Adverse event management in patients with relapsed and refractory multiple myeloma taking pomalidomide plus low‐dose dexamethasone: A pooled analysis
Bibliographic record
Abstract
OBJECTIVES: Heavily pretreated patients with relapsed and refractory multiple myeloma are susceptible to treatment-related adverse events (AEs). Managing AEs are important to ensure patients continue therapy long enough to receive the best clinical benefit. Data from the MM-002, MM-003, and MM-010 trials were pooled to further characterize the safety profile of pomalidomide plus low-dose dexamethasone and AE management. METHODS: This analysis included 1088 patients who received ≥ 2 prior therapies, including lenalidomide and bortezomib, and progressed ≤ 60 days of last therapy. Patients received 28-day cycles of pomalidomide 4 mg/day on days 1-21 and low-dose dexamethasone 40 mg (20 mg if aged > 75 years) weekly until disease progression or unacceptable toxicity. Thromboprophylaxis was required. RESULTS: The most common grade 3/4 AEs were neutropenia (56.2%), anemia (32.3%), and thrombocytopenia (25.8%), which occurred within the first few cycles of treatment. Grade 3/4 infections occurred in 33.7% patients, of whom 13.9% had pneumonia, and 40.3% had neutropenia. Pomalidomide dose reductions or interruptions were reported in 24.2% and 66.0% of patients, respectively. AEs were managed by dose modifications and/or supportive care. CONCLUSIONS: Pomalidomide plus low-dose dexamethasone showed an acceptable safety profile, and AEs were well managed according to study protocols and established guidelines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.015 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".