Assessing the Impact of Marginalization on Survival for Patients Undergoing Allogeneic Stem Cell Transplant in Ontario, Canada
Bibliographic record
Abstract
Background Allogeneic hematopoietic stem cell transplants (allo-SCT) are potentially life-saving interventions used to treat hematologic disorders. Recent studies have shown that living in rural areas may predict worse outcomes after allo-SCT. Marginalization, a term that encompasses social and health-related factors affecting individuals, is predictive of adverse health outcomes. The Ontario Marginalization Index (ON-Marg), an administrative index using variables obtained from census data, was used to identify marginalization status (quintile 1-least marginalized; quintile 5-most marginalized) encompassing four domains: residential instability (area-level concentrations of people who experience high rates of family or housing instability), material deprivation (area-level concentrations of inability for individuals and communities to access and attain basic material needs), dependency (area-level concentrations of people who do not have income from employment), and ethnic concentration (area-level concentrations of people who are recent immigrants and/or a visible minority). In a publicly-funded healthcare context, it is important to know how marginalization impacts survival for patients undergoing allo-SCT. Methods We performed a retrospective population-based study using administrative healthcare databases from Ontario, Canada. Patients were included if they were 18 years or older at the time of allo-SCT, and had undergone allo-SCT for acute myeloid leukemia (AML), myelodysplastic syndrome (MDS) or acute lymphoblastic leukemia (ALL) between 2010 and 2022. Patients were excluded if they were a non-Ontario resident at the time of allo-SCT and as a result lacked ON-Marg data. Patients who received allo-SCT for a different indication were excluded. The primary outcome of this study was 2-year overall survival (OS) from time of transplant to death or end of the study period, based on ON-Marg quintiles. Multivariable Cox regression analysis was used to identify baseline characteristics associated with OS, with ON-Marg as the main exposure. Results A total of 1961 patients underwent allo-SCT for AML/MDS/ALL. The median age of patients undergoing allo-SCT was 55 years (IQR 43-63), and 55% of patients were male. 40% of patients had high aggregated diagnosis group (ADG) comorbidity burden, and a majority of patients (64%) lived within 50 kilometers (km) from the transplant center, with a mean distance of 33 km in the entire study population. The distribution of patients across each quintile of marginalization was not always uniform. For ethnic concentration, 24% of patients were in quintile 5, with 17% of patients in quintile 1. For dependency, 19% of patients were in quintile 5, and 25% of patients were in quintile 1. During the follow-up period, 43% of patients (n = 842) died. 2-year OS was not significantly different across all quintiles of the ethnic concentration domain of marginalization ( Figure 1A). 2-year OS was worse (HR 1.27, 95% CI 1.02-1.57) for patients in quintile 4 compared to quintile 1 of the dependency domain of marginalization ( Figure 1B). This effect persisted in multivariable logistic regression analyses accounting for other demographic variables ( Table 1). Increased age and a higher comorbidity index were significantly associated with worse survival across all domains. Patients with ALL had worse outcomes compared to patients with AML/MDS across all domains of marginalization. There was also a trend toward patients living >200 km from the transplant center having an increased risk of death compared to patients living less than 50 km from the center (HR 1.24, 95% CI 1.00-1.54). Conclusion This study shows that 2-year OS after allo-SCT for AML/MDS/ALL was not affected by marginalization quintile of ethnic concentration. This is in keeping with other published data suggesting that outcomes after allo-SCT are not impacted by socioeconomic factors such as race. Patients in quintile 4 of dependency had worse outcomes than patients in quintile 1, suggesting that employment and income support are crucial to successful patient outcomes. A majority of patients who underwent allo-SCT lived in close proximity to the transplant center. Transplant outcomes in general do not appear to vary based on marginalization status, and it is therefore crucial that all patients who may benefit receive allo-SCT regardless of demographics or distance to treatment centers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".