Obesity Does Not Preclude Safe and Effective Myeloablative Hematopoietic Cell Transplantation (HCT) for Acute Myeloid Leukemia (AML) in Adults
Bibliographic record
Abstract
Abstract INTRODUCTION: Obesity is increasingly common in the US and is frequently associated with co-morbid medical conditions that may increase the risk of HCT, often the optimal treatment for AML. HCT risk and outcomes for AML on the basis of body mass index (BMI) have not been well-characterized. Using data from the Center for International Blood and Marrow Transplant Research (CIBMTR), we have previously shown no significant difference in outcomes for autologous HCT for lymphoma among normal weight, overweight, and obese patients (pts) but worse outcomes for underweight pts (Navarro et al, BBMT 2006, 12(5): 541–51). Here, we compare outcomes by weight groups for AML patients who underwent autologous, related, or unrelated HCT. METHODS: Our final population included patients age ≥ 18 who underwent myeloablative unpurged autologous or allogeneic HCT for AML in 1st or 2nd complete remission, primary induction failure, or 1st relapse reported to the CIBMTR from 1995 to 2004. Cord blood HCTs were excluded. Four weight groups were defined based on BMI (BMI=weight (kg)/ height (m2)): underweight <18; normal=18–25; overweight >25–30; and obese >30. Treatment-related mortality (TRM), relapse, leukemia-free survival (LFS), and overall survival (OS) were compared using multivariable proportional hazards regression analysis accounting for patient, disease and HCT-related variables. RESULTS: We included 373 autologous, 2041 related, and 1801 unrelated transplant recipients. Patient-, disease-, and transplant characteristics were well-matched across weight groups and transplant types. Multivariable analysis examining risks (95% confidence intervals) relative to the normal weight group are: HCT Type Normal Underweight Overweight Obese -- =not done due to insufficient number of pts; NS=not significant; treatment failure = death or recurrence of disease. Autologous n=164 n=5 n=112 n=81 Death -- NS NS Treatment failure -- NS NS Relapse -- NS NS TRM -- NS NS Related Allogeneic n=1161 n=31 n=543 n=268 Death 1.86 (1.24–2.78) NS 1.23 (1.04–1.47) Treatment failure 2.08 (1.37–3.15) NS 1.19 (1.00–1.42) Relapse 2.02 (1.18–3.47) NS NS TRM 2.22 (1.17–4.22) NS 1.32 (1.02–1.70) Unrelated Allogeneic n=846 n=31 n=523 n=368 Death NS NS NS Treatment failure NS NS NS Relapse NS 0.82 (0.68–0.99) 0.76 (0.60–0.96) TRM NS NS NS CONCLUSIONS: There were no significant differences in risk of TRM, LFS, relapse or OS for normal weight, overweight or obese patient groups who received autologous HCT. Obese recipients of related HCT for AML had increased risk of death, treatment failure, and TRM, though the magnitude was small, an effect was not seen in the unrelated HCT group. Underweight patients who received a related, but not unrelated HCT, fared substantially worse than normal weight patients for all outcomes. It may be that the higher risk of the unrelated HCT procedure masks important but less obvious risks associated with being underweight whereas in the related donor HCT setting, such risks become manifest. Small numbers of patients limit the ability to better characterize this finding in underweight patients. Disproportionately, fewer transplants have been reported in underweight patients which suggest they experience disease and patient-related factors that preclude transplantation. No differences were observed for incidence of acute or chronic GVHD for any weight group. Overweight and obesity should not be a barrier to HCT; however, caution should be exercised in selecting underweight patients for HCT.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".