Access to Hematopoietic Stem Cell Transplant in Canada for Patients with Acute Myeloid Leukemia
Bibliographic record
Abstract
Hematopoietic stem cell transplant is a complicated intervention only offered in specialized centers. Access to transplants may vary based on the location of primary residence, income levels, age, and reported race or ethnicity. Using data from the Canadian Institute of Health (CIH) Discharge abstract database (DAD), all non-Quebec Canadians under the age of 65 with a diagnosis of AML between 2004 and 2015 were included in this study. Descriptive statistics were produced for the variables of interest: time period, age, sex, rurality, transplant status, proportion of visible minorities, proportion identifying as indigenous, and proportion of low-income families. Transplant rates were compared and reported using univariable and multivariable analysis. In multivariable analysis, time period, province of residence, gender, and age were significantly associated with the receipt of an allogeneic hematopoietic stem cell transplant. However, differences in transplant rates observed in indigenous patients, low-income families, and visible minorities were not found to be statistically significant. In non-Quebec Canada, transplant rates vary significantly with province of residence, with the highest rates recorded in Alberta. Contrary to findings previously reported in studies exploring access to transplant in the United States, a low-income level was not associated with lower rates of transplants. This might suggest that Canada's universal health care insurance program is protective against socioeconomic barriers that impact access to health care services.
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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 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".