Older Age As a Prognostic Factor for Overall Survival for Multiple Myeloma Patients Undergoing Upfront Autologous Hematopoietic Stem Cell Transplantation

Blood ◽

10.1182/blood-2018-99-114200 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 2144-2144

Author(s):

David M. Cordas Dos Santos ◽

Rima M. Saliba ◽

Romil Patel ◽

Qaiser Bashir ◽

Chitra Hosing ◽

...

Keyword(s):

Stem Cell ◽

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Older Age ◽

Stage Ii ◽

Advisory Committees ◽

Post Transplant ◽

Cart Analysis ◽

Significant Difference

Abstract Background High-dose chemotherapy and autologous hematopoietic stem cell transplantation (auto-HCT) is considered the standard of care for newly diagnosed, transplant-eligible multiple myeloma (MM) patients. Due to improvements in induction, stem cell mobilization, and dose adjustment of the conditioning regimen, auto-HCT is increasingly used in older MM patients, with several retrospective analyses showing similar clinical outcomes compared to younger patients. Methods To further confirm these results, we performed a single-center retrospective analysis of MM patients undergoing auto-HCT between January 2006 and December 2016. Patients were divided into two groups: older (> 70 years) and younger (≤ 70 years). Results 1128 patients (182 older, 946 younger) were included in this analysis. Patient characteristics are summarized in the attached Table. More patients (59% vs. 45%, p = 0.01) in the older cohort had ISS stage II or III disease. Older cohort was more likely to receive reduced-dose melphalan (140 mg/m²) as conditioning regimen (32% vs 3%, p = <0.0001). There was no significant difference in high-risk cytogenetics, induction regimens, and response to induction, or post-transplant maintenance between the older and younger cohorts. The overall median follow-up among survivors was 49 months in the older and 52 months in the younger group. One-hundred-day non-relapse mortality (NRM) was 2/182 (1.1%) and 6/946 (0.6%) (p = 0.5) in the older and younger groups, respectively. However, 1-year NRM was significantly higher in the older vs. younger cohort (7 /182 (4%; unknown 3, pneumonia or respiratory failure 4) vs. 9/946 (1%; unknown 2, pneumonia or respiratory failure 4, cardiac failure 3), HR 4.1, p = 0.005). Post-transplant, 75 (41%) and 431 (45%) achieved complete remission (CR) in the older and younger groups, respectively (p = 0.29). There was no significant difference in the rate of disease progression post-transplant between older (31%) and younger (30%) groups (p = 0.3). The 5-year progression free survival (PFS) was 24% and 37% in the older and younger groups, respectively (HR 1.3, p = 0.02). Similarly, 5-year overall survival (OS) was 56% and 73% in the older and younger groups (HR 1.8, p = <0.001). In univariate analyses, age > 70 years, high-risk cytogenetics, serum creatinine level > 2 mg/dl and ISS stage III were associated with worse PFS and OS. In contrast, melphalan 200 mg/m² for conditioning and achievement of CR after induction therapy were associated with better PFS and OS. These 6 factors were studied in multivariate analyses using a classification and regression tree (CART) method. In CART analysis for PFS, ISS stage II or III, and high-risk cytogenetics were associated with shorter PFS. Similarly, in CART analysis for OS, older age (> 69 years), ISS stage II or III, and high-risk cytogenetics were associated with a shorter OS. Conclusion In this large single-center analysis, there was no difference in 100-day NRM, CR rates and the risk of progression after auto-HCT between the older and the younger patients. However, older age was associated with a shorter PFS and OS due to increased NRM. On multivariate CART analysis, ISS stage II or III and high-risk cytogenetics were associated with a worse PFS and OS, while age > 69 years was associated with a worse OS only. The impact of comorbidities on NRM is being evaluated in ongoing analyses. Disclosures Lee: Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies Corporation: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Chugai Biopharmaceuticals: Consultancy; Takeda Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees. Patel:Abbvie: Research Funding; Takeda: Research Funding; Poseida Therapeutics, Inc.: Research Funding; Celgene: Research Funding. Thomas:Bristol Myers Squibb Inc.: Research Funding; Celgene: Research Funding; Acerta Pharma: Research Funding; Amgen Inc: Research Funding; Array Pharma: Research Funding. Orlowski:BioTheryX, Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees; Poseida: Research Funding; Bristol Myers Squibb: Consultancy; Genentech: Consultancy; Millenium Pharmaceuticals: Consultancy, Research Funding; Janssen Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Champlin:Otsuka: Research Funding; Sanofi: Research Funding.

