Teclistamab Improves Patient-Reported Symptoms and Health-Related Quality of Life in Relapsed or Refractory Multiple Myeloma: Results From the Phase II MajesTEC-1 Study
Bibliographic record
Abstract
INTRODUCTION: Patients with relapsed or refractory multiple myeloma (RRMM) report significantly lower HRQoL compared with patients with newly diagnosed MM and experience further deterioration in HRQoL with each relapse and subsequent treatment. Therefore, consideration of the impact of treatment on HRQoL in addition to clinical outcomes is vital. PATIENTS AND METHODS: In the phase I/II MajesTEC-1 (NCT03145181, NCT04557098) study, patients with RRMM who received teclistamab, an off-the-shelf, T-cell redirecting BCMA × CD3 bispecific antibody, had deep and durable responses with manageable safety. HRQoL was assessed using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire core 30-item and the EuroQol 5 Dimension 5 Level descriptive questionnaire. Changes over time from baseline were measured with a repeated measures mixed-effects model. Proportions of patients with clinically meaningful improvement after starting treatment and time to clinically meaningful worsening were assessed. RESULTS: Compliance was maintained throughout the study. Compared with baseline, positive changes were observed for pain, global health status, and emotional functioning with treatment; other assessments were largely unchanged from baseline. Post hoc analysis showed patients with deeper clinical response generally reported improved HRQoL outcomes. Following an initial decline in HRQoL in some scales, the proportion of patients reporting clinically meaningful improvements increased, while the proportion reporting clinically meaningful worsening decreased over time. Clinically meaningful improvements in pain were reported in ≥40% of patients at most assessment time points. CONCLUSIONS: These results complement previously reported clinical benefits and support teclistamab as a promising therapeutic option for patients with RRMM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".