Impact of comorbidities constituting the hematopoietic cell transplant (HCT)‐comorbidity index on the outcome of patients undergoing allogeneic HCT for acute myeloid leukemia
Bibliographic record
Abstract
OBJECTIVE: To investigate the prognostic impact of the individual component comorbidities of the hematopoietic cell transplant comorbidity index (HCT-CI) in patients with acute myeloid leukemia (AML) that underwent allogeneic hematopoietic cell transplant (HCT). METHOD: This single-center study retrospectively investigated the individual comorbidities of the HCT-CI on the outcome of 418 patients that underwent HCT for AML, in CR1 (n = 303, 72%) or CR2 (n = 115, 28%) at our center between 1999 and 2014. RESULTS: Median age at HCT was 50 years (range 18-71). Univariate analysis of the HCT-CI, grouped as score 0 (n = 109), 1-2 (n = 157) and ≥3 (n = 152), demonstrated significant influence on overall survival (OS) (P = .004) and non-relapse mortality (NRM) (P = .02). For individual comorbidities constituting the HCT-CI, variables with a P-value ≤ .2 on univariate analysis were included in the multivariable analysis. For OS, none of the comorbidities of the HCT-CI demonstrated independent prognostic relevance. However, for NRM, multivariable analysis demonstrated pretransplant diabetes (HR = 2.17, 95% CI = 1.31-3.60, P = .003) and cardiovascular comorbidity (HR = 1.78, 95% CI = 1.15-2.76, P = .01) to be independent predictors of NRM post-transplant. CONCLUSION: Among the comorbidities that compose the HCT-CI, diabetes and cardiovascular comorbidity independently predict NRM in patients undergoing allogeneic HCT for AML. This information should be taken into consideration regarding post-transplant monitoring and care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".