Transition from subcutaneous to intravenous immunoglobulin therapy in primary immunodeficiency: A case series highlighting patient-centered treatment optimization
Bibliographic record
Abstract
Background: Immunoglobulin replacement therapy (IgRT) is a cornerstone therapy for managing primary immuneodeficiency (PID) and other immune-related disorders. While both intravenous immunoglobulin (IVIg) and subcutaneous immunoglobulin (SCIg) are effective, patient tolerance and preferences can influence treatment success. Objective: To evaluate the reasons for switching from SCIg to IVIg in 4 PID patients and to assess the resulting clinical outcomes and patient-reported experiences. Methods: This case series includes 4 individuals with PID who transitioned from SCIg to IVIg due to persistent side effects. Data were collected on adverse reactions during SCIg therapy, changes in immunoglobulin (IgG) levels, and patient-reported outcomes following the switch to IVIg. Results: All patients experienced adverse effects with SCIg, including headaches, fatigue, shortness of breath, and difficulty managing infusions. Following the transition to IVIg, patients reported improved tolerance, fewer side effects, and greater convenience with treatment schedules. IgG levels remained stable or improved post-switch, indicating sustained therapeutic efficacy. Conclusion: IVIg is a viable and effective alternative for PID patients who experience intolerance to SCIg. Individualized IgRT strategies that consider side effect profiles and patient preferences can enhance treatment adherence and quality of life. Statement of Novelty: This case series highlights patient-driven transitions from SCIg to IVIg therapy in primary immunodeficiency patients. This study provides insights into a subset of patients who experience persistent SCIg-related side effects, underscoring the importance of personalized IgRT approaches based on patient tolerance and quality-of-life considerations.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".