Association of area sociodemographic characteristics and capacity for treatment with disparities in colorectal cancer care and mortality
Bibliographic record
Abstract
BACKGROUND: Disparities in treatment and mortality for colorectal cancer (CRC) may reflect differences in access to specialized care or other characteristics of the area where an individual lives. METHODS: Surveillance, Epidemiology and End Results Program-Medicare data for seniors diagnosed with CRC were linked to area measures of the sociodemographic characteristics and the capacity of surgeons, medical oncologists, and radiation oncologists. Outcomes included receipt of stage-appropriate CRC care and mortality. RESULTS: After adjustment, blacks and Hispanics were less likely than whites to undergo surgery (odds ratio [OR] 0.57, 95% confidence interval (CI) 0.52-0.63 and OR 0.82, 95% CI 0.70-0.95, respectively). Individuals who lived in areas with the highest tertile of surgeon capacity were more likely to undergo resection than those in the lowest, and use of surgery declined as the percentage of blacks in the area increased. Adjustment for the area measures resulted in a modest decline in disparities in care relative to whites (5.3% for black). Blacks also experienced greater all-cause and cancer-specific mortality than whites. Further adjustment for area sociodemographics and surgeon capacity reduced the disparity in mortality between blacks and whites. Although there was a similar black/white disparity in the use of adjuvant chemotherapy, the disparity remained after adjustment for area characteristics, although use of chemotherapy was greater in areas with the greatest capacity of medical oncologists. CONCLUSIONS: Sociodemographic characteristics and measures of the availability of specialized cancer providers in the area in which an individual resides modestly mediated disparities in the receipt of CRC care and mortality, suggesting that other factors may also be important.
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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".