A multicenter review of infusion-related reactions to daratumumab for relapsed multiple myeloma in the real world setting
Bibliographic record
Abstract
BACKGROUND: Daratumumab is used in the treatment of relapsed multiple myeloma. Daratumumab infusion-related reactions can occur with the highest incidence on the first infusion. METHODS: A retrospective review of all daratumumab infusions used as part of the DVd and DRd regimens for relapsed multiple myeloma was undertaken. The review of infusion-related reactions was conducted by reviewing the treatment room nursing note on the days that daratumumab was administered. If the patient experienced an infusion-related reaction, then the data captured included if the full dose was administered. RESULTS: Daratumumab infusion-related reactions occurred most frequently on the first dose. The rates of infusion-related reactions using a split dose approach for daratumumab administration were lower than that reported in clinical trials. All of the infusion-related reactions were managed with appropriate interventions in the outpatient setting. The adoption of rapid infusion daratumumab beginning with cycle 2 of DVd and DRd was well tolerated. CONCLUSIONS: Our experience of daratumumab infusions using a split dose approach was associated with an infusion-related reaction rate in 28% of patients on cycle 1, day 1 of DVd and DRd regimens. All patients were able to complete full doses of daratumumab by utilizing split dose. The rates of daratumumab infusion-related reactions are highest on the first infusion. In addition, our adoption of rapid infusion daratumumab was safe.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".