Race, Income, and Survival in Stage III Colon Cancer: CALGB 89803 (Alliance)
Bibliographic record
Abstract
Abstract Background Disparities in colon cancer outcomes have been reported across race and socioeconomic status, which may reflect, in part, access to care. We sought to assess the influences of race and median household income (MHI) on outcomes among colon cancer patients with similar access to care. Methods We conducted a prospective, observational study of 1206 stage III colon cancer patients enrolled in the CALGB 89803 randomized adjuvant chemotherapy trial. Race was self-reported by 1116 White and 90 Black patients at study enrollment; MHI was determined by matching 973 patients’ home zip codes with publicly available US Census 2000 data. Multivariate analyses were adjusted for baseline sociodemographic, clinical, dietary, and lifestyle factors. All statistical tests were 2-sided. Results Over a median follow-up of 7.7 years, the adjusted hazard ratios for Blacks (compared with Whites) were 0.94 (95% confidence interval [CI] = 0.66 to 1.35, P = .75) for disease-free survival, 0.91 (95% CI = 0.62 to 1.35, P = .65) for recurrence-free survival, and 1.07 (95% CI = 0.73 to 1.57, P = .73) for overall survival. Relative to patients in the highest MHI quartile, the adjusted hazard ratios for patients in the lowest quartile were 0.90 (95% CI = 0.67 to 1.19, Ptrend = .18) for disease-free survival, 0.89 (95% CI = 0.66 to 1.22, Ptrend = .14) for recurrence-free survival, and 0.87 (95% CI = 0.63 to 1.19, Ptrend = .23) for overall survival. Conclusions In this study of patients with similar health-care access, no statistically significant differences in outcomes were found by race or MHI. The substantial gaps in outcomes previously observed by race and MHI may not be rooted in differences in tumor biology but rather in access to quality care.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".