Successful treatment of refractory red cell aplasia after allogeneic hematopoietic cell transplantation with daratumumab
Bibliographic record
Abstract
Pure red cell aplasia (PRCA) is an uncommon complication secondary to ABO mismatched allogeneic stem-cell transplantation (allo-HSCT). The best approach for PRCA after allo-HSCT remains unclear. We aim to report a single case with refractory PRCA post-ABO mismatched allo-HSCT resolved with daratumumab. A 34-year-old male diagnosed with aplastic anemia in March 2014 received a peripheral blood reduced-intensity allo-HSCT from an HLA-matched related donor in July 2016. Donor and recipient blood groups were AB positive and 0 positive, respectively, indicating a major ABO incompatibility. The patient was diagnosed with PRCA 2 months after allo-HSCT. After failing multiple standard lines of treatment, compassionate treatment with daratumumab was requested. After receiving six doses of daratumumab, the patient had a marked reticulocyte response and consecutively become transfusion independent. In conclusion, Daratumumab is a human IgG1κ monoclonal antibody targeting CD38 and is used to treat multiple myeloma. The use of anti-CD38 therapy with daratumumab to target residual host plasma cells is safe and effective, and it can be considered in refractory recipients with PRCA after allo-HSCT secondary to ABO incompatibility.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".