Weight Loss Post Allogeneic Stem Cell Transplant is Associated with Increased Transplant Related Mortality
Bibliographic record
Abstract
Abstract Purpose: Allogeneic Stem Cell Transplant (allo-HSCT) patients are at risk of malnutrition and weight loss from impaired oral intake resulting from gastrointestinal toxicities, dysgeusia, and psychological effects. Methods: A retrospective review of 264 adult patients transplanted at Princess Margaret Cancer Centre who achieved relapse-free survival up to 3 months after allo-HSCT was performed. Results: Overall incidence of patients who experienced WL (WL) ≥10% from HSCT to 3 months post-transplant was 45.9% and from HSCT to 6 months was 56.6%. Patients with ≥10% WL from allo-HSCT at 3-months and 6 months had similar 2-year overall survival (OS) compared to those with <10% WL, 55.7% vs. 62.8% (HR=1.38, p=0.11) and 71.1% vs. 77.2% (HR=1.37, P=0.27), respectively. Patients with ≥10% WL 3- and 6-months from allo‑HSCT also had similar 2-year relapse-free survival (RFS) compared to those with <10% WL, 48.1% vs. 55.8% (HR=1.26, p=0.22), and 62.7% vs 69.8% (HR=1.29, p=0.31), respectively. The 2-year transplant-related mortality (TRM) was higher for those with ≥10% WL from allo-HSCT to 3-months, 35.4% vs. 16.9% (HR=2.39, p=0.0007) and 6 months, 22% vs. 8% (HR=3.1, p=0.0034). Although statistical significance was not observed for OS or RFS, patients who experienced ≥10% WL 3- and 6-months post allo-HSCT experienced higher 2-year TRM. These results highlight the importance of early intervention and close monitoring of weight post allo-HSCT. Conclusion: Approaches to WL post allo-HSCT should be multifaceted and include members of the interdisciplinary team in order to decrease TRM.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".