early relapse
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2022 ◽  
Vol 2022 ◽  
pp. 1-3
Author(s):  
Ingolf Molle ◽  
Irma Petruskevicius ◽  
Peter Kamper ◽  
Francesco d’Amore

Treatment of early relapses of T lymphoblastic leukemia/lymphoma is often unsuccessful. We tested an experimental regimen containing daratumumab and nelarabine in two young patients with early relapses of T lymphoblastic lymphoma and T-ALL, respectively. Both patients achieved a deep complete remission. Combining daratumumab with chemotherapy may have a role in relapsing T lymphoblastic leukemia/lymphoma.


Leukemia ◽  
2022 ◽  
Author(s):  
Sriram Ravichandran ◽  
Steven Law ◽  
Shameem Mahmood ◽  
Brenden Wisniowski ◽  
Darren Foard ◽  
...  

2021 ◽  
Vol 66 (4) ◽  
pp. 512-525
Author(s):  
E. A. Mamaeva ◽  
L. P. Mendeleeva ◽  
M. V. Solovyev ◽  
M. V. Firsova ◽  
A. A. Kraizman ◽  
...  

Introduction. Autologous haematopoietic stem cell transplantation (auto-HSCT) is a highly effective treatment for multiple myeloma (MM). Auto-HSCT allows a signifi cant improvement of haematological response leading to higher overall survival and quality of life in MM patients. Nonetheless, the majority of patients develop relapse.Aim — a comparison of clinical MM relapses developing at variant terms after auto-HSCT.Patients and methods. A retrospective study enrolled 65 MM patients aged between 39 and 64 years. All patients had auto-HSCT during 2009–2019, all had achieved complete response (CR) or very good partial response (VGPR) and all since developed immunochemical MM relapse in laboratory evidence. Patients were divided in two cohorts by relapse term, the early (within 12 months of auto-HSCT) and late relapse.Results. Early immunochemical relapse was diagnosed in 13 (20 %), late relapse — in 52 (80 %) patients. The dependence between relapse term and depth of post-auto-HSCT antitumour response has been determined. The proportion of CR patients was signifi cantly higher in late than in early relapse (55.8 vs. 23 %). In follow-up, 60 patients (92.3 %) were initiated on antirelapse therapy, all early relapse and 90.3 % late relapse patients. On day +100 of auto-HSCT, CR patients had later relapse vs. VGPR individuals (median 24 vs. 19.9 months, p = 0.08) with signifi cantly weaker paraprotein secretion resembling the clinical course of monoclonal gammopathy of unclear signifi cance (MGUS).Conclusion. Auto-HSCT allows long-term control of the disease. A signifi cant prognostic factor is antitumour response on +100 day of auto-HSCT. Patients attaining CR have later relapse progressing in a MGUS-like manner. Patients with late indolent relapse can be managed long-term without antitumour therapy.


2021 ◽  
Vol 75 ◽  
pp. 102008
Author(s):  
Sherin A. Said ◽  
Reini W. Bretveld ◽  
Hendrik Koffijberg ◽  
Gabe S. Sonke ◽  
Roy F.P.M. Kruitwagen ◽  
...  

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 1261-1261
Author(s):  
Ing S Tiong ◽  
Sun Loo ◽  
Emad Uddin Abro ◽  
Devendra Hiwase ◽  
Shaun Fleming ◽  
...  

