External Validation and Revision of Thrombosis Lymphoma /Throly/ Score

Abstract Introduction Lymphoma patients are at increased risk of thromboembolic events (TE), however, thromboprophylaxis in these patients is largely under utilized. Actual guidelines recommend different models for thromboembolic risk estimation in cancer patients. Proposed models are of limited use in lymphoma patients as their development is not based on specific characteristics for this patient population. Previously, we developed and internally validated a simple model, based on individual clinical and laboratory patient characteristics that would classify lymphoma patients at risk for a TE. The variables independently associated with the risk for thromboembolism were: previous venous and/or arterial events, mediastinal involvement, BMI>30 kg/m2, reduced mobility, extranodal localization, development of neutropenia and hemoglobin level < 100g/L. For patients classified at risk in derivation cohort (n=1236), the model revealed positive predictive value of 25.1%, negative predictive value of 98.5%, sensitivity of 75.4%, and specificity of 87.5%. The diagnostic performance measures retained similar values in the internal validation cohort (n=584). The aim of this study was to perform external validation of the previously developed thrombosis lymphoma (Throly) score. Methods The study population included patients with a confirmed diagnosis of non-Hodgkin lymphoma (NHL), Hodgkin lymphoma (HL), and chronic lymphocytic leukemia (CLL)/ small lymphocytic lymphoma (SLL) from 8 lymphoma centers from USA, France, Spain, Croatia, Austria, Switzerland, Macedonia, and Jordan. During 2015 to 2016, data were prospectively collected for venous TE events from time of diagnosis to 3 months after the last cycle of therapy for newly diagnosed and relapsed patients who had completed a minimum of one chemotherapy cycle. The score development and validation were done according to TRIPOD suggested guidelines. Sensitivity analyses were carried out to test the model robustness to possible different settings, according to in/out patient settings and according to different countries included. Results External validation cohort included 1723 patients, similar to the developed group and consisted of 467 indolent NHL, 647 aggressive NHL, 235 CLL/SLL and 366 HL patients, out of which 121 (7%) patients developed venous thromboembolic events. For patients classified at risk in external validation cohort, the model resulted in positive and negative predictive values of 17% and 93%, respectively. Based on new available information from this large prospective cohort study this model was revised to include the following variables: diagnosis/clinical stage, previous VTE, reduced mobility, hemoglobin level < 100g/L and presence of vascular devices. In the new score we divided patients in two groups: low risk patients, score value ≤ 2; and high risk patients, score value > 2. For patients classified at risk by the revised model, the model produced positive predictive value of 22%, negative predictive value of 96%, sensitivity of 51%, and specificity of 72%. In sensitivity analysis, the final model proved its robustness in different settings of major importance for lymphoma patients. The final model presented good discrimination and calibration performance. Concordance C statistics was 0.794 (95% CI 0.750-0.837). Conclusions Revised Thrombosis Lymphoma - ThroLy score is more specific for lymphoma patients than any other available score targeting thrombosis risk in solid cancer patients. We included biological characteristic of lymphoma, indolent vs aggressive, as well as data about dissemination of disease, localized vs advanced stage, reflecting specificity of lymphomas comparing to other types of cancer. Also, we pointed out significance of central vascular devices as risk factor having considered the role of vascular damage during insertion as a potential trigger for activation of the clotting cascade. This score is user friendly for daily clinical practice and provides a very good predictive power to identify patients who are candidates for pharmacological thromboprophylaxis. Disclosures Cheson: AbbVie, Roche/Genentech, Pharmacyclics, Acerta, TG Therapeutics: Consultancy. Ghielmini:Roche: Consultancy, Honoraria, Research Funding, Speakers Bureau. Jaeger:Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; AOP Orphan: Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; MSD: Research Funding; Bioverativ: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Honoraria; Mundipharma: Membership on an entity's Board of Directors or advisory committees; Takeda-Millenium: Membership on an entity's Board of Directors or advisory committees; Takeda-Millenium: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Infinity: Membership on an entity's Board of Directors or advisory committees.

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Novel Prognostic Scoring System for Autologous Hematopoietic Cell Transplantation (AHCT) in Multiple Myeloma (MM)

Blood ◽

10.1182/blood-2019-126646 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 783-783 ◽

Cited By ~ 2

Author(s):

Binod Dhakal ◽

Raphael Fraser ◽

Zhubin Gahvari ◽

Aric C. Hall ◽

Natalie Scott Callander ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Scoring System ◽

