Community health status and outcomes after allogeneic hematopoietic cell transplantation in the United States
Bibliographic record
Abstract
BACKGROUND: The association of community factors and outcomes after hematopoietic cell transplantation (HCT) has not been comprehensively described. Using the County Health Rankings and Roadmaps (CHRR) and the Center for International Blood and Marrow Transplant Research (CIBMTR), this study evaluated the impact of community health status on allogeneic HCT outcomes. METHODS: This study included 18,544 adult allogeneic HCT recipients reported to the CIBMTR by 170 US centers in 2014-2016. Sociodemographic, environmental, and community indicators were derived from the CHRR, an aggregate community risk score was created, and scores were assigned to each patient (patient community risk score [PCS]) and transplant center (center community risk score [CCS]). Higher scores indicated less healthy communities. The impact of PCS and CCS on patient outcomes after allogeneic HCT was studied. RESULTS: The median age was 55 years (range, 18-83 years). The median PCS was -0.21 (range, -1.37 to 2.10; standard deviation [SD], 0.42), and the median CCS was -0.13 (range, -1.04 to 0.96; SD, 0.40). In multivariable analyses, a higher PCS was associated with inferior survival (hazard ratio [HR] per 1 SD increase, 1.04; 99% CI, 1.00-1.08; P = .0089). Among hematologic malignancies, a tendency toward inferior survival was observed with a higher PCS (HR, 1.04; 99% CI, 1.00-1.08; P = .0102); a higher PCS was associated with higher nonrelapse mortality (NRM; HR, 1.08; 99% CI, 1.02-1.15; P = .0004). CCS was not significantly associated with survival, relapse, or NRM. CONCLUSIONS: Patients residing in counties with a worse community health status have inferior survival as a result of an increased risk of NRM after allogeneic HCT. There was no association between the community health status of the transplant center location and allogeneic HCT outcomes.
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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 | 0.003 |
| 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 | 0.001 |
| 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".