Matching-adjusted indirect comparisons of zanubrutinib (MAGNOLIA, BGB-3111-AU-003) versus ibrutinib (PCYC-1121) and rituximab (CHRONOS-3) in relapsed/refractory marginal zone lymphoma
Bibliographic record
Abstract
In the absence of head-to-head randomized trials, unanchored matching-adjusted indirect comparisons were conducted to estimate the relative efficacy of zanubrutinib versus ibrutinib and zanubrutinib versus rituximab in relapsed or refractory marginal zone lymphoma (MZL). Logistic propensity score models were used to estimate weights for the patient-level data from two phase II single-arm trials, MAGNOLIA and BGB-3111-AU-003, such that their characteristics matched the ibrutinib and rituximab aggregate-level data from PCYC-1121 and CHRONOS-3, respectively. The base case model for each comparison incorporated four key prognostic factors: prior lines of therapy, MZL subtype, response to prior therapy, and age. A sensitivity analysis incorporating additional prognostic factors was also conducted for the ibrutinib comparison. The impact of each covariate was explored via a leave-one-out analysis. Compared with ibrutinib and rituximab, zanubrutinib demonstrated significant benefits in terms of both overall response and progression-free survival in patients with previously treated MZL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".