Research Funding ◽

Validation Cohort ◽

Progression Free Survival ◽

Low Risk ◽

Advisory Committees ◽

Final Model ◽

Free Survival

Background: Novel agent induction and AHCT remains the preferred initial therapeutic strategy for transplant-eligible MM patients. Current prognostic tools in MM focus solely on disease-specific factors at diagnosis to determine patient prognosis-International Staging System (ISS) and revised-ISS (R-ISS). A major limitation to both, the ISS and R-ISS, is that they are not specific for HCT-eligible patients and do not take into account other patient factors that may enter into a decision to pursue AHCT. The data used to generate these staging systems were from broad populations with varying upfront treatment strategies and included patients who were ineligible for intensive therapy. Additionally, there is considerable interest in identifying the population that relapses early despite modern induction/AHCT approaches who are candidates for novel approaches for maintenance/consolidation. To address these problems, we used data from the Center for Blood and Marrow Transplant Research (CIBMTR) registry to identify disease-, patient-, and transplantation-specific variables that are associated with progression-free survival (PFS) in patients undergoing upfront AHCT (within 12 months of diagnosis). Methods: We used the outcomes of 2528 MM patients undergoing upfront AHCT from 2008-2017 reported to the CIBMTR. Patients were divided into training and validation sets with a 50% random split. High risk cytogenetics was defined as the presence of one or more of the following: t(4;14), t (14;16), t (14;20), del 13q, del 17p, 1q gain, or 1p deletion. We used a Cox multivariable model to identify factors prognostic of progression free survival (PFS) in a training subset. The regression coefficients of the final model was transformed into a risk score with an appropriate transformation. A weighted score using these factors was assigned to the training cohort (n = 917) and validation cohort (n=897) using subset that had all values that entered the final model. Kaplan-Meier estimates of the individual scores were used to classify patients into risk groups for both cohorts. Results: Baseline characteristics of these patients are shown in Table 1. No cytogenetic abnormality, VRD induction, pre-AHCT bone marrow plasma cells (BMPCs) <10% and 1 line of induction chemotherapy were assigned 0 points. Pre-AHCT BMPCs ≥10% (hazard ratio HR, 1.47; 95% CI, 1.19-1.83), use of ≥2 lines of induction chemotherapy prior to AHCT (HR 1.32; 95% CI 1.06-1.64), standard cytogenetic risk vs. no abnormality (HR 1.41; 95% CI 1.13-1.77) and induction regimens (non-VRD regimens vs. VRD) (HR 1.4, 95% CI 1.17-1.74) were associated with increased hazard of progression and assigned 1 point in the scoring system. Presence of high-risk cytogenetics vs. no abnormality (HR 1.87; 95% CI 1.45-2.42) was assigned 2 points, and the use of thalidomide and dexamethasone (TD) as an induction regimen (HR 2.19; 95% CI 1.48-3.2) was assigned 3 points. A two-category system was created based on the scoring: low risk (0-3) and high risk (4-6). The scoring system was prognostic for PFS when applied to both cohorts. High-risk group was found to have significantly higher risk of progression and/or death compared to low risk in training (HR 2.2; 95% CI 1.74-2.86; p<0.0001) and validation cohort (HR 1.7, 95% CI 1.30-2.22; p=0.0001) respectively (Table 2). The 3-year PFS in the training cohort was 60% (95% CI 56%-64%) in low risk and 27% (95% CI 17%- 36%) in high risk while in the validation cohort was 51% (95% CI 47%-55%) in low risk and 28% (95% CI 16%- 39%) in high risk (Figure 1A and 1B). Conclusions: We describe a prognostic model specifically for patients undergoing upfront AHCT in MM which can identify patients at very high risk for early relapse/progression. These patients should be ideal candidates for studies of immunotherapy or other interventions after AHCT aimed at reducing relapse. Disclosures Dhakal: Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria; Takeda: Membership on an entity's Board of Directors or advisory committees. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Shah:Genentech, Seattle Genetics, Oncopeptides, Karoypharm, Surface Oncology, Precision biosciences GSK, Nektar, Amgen, Indapta Therapeutics, Sanofi: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Nkarta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Teneobio: Consultancy, Membership on an entity's Board of Directors or advisory committees; University of California, San Francisco: Employment; Poseida: Research Funding; Indapta Therapeutics: Equity Ownership; Celgene, Janssen, Bluebird Bio, Sutro Biopharma: Research Funding. Qazilbash:Amgen: Consultancy, Other: Advisory Board; Autolus: Consultancy; Bioclinical: Consultancy; Genzyme: Other: Speaker. D'Souza:EDO-Mundapharma, Merck, Prothena, Sanofi, TeneoBio: Research Funding; Prothena: Consultancy; Pfizer, Imbrium, Akcea: Membership on an entity's Board of Directors or advisory committees. Hari:AbbVie: Consultancy, Honoraria; Cell Vault: Equity Ownership; Sanofi: Honoraria, Research Funding; Spectrum: Consultancy, Research Funding; Amgen: Research Funding; Kite: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; BMS: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding.

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Psychosocial Risk Is Associated with High Readmission Rates and Increased Length of Stay for Patients Following Hematopoietic Stem Cell Transplantation

Blood ◽

10.1182/blood.v128.22.1241.1241 ◽

2016 ◽

Vol 128 (22) ◽

pp. 1241-1241

Author(s):

Daniel R Richardson ◽

Ying Huang ◽

Patrick Elder ◽

Joanna Newlin ◽

Cyndi Kirkendall ◽

...

Keyword(s):

Risk Factors ◽

At Risk ◽

Length Of Stay ◽

Board Of Directors ◽

Hospital Readmission ◽

Research Funding ◽

Psychosocial Risk ◽

Moderate Risk ◽

Advisory Committees ◽

Risk Patients

Abstract Background: Patients undergoing hematopoietic stem cell transplantation (HSCT) are routinely screened for psychological and social risk factors prior to transplantation to determine eligibility and optimize support. Although patients with psychosocial risk factors have been shown to have a higher rate of depression and anxiety, the relationship between psychosocial risk and clinical outcomes in HSCT is not well established. We hypothesized that psychosocially vulnerable patients would be at a higher risk for adverse clinical outcomes including hospital readmission and increased length of stay (LOS) following HSCT. Methods: We performed a retrospective observational study at a single center of 395 consecutive HSCT patients who underwent pre-transplant psychosocial screening using the Transplant Evaluation Rating Scale (TERS). The TERS is a validated screening tool utilized to identify patients who are psychosocially vulnerable (κ=0.89-0.98, α=0.76, p=<0.001). TERS scoring is based on an aggregate of 10 different factors (Axis I diagnosis, Axis II diagnosis, substance abuse, compliance, health behaviors, family/social support, coping history, disease coping, affect quality, and mental status). The primary endpoint was time to readmission or death (TTRD) and was calculated as time from transplant discharge to readmission or death, censoring patients without an event at last follow-up or 90 days post-transplant. Estimates for TTRD were obtained using the Kaplan-Meier method and compared by the log-rank test. Multivariable regression analyses were performed to determine hazard ratios (HR) of TERS adjusting for other important covariates. Results: Patients underwent autologous (n=218, 55%) and allogeneic (n=177, 45%) HSCT for acute leukemia (n=140, 35%), multiple myeloma (n=134, 34%), lymphoma (n=93, 24%) and other indications (n=28, 7%). Patients were classified according to psychosocial risk as no-risk (TERS=26.5, 52%) vs. at-risk (TERS>26.5, 48%), with at-risk patients subdivided into mild risk (TERS=27-35.5, 39%) and moderate risk (TERS>35.5, 9%). Psychiatric conditions (24%), poor health behaviors (16%), and poor coping history (13%) were the most common identified risk factors while substance abuse (7%) and non-compliance (2%) were less frequent. Characteristics were similar among TERS groups with respect to race, disease, remission status, type of HSCT, and graft source. Patients with higher TERS scores tended to be younger (no-risk [median age = 58 years] vs. moderate risk [median age = 50.5 years], p=0.04). In multivariable analysis controlling for comorbidity index and disease type, at-risk patients were significantly more likely to be readmitted within 90 days (mild risk HR=1.53 (95% CI [1.04-2.26], p=0.03), moderate risk HR=1.88 (95% CI [1.08-3.29], p=0.03)). This association held across diseases and HSCT type when examined separately. Additionally, in the multiple myeloma cohort, mild risk patients tended to have longer LOS (mean LOS = 19.06 days) than no-risk patients (mean LOS = 16.78 days, p=0.005). Overall survival did not differ significantly among groups. Conclusion: All patients who are identified pre-transplant to have any degree of psychosocial vulnerability are at higher risk for hospital readmission following HSCT and certain groups are at risk for longer length of stay. Hospital readmission in HSCT patients is associated with poor overall survival, increased cost, and worse quality of life. As many psychosocial risk factors are potentially modifiable, at-risk patients undergoing HSCT would be an ideal population for a prospective study with targeted interventions such as early utilization of cancer psychologists, counselors, or healthcare navigators. Further research needs to be pursued to delineate which, if any, particular psychosocial risk factors are driving this association. Figure. Figure. Disclosures Andritsos: Hairy Cell Leukemia Foundation: Research Funding. Hofmeister:Arno Therapeutics, Inc.: Research Funding; Signal Genetics, Inc.: Membership on an entity's Board of Directors or advisory committees; Janssen: Pharmaceutical Companies of Johnson & Johnson: Research Funding; Incyte, Corp: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Karyopharm Therapeutics: Research Funding; Takeda Pharmaceutical Company: Research Funding; Teva: Membership on an entity's Board of Directors or advisory committees.

