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Open accessJournal ArticleDOI: 10.1001/JAMA.2021.0669

Effect of Postreinduction Therapy Consolidation With Blinatumomab vs Chemotherapy on Disease-Free Survival in Children, Adolescents, and Young Adults With First Relapse of B-Cell Acute Lymphoblastic Leukemia: A Randomized Clinical Trial

02 Mar 2021-JAMA (American Medical Association)-Vol. 325, Iss: 9, pp 833-842
Abstract: Importance Standard chemotherapy for first relapse of B-cell acute lymphoblastic leukemia (B-ALL) in children, adolescents, and young adults is associated with high rates of severe toxicities, subsequent relapse, and death, especially for patients with early relapse (high risk) or late relapse with residual disease after reinduction chemotherapy (intermediate risk). Blinatumomab, a bispecific CD3 to CD19 T cell-engaging antibody construct, is efficacious in relapsed/refractory B-ALL and has a favorable toxicity profile. Objective To determine whether substituting blinatumomab for intensive chemotherapy in consolidation therapy would improve survival in children, adolescents, and young adults with high- and intermediate-risk first relapse of B-ALL. Design, setting, and participants This trial was a randomized phase 3 clinical trial conducted by the Children's Oncology Group at 155 hospitals in the US, Canada, Australia, and New Zealand with enrollment from December 2014 to September 2019 and follow-up until September 30, 2020. Eligible patients included those aged 1 to 30 years with B-ALL first relapse, excluding those with Down syndrome, Philadelphia chromosome-positive ALL, prior hematopoietic stem cell transplant, or prior blinatumomab treatment (n = 669). Interventions All patients received a 4-week reinduction chemotherapy course, followed by randomized assignment to receive 2 cycles of blinatumomab (n = 105) or 2 cycles of multiagent chemotherapy (n = 103), each followed by transplant. Main outcome and measures The primary end point was disease-free survival and the secondary end point was overall survival, both from the time of randomization. The threshold for statistical significance was set at a 1-sided P Results Among 208 randomized patients (median age, 9 years; 97 [47%] females), 118 (57%) completed the randomized therapy. Randomization was terminated at the recommendation of the data and safety monitoring committee without meeting stopping rules for efficacy or futility; at that point, 80 of 131 planned events occurred. With 2.9 years of median follow-up, 2-year disease-free survival was 54.4% for the blinatumomab group vs 39.0% for the chemotherapy group (hazard ratio for disease progression or mortality, 0.70 [95% CI, 0.47-1.03]); 1-sided P = .03). Two-year overall survival was 71.3% for the blinatumomab group vs 58.4% for the chemotherapy group (hazard ratio for mortality, 0.62 [95% CI, 0.39-0.98]; 1-sided P = .02). Rates of notable serious adverse events included infection (15%), febrile neutropenia (5%), sepsis (2%), and mucositis (1%) for the blinatumomab group and infection (65%), febrile neutropenia (58%), sepsis (27%), and mucositis (28%) for the chemotherapy group. Conclusions and relevance Among children, adolescents, and young adults with high- and intermediate-risk first relapse of B-ALL, postreinduction treatment with blinatumomab compared with chemotherapy, followed by transplant, did not result in a statistically significant difference in disease-free survival. However, study interpretation is limited by early termination with possible underpowering for the primary end point. Trial registration Identifier: NCT02101853.

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Topics: Blinatumomab (63%), Chemotherapy regimen (56%), Febrile neutropenia (55%) ... read more

24 results found

Open accessJournal ArticleDOI: 10.3390/JCM10091926
Hiroto Inaba1, Ching-Hon Pui2, Ching-Hon Pui1Institutions (2)
Abstract: The outcomes of pediatric acute lymphoblastic leukemia (ALL) have improved remarkably during the last five decades. Such improvements were made possible by the incorporation of new diagnostic technologies, the effective administration of conventional chemotherapeutic agents, and the provision of better supportive care. With the 5-year survival rates now exceeding 90% in high-income countries, the goal for the next decade is to improve survival further toward 100% and to minimize treatment-related adverse effects. Based on genome-wide analyses, especially RNA-sequencing analyses, ALL can be classified into more than 20 B-lineage subtypes and more than 10 T-lineage subtypes with prognostic and therapeutic implications. Response to treatment is another critical prognostic factor, and detailed analysis of minimal residual disease can detect levels as low as one ALL cell among 1 million total cells. Such detailed analysis can facilitate the rational use of molecular targeted therapy and immunotherapy, which have emerged as new treatment strategies that can replace or reduce the use of conventional chemotherapy.

