4CPS-141 Real-life impact of including montelukast as premedication on the incidence of infusion-related reactions to isatuximab and description of risk factors
Bibliographic record
Abstract
<h3>Background and Importance</h3> Infusion-related reactions (IRR) are one of isatuximab’s most frequent and significant adverse reactions that may lead to treatment discontinuation despite premedicating with dexamethasone, paracetamol, and anti-H1 antihistamines. Similarly to daratumumab, adding montelukast as premedication could improve its tolerability. Additionally, there are no studies to date describing which risk factors (RF) may affect the likeliness of an isatuximab IRR. <h3>Aim and Objectives</h3> The primary objective was to assess the impact of including montelukast as premedication on the incidence of IRR (iIRR) associated with the administration of isatuximab. Secondary objectives included describing the iIRR in a real-life setting and evaluating possible risk factors: food, environmental or medicine allergies; previous IRR; and infusion bag concentration. <h3>Material and Methods</h3> Multicentric retrospective study conducted in one secondary and three tertiary hospitals. Eligibility criteria included adults having started isatuximab and excluded patients receiving off-label corticosteroid doses and those enrolled in clinical trials. Follow-up was carried out until September 2023, treatment discontinuation or death. Baseline characteristics were sex, age, treatment regimen, premedication regimen, number of isatuximab doses and occurrence of IRR. These numerical and categorical variables were expressed as number of observations and medians respectively. Odds ratios (OR) and Mann-Whitney U tests were calculated to evaluate qualitative and quantitative RF, respectively. Absolute risk reduction (ARR) and number needed to treat (NNT) were used to assess the impact of montelukast as premedication. 95% confidence intervals (95%CI) were applied. <h3>Results</h3> 40 patients were included, with a median age of 66 (54 – 72) years, 60.0% being men. The median number of isatuximab doses per patient was 8 (4–18). The iIRR for cycle-one-day-one was 7.7% for the group premedicated with montelukast and 29.6% without. OR was 0.20 (95% CI 0.02 – 1.79), ARR was 0.22 (95% CI -0.01 – 0.44) and NNT was 5. No IRR were found for second or further doses in any patient and no risk factors were found. <h3>Conclusion and Relevance</h3> In our experience, iIRR observed for isatuximab was lower compared to pivotal clinical trials. The inclusion of montelukast as premedication might reduce IRR, which should be confirmed in subsequent studies. <h3>References and/or Acknowledgements</h3> <h3>Conflict of Interest</h3> No conflict of interest.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".