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Easix for Prediction of Survival in Myelodysplastic Syndromes

Blood ◽

10.1182/blood-2019-122622 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1722-1722

Author(s):

Almuth Maria Anni Merz ◽

Ulrich Germing ◽

Guido Kobbe ◽

Jennifer Kaivers ◽

Anna Jauch ◽

...

Keyword(s):

Endothelial Dysfunction ◽

Board Of Directors ◽

Lower Risk ◽

Research Funding ◽

Validation Cohort ◽

P Value ◽

Advisory Committees ◽

Training Cohort ◽

Risk Patients ◽

Support Research

Introduction Patients with myelodysplastic syndromes (MDS) are at risk of early death from cardiovascular complications due to the link between clonal hematopoiesis and endothelial dysfunction. EASIX (Endothelial Activation and Stress Index) has been established to predict endothelial complications after allogeneic stem cell transplantation (alloSCT). EASIX is an endothelial dysfunction related biomarker that can be easily obtained with routine laboratory markers (creatinine× LDH/thrombocytes). We analyzed whether EASIX can predict mortality in higher-risk and in lower-risk MDS patients. Since alloSCT can alter the natural history of MDS and may be an independent contributor to endothelial complications, this analysis was restricted to patients who did not undergo alloSCT during the course of their disease. Patients and Methods We investigated the impact of EASIX measured at first diagnosis on survival of patients with lower- and higher-risk MDS (no allogeneic transplantation) in two independent institutions: n=192 (training cohort) and n=333 (validation cohort). For the purposes of this study, patients with low and intermediate-1 according to IPSS and very low and low-risk according to IPSS-R, respectively, were considered to have lower-risk MDS, while patients with intermediate-2 and high-risk according to IPSS and intermediate, high and very-high according to IPSS-R, respectively, were considered to have higher-risk MDS. Serum markers of endothelial cell distress were measured and correlated to EASIX. Results While no effects of EASIX on survival were observed in higher-risk patients, EASIX was associated with shorter survival in patients with lower-risk MDS in both cohorts (univariate: training cohort: hazard ratio (HR): 1.46; 95% confidence interval (CI) 1.24-1.71; p-value < 0.001 / validation cohort: HR 1.31 [1.17-1.48]; p-value < 0.001). We visualized this continuous effect of EASIX in lower-risk disease by grouping patients into quartiles according to EASIX (Figure 1 A and B). In both cohorts, patients in the highest quartile had a shorter survival compared to patients in lower quartiles. Confining our analysis to lower-risk patients who did not develop AML within the observation period, EASIX similarly predicted OS in both cohorts (training: n=78, no. of events n=17, HR per log2 increase 1.43 [1.05-1.94]; p=0.02; validation: n=267, no. of events n=93, HR per log2 increase 1.33 [1.21-1.47]; p<0.00). Multivariate Cox regression analysis and prediction error analyses confirmed that EASIX remained a significant predictor of survival after adjustment for age, sex, cytogenetic abnormalities and bone marrow blasts in lower-risk patients. The model of the training cohort could be validated. No effect of EASIX on survival was found in higher-risk patients from both cohorts in univariate and multivariate analysis. Serum levels of Angiopioetin-2 correlated significantly with EASIX whereas S100A9 or IL-1b did not. However, we observed a strong intra-pathway correlation of S100A9 with IL1b, IL18, IL37, and HMGB1. Conclusion We introduce EASIX as an easily accessible and independent predictor for survival in patients with lower-risk MDS. The strong correlation of EASIX and ANG2 underlines the endothelial nature of this biomarker. Disclosures Germing: Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Jazz Pharmaceuticals: Honoraria; Amgen: Honoraria. Kobbe:Neovii: Honoraria, Other: Travel support; Pfizer: Honoraria, Other: Travel support; Medac: Honoraria, Other: Travel support; Abbvie: Honoraria, Other: Travel support; Biotest: Honoraria, Other: Travel support; Jazz: Honoraria, Other: Travel support; Celgene: Honoraria, Other: Travel support, Research Funding; Roche: Honoraria, Other: Travel support; Amgen: Honoraria, Other: Travel support, Research Funding; MSD: Honoraria, Other: Travel support; Novartis: Honoraria, Other: Travel support; Takeda: Honoraria, Other: Travel support. Kaivers:Jazz Pharmaceuticals: Other: Travel Support. Merz:Janssen: Other: Travel grants; Amgen: Membership on an entity's Board of Directors or advisory committees, Other: Travel grants; Abbvie: Other: Travel grants; Celgene: Other: Travel grants; Takeda Vertrieb GmbH: Other: Travel grants, Research Funding. Dreger:MSD: Membership on an entity's Board of Directors or advisory committees, Other: Sponsoring of Symposia; Neovii, Riemser: Research Funding; AbbVie, Gilead, Novartis, Riemser, Roche: Speakers Bureau; AbbVie, AstraZeneca, Gilead, Janssen, Novartis, Riemser, Roche: Consultancy.

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Impact of DNMT3a Status on Post Induction NPM1 MRD Predictive Value on Survival in Elderly AML Patients Treated Intensively

Blood ◽

10.1182/blood-2020-141890 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 7-8

Author(s):

Maël Heiblig ◽

Hélène Labussière ◽

Marie Virginie Larcher ◽

Gaelle Fossard ◽

Marie Balsat ◽

...

Keyword(s):