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7 Citations

Open accessJournal ArticleDOI: 10.1016/J.EJCA.2021.03.034
Abstract: Aim Outcomes of children with high-risk (HR) relapsed acute lymphoblastic leukaemia (ALL) (N = 393), recruited to ALLR3 and ALL-REZ BFM 2002 trials, were analysed. Minimal residual disease (MRD) was assessed after induction and at predetermined time points until haematopoietic stem cell transplantation (SCT). Methods Genetic analyses included karyotype, copy-number alterations and mutation analyses. Ten-year survivals were analysed using Kaplan-Meier and Cox models for multivariable analyses. Results Outcomes of patients were comparable in ALLR3 and ALL-REZ BFM 2002. The event-free survival of B-cell precursor (BCP) and T-cell ALL (T-ALL) was 22.6% and 26.2% (P = 0.94), respectively, and the overall survival (OS) was 32.6% and 28.2% (P = 0.11), respectively. Induction failures (38%) were associated with deletions of NR3C1 (P = 0.002) and BTG1 (P = 0.03) in BCP-ALL. The disease-free survival (DFS) and OS in patients with good vs poor MRD responses were 57.4% vs 22.6% (P Conclusion Improvements in outcomes for HR ALL relapses require novel compounds in induction therapy to improve remission rates and immune targeted therapy after induction to maintain remission after SCT. Trial registration ALLR3: NCT00967057 ; ALL REZ-BFM 2002: NCT00114348

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2 Citations

Journal ArticleDOI: 10.1080/14656566.2021.1931683
Abstract: Introduction: Despite the significant survival improvement in childhood acutelymphoblastic leukemia (ALL), 15-20% of patients continue to relapse; outcomes following relapse remain suboptimal and have room for further improvement. Advances in genomics have shed new insights on the biology of ALL, led to the discovery of novel genomically defined ALL subtypes, refined prognostic significance and revealed new therapeutic vulnerabilities.Areas covered: In this review, the authors provide an overview of the genomic landscape of childhood ALL and highlight recent advances in molecular-based and antibody-based pharmacological approaches in the treatment of childhood ALL, from emerging preclinical evidence to published results of completed clinical trials.Expert opinion: Molecularly targeted therapies and immunotherapies have expanded the horizons of ALL therapy and represent promising therapeutic avenues for high-risk and relapsed/refractory ALL. These novel therapies are now moving into frontline ALL therapy and may define new treatment paradigms that aim to further improve survival and reduce chemotherapy-related toxicities in the management of pediatric ALL.

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1 Citations

Open accessJournal ArticleDOI: 10.3390/JCM10122544
Manon Queudeville1, Martin Ebinger1Institutions (1)
Abstract: Acute lymphoblastic leukemia is by far the most common malignancy in children, and new immunotherapeutic approaches will clearly change the way we treat our patients in future years. Blinatumomab is a bispecific T-cell-engaging antibody indicated for the treatment of relapsed/refractory acute lymphoblastic leukemia (R/R-ALL). The use of blinatumomab in R/R ALL has shown promising effects, especially as a bridging tool to hematopoietic stem cell transplantation. For heavily pretreated patients, the response to one or two cycles of blinatumomab ranges from 34% to 66%. Two randomized controlled trials have very recently demonstrated an improved reduction in minimal residual disease as well as an increased survival for patients treated with blinatumomab compared to standard consolidation treatment in first relapse. Current trials using blinatumomab frontline for high-risk patients or as a consolidation treatment post-transplant will show whether efficacy is even higher in less heavily pretreated patients. Due to the distinct pattern of adverse events compared to high-dose conventional chemotherapy, blinatumomab could play an important role for patients with a risk for severe chemotherapy-associated toxicities. This systematic review discusses all published results for blinatumomab in children as well as all ongoing clinical trials.

