Long-term follow-up of IPEX syndrome patients after different therapeutic strategies: An international multicenter retrospective study
Bibliographic record
Abstract
BACKGROUND: Immunodysregulation polyendocrinopathy enteropathy x-linked (IPEX) syndrome is a monogenic autoimmune disease caused by FOXP3 mutations. Because it is a rare disease, the natural history and response to treatments, including allogeneic hematopoietic stem cell transplantation (HSCT) and immunosuppression (IS), have not been thoroughly examined. OBJECTIVE: This analysis sought to evaluate disease onset, progression, and long-term outcome of the 2 main treatments in long-term IPEX survivors. METHODS: Clinical histories of 96 patients with a genetically proven IPEX syndrome were collected from 38 institutions worldwide and retrospectively analyzed. To investigate possible factors suitable to predict the outcome, an organ involvement (OI) scoring system was developed. RESULTS: We confirm neonatal onset with enteropathy, type 1 diabetes, and eczema. In addition, we found less common manifestations in delayed onset patients or during disease evolution. There is no correlation between the site of mutation and the disease course or outcome, and the same genotype can present with variable phenotypes. HSCT patients (n = 58) had a median follow-up of 2.7 years (range, 1 week-15 years). Patients receiving chronic IS (n = 34) had a median follow-up of 4 years (range, 2 months-25 years). The overall survival after HSCT was 73.2% (95% CI, 59.4-83.0) and after IS was 65.1% (95% CI, 62.8-95.8). The pretreatment OI score was the only significant predictor of overall survival after transplant (P = .035) but not under IS. CONCLUSIONS: Patients receiving chronic IS were hampered by disease recurrence or complications, impacting long-term disease-free survival. When performed in patients with a low OI score, HSCT resulted in disease resolution with better quality of life, independent of age, donor source, or conditioning regimen.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".