Elderly Patients ◽

Board Of Directors ◽

Predictive Value ◽

Scoring System ◽

Research Funding ◽

Risk Group ◽

Advisory Committees ◽

Post Induction ◽

Mutational Status ◽

Elderly Aml

Minimal residual disease is now a powerfull surrogate marker to assess response to chemotherapy in acute myeloid leukemia (AML). In younger adults, NPM1 MRD has recently demonstrated to be a favorable predictive marker for EFS and OS independently of fms-like tyrosine kinase-3 internal tandem duplications (FLT3-ITD) status. However, there is very few datas regarding predictive value of NPM1 MRD in elderly patients treated with intensive chemotherapy. Moreover, numerous studies have suggested the negative impact of DNMT3a mutation in NPM1 AML patients, especially in those with concurrent FLT3-ITD mutation. In this study, we aimed to investigate the impact of DNMT3a status on post induction NPM1 MRD1 predictive value for survival in a retrospective cohort of AML patients aged over 60 years old treated intensively. A total of 138 patients treated for NPM1 mutated AML in two French institutions (Lyon, Lille) were analyzed retrospectively. Median age of the entire cohort was 66.1 years old (range 60-78.2). An FLT3-ITD mutation was evidenced in 52 of 138 patients (37.6%) with a median FLT3-ITD AR of 0.53 (range, 0.05-3). With a median follow-up of 19.61 months (0.07-128.4), the overall CR rate was 89.9% with no influence of DNMT3a or FLT3 mutational status on the probability of CR. In this elderly cohort of NPM1mut patients, a 4log reduction of NPM1 bone marrow (BM) MRD1 was associated with better outcome (median OS: NR vs 13.4 months, HR=0.35, p<0.01)(Figure A). Overall, DNMT3 status did not influence the probability of having a ≥ 4log MRD1 reduction after induction. However, only 9/44 (20.4%) FLT3-ITD patients reached ≥ 4log MRD1 reduction whereas 38/80 FLT3wt (47.5%) were good molecular responders (p<0.001). FLT3-ITD mutated patients who achieved a 4log reduction had a superior outcome compared to those who did not (HR=0.34; 95% CI, 0.16 to 0.70; P <0.001). Similarly, NPM1mut FLT3wt patients with a 4log reduction in NPM1 BM-MRD1 had a longer OS (3-year OS, 68.1%; 95% CI, 48.8 to 82.9) than those without good molecular response (3-year OS, 46.5%; 95% CI, 30.2 to 61.7)(Figure B). DNMT3a negative patients who achieved a 4log reduction had a superior outcome to those who did not reached at least a 4log reduction (HR=0.23; 95% CI, 0.07 to 0.72; P <0.001). However, postinduction NPM1 MRD1 reduction was not predictive of OS and leukemia free survival (LFS) in DNMT3amut patients. DNMT3amut patients has a very poor LFS which was even worst in poor NPM1 MRD1 responders compared to those who reached at least 4log reduction (median LFS: 8.3 months vs 17.4 months, HR = 0.48, 95% CI, 0.25-0.91, p=0.023)(Figure C). In multivariate analysis, only DNMT3a mutational status and a 4-log reduction in NPM1 BM-MRD were significantly associated with survival. Based on these results, we identified among NPM1 positive patients 3 groups with distinct prognosis, based on FLT3-ITD, DNMT3a status and NPM1 BM-MRD post induction response (NPM1 scoring system)(Figure D). When compared to ELN 2017 intermediate risk group (AUC=0.695), NPM1 scoring system (NPM1 SS) was more accurate for OS prediction in patients within intermediate (AUC=0.833) and unfavorable (AUC=0.863) NPM1 SS risk group. However, there was no significant difference in AUC between NPM1 SS favorable and ELN 2017 favorable risk group. These results confirm that post-induction NPM1 MRD1 is a reliable tool to assess disease outcome in elderly AML patients. However, the presence of DNMT3a also identify a subgroup of patients at very high risk of relapase, despite good molecular responses. As hematopoietic stem cell transplantation (HSCT) might improve OS in elderly patients, DNMT3a positive AML elderly patients should be considered for HSCT or post induction maintenance strategies, even within the favorable ELN risk group. Figure Disclosures Sujobert: Gilead/Kyte: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sunesis: Research Funding.

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ABVD Versus Escalated Beacopp in Advanced Stage Hodgkin's Lymphoma: Results from a Retrospective, Multicenter European Study

Blood ◽

10.1182/blood-2019-128198 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1565-1565 ◽

Cited By ~ 1

Author(s):

Patrizia Mondello ◽

Irene Dogliotti ◽

Jan-Paul Bohn ◽

Federica Cavallo ◽

Simone Ferrero ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Advanced Stage ◽

Advisory Committees ◽

Free Survival ◽

High Risk Patients ◽

Risk Patients

Purpose: Hodgkin's lymphoma (HL) is a highly curable disease even in advanced-stage, with >90% of long-term survivors. Currently, the standard of care is ABVD (doxorubicin, etoposide, vinblastine and dacarbazine), as it is less toxic and as effective as other more intensive chemotherapy regimens. Alternatively, BEACOPP (bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine and prednisone) has been proposed as front-line intensified regimen with a better initial disease control and prolonged time to relapse when compared to ABVD. However, this advantage is associated with higher rates of severe hematologic toxicity, treatment-related deaths, secondary neoplasms and infertility. To date, the debate regarding which regimen should be preferred as first line for advanced-stage HL is still ongoing. To shed some light on this open question we compared efficacy and safety of both regimens in clinical practice. Patients and Methods: From October 2009 to October 2018, patients with HL stage III-IV treated with either ABVD or BEACOPP escalated (BEACOPPesc) were retrospectively assessed in 7 European cancer centers. Results: A total of 372 consecutive patients were included in the study. One-hundred and ten patients were treated with BEACOPPesc and 262 with ABVD. The baseline characteristics of the two groups did not differ significantly, except for a higher rate of high-risk patients in the BEACOPPesc group in contrast to the ABVD one (47% vs 18%; p= 0.003). Complete response rate (CR) assessed by PET imaging at the end of the second cycle was 67% and 78% for the ABVD and BEACOPPesc group (p= 0.003), respectively. Thirteen patients of the ABVD group achieved stable disease (SD) and 6 had a progression disease (PD). On the other hand, 4 of the patients in the BEACOPPesc group progressed, another 2 interrupted therapy because life-threatening toxicity. At the end of the therapy, CR was 76% in the ABVD group and 85% in the BEACOPPesc group (p= 0.01). A total of 20% patients in the ABVD group and 14% patients in the BEACOPPesc group received consolidation radiotherapy on the mediastinal mass at the dose of 30Gy. After radiotherapy, the number of patients with CR increased to 79% and 87% in the two groups (p= 0.041), respectively. Thirty-nine patients (35%) in the BEACOPPesc group required dose reduction of chemotherapy due to toxicity compared to 12 patients (5%; p= <0.001) in the ABVD group. Overall, the rate of severe toxicities was higher in the BEACOPPesc group in comparison with the ABVD cohort. In particular, there was a significant increased frequency of acute grade 3-4 hematologic adverse events (neutropenia 61% vs 24%; anemia 29% vs 4%; thrombocytopenia 29% vs 3%), febrile neutropenia (29% vs 3%), severe infections (18% vs 3%). Myeloid growth factors were administered to 85% and 59% of patients in the BEACOPPesc group compared to the ABVD group. Blood transfusions were required in 51% and 6% of patients in the BEACOPPesc group compared to the ABVD cohort. Progression during or shortly after treatment occurred in 5 patients in the BEACOPPesc group (4%) and in 16 patients in the ABVD group (6%; p= 0.62). Among the 96 patients who achieved a CR after BEACOPPesc and radiotherapy, 8 relapsed (8%), compared to 29 of 208 patients in the ABVD group (14%; p= 0.04). At a median follow-up period of 5 years, no statistical difference in progression free survival (PFS; p=0.11) and event-free survival (EFS; p=0.22) was observed between the BEACOPPesc and ABVD cohorts. Similarly, overall survival (OS) did not differ between the two groups (p=0.14). The baseline international prognostic score (IPS <3 vs ≥ 3) significantly influenced the EFS with an advantage for the high-risk group treated with BEACOPPesc (Figure 1A; p=0.03), but not the PFS (Figure 1B; p=0.06) and OS (Figure 1C; p=0.14). During the follow-up period, in the BEACOPPesc group one patient developed myelodysplasia and one acute leukemia. Second solid tumors developed in one patient in the ABVD group (lung cancer) and one in BEACOPPesc group (breast cancer). Conclusion: We confirm that the ABVD regimen is an effective and less toxic therapeutic option for advanced-stage HL. Although BEACOPP results in better initial tumor control especially in high-risk patients, the long-term outcome remains similar between the two regimens. Disclosures Ferrero: EUSA Pharma: Membership on an entity's Board of Directors or advisory committees; Servier: Speakers Bureau; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Speakers Bureau. Martinelli:BMS: Consultancy; Pfizer: Consultancy; ARIAD: Consultancy; Roche: Consultancy; Novartis: Consultancy. Willenbacher:European Commission: Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Myelom- und Lymphomselbsthilfe Österreich: Consultancy, Honoraria; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead Science: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; IQVIA: Membership on an entity's Board of Directors or advisory committees; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees; oncotyrol: Employment, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Fujimoto: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tirol Program: Research Funding; Abbvie: Consultancy, Honoraria; Sandoz: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees.

