Excellent outcomes following hematopoietic cell transplantation for Wiskott-Aldrich syndrome: a PIDTC report
Bibliographic record
Abstract
Wiskott-Aldrich syndrome (WAS) is an X-linked disease caused by mutations in the WAS gene, leading to thrombocytopenia, eczema, recurrent infections, autoimmune disease, and malignancy. Hematopoietic cell transplantation (HCT) is the primary curative approach, with the goal of correcting the underlying immunodeficiency and thrombocytopenia. HCT outcomes have improved over time, particularly for patients with HLA-matched sibling and unrelated donors. We report the outcomes of 129 patients with WAS who underwent HCT at 29 Primary Immune Deficiency Treatment Consortium centers from 2005 through 2015. Median age at HCT was 1.2 years. Most patients (65%) received myeloablative busulfan-based conditioning. With a median follow-up of 4.5 years, the 5-year overall survival (OS) was 91%. Superior 5-year OS was observed in patients <5 vs ≥5 years of age at the time of HCT (94% vs 66%; overall P = .0008). OS was excellent regardless of donor type, even in cord blood recipients (90%). Conditioning intensity did not affect OS, but was associated with donor T-cell and myeloid engraftment after HCT. Specifically, patients who received fludarabine/melphalan-based reduced-intensity regimens were more likely to have donor myeloid chimerism <50% early after HCT. In addition, higher platelet counts were observed among recipients who achieved full (>95%) vs low-level (5%-49%) donor myeloid engraftment. In summary, HCT outcomes for WAS have improved since 2005, compared with prior reports. HCT at a younger age continues to be associated with superior outcomes supporting the recommendation for early HCT. High-level donor myeloid engraftment is important for platelet reconstitution after either myeloablative or busulfan-containing reduced intensity conditioning. (This trial was registered at www.clinicaltrials.gov as #NCT02064933.).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".