Low Body Mass Index Is Associated with Increased Risk of Acute GVHD after Umbilical Cord Blood Transplantation in Children and Young Adults with Acute Leukemia: A Study on Behalf of Eurocord and the EBMT Pediatric Disease Working Party
Bibliographic record
Abstract
Body mass index (BMI) may influence outcomes after allogeneic hematopoietic stem cell transplantation (HSCT). However, the impact of BMI on survival in children undergoing HSCT is not well defined, with conflicting results being reported on this issue. We analyzed 855 patients age 2 to 20 years with diagnosis of acute leukemia who underwent umbilical cord blood transplantation (UCBT) from 1990 to 2015. Patients were classified according to BMI as normal (fifth to 85th percentile), underweight (less than fifth percentile), overweight (85th to 95th percentile), and obese (>95th percentile) using growth charts for age and sex. All patients received single-unit UCBT after a myeloablative conditioning regimen. Diagnosis was acute lymphoblastic leukemia in 68% of the patients. Sixty-one percent of patients (n = 523) were in the normal BMI category, 11% (n = 96) were underweight, 16% (n = 137) overweight, and 12% (n = 99) obese. The cumulative incidence of grade II to IV acute graft-versus-host disease (aGVHD) was 35% (32% to 38%). According to pretransplantation BMI, aGVHD was 46% (33% to 59%) for underweight, 34% (31% to 42%) for normal, 36% (18% to 38%) for overweight, and 27% (15% to 37%) for obese (P = .04). In multivariate analysis, a BMI less than the fifth percentile was associated with higher incidence of acute grade II to IV GVHD compared with normal-BMI patients (hazard ratio, 1.61; 95% confidence interval, 1.15 to 2.26; P = .006). Our results show that being underweight at the time of transplantation is associated with an increased risk of aGVHD, highlighting the importance of nutritional status before UCBT.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".