Abstract Introduction Rising molecular measurable residual disease (MRD) is an arbiter of clinical relapse in acute myeloid leukemia (AML). Venetoclax (VEN) is active against IDH and NPM1 mutant (mt) AML as monotherapy (Konopleva et al, 2016 and Chua et al, 2020) and can yield MRD negative remission when combined with low dose ara-C (LDAC) in patients unfit for intensive chemotherapy (DiNardo and Tiong et al, 2020). In a retrospective study, we showed that VEN in combination with hypomethylating agents or LDAC could erase rising NPM1mt MRD in 6/7 cases (Tiong et al, 2020). We now present a prospective phase 2 study of VEN and LDAC in patients with molecular MRD failure or oligoblastic AML relapse. Methods This multicenter phase 2 study stratified patients into oligoblastic relapse (marrow blasts 5-15%; Group A), or molecular MRD failure (Group B) as defined by the European LeukemiaNet (ELN) recommendations (failure confirmed by 2 interval samples) (Schuurhuis et al, 2018). Patients received VEN 600 mg (days 1-28) and LDAC 20 mg/m 2 (days 1-10). Primary objectives were morphologic or MRD response (≥1 log reduction) in groups A and B, respectively. Key secondary objectives were allogeneic hematopoietic cell transplantation (allo-HCT) realization and relapse-free (RFS) and overall survival (OS). The study had Alfred Health ethics approval (196/19). NPM1mt and other fusion transcript levels (per 10 5 ABL) from bone marrow were analyzed by RT-qPCR, IDH1 and IDH2 by Bio-Rad TM droplet digital PCR. Results The study enrolled 32 patients, with 29 evaluable (cut-off date 15/7/21). The median age of the study population was 62 years; 79% had intermediate cytogenetic risk, 66% NPM1mt, 11% FLT3-ITD and 37% IDH1/IDH2 mt. Most received prior intensive chemotherapy (93%) and 2 (7%) allo-HCT in first remission. Median interval from AML diagnosis to study entry was 12.6 months (Table 1). After a median follow-up of 7.9 months, patients had received a median of 3 cycles (range 1-14) of VEN-LDAC, with 13 patients ongoing. The main reasons for treatment cessation were allo-HCT (n=10; 34%) or donor lymphocyte infusion (n=2; 7%), treatment failure (n=3) or an adverse event (n=1). Hematologic complete/incomplete response (CR/CRi) among 11 patients with oligoblastic relapse (group A) was 73% and included: CR (n=5, 45%) or CRi (n=3, 27%), with an additional patient with morphologic leukemia-free state and 2 patients with stable disease. Overall, across both groups, median RFS and OS were not reached, estimated at 78% and 91% at 1 year, respectively. Among 18 patients with molecular MRD failure (group B) treated with VEN+LDAC, molecular response (≥1 log reduction) was achieved in 72%, and the RFS and OS were estimated at 83% and 87% at 1 year, respectively. Analysis of a sub-group of patients with NPM1mt (n=18); 6 and 12 from Groups A and B, respectively revealed the median NPM1mt transcript level at study entry to be 8985 copies (IQR 826, 94,431). A molecular response was achieved in 14 (78%) patients, including 9 (50%) with complete molecular remission (CR MRD-), with most responses achieved within 2 cycles of therapy (Figure B). Treatment with VEN-LDAC was generally well tolerated, with 15 serious adverse events reported within the first 2 cycles, including infection (n=6; 19%) and febrile neutropenia (n=3; 9%). Only one subject discontinued treatment due to stroke. Conclusions In this prospective study, in patients with first oligoblastic relapse or MRD failure, VEN in combination with LDAC induced a high rate of molecular MRD remission that was rapidly achieved, resulting in a high rate of survival at 12-months (>90%) and with low toxicity. Follow-up is ongoing to determine the durability of response. Treatment of patients with MRD or early clinical failure may represent an attractive clinical trial setting for investigation of novel, non-intensive AML therapies. This approach will be investigated in a future multi-arm, precision-based platform trial called INTERCEPT (Investigating Novel Therapy to Target Early Relapse and Clonal Evolution as Pre-emptive Therapy in AML). Figure 1 Figure 1. Disclosures Tiong: Servier: Consultancy, Speakers Bureau; Amgen: Speakers Bureau; Pfizer: Consultancy. Hiwase: Novartis: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees. Fleming: Amgen Inc: Research Funding. Bajel: Amgen: Speakers Bureau; Abbvie, Amgen, Novartis, Pfizer: Honoraria. Fong: Amgen, BMS: Speakers Bureau; Amgen: Research Funding; AbbVie, Amgen, Novartis, Pfizer, Astellas: Honoraria. Wei: Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Agios: 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, Speakers Bureau; Genentech: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Astellas: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Macrogenics: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees, Research Funding. OffLabel Disclosure: This presentation will discuss the use of venetoclax in targeting measurable residual disease and early relapse of acute myeloid leukemia.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3577-3577
Author(s):  
Aino Launonen ◽  
Rodrigo Ho ◽  
Andrea Knapp ◽  
Irene Canales Ruiz ◽  
Leonardo Simonella ◽  
...  

