PAIN MITIGATION AND MANAGEMENT STRATEGIES FOR ANTI-GD2 INFUSIONS
Bibliographic record
Abstract
Monoclonal antibodies (mAbs) targeting disialoganglioside 2 (GD2) are an important treatment advance for high-risk neuroblastoma, including in patients with refractory or relapsed disease. Dinutuximab and dinutuximab beta are administered for ≥8 hours (and up to 10 days for dinutuximab beta), whereas naxitamab is administered over 0.5 to 2 hours as tolerated. As acute pain is a class effect of anti-GD2 mAbs, effective pain management is crucial to successful treatment. Here, we provide an overview of current pain-management strategies for anti-GD2 mAb infusions, including discussion of opioid analgesics, ketamine, gabapentin, and other similar agents, and non-pharmacologic approaches. Potential future pain management options are also discussed, in addition to the use of sedatives to reduce the anxiety that may be associated with infusion-related pain. Specific guidance for pain management during naxitamab infusions is provided, as these infusions are administered over 0.5 to 2 hours and may not need overnight hospitalization based on the physician’s assessment, and require rapid-onset analgesia options suitable for potential outpatient administration.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".