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Multiple Low Level Mutations Identifies Imatinib Resistant CML Patients At Risk of Poor Response to Second-Line Inhibitor Therapy, Irrespective of the Resistance Profile of the Mutations

Blood ◽

10.1182/blood.v118.21.111.111 ◽

2011 ◽

Vol 118 (21) ◽

pp. 111-111

Author(s):

Wendy T Parker ◽

Musei Ho ◽

Hamish S Scott ◽

Timothy P. Hughes ◽

Susan Branford

Keyword(s):

At Risk ◽

Board Of Directors ◽

Mutation Analysis ◽

Research Funding ◽

Poor Response ◽

Advisory Committees ◽

Low Level ◽

Mass Spec ◽

Imatinib Resistant

Abstract Abstract 111 Specific imatinib resistant BCR-ABL1 mutations confer clinical resistance to nilotinib (NIL; Y253H, E255K/V, T315I, F359V/C) and/or dasatinib (DAS; V299L, T315I/A, F317L/I/V/C). Therefore, mutation analysis is recommended for CML patients (pts) after imatinib failure to facilitate selection of appropriate therapy. However, around 40% of chronic phase (CP) pts without these NIL/DAS resistant mutations also fail second line inhibitor therapy. For imatinib resistant pts without these mutations at the time of commencing NIL/DAS therapy (switchover) we investigated whether sensitive mutation analysis could identity pts at risk of poor response to subsequent therapy. Switchover samples of 220 imatinib resistant pts (DAS n=131, NIL n=89) were analysed by direct sequencing (detection limit 10–20%) and sensitive, high throughput mass spectrometry (mass spec; Sequenom MassARRAY, detection limit 0.05–0.5%), which detects 31 common BCR-ABL1 mutations (approximately 89% of mutations detected in pts receiving imatinib). We previously demonstrated that mass spec could detect NIL/DAS resistant mutations at switchover in an extra 9% of pts compared to sequencing and that these low level resistant mutations were associated with subsequent failure of these inhibitors (Parker et al, JCO. 2011 In Press). Therefore, for the current analysis, pts with NIL/DAS resistant mutations detected by either method (n=45) were excluded since response is already known to be poor in these cases. In the switchover samples of the remaining 175 pts, 159 mutations were detected in 86 pts by mass spec, but just 108 mutations were detected in 89 pts by sequencing. Thirteen rare mutations detected by sequencing were not included in the mass spec assay design. Mass spec detected all other mutations detected by sequencing, plus an additional 64 low level mutations. Multiple NIL/DAS sensitive mutations (≥2 mutations) were detected at switchover in more of the 175 pts by mass spec (34/175, 19%; 2–9 mutations per pt) than sequencing (16/175, 9%; 2–3 mutations per pt), P=.009. We divided pts into 2 groups; those with multiple mutations detected by mass spec at switchover (n=34) and those with 0/1 mutation (n=141), and investigated the impact of multiple mutations on response to subsequent NIL/DAS therapy. Pts with 0 or 1 mutation, and similarly pts with 2 or >2 mutations, were grouped together, as no difference in response was observed. The median follow up for CP, accelerated phase and blast crisis pts was 17 (2–33), 18 (1–33) and 3 (1–27) mo, and the frequency of multiple mutations was 18%, 24% and 18%, respectively. During follow up, multiple mutations at switchover was associated with lower rates of complete cytogenetic response (CCyR; 21% vs 50%, P=.003, Fig 1A) and major molecular response (MMR; 6% vs 31%, P=.005, Fig 1B), and a higher incidence of acquiring new NIL/DAS resistant mutations detectable by sequencing (56% vs 25%, P=.0009, Fig 1C). At 18 mo, the failure-free survival rate (European LeukemiaNet recommendations) for CP pts with multiple mutations at switchover was 33% compared to 51% for CP pts with 0 or 1 mutation (P=.26, Fig 1D). The number of mutations detected per pt by mass spec at switchover (max of 9, 8 of 86 pts with mutations had ≥4, 9%) far exceeded the number concurrently detected by sequencing (max of 3). This suggests that mass spec detected a pool of subclonal mutants, each with a small survival advantage after imatinib therapy that was insufficient for their clonal predominance. Multiple low level mutations may be a marker of an increased propensity for subsequent selection of resistant mutations, possibly driven by genetic instability, demonstrating the advantage of a sensitive multiplex mutation assay. In conclusion, sensitive mutation analysis identified a poor-risk subgroup with multiple mutations that were not identified by sequencing. This subgroup represented 15.5% of the total cohort (34/220), who would not otherwise be classified as being at risk of poor response on the basis of their mutation status. These pts did not have NIL/DAS resistant mutations at switchover; however, they had a lower incidence of CCyR and MMR, and higher incidence of acquiring new NIL/DAS resistant mutations during NIL/DAS therapy compared to pts with 0 or 1 mutation. This poor-risk subgroup may warrant closer monitoring or experimental approaches to reduce the high risk of kinase inhibitor failure after imatinib resistance. Disclosures: Hughes: Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Ariad: Honoraria, Membership on an entity's Board of Directors or advisory committees. Branford:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Research Funding; Ariad: Research Funding.