Abstract Background: Most patients (pts) with diffuse large B-cell lymphoma (DLBCL) receiving first-line (1L) rituximab plus CHOP (R-CHOP) have similar mortality to the general population (gen popn) if they are progression-free at 24 months (PFS24; Maurer et al. Ann Oncol 2018). Characterization of quality of life (QoL) and clinical outcomes may enable more patient-relevant treatment decisions. Using GOYA trial data (NCT01287741) comparing obinutuzumab (G) + CHOP (G-CHOP) with R-CHOP, we present an exploratory analysis of 1L DLBCL pts with IPI 2-5 and assess overall survival (OS) and QoL relative to the gen popn. GOYA was not included in the previous PFS24 analysis by Maurer et al. Methods: We used data from both GOYA treatment arms to identify pts with IPI 2-5 DLBCL (n=1132 pts, intent-to-treat popn). Post-progression survival (PPS) in DLBCL is independent of prior treatment (Coiffier et al. Blood 2010) and as PFS was similar between treatment arms in GOYA, we assumed similar mortality after PFS24. Clinical outcomes were PFS24 (progression-free ≥24 months [m] from treatment start); early relapse (disease progression [PD]<24m from treatment start); late relapse (PD after PFS24). Outcomes for study pts vs gen popn were evaluated using standardized mortality ratios (SMR; deaths in study pts relative to expected deaths in gen popn matched by age, sex, country, and calendar time-at-risk). Expected deaths were derived using the Human Mortality Database, which provides detailed mortality and population data by country and can be used to estimate the background mortality during the observation period. Post-relapse survival in pts with early vs late relapse was assessed using Kaplan-Meier (KM) estimates and Cox regression. QoL was assessed using EQ-5D-3L and UK-based tariffs (Dolan. Med Care 1997); association between QoL and clinical outcomes used a linear mixed-effects model. The proportion of pts with PFS24 reporting QoL problems at baseline and after 24m was compared with age- and country-matched values in the gen popn (Janssen et al. Springer 2014). Data cut-off was Jan 2018 (GOYA final data cut); overall median follow-up was 48m. Results: In the overall IPI 2-5 population, mean age at treatment initiation was 61 yrs. 711 pts reached PFS24, of whom 64 experienced a late relapse (Table 1). Early relapse was experienced by 261 pts, of whom 164 were <6 months from end of treatment (EOT). OS following PFS24 was 98.6% at 2 years (including patients who later relapsed). 2-year PPS was 35.7% for pts with early relapse vs 74.8% for patients with late relapse (Figure 1.) Mortality following PFS24 was 72% of the matched gen popn (SMR 0.72; not significant: 95% CI 0.44-1.11). Mortality following relapse in pts who experienced early relapse was over 33 times higher than expected in the matched gen popn (SMR 33.57, 95% CI 27.69-40.33). However, risk of death following late relapse was reduced by 78% compared with risk following early relapse (HR 0.22 95 CI% 0.12-0.40), and mortality following late relapse was significantly higher than in the matched gen popn (SMR 6.7, 95% CI 3.05-12.67). Mean QoL utility score at baseline was 0.69 for all pts. After pts reached PFS24, estimated mean utility score was 0.86 (95% CI 0.84-0.87) and worsened by -0.07 (95% CI -0.14 to -0.01) at time of subsequent relapse. For early-relapsing pts, the worsening in utility was -0.15 (95% CI -0.20 to -0.10) compared with those still progression-free (Table 2). Among all PFS24 pts at baseline, problems were reported with mobility (28.1%), self-care (12.6%), usual activities (41.8%), pain/discomfort (62.7%), and anxiety/depression (48.8%); these rates were 2.2-4.7 times higher than the gen popn based on age- and country-standardized values. Compared with the gen popn, after pts reached PFS24, pain/discomfort was 10% lower, whereas anxiety/depression was 34% higher and other QoL items were approximately 20% higher. Conclusions: Most of the clinical course of 1L DLBCL occurred ≤2 years after start of treatment. In DLBCL pts with IPI 2-5 achieving PFS24, mortality was similar to the gen popn, and with the exception of mental health metrics, QoL scores were also similar to the gen popn. Late relapse (≥2 yrs) was associated with better post-relapse survival than early relapse (<2 yrs); however, this was inferior to the gen popn. Health state utilities improved whilst patients were relapse-free but the decline in QoL after early relapse was worse than after late relapse. Figure 1 Figure 1. Disclosures Launonen: F. Hoffmann-La Roche Ltd: Current Employment. Ho: F. Hoffmann-La Roche Ltd: Current Employment. Knapp: F. Hoffmann-La Roche Ltd: Current Employment. Canales Ruiz: Clinical Project Manager in Clinica Universidad de Navarra: Current Employment. Simonella: F. Hoffmann-La Roche Ltd: Current Employment. Thuresson: F. Hoffmann-La Roche Ltd: Current Employment, Current equity holder in publicly-traded company.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3937-3937
Author(s):  
Meral Beksac ◽  
Simona Iacobelli ◽  
Linda Koster ◽  
Didier Blaise ◽  
Jan J. Cornelissen ◽  
...  

