Race, insurance type, and stage of presentation among lung cancer patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this study was to determine whether African-American lung cancer patients are diagnosed at a later stage than white patients, regardless of insurance type. The relationship between race and stage at diagnosis by insurance type was assessed using a Poisson regression model, with relative risk as the measure of association. The setting of the study was a large tertiary care cancer center located in the southeastern United States. Patients who were diagnosed with lung cancer between 2001 and 2010 were included in the study. A total of 717 (31%) African-American and 1,634 (69%) white lung cancer patients were treated at our facility during the study period. Adjusting for age, sex, and smoking-related histology, African-American patients were diagnosed at a statistically significant later stage (III/IV versus I/II) than whites for all insurance types, with the exception of Medicaid. Our results suggest that equivalent insurance coverage may not ensure equal presentation of stage between African-American and white lung cancer patients. Future research is needed to determine whether other factors such as treatment delays, suboptimal preventive care, inappropriate specialist referral, community segregation, and a lack of patient trust in health care providers may explain the continuing racial disparities observed in the current study.
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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 it