Transfer and loss of allergen‐specific responses via stem cell transplantation: A prospective observational study
Bibliographic record
Abstract
BACKGROUND: Currently, no estimates can be made on the impact of hematopoietic stem cell transplantation on allergy transfer or cure of the disease. By using component-resolved diagnosis, we prospectively investigated 50 donor-recipient pairs undergoing allogeneic stem cell transplantation. This allowed calculating the rate of transfer or maintenance of allergen-specific responses in the context of stem cell transplantation. METHODS: Allergen-specific IgE and IgG to 156 allergens was measured pretransplantation in 50 donors and recipients and at 6, 12 and 24 months in recipients post-transplantation by allergen microarray. Based on a mixed effects model, we determined risks of transfer of allergen-specific IgE or IgG responses 24 months post-transplantation. RESULTS: After undergoing stem cell transplantation, 94% of allergen-specific IgE responses were lost. Two years post-transplantation, recipients' allergen-specific IgE was significantly linked to the pretransplantation donor or recipient status. The estimated risk to transfer and maintain individual IgE responses to allergens by stem cell transplantation was 1.7% and 2.3%, respectively. Allergen-specific IgG, which served as a surrogate marker of maintaining protective IgG responses, was highly associated with the donor's (31.6%) or the recipient's (28%) pretransplantation response. CONCLUSION: Hematopoietic stem cell transplantation profoundly reduces allergen-specific IgE responses but also comes with a considerable risk to transfer allergen-specific immune responses. These findings facilitate clinical decision-making regarding allergic diseases in the context of hematopoietic stem cell transplantation. In addition, it provides prospective data to estimate the risk of transmitting allergen-specific responses via hematopoietic stem cell transplantation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".