Abstract Rationale and Aim: In patients with Myeloma, early relapse following Autologous Haematopoietic Cell Transplantation (Auto-HCT) is a poor prognostic marker. Two groups have published scoring systems to predict early relapse. The CIBMTR score is based on cytogenetics, the bone marrow plasma cell percentage at the time of Auto-HCT and serum albumin. The GIMEMA Simplified early relapse in multiple myeloma (S-ERMM) score is a cumulative score based on a raised serum lactate dehydrogenase (LDH), t(4;14), del17p, low albumin, bone marrow plasma percentage >60%, and lambda light chain. The aim of the current study was to develop a scoring system to predict early relapse post-Auto-HSCT-1 using readily available variables. Study design and statistics: Within the EBMT database, there were 8,206 patients meeting the following eligibility criteria: First auto transplant 2014-2019, Known sex, ISS at diagnosis, cytogenetics analysis at diagnosis, disease status at Auto-HCT, Interval diagnosis-Auto-HCT > 1 month and <= 12 months, conditioning with Melphalan 200 mg/m2 and known information on relapse; tandem auto-allo patients were excluded. The analysis consisted of two steps: (1) Training: modeling based on 4,389 patients (611 events for PFS12) transplanted between 2014 and 2017, with internal validation carried out by bootstrapping; and (2) Testing: the models obtained were applied to 3,817 patients (346 events for PFS12) transplanted in 2018 and 2019 for external validation. The characteristics of the two cohorts are first reported separately and then together (Table 1). Possible adjustment factors analyzed for the prognostic model included Age at Auto-HCT, Known sex, ISS at diagnosis, disease status at Auto-HCT, and time from diagnosis to Auto-HCT. Complete cytogenetic information was not available at the time of this analysis and will be included in the later analysis. The shape of the effect of age and of time from diagnosis to Auto-HCT was investigated both by the analysis of residuals and by applying boot-strap backward selection among different alternatives. The final results were confirmed in a robustness analysis excluding patients undergoing tandem Auto-HCT. Results: Comparison of the training and validation cohorts revealed no relevant differences (Table 1). Importantly, OS and PFS of both cohorts were overlapping with the probability of PFS at 12 months being 83.3% and 86.8%, respectively. The cumulative incidence of relapse at 12 month was 15.7% and 12.1%, respectively. Among patients who relapsed early, this occurred at a median of 6.64 months (0.56-11.99) in the first cohort, and at 5.85 months (0.1- 11.99) in the second cohort. The final model included (1) disease status at Auto-HCT, (2) age at Auto-HCT, and (3) ISS at diagnosis. Considering the order of magnitude of the coefficients, the points attributed in the risk score were: 0 for CR or VGPR; 1 for PR or SD/MR; 3 for Rel/Prog; 0 / 1/ 2 respectively for ISS I / II / III and -1 for Age<=55 yrs; -2 for Age (55-75 yrs]; -3 for Age>=75 yrs. The Hazard Ratio for a +1 point is 1.52 i.e. the risk of early relapse/death increased on average by 52% for each additional point in the score. The distribution of risk scores was as follows: Score= -2 (n=757), -1 (n=1,481), 0 (n=1,358), 1 (n=647), and 2 (n=146). The score allows separation of the PFS12 curves (Figure 1), with the lowest risk group (N=757) having a PFS at 12 months of 91%, and the highest risk group (N=146) having a PFS at 12 months of 65%. Despite some minor differences in the risk factors between the training and validation cohorts, the score has a similar average effect (HR=1.48 i.e. + 48% hazard for each additional point) and worked well in separating the curves, in particular in identifying the patients at high risk of early relapse. Discussion and conclusion: The new EBMT score to predict early relapse post-Auto-HCT uses the easily available variables of age and ISS stage at diagnosis as well as the dynamic variable of response to induction. With this simple approach, we were able to clearly identify patients at high risk of early relapse. To our surprise, older age emerged as a protective factor against relapse. This may reflect a relative selection bias in that older patients with higher risk disease may not have been selected for transplant. Impact of cytogenetics will be presented at the Congress. In conclusion, this novel scoring system is robust and easy to use in routine daily practice. Figure 1 Figure 1. Disclosures Beksac: Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Sanofi: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Oncopeptides: Consultancy. Blaise: Jazz Pharmaceuticals: Honoraria. Leleu: Karyopharm Therapeutics: Honoraria; AbbVie: Honoraria; Bristol-Myers Squibb: Honoraria; Amgen: Honoraria; Merck: Honoraria; Mundipharma: Honoraria; Novartis: Honoraria; Carsgen Therapeutics Ltd: Honoraria; Oncopeptides: Honoraria; Janssen-Cilag: Honoraria; Gilead Sciences: Honoraria; Celgene: Honoraria; Pierre Fabre: Honoraria; Roche: Honoraria; Sanofi: Honoraria; Takeda: Honoraria, Other: Non-financial support. Forcade: Novartis: Consultancy, Other: Travel Support, Speakers Bureau; Gilead: Other: Travel Support, Speakers Bureau; Jazz: Other: Travel Support, Speakers Bureau; MSD: Other: Travel Support. Rabin: Janssen: Consultancy, Honoraria, Other: Travel support for meetings; BMS / Celgene: Consultancy, Honoraria, Other: Travel support for meetings; Takeda: Consultancy, Honoraria, Other: Travel support for meetings. Kobbe: Celgene: Research Funding. Sossa: Amgen: Research Funding. Hayden: Jansen, Takeda: Other: Travel, Accomodation, Expenses; Amgen: Honoraria. Schoenland: Pfizer: Honoraria; sanofi: Research Funding; janssen,Prothena,Takeda,: Consultancy, Honoraria. Yakoub-Agha: Jazz Pharmaceuticals: Honoraria.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3462-3462
Author(s):  
Luis Miguel Veiga Veiga Nobre ◽  
Salvatore Federico Pedicona ◽  
Arran Dokal ◽  
Andrea Arruda ◽  
Ryan Smith ◽  
...  

