Economic benefits of subcutaneous rapid push versus intravenous immunoglobulin infusion therapy in adult patients with primary immune deficiency
Bibliographic record
Abstract
OBJECTIVE: The objective of this study is to evaluate the economic benefits of immunoglobulin replacement therapy achieved subcutaneously (subcutaneous immunoglobulin, SCIG) by the rapid push method compared to intravenous infusion therapy (intravenous immunoglobulin, IVIG) in primary immune deficiency (PID) patients from the healthcare system perspective in the context of the adult SCIG home infusion program based at St Paul's Hospital, Vancouver, Canada. MATERIALS AND METHODS: SCIG and IVIG options were compared in cost-minimisation and budget impact models (BIMs) over 3 years. Sensitivity analyses were performed for both models to evaluate the impact of varying modality of IVIG treatments and proportion of patients switching from IVIG to SCIG. RESULTS: The cost-minimisation model estimated that SCIG treatment reduced cost to the healthcare system per patient of $5736 over 3 years, principally because of less use of hospital personnel. This figure varied between $5035 and $8739 depending on modality of IVIG therapy. Assuming 50% of patients receiving IVIG switched to SCIG, the BIM estimated cost savings for the first 3 years at $1·308 million or 37% of the personnel and supply budget. These figures varied between $1·148 million and $2·454 million (36 and 42%) with varying modalities of IVIG therapy. If 75% of patients switched to SCIG, the reduced costs reached $1·962 million or 56% of total budget. CONCLUSION: This study demonstrated that from the health system perspective, rapid push home-based SCIG was less costly than hospital-based IVIG for immunoglobulin replacement therapy in adult PID patients in the Canadian context.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".