Current Status of Allogeneic Hematopoietic Stem Cell Transplantation for Paroxysmal Nocturnal Hemoglobinuria
Bibliographic record
Abstract
Treatment of patients with paroxysmal nocturnal hemoglobinuria (PNH) has been traditionally empirical, primarily aiming at ameliorating symptoms or treating complications resulting from the disease. Novel therapies such as eculizumab result in stabilization of hemoglobin levels and improvement in quality of life, but does not cure PNH. Nonrandomized studies suggest that long-term remissions are achievable when using myeloablative or nonmyeloablative/reduced-intensity (NMT/RIC) allogeneic hematopoietic stem cell transplantation (HSCT) as treatment for PNH. Nevertheless, patients with previous life-threatening complications from PNH may be more appropriately treated with an NMT/RIC regimen, rather than a myeloablative approach, because of the increased transplant mortality associated with the latter. The decision to perform an allogeneic HSCT (allo-HSCT) should weigh disease prognosis, by incorporating known adverse prognostic factors such as previous history of thrombosis and/or evolution to pancytopenia, among others, against the risk of transplant-related complications. Selection of the appropriate candidate and, equally important, the right time to perform an allo-HCT are important questions that need to be answered in the context of large prospective randomized trials.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".