Health-related quality-of-life in patients with newly diagnosed multiple myeloma in the FIRST trial: lenalidomide plus low-dose dexamethasone versus melphalan, prednisone, thalidomide
Bibliographic record
Abstract
We compared the health-related quality-of-life of patients with newly diagnosed multiple myeloma aged over 65 years or transplant-ineligible in the pivotal, phase III FIRST trial. Patients received: i) continuous lenalidomide and low-dose dexamethasone until disease progression; ii) fixed cycles of lenalidomide and low-dose dexamethasone for 18 months; or iii) fixed cycles of melphalan, prednisone, thalidomide for 18 months. Data were collected using the validated questionnaires (QLQ-MY20, QLQ-C30, and EQ-5D). The analysis focused on the EQ-5D utility value and six domains pre-selected for their perceived clinical relevance. Lenalidomide and low-dose dexamethasone, and melphalan, prednisone, thalidomide improved patients' health-related quality-of-life from baseline over the duration of the study across all pre-selected domains of the QLQ-C30 and EQ-5D. In the QLQ-MY20, lenalidomide and low-dose dexamethasone demonstrated a significantly greater reduction in the Disease Symptoms domain compared with melphalan, prednisone, thalidomide at Month 3, and significantly lower scores for QLQ-MY20 Side Effects of Treatment at all post-baseline assessments except Month 18. Linear mixed-model repeated-measures analyses confirmed the results observed in the cross-sectional analysis. Continuous lenalidomide and low-dose dexamethasone delays disease progression versus melphalan, prednisone, thalidomide and has been associated with a clinically meaningful improvement in health-related quality-of-life. These results further establish continuous lenalidomide and low-dose dexamethasone as a new standard of care for initial therapy of myeloma by demonstrating superior health-related quality-of-life during treatment, compared with melphalan, prednisone, thalidomide.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".