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Impact of Bortezomib- or Lenalidomide-Based Induction Treatment on High Risk Cytogenetic Transplant-Ineligible Patients with Newly Diagnosed Multiple Myeloma Enrolled in the Gimema-MM-03-05 and EMN01 Trials

Blood ◽

10.1182/blood.v130.suppl_1.744.744 ◽

2017 ◽

Vol 130 (Suppl_1) ◽

pp. 744-744 ◽

Cited By ~ 1

Author(s):

Alessandra Larocca ◽

Massimo Offidani ◽

Pellegrino Musto ◽

Francesca Patriarca ◽

Lorenzo De Paoli ◽

...

Keyword(s):

Sensitivity Analysis ◽

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Newly Diagnosed ◽

Advisory Committees ◽

Risk Of Death ◽

Significant Difference ◽

Reduced Risk

Abstract Introduction : Cytogenetic abnormalities by fluorescence in situ hybridization (FISH) are clinically relevant prognostic factors in MM. Data in transplant ineligible patients treated with bortezomib or lenalidomide in first-line therapy for high-risk (HiR) patients is limited. Careful analysis of cytogenetic subgroups in trials comparing different treatments remains an important goal. This sub-analysis evaluates the impact of cytogenetics on outcomes in transplant-ineligible patients with newly diagnosed MM (NDMM) treated with bortezomib-based induction (BORT) or lenalidomide-based (LEN) treatment. Methods : In the GIMEMA-MM-03-05-trial, patients were randomized to bortezomib-melphalan-prednisone-thalidomide for 9 cycles followed by maintenance with bortezomib-thalidomide (VMPT-VT) vs VMP for 9 cycles, without maintenance. In the EMN01-trial, patients were randomized to melphalan-prednisone-lenalidomide (MPR) or cyclophosphamide-prednisone-lenalidomide (CPR) or lenalidomide plus low-dose dexamethasone (Rd) for 9 cycles, followed by maintenance with lenalidomide alone or plus prednisone continuously. Results of these studies have previously been reported (Palumbo A et al JCO 2010 and 2014; Magarotto V et al Blood 2016 127(9)). Cytogenetics were assessed using FISH. Patients were categorized into cytogenetic risk groups according to International Myeloma Working Group criteria. HiR cytogenetics included del(17p), t(4;14), and t(14;16); all other patients were categorized as standard risk (StR). Subgroup analyses were performed to determine the consistency of treatment effects of BOR vs LEN in the different subgroups using interaction terms between treatment and FISH, ISS, age, sex, Karnofsky PS and LDH. The different effect of BORT vs LEN in cytogenetic subgroups was confirmed by one sensitivity analysis where the follow-up of the BORT study was reduced to make the follow-up times similar; and by another sensitivity analysis with multiple imputation method for missing cytogenetic value. Results : 902 of 1165 patients from the intent-to-treat population had available cytogenetic profiles, with 243 (27%) patients in the HiR group and 659 (73%) in the StR group. In the BORT vs LEN groups, median age was 71 vs 73 years (p<0.001), ISS3 20% vs 27% (P=0.65), HiR patients were 29% vs 26%, StR patients were 71% vs 74% (p=0.32) and the median follow-up was 72.3 and 63.6 months, respectively. In the subgroup analysis, a significant difference was found in the cytogenetic subgroup with a superior advantage of BORT versus LEN in HiR group, whereas no significant difference was found between BORT and LEN in the other subgroups analyzed (ISS, age, sex, Karnofsky PS and LDH) (interaction-p=0.01) (Fig. 1 B). BORT treatment resulted in a reduced risk of death or progression compared with LEN in patients with HiR. In HiR patients, median PFS was 30.8 with BORT compared with 14.8 months with LEN (HR: 0.54; 95% CI: 0.41-0.72); in StR, median PFS was 29.1 with BORT compared with 22.1 months with LEN (HR: 0.87; 95%; CI: 0.72-1.05) (Fig. 1 A). Considering the standard of care VMP and Rd, in the HiR group (n=95) VMP resulted in a 48% reduced risk of death or progression compared with Rd (HR: 0.53; 95% CI: 0.34-0.83), whereas no significant difference in PFS was found in the StR group (n=273) (HR: 1.00; 95% CI: 0.75-1.33), interaction-p=0.02. BORT treatment resulted in a reduced risk of death in patients with HiR cytogenetics: median OS was 62.4 months with BORT compared with 43.2 months with LEN (HR: 0.68; 95% CI: 0.47-0.96); in StR, median OS was 78.1 months with BORT and was not reached with LEN (HR: 1.06; 95% CI: 0.82-1.36), interaction-p=0.04 (Fig. 1 A). In patients with del(17p) (n=131) median PFS was 18.0 vs 12.9 months for BORT vs LEN (HR: 0.71; 95% CI: 0.49-1.04), interaction-p=0.73. In patients with t(4;14) (n=118) median PFS was 31.5 vs 15.2 months for BORT vs LEN (HR: 0.41; 95% CI: 0.27-0.62) interaction-p=0.002. In patients with t(14;16) (n=31) median PFS was 36.2 vs 9.8 months for BORT vs LEN treated patients (HR: 0.34; 95% CI: 0.16-0.76), interaction-p=0.045. Conclusions : BORT treatment resulted in a PFS and OS benefit vs LEN in patients with HiR cytogenetics. Treatment with VMP led to a significant reduction of the risk of death or progression vs Rd in HiR patients. These results support VMP induction as a standard treatment option for patients with NDMM who are ineligible for transplant with HiR cytogenetics. Disclosures Larocca: Celgene: Honoraria; Janssen: Honoraria; Bristol-Myers Squibb: Honoraria; Amgen: Honoraria. Offidani: celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Musto: Janssen: Honoraria; Celgene: Honoraria. Patriarca: MSD Italia: Honoraria; Janssen: Honoraria. Corradini: Gilead: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Roche: Honoraria; Celgene: Honoraria; Sanofi: Honoraria; Takeda: Honoraria; Novartis: Honoraria. Bosi: Amgen: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Takeda: Membership on an entity's Board of Directors or advisory committees. Petrucci: Celgene: Honoraria; Janssen: Honoraria; Bristol-Myers Squibb: Honoraria; Takeda: Honoraria; Amgen: Honoraria. Boccadoro: Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; Mundipharma: Research Funding; AbbVie: Honoraria.