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Global DNA Methylation Analysis Identifies Key Pathway Differences Between Poor (Low OCT-1 Activity) and Standard Risk CP-CML Patients At Diagnosis

Blood ◽

10.1182/blood.v120.21.3730.3730 ◽

2012 ◽

Vol 120 (21) ◽

pp. 3730-3730

Author(s):

Dale B. Watkins ◽

Chung Hoow Kok ◽

Richard J. D'Andrea ◽

Timothy P. Hughes ◽

Deborah L. White

Keyword(s):

Dna Methylation ◽

Board Of Directors ◽

Research Funding ◽

Global Dna Methylation ◽

Advisory Committees ◽

Poor Risk ◽

Normal Individuals ◽

Risk Patients ◽

Dna Methylation Analysis ◽

Standard Risk

Abstract Abstract 3730 Background: DNA methylation, specifically CpG methylation, is an essential mediator of epigenetic gene expression which is of vital importance to many biological processes and human malignancies. DNA hypermethylation has been previously described in a small number of genes in chronic myeloid leukemia (CML); however, current published studies have only examined the methylation status of selected genes, often based on the results of studies in other malignancies. Therefore, the global DNA methylation profile of chronic phase-CML (CP-CML) remains poorly understood, as does the impact of the epigenome on patient response to tyrosine kinase inhibitors (TKIs) including imatinib. The organic cation transport-1 (OCT-1) protein is the major active protein involved in imatinib transport, and we have previously demonstrated that measuring its function in leukemic mononuclear cells, expressed as OCT-1 activity (OA), in patient cells prior to imatinib therapy, provides a strong prognostic indicator. Notably, very low OA (poor risk cohort) is associated with patients at significant risk for poor molecular response, mutation development and leukemic transformation on imatinib therapy. Therefore, it is of particular interest to ascertain whether epigenetic changes are distinct and potentially biologically relevant in these poor risk patients. Aim: To investigate the global DNA methylation profile in CP-CML patients with a particular focus on poor risk patients (very low OCT-1 activity), and to ascertain whether aberrant epigenetic programming may underlie their poor response. Method: Cells were isolated from the blood of 55 CP-CML patients at diagnosis and 5 normal individuals. CP-CML patients were classified according to their OA values, with 29 classified as poor (very low OA) and 26 standard risk (high OA). Whole genome DNA methylation analysis was performed using the Illumina Infinium® HumanMethylation450 BeadChip. Analysis of array data was performed with R v2.15.0, using the minfiBioconductor package. Results: The methylation profile of CP-CML was significantly different to that of normal individuals, as shown in Table 1. GeneGo enrichment analysis revealed a significant enrichment in CML for genes known to be involved in other leukemias (p=4.92e−26) particularly AML and CLL, suggesting similar pathways may be under epigenetic control in CML. A significant number of polycomb group (BMI1 and EZH2) target genes were also identified, suggesting the likely involvement of this pathway in CML. Table 1: Summary of significant CpGs and corresponding genes when comparisons of CP-CML to normal individuals, and poor to standard risk patients, are made using methylation profiles. A significant difference was also observed when the methylation profiles of poor and standard risk CP-CML patients were analysed (Table 1). GeneGo analysis again identified polycomb group (SUZ12 and EZH2) target enrichment and significant enrichment of NOTCH, Hedgehog and WNT signalling (p=7.93e−9, p=2.42e−5 and p=3.66e−5 respectively) in poor risk patients, indicating these pathways may play a significant role in the unfavourable responses observed in many of these patients. Of particular interest were the ten CpGs where a fold change >4 was observed between the methylation profiles of poor and standard risk patients. Using the Prediction Analysis of Microarrays supervised learning algorithm, a classifier for patient OA prediction based on this 10 CpG signature was evaluated. This classifier had an overall accuracy of 94% (sensitivity: 95%, specificity: 93%). Conclusion: We present a comprehensive global DNA methylation analysis of CP-CML that indicates significant and widespread changes to the CML epigenome, compared with that of normal individuals. Importantly, we have generated a classifier, which identifies the poor risk patient subgroup (very low OA) with 94% accuracy. Validation of this classifier is currently in progress. The epigenetic changes identified here may contribute to CML pathogenesis, and also to the response heterogeneity observed between CP-CML patients treated with TKI therapy. Disclosures: Hughes: Novartis Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Ariad: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. White:Novartis Oncology: Honoraria, Research Funding; BMS: Research Funding; CSL: Research Funding.

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Presence of a Translocation Is Associated with Short Time to Treatment from Diagnosis in IGHV Mutated Chronic Lymphocytic Leukemia (CLL) Patients

Blood ◽

10.1182/blood.v128.22.4372.4372 ◽

2016 ◽

Vol 128 (22) ◽

pp. 4372-4372 ◽

Cited By ~ 1

Author(s):

Nyla A. Heerema ◽

Qiuhong Zhao ◽

Amy S. Ruppert ◽

Heather Breidenbach ◽

Jeffrey Jones ◽

...

Keyword(s):

