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P1113: COMPARATIVE EFFICACY OF ZANUBRUTINIB (ZANU) VERSUS RITUXIMAB (RTX) IN RELAPSED MARGINAL ZONE LYMPHOMA (MZL): MATCHING-ADJUSTED INDIRECT COMPARISON (MAIC)

2023· article· en· W4385707156 on OpenAlexaff
Catherine Thiéblemont, Kaijun Wang, Sam Keeping, Ina Zhang, Keri Yang, Boxiong Tang, Leyla Mohseninejad

Bibliographic record

VenueHemaSphere · 2023
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsPrecision Nanosystems (Canada)
Fundersnot available
KeywordsMedicinePropensity score matchingOncologyInternal medicineProgression-free survivalRituximabPopulationOverall survivalLymphoma

Abstract

fetched live from OpenAlex

Topic: 36. Ethics and health economics Background: ZANU is a Bruton tyrosine kinase inhibitor that has been evaluated for relapsed/refractory MZL in two phase 2, single-arm (MAGNOLIA, n=66, NCT03846427; BGB-3111-AU-003, n=20, NCT02343120). At 28 and 35 months of study follow-up in MAGNOLIA and BGB-3111-AU-003, respectively, median progression-free survival (PFS) and overall survival (OS) were not reached. Aims: Here, we conducted an unanchored MAIC to estimate relative treatment effects of ZANU versus RTX, a commonly used treatment for patients with relapsed MZL. Note the comparison was restricted to the relapsed population because RTX refractory patients would not be retreated with RTX. Methods: The MAIC was performed using pooled individual patient-level data from MAGNOLIA and BGB-3111-AU-003. Study level-data of RTX in relapsed patients were used from CHRONOS-3 (Özcan et al., Ann Oncol 2021) which was identified as the most suitable comparator study via a systematic literature review. A logistic propensity score model was used to estimate weights for patients in the ZANU trials such that their weighted mean baseline characteristics matched those of CHRONOS-3. The following characteristics were identified as key prognostic factors and included in the base case propensity score model: prior lines of therapy, MZL subtype, relapse after prior therapy, and age. Sensitivity analyses incorporating additional characteristics were not possible owing to a lack of reporting from CHRONOS-3, but the impact of each covariate in the base model was explored via a leave-one-out analysis. Comparisons were conducted for OS, PFS, and objective response rate (ORR) by independent review committee using weighted statistical models, with relative treatment effects presented as hazard ratios (HRs), odds ratios (ORs), and 95% confidence intervals (CIs). Results: After applying weights estimated from the base case propensity score model, the effective sample size (ESS) for ZANU was 39. ZANU significantly reduced the risk of progression (HR 0.29; 95% CI 0.13–0.65, P=0.003) and had a higher probability of response (OR 5.09; 95% CI: 1.84–14.08, P=0.0017) when compared with RTX (Table). OS was comparable for ZANU and RTX, which is consistent with the survival expectancy for indolent lymphomas. The leave-one-out analysis showed that removing any of the characteristics from the propensity score model yielded comparable results. Summary/Conclusion: MAIC results suggest ZANU is associated with improved PFS and ORR compared with RTX in relapsed MZL.Keywords: Marginal zone, Tyrosine kinase inhibitor, Indolent non-Hodgkin’s lymphoma, relapsed/refractory

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.096
GPT teacher head0.371
Teacher spread0.275 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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