Costs and Cost-Effectiveness of Allogeneic Stem Cell Transplantation in Children Are Predictable
Bibliographic record
Abstract
The overall costs of pediatric stem cell transplantation (SCT), including donor search and costs during the first year post-SCT, were calculated in a cohort of 141 consecutive children undergoing SCT in a single institution. Costs were correlated with patient and transplantation characteristics and with a risk score for transplantation-related mortality. Cost-effectiveness was calculated based on the overall cost per surviving patient. Life-years gained were extrapolated from overall survival, and the costs per expected life-year gained were calculated. The overall median cost was €136,382 (175,815$), with a wide range, of €26,897 (34,679$) to €601,348 (775,343$). Increased costs were significantly associated with age, use of donors other than matched siblings, and advanced disease. There was a strong correlation of costs with a simple transplantation-related mortality risk score; median total costs were €89,550 (115,463$) for a score of 0, €127,349 (164,179$) for a score of 1, €156,578 (201,861$) for a score of 2, and €274,915 (354,499$) for a score of 3 (P < .001). Cost-effectiveness decreased with increasing transplantation-related mortality risk score; costs per survivor increased from €93,209 (120,200$) for a score of 0 to a maximum of €1,216,348 (1,568,579$) for a score of 3. Costs associated with pediatric SCT vary substantially; however, the combination of variables such as age, disease, and donor type is predictive of costs and cost-effectiveness. Costs per life-year gained are within the broadly accepted range in life-threatening hemato-oncologic diseases, even in the most cost-intensive patient cohort.
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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 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".