Abstract Background: Midostaurin is approved for FLT3 mutant-positive (FLT3+) acute myeloid leukemia (AML), however efficacy has also been observed in a subpopulation of FLT3 mutant-negative AML, suggesting that FLT3 mutation is not the only determinant conferring midostaurin sensitivity. Casado et al previously described phosphoprotein signatures significantly associated with ex vivo responses to midostaurin in primary AML blasts (Casado et al Leukaemia 2018). In the current study, we tested whether our signatures could group FLT3+ patients based on clinical responses to midostaurin plus chemotherapy. Methods: FLT3+ bone marrow (BM) and peripheral blood (PB) specimens were collected at diagnosis, post-treatment and relapse (n=54 cases) from the Leukemia Tissue Bank at Princess Margaret Cancer Centre. All patients in this study were treated with standard chemotherapy plus midostaurin. Protein/phosphoprotein-signatures for BM and PB samples were analysed independently. Case-studies with multiple post-treatment time-points or relapse events following second line treatments were also analysed. Peptides (proteomics) and enriched phosphopeptides (phosphoproteomics) were quantified using liquid chromatography - tandem mass spectrometry. A classification machine learning (ML) algorithm was trained to group patients based on response to treatment as a function of protein/phosphoprotein-signature status. Other features (e.g. genetic mutations, HSC-transplant) were also analysed. Differential survival analysis between patient groups was carried out with Kaplan-Meier and Log Rank test methods. Pathways upregulated in post-treatment or relapse specimens, particularly from those cases that responded poorly to chemo + midostaurin (i.e. early relapse / refractory disease) were investigated using enrichment statistical methods including kinase-substrate enrichment analysis (KSEA) and gene ontology analysis and identified as potential mechanisms of resistance. Statistical significance of enrichment was determined using parametric methods and p-values adjusted for multiple testing using the Benjamini-Hochberg method. Results: ML models were developed based on the ex-vivo phosphoproteomics signatures described in the Casado et al study, from which we trained a predictive model (model 1). Patients positive for model 1 exhibited a survival probability of 243 weeks, compared to 126 weeks in signature negative patients (averages by geometric mean, Log Rank p = 9.88e-05). As the patients in the current study received chemotherapy, in addition to midostaurin, we identified a new phosphoproteomic signature consisting of 26 phospho-sites which partially overlapped with the ex-vivo signature. Patients positive for this new phosphoproteomic signature showed a markedly longer survival time than negative patients (269 vs 76 weeks, Log Rank p = 1.30e-05 for PB and 241 vs 56, Log Rank p = 2.13e-09 for BM specimens, Table). A proteomic signature was also identified in the current study. Positive patients showed a longer survival time than negative patients (330 vs 173 weeks, Log Rank p = 5.0e-04 for PB and 460 vs 156, Log Rank p = 5.2e-06 for BM specimens, Table), however this was less differentiating than the phosphoproteomic signature. Pathways upregulated in post-treatment or relapse specimens from early relapse or refractory cases were associated with molecular functions such as cell proliferation, anti-apoptosis, non-homologous end-joining, transcriptional regulation, spliceosome and cytoskeleton remodelling. Conclusions: We have identified protein and phosphoprotein signatures with the potential to further stratify AML for midostaurin treatment. Phosphoproteomic signatures differentiated according to response better than the proteomic signatures. Pathways upregulated in relapse/refractory cases may have a role in resistance and this will be determined in follow up studies. Analysis will also be performed on FLT3 mutant-negative cases to validate the signatures and elucidate mechanisms of resistance in this group. Disclosures Veiga Nobre: Kinomica Ltd.: Current Employment. Minden: Astellas: Consultancy. Gribben: Janssen: Honoraria, Research Funding; AZ: Honoraria, Research Funding; Abbvie: Honoraria; BMS: Honoraria; Gilead/Kite: Honoraria; Morphosys: Honoraria; Novartis: Honoraria; Takeda: Honoraria; TG Therapeutics: Honoraria. Britton: Kinomica Ltd.: Current Employment, Current equity holder in publicly-traded company.


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