Chronic Lymphocytic Leukemia ◽

Board Of Directors ◽

Research Funding ◽

Statistical Significance ◽

Patient Characteristics ◽

Lymphocytic Leukemia ◽

Advisory Committees ◽

Final Model ◽

Time To Treatment ◽

Short Time

Abstract Chronic Lymphocytic Leukemia (CLL) has a varied clinical course; some patients experience a long survival and others succumb to disease in a short time. Clinical factors correlated with either time to first treatment (TFT) and/or overall survival include Rai stage, IGHV somatic hypermutation status, fluorescence in situ hybridization (FISH) abnormalities, especially del(17p), karyotypic complexity and the presence of a cytogenetic translocation. Previous studies have included patients both at diagnosis and at various times throughout their diseases, and many included limited numbers of patients, precluding extensive analyses of relationships between the prognostic factors and their relative impact on clinical outcome. We sought to identify which factors determined within a short time of diagnosis (i.e., 1 year) were prognostic for TFT in untreated CLL patients. We identified 329 untreated CLL patients who had stimulated karyotypic and FISH analyses within 1 year of diagnosis seen at The Ohio State University (OSU). Patient characteristics and outcome were obtained from patient records. The studies were approved by the OSU IRB and were conducted according to the Declaration of Helsinki. A complex karyotype was defined as ≥ 3 unrelated aberrations by karyotype. Patient characteristics are given in Table 1. Translocations occurred in 87 (26.4%) patients: 38 balanced and 49 unbalanced translocations. Initial statistical analyses showed no large difference in TFT between balanced and unbalanced translations, so they were combined for final analyses. 144 patients (49 with and 95 without a translocation) had unmutated IGHV, and 144 patients (22 with and 122 without a translocation) had mutated IGHV. IGHV data were not available for 41 patients. TFT was calculated from date of diagnosis to date of first treatment. Untreated patients were censored at last known untreated date. Kaplan-Meier curves estimated TFT probability, and proportional hazard models were used to examine the association between potential risk factors and TFT. Using backward selection, variables with statistical significance when adjusting for all other covariates were included in the final model. To evaluate potential effect modifications, pairwise interactions among all the variables in the final model were examined and retained if statistically significant. Stata 14 (College Station TX) was used, and all tests were two-sided with statistical significance set at p<0.05. Median follow-up for censored patients was 30 months (range 0.03-102 months). Median TFT for the entire cohort was 47 months (95% confidence interval (CI) 40-63 months). In a univariable model, the following factors were significant: presence of a translocation (hazard risk (HR) 2.69, CI 1.91-3.78, p<0.001), Rai stage III/IV (HR 3.73, CI 2.32-5.99, p<0.001), complexity (HR 2.92, CI 1.98-4.31, p<0.001), unmutated IGHV (HR 3.54, CI 2.42-5.17, p<0.0001), del17p (HR 2.10, CI 1.31-3.37, p=0.002), del11q (HR 2.91,CI 1.92-4.40, p<0.001). In the multivariable model, there was significant effect modification of IGVH status on the relationship between translocation and TFT (p<0.001). In IGHV mutated patients, those with a translocation had over 5 times the risk of starting treatment relative to those without a translocation (HR 5.30, CI 2.76-10.17); however, in IGHV unmutated patients, a translocation did not significantly increase the risk of starting treatment (HR 1.32, CI 0.86-2.03). Independent of IGHV and translocation, Rai Stage (HR 2.07, CI 1.24-3.45, p=0.01) and del11q (HR 1.68, CI 1.09-2.60, p=0.02) were the only variables that remained statistically significant. Notably, once these variables were accounted for in the model, complexity did not provide additional significant prognostic information (p=0.12), perhaps due to its strong association with a translocation (p<0.001). In summary, the presence of a translocation in IGHV mutated patients appeared to negate the improved prognosis associated with mutated IGHV, but the presence of a translocation did not have an effect on TFT in high-risk IGHV unmutated patients (Figure 1). Table 1 Table 1. Figure 1 Time to Treatment for patients with vs without a translocation and with mutated vs unmutaed IGVH Figure 1. Time to Treatment for patients with vs without a translocation and with mutated vs unmutaed IGVH Disclosures Jones: Pharmacyclics, LLC, an AbbVie Company: 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; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding. Andritsos:Hairy Cell Leukemia Foundation: Research Funding. Woyach:Morphosys: Research Funding; Acerta: Research Funding; Karyopharm: Research Funding. Awan:Pharmacyclics: Consultancy; Novartis Oncology: Consultancy; Innate Pharma: Research Funding.

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Expanded Access Program: Evaluating Safety of Erythrocytes Encapsulating L-Asparaginase in Combination with Polychemotherapy in Patients Under 55 Years Old with Acute Lymphoblastic Leukaemia (ALL) at Risk to Receive Other Formulations of Asparaginase

Blood ◽

10.1182/blood-2021-147834 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 1214-1214

Author(s):

Yves Bertrand ◽

Nicolas Boissel ◽

Claudine Schmitt ◽

Alban Villate ◽

Emmanuel Gyan ◽

...

Keyword(s):

At Risk ◽

Board Of Directors ◽

Whole Blood ◽

Research Funding ◽

Advisory Committees ◽

E Coli ◽

Expanded Access ◽

Expanded Access Program ◽

To Receive ◽

Access Program

Abstract Introduction Asparaginase is an important part of the treatment of acute lymphoblastic leukemia (ALL). Hypersensitivity is found in 16.8% of patients treated with pegylated asparaginase (PEG-asp). Hypersensitivity is the most common cause of truncated asparaginase therapy which has been associated with decreased event free survival. Asparaginase (ASNase) encapsulated in erythrocytes (eryaspase) is an alternative formulation of ASNase aiming to prolong the half-life of ASNase and to reduce toxicity e.g. hypersensitivity, since the erythrocyte membrane protects asparaginase against elimination and prevents activation of the immune system. In the NOR-GRASPALL 2016 trial eryaspase consistently demonstrated prolonged ASNase activity in patients who developed hypersensitivity reactions to PEG-asp. Treatment with eryaspase was well tolerated when combined with multiagent chemotherapy. The objective of this expanded access program was to explore the tolerability of eryaspase (150 U/Kg) combined with polychemotherapy in patients under 55 years of age with ALL, unable or at risk to receive any other available ASNase formulation. Patients in this study had developed hypersensitivities to prior E-Coli- and Erwinia-derived asparaginase therapies. Methods This was a non-randomized, multicentre, open label, Phase 1 study to assess the limiting toxicities, global safety and biological efficacy of eryaspase in combination with chemotherapy regimens. Patients were under 55 years of age with ALL de novo or in relapse or refractory; eligible for a chemotherapy treatment including ASNase; known contraindication and/or at risk of toxicity from other ASNase formulations. Eryaspase (150 U/Kg) was given as a replacement therapy for the remaining intended courses of asparaginase therapy. The number of courses was not defined and depended on therapeutic treatment chosen by the Investigator and the patient's response and tolerance. The primary endpoint was the exploration of the toxicity of eryaspase defined as the number and percent of patients presenting at least one limiting toxicity (LT) of eryaspase in combination with chemotherapy. Major secondary endpoints included: adverse events (AEs), pharmacokinetics (PK), pharmacodynamics (PD) and complete remission (CR) status at end of induction and survival status up to 12 months after inclusion. Results Eighteen patients enrolled of which seven (38.8%) patients experienced a total of 24 AE limiting toxicities, which were primarily bone marrow failure, and were indicative of the underlying ALL disease process and of the concomitant chemotherapy-related myelosuppression. All patients experienced at least one AE and Treatment Emergent (TEAE) and most (11 [61.1%] patients) experienced at least one SAE. A total of 17 (94.4%) patients experienced a TEAE of Grade 3 or above. No TEAEs led to withdrawal or dose reduction of eryaspase. Sparse whole blood ASNase concentrations following 150 U/Kg were within the range of concentrations expected for this dose level. At 14 days following the first infusion, the range of whole blood ASNase was 111 to 1160 U/Kg, which would be equivalent to the trough (nadir) for infusions every 2 weeks. Mean and median plasma asparagine (ASN) concentrations over time demonstrated a reduction by approximately 50% at 3 days post eryaspase infusion, followed by a slow return toward baseline before the next infusion of eryaspase. Seventeen (94.4%) patients achieved CR at least once overall. Fourteen (77.8%) patients were alive at the end of the study. Survival rate was 88.9% at 6 months and 77.8% at 12 and 18 months. Conclusion The AE profile of eryaspase was consistent with other studies and was as expected for this cohort of patients. Serious AEs were generally consistent with those that would be expected in this study population. A total of 17 patients in the study achieved a CR at least once overall and 14 were still alive at the end of the study. This study evaluated additional asparaginase therapy in double (and even triple) allergic patient population, who have received prior E-Coli- or Erwinia-derived asparaginase therapy. All patients achieved target asparaginase activity. Therefore, eryaspase provides an additional option for patients for whom further ASNase treatment is contraindicated due to toxicity and/or immunization. Disclosures Boissel: Amgen: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; JAZZ Pharma: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Incyte: Honoraria; Servier: Consultancy, Honoraria; SANOFI: Honoraria; PFIZER: Consultancy, Honoraria; CELGENE: Honoraria. Recher: Daiichi Sankyo: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Macrogenics: Honoraria, Membership on an entity's Board of Directors or advisory committees; MaatPharma: Research Funding; Incyte: Honoraria; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astellas: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS/Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Agios: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. El-Hariry: Erytech: Current Employment, Current holder of stock options in a privately-held company.