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Topics: Blinatumomab (77%), Minimal residual disease (52%)

1 Citations


26 results found

Journal ArticleDOI: 10.1093/BIOMET/81.3.515
Patricia Grambsch1, Terry M. Therneau2Institutions (2)
01 Sep 1994-Biometrika
Abstract: SUMMARY Nonproportional hazards can often be expressed by extending the Cox model to include time varying coefficients; e.g., for a single covariate, the hazard function for subject i is modelled as exp { fl(t)Zi(t)}. A common example is a treatment effect that decreases with time. We show that the function /3(t) can be directly visualized by smoothing an appropriate residual plot. Also, many tests of proportional hazards, including those of Cox (1972), Gill & Schumacher (1987), Harrell (1986), Lin (1991), Moreau, O'Quigley & Mesbah (1985), Nagelkerke, Oosting & Hart (1984), O'Quigley & Pessione (1989), Schoenfeld (1980) and Wei (1984) are related to time-weighted score tests of the proportional hazards hypothesis, and can be visualized as a weighted least-squares line fitted to the residual plot.

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4,183 Citations

Journal ArticleDOI: 10.1080/00401706.1982.10487769
01 Aug 1982-Technometrics
Abstract: Preface.1. Introduction.1.1 Failure Time Data.1.2 Failure Time Distributions.1.3 Time Origins, Censoring, and Truncation.1.4 Estimation of the Survivor Function.1.5 Comparison of Survival Curves.1.6 Generalizations to Accommodate Delayed Entry.1.7 Counting Process Notation.Bibliographic Notes.Exercises and Complements.2. Failure Time Models.2.1 Introduction.2.2 Some Continuous Parametric Failure Time Models.2.3 Regression Models.2.4 Discrete Failure Time Models.Bibliographic Notes.Exercises and Complements.3. Inference in Parametric Models and Related Topics.3.1 Introduction.3.2 Censoring Mechanisms.3.3 Censored Samples from an Exponential Distribution.3.4 Large-Sample Likelihood Theory.3.5 Exponential Regression.3.6 Estimation in Log-Linear Regression Models.3.7 Illustrations in More Complex Data Sets.3.8 Discrimination Among Parametric Models.3.9 Inference with Interval Censoring.3.10 Discussion.Bibliographic Notes.Exercises and Complements.4. Relative Risk (Cox) Regression Models.4.1 Introduction.4.2 Estimation of beta.4.3 Estimation of the Baseline Hazard or Survivor Function.4.4 Inclusion of Strata.4.5 Illustrations.4.6 Counting Process Formulas. 4.7 Related Topics on the Cox Model.4.8 Sampling from Discrete Models.Bibliographic Notes.Exercises and Complements.5. Counting Processes and Asymptotic Theory.5.1 Introduction.5.2 Counting Processes and Intensity Functions.5.3 Martingales.5.4 Vector-Valued Martingales.5.5 Martingale Central Limit Theorem.5.6 Asymptotics Associated with Chapter 1.5.7 Asymptotic Results for the Cox Model.5.8 Asymptotic Results for Parametric Models.5.9 Efficiency of the Cox Model Estimator.5.10 Partial Likelihood Filtration.Bibliographic Notes.Exercises and Complements.6. Likelihood Construction and Further Results.6.1 Introduction.6.2 Likelihood Construction in Parametric Models.6.3 Time-Dependent Covariates and Further Remarks on Likelihood Construction.6.4 Time Dependence in the Relative Risk Model.6.5 Nonnested Conditioning Events.6.6 Residuals and Model Checking for the Cox Model.Bibliographic Notes.Exercises and Complements.7. Rank Regression and the Accelerated Failure Time Model.7.1 Introduction.7.2 Linear Rank Tests.7.3 Development and Properties of Linear Rank Tests.7.4 Estimation in the Accelerated Failure Time Model.7.5 Some Related Regression Models.Bibliographic Notes.Exercises and Complements.8. Competing Risks and Multistate Models.8.1 Introduction.8.2 Competing Risks.8.3 Life-History Processes.Bibliographic Notes.Exercises and Complements.9. Modeling and Analysis of Recurrent Event Data.9.1 Introduction.9.2 Intensity Processes for Recurrent Events.9.3 Overall Intensity Process Modeling and Estimation.9.4 Mean Process Modeling and Estimation.9.5 Conditioning on Aspects of the Counting Process History.Bibliographic Notes.Exercises and Complements.10. Analysis of Correlated Failure Time Data.10.1 Introduction.10.2 Regression Models for Correlated Failure Time Data.10.3 Representation and Estimation of the Bivariate Survivor Function.10.4 Pairwise Dependency Estimation.10.5 Illustration: Australian Twin Data.10.6 Approaches to Nonparametric Estimation of the Bivariate Survivor Function.10.7 Survivor Function Estimation in Higher Dimensions.Bibliographic Notes.Exercises and Complements.11. Additional Failure Time Data Topics.11.1 Introduction.11.2 Stratified Bivariate Failure Time Analysis.11.3 Fixed Study Period Survival Studies.11.4 Cohort Sampling and Case-Control Studies.11.5 Missing Covariate Data.11.6 Mismeasured Covariate Data.11.7 Sequential Testing with Failure Time Endpoints.11.8 Bayesian Analysis of the Proportional Hazards Model.11.9 Some Analyses of a Particular Data Set.Bibliographic Notes.Exercises and Complements.Glossary of Notation.Appendix A: Some Sets of Data.Appendix B: Supporting Technical Material.Bibliography.Author Index.Subject Index.

