Surveillance after resection for colorectal cancer
Bibliographic record
Abstract
BACKGROUND: Professional societies recommend posttreatment surveillance for colorectal cancer (CRC) survivors. This study describes the use of surveillance over time, with a particular focus on racial/ethnic disparities, and also examines the role of area characteristics, such as capacity for CRC screening, on surveillance. METHODS: Surveillance, Epidemiology, and End Results (SEER)-Medicare data were used to identify individuals aged 66 to 85 years who were diagnosed with CRC from 1993 to 2005 and treated with surgery. The study examined factors associated with subsequent receipt of a colonoscopy, carcinoembryonic antigen (CEA) testing, primary care (PC) visits, and a composite measure of overall surveillance. RESULTS: Of eligible subjects, 61.0% had a colonoscopy, 68.0% had CEA testing, 77.1% had PC visits, and 43.0% received overall surveillance. After adjustment, blacks were less likely than whites to undergo colonoscopy (odds ratio [OR] 0.76, 95% confidence interval [CI] = 0.69-0.83) and to receive CEA testing and overall surveillance, whereas white/Hispanic rates did not differ. Rates for all outcomes increased from 1993 to 2005, but black/white disparities remained. Individuals in areas with greatest capacity for CRC screening were more likely (OR = 1.09, 95% CI = 1.02-1.18) to receive colonoscopy, and those in areas with the greatest percentage of blacks were less likely (OR = 0.89, 95% CI = 0.83-0.95) to receive colonoscopy. Those living in areas with shortage of PC were less likely to receive PC visits (OR = 0.55, 95% CI = 0.48-0.64) and overall surveillance (OR = 0.83, 95% CI = 0.71-0.98). CONCLUSIONS: Many CRC survivors do not get recommended surveillance, and black/white disparities in rates of surveillance have not improved. Characteristics of the area where an individual lives contribute to the use of surveillance.
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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".