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Trial in Progress: A Multicentre, Parallel Arm, Open-Label Trial of Frontline R-CHOP/Polatuzumab Vedotin-RCHP and Glofitamab in Younger Patients with Higher Risk Diffuse Large B Cell Lymphoma (COALITION)

Blood ◽

10.1182/blood-2021-147636 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 3571-3571

Author(s):

Adrian Minson ◽

Nada Hamad ◽

Costas K. Yannakou ◽

Shu Min Wong ◽

Jason P Butler ◽

...

Keyword(s):

High Risk ◽

B Cell ◽

Board Of Directors ◽

Research Funding ◽

Cell Lymphoma ◽

B Cell Lymphoma ◽

Response Rates ◽

Line Treatment ◽

Front Line ◽

Advisory Committees

Abstract Background: R-CHOP remains a standard frontline treatment for patients with DLBCL and high-grade B-cell lymphoma (HGBL). A significant proportion of patients will have refractory disease or subsequently relapse, particularly those with high-risk features such as an elevated IPI score or rearrangements of MYC and BCL2 and/or BCL6 (double/triple hit (DH/TH)). This population remains in need of improved induction treatments that can reduce the requirement for subsequent therapies which are associated with significant toxicities and diminishing response rates. Rationale: Glofitamab is a novel full-length bispecific antibody with a unique 2:1 configuration (two CD20 binding domains and one CD3 binding domain). In combination with a single pre-dose of obinutuzumab, glofitamab has demonstrated >70% complete remission in aggressive B-cell lymphoma at the recommended target dose in a phase 1 trial (Carlo-Stella, EHA 2021). Pre-clinical studies suggest that glofitamab's activity is retained in the presence of concomitant cytotoxic and CD20 antibody therapies, making it an attractive agent for combination with R-CHOP-like induction. Polatuzumab vedotin (pola) is an antibody-drug conjugate approved for R/R DLBCL in combination with BR, and is currently in evaluation for the front-line treatment of DLBCL in combination with RCHP in a randomised trial. The safety and preliminary efficacy of glofitamab in combination with R-CHOP, or pola-RCHP as a front-line treatment for high risk DLBCL is being evaluated. Study Design and Methods: This is a parallel-arm phase Ib/II trial. Treatment consists of an initial cycle of R-CHOP, followed by 5 cycles of combination induction treatment and 2 cycles of consolidation glofitamab monotherapy. Key inclusion criteria are: age 18-65 years, a diagnosis of DLBCL or HBGL, high-risk features (IPI ≥3 or NCCN-IPI ≥4 or presence of DH/TH), treatment naïve or after 1 cycle of R-CHOP, ECOG 0-3. The primary endpoint is the safety of the combination and secondary endpoints include complete response rates at interim and end of treatment FDG-PET assessments by Lugano criteria, progression free survival and overall survival. Correlative studies assessing baseline immunologic profiles, tumour phenotype and potential resistance mechanisms are planned. Approximately 40 patients will be treated in each arm across 12-14 Australian sites. The trial commenced recruitment in July 2021 (NCT04914741). The ability to recruit prior to either cycle 1 or cycle 2 allows seamless cross-referral from non-trial sites. Figure 1 Figure 1. Disclosures Minson: Hoffman La Roche: Research Funding; Novartis: Research Funding. Hamad: Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Seymour: AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sunesis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Morphosys: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Mei Pharma: 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; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau. Dickinson: Celgene: Research Funding; Amgen: Honoraria; Takeda: Research Funding; MSD: Consultancy, Honoraria, Research Funding, Speakers Bureau; Gilead Sciences: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Other: travel, accommodation, expenses, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau.

