Impact of age on outcomes after bone marrow transplantation for acquired aplastic anemia using HLA-matched sibling donors
Bibliographic record
Abstract
BACKGROUND: Transplantation from an HLA-matched sibling is the treatment of choice for young patients with acquired severe aplastic anemia. For older patients, the acceptable upper age limit for transplantation as first-line treatment varies. The current analysis, therefore, sought to identify age or ages at transplantation at which survival differed. DESIGN AND METHODS: We studied the effect of patients' age, adjusting for other significant factors affecting outcomes, in 1307 patients with severe aplastic anemia after HLA-matched sibling transplantation using logistic and Cox regression analysis. Age categories (<20 years, 20-40 years, >40 years) were determined using Martingale residual plots for overall survival and categories based on differences in survival. RESULTS: Patients aged over 40 years old were more likely to have had immunosuppressive therapy, a poor performance score and a longer interval between diagnosis and transplantation. Neutrophil recovery was similar in all age groups but patients aged over 40 years had a lower likelihood of platelet recovery compared to patients aged less than 20 years (OR 0.45, P=0.01) but not compared to those aged 20-40 years (OR 0.60, P=0.10). Compared to the risk of mortality in patients aged less than 20 years, mortality risks were higher in patients over 40 years old (RR 2.70, P<0.0001) and in those aged 20-40 years (RR 1.69, P<0.0001). The mortality risk was also higher in patients aged over 40 years than in those 20-40 years old (RR 1.60, P=0.008). CONCLUSIONS: Mortality risks increased with age. Risks were also higher in patients with a poor performance score and when the interval between diagnosis and transplantation was longer than 3 months, implying earlier referral would be appropriate when this treatment option is being considered.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".