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Safe and Effective Treatment of Patients with Relapsed or Refractory Peripheral T-Cell Lymphoma (PTCL) and Low Baseline Platelet Counts with Belinostat

2014· article· en· W2486896794 on OpenAlexaff
Kerry J. Savage, Steven M. Horwitz, Pier Luigi Zinzani, Achiel Van Hoof, Sarit Assouline, Gajanan Bhat, Mi Rim Choi, Lee F. Allen, Dina Ben‐Yehuda, Wojciech Jurczak, Tamás Masszi, Andrei R. Shustov

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHistone Deacetylase Inhibitors Research
Canadian institutionsMcGill UniversityBC Cancer Agency
Fundersnot available
KeywordsMedicineInternal medicineTolerabilityPeripheral T-cell lymphomaClinical endpointVincristineClinical trialPrednisoneGastroenterologyCyclophosphamideCHOPLymphomaRefractory (planetary science)OncologyAdverse effectSurgeryChemotherapyImmunologyT cellImmune system

Abstract

fetched live from OpenAlex

Abstract Background: Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of non-Hodgkin lymphomas associated with a poor prognosis for most subtypes. Anthracycline-based therapies such as cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) are commonly used for frontline treatment of PTCL; however, durable remissions are uncommon with these regimens. Patients with relapsed or refractory (R/R) PTCL and platelet counts <100,000/µL typically have poorer outcomes, and often are not eligible to participate in clinical trials or require dose reductions to safely administer many of the currently approved agents in this setting. Thus, it is important to identify appropriate treatment strategies for these patients, particularly in the salvage setting. Belinostat (Beleodaq) is a potent, pan-histone deacetylase inhibitor that was recently approved in the United States for the treatment of patients with R/R PTCL. Approval was based on results from the pivotal Phase 2 BELIEF study of belinostat in R/R PTCL (N = 129 enrolled, N = 120 evaluable), which demonstrated durable clinical benefit (objective response rate [ORR] 25.8%) and tolerability. This analysis presents BELIEF study data for the subgroup of patients who had thrombocytopenia (<100,000/µL) at study entry (n = 24 enrolled, n = 20 evaluable). Methods: Patients with R/R PTCL received belinostat as a 1000 mg/m2 intravenous infusion on Days 1-5 of 21-day cycles. The primary endpoint of the study was ORR (complete response [CR] + partial response [PR]) determined by an Independent Review Committee. For this subset analysis, efficacy and safety data for the 20 evaluable patients with low baseline platelet counts were examined and compared to the overall study population. Results : For both the low baseline platelet count (<100,000/µL) subgroup (n = 20 evaluable) and the overall evaluable study population, a median of 2.0 treatment cycles and 10.0 belinostat doses were administered, with a relative dose intensity of 98.5% and 98.3%, respectively. Baseline bone marrow involvement was present for 50% of patients with low baseline platelet counts and 29% of the overall population. For 2/20 patients, the belinostat dose was reduced for low platelets. The ORR in the low baseline platelet count subgroup was 15%, with 2 PRs and 1 CR. The median duration of response by International Working Group criteria was 4.1 months, with a median overall survival of 4.3 months and median progression-free survival of 1.3 months, based on a median follow-up of 11.2 months (Table). The majority of Grade ≥3 treatment-related adverse events (AEs) reported in >5% of the evaluable patients with low baseline platelet counts were largely hematologic, including anemia (5.4% overall and 10.0% low platelet group), thrombocytopenia (4.7% and 15.0%), leukopenia (2.3% and 10.0%), and neutropenia (4.7% and 10.0%). Platelet counts tended to increase over time on study for the low baseline platelet subgroup (Figure). Conclusions: Complete and partial responses were seen with belinostat overall and in the subgroup of patients with low baseline platelet counts. Patients with baseline platelet counts <100,000/µL tolerated belinostat at a high dose intensity that was similar to that of patients with baseline platelet counts ≥100,000/µL, did not experience a higher proportion of AEs, and benefited from belinostat treatment. Thus, belinostat is suitable for use in patients with R/R PTCL and low baseline platelet counts, and may also be useful in developing new treatment regimens in combination with other cytotoxic agents. Table Summary of IRC Assessment of Efficacy Endpoints by Baseline Platelet Count E ndpoint All Evaluable Patients(N = 120) Platelets ≥100,000/µL(N = 100) Platelets <100,000/µL(N = 20) ORR (CPRG), n (%) 31 (25.8) 28 (28.0) 3 (15.0) Median DoR, months (95% CI) 13.6 (4.5-29.4) 13.6 (5.6-29.4) 4.1 (2.2-9.8) Median PFS, months (95% CI) 1.6 (1.4-2.7) 1.8 (1.5-2.8) 1.3 (1.1-1.5) Median OS, months (95% CI) 7.9 (6.1-13.9) 9.2 (6.4-17.7) 4.3 (2.4-7.9) Median TTR, weeks (95% CI) 5.6 (4.3-50.4) 5.6 (4.3-50.4) 6.4 (4.3-12.7) Abbreviations: CI = confidence interval; CPRG = Central Pathology Review Group; DoR = duration of response; IRC = Independent Review Committee; ORR = objective response rate; OS = overall survival; PFS = progression-free survival; TTR = time to response Figure 1 Figure 1. Disclosures Horwitz: Celgene: Consultancy, Research Funding; Millenium: Consultancy, Research Funding; Infinity: Research Funding; Kiowa-Kirin: Research Funding; Seattle Genetics: Consultancy, Research Funding; Spectrum: Consultancy, Research Funding; Amgen: Consultancy; Bristol-Myers Squibb: Consultancy; Jannsen: Consultancy. Bhat:Spectrum Pharmaceuticals: Employment. Choi:Spectrum Pharmaceuticals: Employment. Allen:Spectrum Pharmaceuticals: Employment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.204
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2014
Admission routes1
Has abstractyes

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