Clonal hematopoiesis in the donor does not adversely affect long-term outcomes following allogeneic hematopoietic stem cell transplantation: result from a 13-year follow-up
Bibliographic record
Abstract
Donor clonal hematopoiesis may be transferred to the recipient through allogeneic hematopoietic stem cell transplantation (HSCT), but the potential for adverse long-term impact on transplant outcomes remains unknown. A total of 744 samples from 372 recipients who received HSCT and the corresponding donors were included. Bar-coded error-corrected sequencing using a modified molecular inversion probe capture protocol was performed, which targeted 33 genes covering mutations involved in clonal hematopoiesis with indeterminate potential (CHIP) and other acute myeloid leukemia-related mutations. A total of 30 mutations were detected from 25 donors (6.7%): the most frequently mutated gene was TET2 (n=7, 28%), followed by DNMT3A (n=4, 16%), SMC3 (n=3, 12%) and SF3B1 (n=3, 12%). With a median follow-up duration of 13 years among survivors, the presence of CHIP in the donor was not associated with recipient overall survival (P=0.969), relapse incidence (P=0.600) or non-relapse mortality (P=0.570). Donor CHIP did not impair neutrophil (P=0.460) or platelet (P=0.250) engraftment, the rates of acute (P=0.490), or chronic graft-versus-host disease (P=0.220). No significant difference was noted for secondary malignancy following HSCT between the two groups. The present study suggests that the presence of CHIP in allogeneic stem donors does not adversely affect transplant outcomes after HSCT. Accordingly, further study is warranted to reach a clearer conclusion on whether molecular profiling to determine the presence of CHIP mutations is necessary for the pretransplant evaluation of donors prior to stem cell donation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".