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Record W4411332234 · doi:10.1002/hon.70093_134

134 | EFFICACY AND SAFETY OF FIRST‐LINE IBRUTINIB PLUS VENETOCLAX IN PATIENTS WITH MANTLE CELL LYMPHOMA (MCL) WHO WERE OLDER OR HAD TP53 MUTATIONS IN THE SYMPATICO STUDY

2025· article· en· W4411332234 on OpenAlexaff
M. Wang, Marc Hoffmann, Tomasz Wróbel, Marek Trněný, David Belada, Fatih Demırkan, Panayiotis Panayiotidis, Wojiech Jurczak, Pier Luigi Zinzani, Mary‐Margaret Keating, Sung‐Soo Yoon, M. Egyed, Constantine S. Tam, Nathalie A. Johnson, Edith Szafer‐Glusman, Jennifer Lin, James P. Dean, Jutta K. Neuenburg, Gottfried von Keudell

Bibliographic record

VenueHematological Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsJewish General HospitalQueen Elizabeth II Health Sciences Centre
FundersPharmacyclics
KeywordsIbrutinibMantle cell lymphomaVenetoclaxLymphomaMedicineCancer researchOncologyInternal medicineLeukemiaChronic lymphocytic leukemia

Abstract

fetched live from OpenAlex

NCT03112174 Introduction: The phase 3 SYMPATICO study evaluated ibrutinib (Ibr) combined with venetoclax (Ven) in 3 cohorts of patients with MCL: an open-label safety run-in phase to evaluate concurrent initiation of IbrþVen in relapsed/refractory (R/ R) MCL; a randomized phase to evaluate IbrþVen versus Ibrþplacebo (Pbo) in R/R MCL; and an open-label cohort to evaluate first-line IbrþVen in treatment-naive (TN) MCL.Primary analysis of the randomized phase showed superior progression-free survival (PFS) with IbrþVen versus IbrþPbo in patients with R/R MCL (Wang M et al.Lancet Oncol.2025).Here, we report efficacy and safety of IbrþVen in patients with TN MCL in older patients (≥ 65 years) or younger patients with a TP53 mutation (TP53mut) (≥ 18 years) who are in need of novel and better tolerated treatment options.Methods: Older patients (≥ 65 years) or patients with a TP53mut with TN MCL received oral Ibr 560 mg once daily and Ven (5-week ramp-up to 400 mg once daily) for 2 years, then single-agent Ibr 560 mg until progressive disease (PD) or unacceptable toxicity.The primary endpoint was complete response (CR) rate assessed by investigator per Lugano criteria.Key secondary endpoints included overall response rate (ORR), duration of response (DOR), PFS, overall survival (OS), and time to next treatment.Subgroup analyses were performed according to TP53mut status and age.Results: In total, 78 patients with TN MCL were enrolled.At baseline, 83% of patients were ≥ 65 years, 97% had Eastern Cooperative Oncology Group performance status of 0-1, 45% had high-risk simplified MCL International Prognostic Index score, 31% had bulky disease (≥ 5 cm), 78% had bone marrow involvement, 46% had splenomegaly, and 37% had TP53mut.Median time on study was 40.5 months (range, 0.6þ-46.9).The CR rate was 69% (95% CI: 58-79), and the ORR was 95% (95% CI: 87-99).Median DOR was 37.1 months (95% CI: 30.3-NE).Median PFS was 40.2 months, and 3-year OS was 79%.The CR rate was 76% in patients ≥ 65 years without TP53mut, 44% in patients ≥ 65 years with TP53mut, and 73% in patients < 65 years with TP53mut; median PFS was 40.2, 22.0, and 15.4 months, and 3-year OS was 85%, 66%, and 73%, respectively (Table ).Median duration of treatment was 24.0 months (range, 0.3-46.9).Most common adverse events (AEs) were diarrhea (49%), fatigue (37%), neutropenia (35%), and COVID-19 (32%).The most common grade ≥ 3 AE was neutropenia (29%).Conclusions: First-line IbrþVen showed promising efficacy with high CR rates and durable remissions in patients with TN MCL with and without TP53mut.Safety was acceptable and trended better in younger patients.IbrþVen may be an option for older patients with TN MCL or patients of any age with TP53mut.

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)0.001
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.332
Teacher spread0.310 · 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 designRandomized 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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Citations1
Published2025
Admission routes1
Has abstractyes

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