Incidence and Prognostic Value of Eosinophilia in Chronic Graft-versus-Host Disease after Nonmyeloablative Hematopoietic Cell Transplantation
Bibliographic record
Abstract
Data from a number of cohorts indicate that eosinophilia (Eo) could be associated with better outcomes following allogeneic hematopoietic cell transplant (HCT). However, little is known about its significance and prognostic value in chronic graft-versus-host disease (cGVHD) after nonmyeloablative (NMA) transplantation. Data were collected from 170 patients who underwent HCT using the same preparative regimen and GVHD prophylaxis. Donors were 6/6 HLA-matched siblings and stem cell source was peripheral blood. An eosinophil count of ≥0.5 × 10(9)/L was defined as Eo. Patients were transplanted mainly for lymphoproliferative disorders. Median age and follow-up were 54 years and 58 months, respectively. Incidents of grade II-IV acute GVHD (aGVHD) and cGVHD were 8.2% and 81.2%. Median time from HCT to cGVHD diagnosis was 142 days. Organs involved were: mouth in 80% of patients, skin in 75%, liver in 57%, eyes in 37%, gut in 14%, lungs in 5%, others in 5%. Eo was found in 44% of patients at diagnosis of cGVHD (range: 0.5-4.4 × 10(9)/L). Median time between first appearance of Eo and diagnosis of cGVHD was 4.5 days. We found no correlation between organ involvement and Eo but a lower prevalence of Eo in cGVHD associated with thrombocytopenia (P = .023). Nevertheless, we observed no association among Eo and overall survival (OS), relapse incidence, or nonrelapse mortality (NRM) in the overall cohort, nor in subsets of patients with multiple myeloma and follicular non-Hodgkin lymphoma. Although Eo is observed frequently in cGVHD following NMA transplantation, we report no correlation beween Eo and outcome.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".