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Topics: Accelerated failure time model (64%), Survival function (59%), Proportional hazards model (58%) ... read more

3,596 Citations

Journal ArticleDOI: 10.2307/2530245
Peter C. O'Brien1, Thomas R. Fleming1Institutions (1)
01 Sep 1979-Biometrics
Abstract: A multiple testing procedure is proposed for comparing two treatments when response to treatment is both dichotomous (i.e., success or failure) and immediate. The proposed test statistic for each test is the usual (Pearson) chi-square statistic based on all data collected to that point. The maximum number (N) of tests and the number (m1 + m2) of observations collected between successive tests is fixed in advance. The overall size of the procedure is shown to be controlled with virtually the same accuracy as the single sample chi-square test based on N(m1 + m2) observations. The power is also found to be virtually the same. However, by affording the opportunity to terminate early when one treatment performs markedly better than the other, the multiple testing procedure may eliminate the ethical dilemmas that often accompany clinical trials.

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Topics: Test statistic (56%), Statistic (51%), Pocock boundary (51%)

2,778 Citations

Open accessJournal ArticleDOI: 10.1056/NEJMOA1709866
Shannon L. Maude1, Theodore W. Laetsch2, Jochen Buechner3, S. Rives4  +31 moreInstitutions (23)
Abstract: Background In a single-center phase 1–2a study, the anti-CD19 chimeric antigen receptor (CAR) T-cell therapy tisagenlecleucel produced high rates of complete remission and was associated with serious but mainly reversible toxic effects in children and young adults with relapsed or refractory B-cell acute lymphoblastic leukemia (ALL) Methods We conducted a phase 2, single-cohort, 25-center, global study of tisagenlecleucel in pediatric and young adult patients with CD19+ relapsed or refractory B-cell ALL The primary end point was the overall remission rate (the rate of complete remission or complete remission with incomplete hematologic recovery) within 3 months Results For this planned analysis, 75 patients received an infusion of tisagenlecleucel and could be evaluated for efficacy The overall remission rate within 3 months was 81%, with all patients who had a response to treatment found to be negative for minimal residual disease, as assessed by means of flow cytometry The rates of event-f

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Topics: Minimal residual disease (61%), Blinatumomab (53%)

2,044 Citations

Journal ArticleDOI: 10.1093/BIOMET/70.3.659
01 Dec 1983-Biometrika
Abstract: SUMMARY Pocock (1977), O'Brien & Fleming (1979) and Slud & Wei (1982) have proposed different methods to construct discrete sequential boundaries for clinical trials. These methods require that the total number of decision times be specified in advance. In the present paper, we propose a more flexible way to construct discrete sequential boundaries. The method is based on the choice of a function, a*(t), which characterizes the rate at which the error level ac is spent. The boundary at a decision time is determined by a*(t), and by past and current decision times, but does not depend on the future decision times or the total number of decision times.

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1,840 Citations

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