Material deprivation and access to cancer care in a universal health care system
Bibliographic record
Abstract
BACKGROUND: The role of socioeconomic factors as determinants of oncology consultations for advanced cancers in public payer health care systems is unknown. This study examined the association between material deprivation and receipt of cancer care among patients with advanced gastrointestinal (GI) cancer. METHODS: This was a population-based, retrospective cohort study of noncuratively treated patients with GI cancer diagnosed from 2007 to 2017. Material deprivation, representing income, quality of housing, education, and family structure, was defined as quintiles on the basis of 2016 census data. The first consultation with a radiation oncologist or medical oncologist and the receipt of 1 or more instances of radiation and/or chemotherapy were measured in the year after diagnosis. Adjusted, cause-specific Cox proportional hazards competing risk analyses were used (competing event = death). RESULTS: This study included 34,022 noncuratively treated patients with GI cancer. Consultation rates ranged from 67.8% for those in the most materially deprived communities to 73.5% for those in the least materially deprived communities. Among those with a consult, rates of cancer-directed therapy ranged from 58.5% for patients in the most materially deprived communities to 62.3% for patients in the least materially deprived communities. Patients living in the most materially deprived communities were significantly less likely to see a radiation and/or medical oncologist after a diagnosis (hazard ratio [HR], 0.88; 95% confidence interval [CI], 0.85-0.92) and significantly less likely to receive radiation and/or chemotherapy (HR, 0.80; 95% CI, 0.76-0.85) than those living in the least materially deprived communities. CONCLUSIONS: This study identified socioeconomic disparities in accessing cancer care. Continued efforts at examining and developing evidence-based policies for interventions that begin before or at the time of oncologist consultation are required to address root causes of inequities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".