Time to progression of disease and outcomes with second-line BTK inhibitors in relapsed/refractory mantle cell lymphoma
Bibliographic record
Abstract
Time to progression of disease (POD) after first-line (1L) therapy is prognostic in mantle cell lymphoma (MCL), although studies have included a broad range of 1L, second-line (2L), and subsequent lines of therapy. The purpose of this study was to evaluate the factors predicting outcomes in patients with relapsed/refractory (R/R) MCL exclusively initiating 2L Bruton's tyrosine kinase inhibitors (BTKis) after 1L rituximab-containing therapy. Patients were accrued from 8 international centers (7 main, 1 validation cohort). Multivariable models evaluating the association between time to POD and clinical/pathologic factors were constructed and converted into nomograms and prognostic indexes predicting outcomes in this population. A total of 360 patients were included, including 160 in the main cohort and 200 in the validation cohort. Time to POD, Ki67 ≥ 30%, and MCL International Prognostic Index (MIPI) were associated with progression-free survival (PFS2) and overall survival (OS2) from the start of 2L BTKis. C-indexes were consistently ≥0.68 in both cohorts. Web/application-based calculators based on nomograms and prognostic indexes to estimate PFS2 and OS2 were constructed. The 2L BTKi MIPI identifies 3 groups with distinct 2-year PFS2, including high risk (14%), intermediate risk (50%), and low risk (64%). Time to POD, Ki67, and MIPI are associated with survival outcomes in patients with R/R MCL receiving 2L BTKis. Simple clinical models incorporating these variables may assist in planning for alternative therapies such as chimeric antigen receptor T-cell therapy, allogeneic stem cell transplantation, or novel agents with alternative mechanisms of action.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".