Clinical Efficacy, Safety and Tolerability of a New Subcutaneous Immunoglobulin 16.5% (Octanorm [Cutaquig®]) in the Treatment of Patients With Primary Immunodeficiencies
Bibliographic record
Abstract
Introduction: Subcutaneously administered immunoglobulin (SCIG) is increasingly used to treat patients with primary immunodeficiencies (PIDs). Octanorm (marketed as cutaquig® in USA and Canada) is a new 16.5% solution of human SCIG, manufactured by a process based on that of the intravenous preparation (IVIG) octagam®. Objectives: To investigate the efficacy, safety and tolerability of octanorm in a prospective, open-label, single-arm phase 3 study involving adult and pediatric patients with PIDs (NCT01888484; clinicaltrials.gov/ct2/show/NCT01888484). Methods: Patients who were previously treated with IVIG received a total of 64 weekly SCIG infusions, including 12 weekly infusions during the wash-in/wash-out period, followed by 52 weekly infusions during the evaluation period. Results: A total of 61 patients aged 2–73 years received 3,497 infusions of octanorm. The mean dose per patient was 0.175 g/kg/infusion. The mean calculated dose conversion factor from the patients' previous IVIG dose for octanorm was 1.37. No serious bacterial infections developed during the study. The rate of other infections per person-year during the primary observation period was 3.43 (upper 95% CI 4.57). All but one non-bacterial infection were mild or moderate in intensity. IgG trough levels were constant during the course of the study. Eleven patients (18.0%) experienced 14 mild or moderate systemic adverse events (AEs) related to octanorm. The rate of related AEs per infusion was 0.004. In 76.7% of infusions, no infusion site reactions were observed and only two (0.3%) reactions were deemed severe. The incidence of site reactions decreased with successive infusions. Conclusion: The new 16.5% SCIG octanorm was shown to be efficacious in preventing infections in PIDs, and was well tolerated.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".