Exposure-Response Analysis Supports a Lower Dose of Venetoclax in t(11;14)-Positive Relapsed/Refractory Multiple Myeloma Patients When Combined with Daratumumab and Dexamethasone
Bibliographic record
Abstract
Introduction: Venetoclax is a first in class BCL2 inhibitor approved for treatment of CLL and AML and is currently under investigation in other hematological malignancies including multiple myeloma (MM). This analysis aimed to select the optimal venetoclax dose in combination with daratumumab and dexamethasone (VenDd) in t(11;14)-positive relapsed/refractory MM patients using data from Study M15-654 (NCI: NCT03314181) which evaluated VenDd versus bortezomib in combination with daratumumab and dexamethasone (DVd). Methods: 66 subjects (47 receiving VenDd and 19 in the control arm receiving DVd) enrolled in Study NCI: NCT03314181 were included in the analysis. A population pharmacokinetic model was developed and individual subject venetoclax exposures (average area under the concentration time curve [AUCavg] and steady state AUC [AUCss] were determined using the individual post hoc empirical Bayes parameter estimates. The effect of the following covariates on the relationships for the efficacy and safety endpoints were evaluated: number of prior therapies, cytogenetic risk, international staging system (ISS) stage, t(11;14) status, bortezomib co-administration, and daratumumab route of administration. Kaplan-Meier curves and Cox proportional hazards models were used to describe the relationship between venetoclax exposures (AUCavg or AUCss) and progression free survival (PFS). Quartile plots and logistic regression models were used to describe the relationship between venetoclax exposure (AUCavg or AUCss) and the other efficacy and safety endpoints. Results: Exposure-response analysis demonstrated that compared to the control arm, venetoclax resulted in higher response rates (very good partial response or better [≥VGPR] and complete response or better [≥CR]) and longer PFS (PFS data not mature at time of analysis). Within the VenDd treatment arms, evaluating the exposure-response relationships over the venetoclax exposure range in patients receiving 400 mg or 800 mg venetoclax demonstrated that higher venetoclax exposures were not associated with an improved efficacy profile (PFS or ≥VGPR and ≥CR rates) compared to subjects with lower venetoclax exposures. While both 400 mg and 800 mg venetoclax were generally tolerated, higher venetoclax exposures (AUCavg and AUCss) trended with higher rates of treatment-emergent serious adverse events (any grade), and Grade ≥3 treatment-emergent adverse events (AUCss only). Higher venetoclax exposures were not associated with higher rates of Grade ≥2 infections, Grade ≥3 infections or Grade ≥3 neutropenia. Additionally, no other significant covariates were identified for any of the efficacy or safety endpoints evaluated. Conclusion: Exposure-response analyses support the selection and evaluation of the 400 mg QD dosing of venetoclax in combination with daratumumab and dexamethasone in t(11;14)-positive relapsed/refractory MM subjects in future studies. This is a lower dose than that selected for venetoclax when combined only with dexamethasone in t(11;14)-positive relapsed/refractory MM patients.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".