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Validation of a New Clinical Prediction Model for Outcome in Newly Diagnosed Multiple Myeloma Patients Not Eligible for Autologous Stem-Cell Transplantation; A Population-Based Study from the Danish National Multiple Myeloma Registry

Blood ◽

10.1182/blood-2019-128074 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1849-1849

Author(s):

Louise Redder ◽

Tobias Wirenfeldt Klausen ◽

Annette Juul Vangsted ◽

Henrik Gregersen ◽

Niels Frost Andersen ◽

...

Keyword(s):

Multiple Myeloma ◽

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Risk Groups ◽

Population Based ◽

Newly Diagnosed ◽

Advisory Committees ◽

Medium Risk ◽

The Uk

Background : The UK Myeloma Research Alliance recently introduced a new clinical prediction model for outcome in newly diagnosed multiple myeloma (MM) patients not eligible for autologous hematopoietic stem-cell transplantation (ASCT) (Lancet Haematology 2019; 6: e154-66). The score or Myeloma Risk Profile, MRP, includes WHO performance status (PS), the International Staging System (ISS), age, and C-reactive protein (CRP) as prognostic variables. First a score is calculated by the formula: Score = (PS - 2) * 0.199 + (age - 74.4) * 0.0165 + (ISS - 2) * 0.212 + (log(CRP + 1) - 2.08) * 0.0315, where PS and ISS are defined as numbers between 0-4 and 1-3, respectively, and CRP is in mg/L. Next, three risk groups are defined as 1) low risk: score < -0.256, 2) medium risk: -0.256 ≤ score ≤ -0.0283, or 3) high risk: score > -0.0283. The MRP score was generated based on two prospective clinical trial cohorts, the NRCI-Myeloma XI study (ISRCTN49407852) as training set or internal validation, and the NRCI-Myeloma IX study (Blood 2011; 118, 1231-38) as test set or external validation. Both trials investigated conventional oral alkylating agents, cyclophosphamide or melphalan, in combination with thalidomide, lenalidomide, and/or bortezomib; thus including drugs typically used in treatment of elderly MM patients. Establishment of the model included 1852 patients in the training set, and 520 patients in the test set. All patients were recruited as part of clinical trials and therefore fulfilled defined inclusion and exclusion criteria. To validate the MRP score in a population-based setting we performed a study of the entire cohort of transplant ineligible MM patients in the Danish National MM Registry. Methods : The Danish MM registry started 01 January 2005. It includes registration of all diagnosed MM patients in Denmark and given first- and second-line treatment. A data validation study has been performed (J Clin Epidemiology, 2016; 8: 583-587). At 31 December 2014, 2,926 newly diagnosed treatment demanding MM patients were registered, hereof 1,803 patients were above 65 years and found ineligible for ASCT, and constituted the patient population for this study. Results: Of 1,803 transplant in-eligible but treatment demanding newly diagnosed MM patients above 65 years 426 patients had one or more missing values for calculation of the MRP score, most often this was caused by missing ISS. Thus, 1,377 patients were evaluable with a median follow-up of 40.9 months. Patients were treated according to standard of care in Denmark during the 10-years registration period which included upfront conventional alkylating agent, mostly melphalan in 37.7%, thalidomide-based in 25.6%, bortezomib-based in 26.1%, lenalidomide based in 2.7%, and only palliative, mostly steroid-based in 7.9%. The distribution of the risk groups according to MRP was as follows: low risk 28.5%, medium-risk 25.1%, and high-risk 46.4%. Ccompared to the UK datasets we had a higher proportion of high-risk patients which undoubtedly reflects that our cohort is population based. Median survivals for the 3 risk groups are presented in Table 1 and overall survival curves illustrated in Figure 1. The model performed well in separating the patients into subgroups with different survival risks. In conclusion, our real life population-based data confirm that the MRP score is a robust and valuable risk assessment tool for elderly newly diagnosed MM patients older than 65 and not eligible for ASCT. An important advantage of the MRP score is that it is calculated from simple parameters that should be part of everyday diagnostic work-up. Disclosures Vangsted: Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria; Jansen: Honoraria. Plesner:Takeda: Consultancy; Oncopeptides: Consultancy; Genmab: Consultancy; AbbVie: Consultancy; Celgene: Consultancy; Janssen: Consultancy, Research Funding. Frederiksen:Novartis: Research Funding; Janssen: Research Funding; Gilead: Research Funding; Alexion: Research Funding; Abbvie: Research Funding. Abildgaard:Amgen: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding.

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