P888: MATCHED-ADJUSTED INDIRECT COMPARISON OF TALQUETAMAB VS SELINEXOR-DEXAMETHASONE AND VS BELANTAMAB MAFODOTIN IN PATIENTS WITH RELAPSED/REFRACTORY MULTIPLE MYELOMA
Bibliographic record
Abstract
Topic: 14. Myeloma and other monoclonal gammopathies - Clinical Background: Talquetamab, a G protein coupled receptor family C group 5 member D × CD3 bispecific antibody, has shown an overall response rate (ORR) of ≥73% in patients (pts) with triple-class exposed (TCE) relapsed/refractory multiple myeloma (RRMM) in the MonumenTAL-1 (NCT03399799/NCT04636552) trial. Selinexor-dexamethasone (sel-dex) and belantamab mafodotin (belamaf) are approved for the treatment of pts in the same indication, based on results of the STORM part 2 (NCT02336815) and DREAMM-2 (NCT03525678) trials, respectively. Given the absence of a control arm in MonumenTAL-1, matched adjusted indirect comparisons (MAICs) can provide useful insights regarding the relative effectiveness of different treatments. Aims: To compare the effectiveness of talquetamab vs sel-dex and vs belamaf using data from the single-arm MonumenTAL-1 trial, vs STORM and vs DREAMM-2, respectively, in pts with TCE RRMM. Methods: An unanchored MAIC was performed using individual pt data (IPD) for talquetamab 0.4 mg/kg QW and talquetamab 0.8 mg/kg Q2W administered subcutaneously (MonumenTAL-1; data cut-off [DCO]: Sept 2022) and published summary data for sel-dex (STORM; DCO: Aug 2018) and belamaf (DREAMM-2; approved 2.5 mg/kg dose cohort only, DCO: Mar 2022; for PFS data, DCO: Jan 2020). MonumenTAL-1 pts who met key eligibility criteria for STORM (triple-class refractory, refractory to last therapy, refractory to daratumumab, and penta-exposed) and DREAMM-2 (triple-class refractory and refractory to last therapy) were included in the analysis. MonumenTAL-1 pts were reweighted to adjust for imbalances in refractory status, cytogenetic risk, ISS stage, extramedullary disease, and number of prior lines of therapy to match pt populations from STORM and DREAMM-2. A sensitivity analysis excluding MonumenTAL-1 pts who had received prior belamaf treatment was also performed. Outcomes of interest were ORR, complete response or better (≥CR), duration of response (DOR), progression-free survival (PFS), and overall survival (OS). For binary outcomes, response rates were analyzed using weighted logistic regression to estimate odds ratios and relative response ratios (RRs), with respective 95% CIs. Time-to-event endpoints were analyzed using weighted proportional hazards regression to estimate hazard ratios (HRs) and 95% CIs from weighted IPD from MonumenTAL-1, and pseudo-IPD simulated from published Kaplan-Meier curves from both external trials. Results: After reweighting, baseline variables for both analyses were well balanced. Base case analysis showed better effectiveness of talquetamab 0.4 mg/kg QW (N=143) and talquetamab 0.8 mg/kg Q2W (N=145) for all outcomes vs sel-dex (N=122) and for most outcomes vs belamaf (N=97) (see Table). Results were also generally consistent in the sensitivity analysis. Summary/Conclusion: These analyses show superior effectiveness of both talquetamab dosing schedules vs sel-dex and vs belamaf for most outcomes, and highlight talquetamab as a novel, highly effective treatment option for pts with TCE RRMM.Keywords: relapsed/refractory, G-protein-coupled receptors, Bispecific, Multiple myeloma
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".