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A Novel Prognostic Model That Is Superior to FLIPI-1 and FLIPI-2 and Integrates Clinical and Treatment Factors to Predict Progression-Free Survival and Early Treatment Failure in Patients with Follicular Lymphoma in the GALLIUM Trial

Blood ◽

10.1182/blood-2018-99-114620 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 2872-2872 ◽

Cited By ~ 2

Author(s):

Farheen Mir ◽

Andrew Grigg ◽

Michael Herold ◽

Wolfgang Hiddemann ◽

Robert Marcus ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Prognostic Model ◽

Low Risk ◽

Prognostic Variables ◽

Advisory Committees ◽

High Risk Disease ◽

Risk Patients ◽

Equity Ownership

Abstract Introduction: Progression of disease within 24 months of initial therapy (POD24) is associated with poor survival in patients with follicular lymphoma (FL). Existing prognostic models, such as FLIPI-1 and FLIPI-2, show poor sensitivity for POD24, and are derived from cohorts lacking bendamustine-treated patients. More accurate predictive models based on current standard therapies are needed to identify patients with high-risk disease. The Phase III GALLIUM trial (NCT01332968) compared the safety and efficacy of standard chemotherapy regimens plus rituximab (R) or obinutuzumab (G) in patients with previously untreated FL. Using GALLIUM data, we developed a novel risk stratification model to predict both PFS and POD24 in FL patients after first-line immunochemotherapy. Methods: Enrolled patients were aged ≥18 years with previously untreated FL (grades 1-3a), Stage III/IV disease (or Stage II with bulk), and ECOG PS ≤2, and required treatment by GELF criteria. Patients were randomized to receive either G- or R-based immunochemotherapy, followed by maintenance with the same antibody in responders. The chemotherapy arm (CHOP, CVP, or bendamustine) was selected by each study center. POD24 was defined as progressive disease or death due to disease within 24 months of randomization (noPOD24 = no progression or lymphoma-related death in that period). The most strongly prognostic variables, based on PFS hazard ratios, were estimated using penalized multivariate Cox regression methodology via an Elastic Net model. Selected variables were given equal weights, and a clinical score was formed by summating the number of risk factors for each patient. Low- and high-risk categories were determined using a cut-off that provided the best balance between true- and false-positives for PFS. PFS correlation and sensitivity to predict POD24 were assessed. The data used are from an updated GALLIUM efficacy analysis (data cut-off: April 2018; median follow-up: 57 months). Results: 1202 FL patients were enrolled. Based on data availability and biological plausibility (i.e. could reasonably be linked with high-risk disease), 25 potential clinical and treatment-related prognostic variables were entered into the Elastic Net model (Table). A model containing 11 factors was retained by the methodology and chosen as the best model (Table). Patients were categorized as 'low risk' if they scored between 0 and 3 (n=521/1000 patients with complete data) and as 'high risk' if they scored between 4 and 11 (n=479/1000 patients). At 2 years, the PFS rate was 84.5% in the whole FL population. Using our model, 2-year PFS for high-risk patients was 77% compared with 79.9% for FLIPI-1 and FLIPI-2. In low-risk patients, 2-year PFS was 92% compared with 87.9% for FLIPI-1 and 87.6% for FLIPI-2 (low-intermediate-risk patients). Our model increased the inter-group difference in 2-year PFS rate from 8% (FLIPI-1) and 7.7% (FLIPI-2) to 15%. At 3 years, the inter-group difference increased from 6.9% (FLIPI-1) and 9% (FLIPI-2) to 17% (Figure). Sensitivity for a high-risk score to predict POD24 was 73% using our model compared with 55% for FLIPI-1 and 52% for FLIPI-2 (based on 127 POD24 and 873 noPOD24 patients with complete data). Excluding patients who received CVP, which is now rarely used, resulted in an inter-group difference in PFS of 15% at 2 years and 16.8% at 3 years. A sensitivity analysis showed that inclusion of the 9 clinical factors only (i.e. removal of CVP and R treatment as variables) formed a more basic scoring system (low-risk patients, 1-3; high-risk patients, 4-9); the inter-group difference in PFS was 16.5% at 2 years and 17.6% at 3 years. However, sensitivity for POD24 decreased to 56%. Conclusion: Our clinical prognostic model was more accurate at discriminating patients likely to have poor PFS than either FLIPI-1 or FLIPI-2, and its prognostic value was sustained over time. Our model also identified the FL population at risk of POD24 with greater sensitivity. Variables such as age and bone marrow involvement were not retained by our model, and thus may not have a major impact in the current era of therapy. Factors such as sum of the products of lesion diameters were included, as this captures tumor burden more accurately than presence of bulk disease. Future studies will aim to improve the accuracy of the model by considering gene expression-based prognostic markers and DNA sequencing to form a combined clinico-genomic model. Disclosures Mir: F. Hoffmann-La Roche: Employment. Hiddemann:F. Hoffman-La Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Consultancy, Research Funding. Marcus:F. Hoffman-La Roche: Other: Travel support and lecture fees; Roche: Consultancy, Other: Travel support and lecture fees ; Gilead: Consultancy. Seymour:Genentech Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Consultancy; AbbVie: Consultancy, Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Bolen:Roche: Other: Ownership interests PLC*. Knapp:Roche: Employment. Launonen:Launonen: Other: Ownership interests none PLC; Travel, accommodation, expenses; Novartis: Consultancy, Equity Ownership, Other: Ownership interests none PLC; Travel. accommodation, expenses; Roche: Employment, Other: Travel, accommodation, expenses. Mattiello:Roche: Employment. Nielsen:F. Hoffmann-La Roche Ltd: Employment, Other: Ownership interests PLC. Oestergaard:Roche: Employment, Other: Ownership interests PLC. Wenger:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership, Other: Ownership interests PLC. Casulo:Gilead: Honoraria; Celgene: Research Funding.

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