Insurance status and distant‐stage disease at diagnosis among adolescent and young adult patients with cancer aged 15 to 39 years: National Cancer Data Base, 2004 through 2010
Bibliographic record
Abstract
BACKGROUND: The percentage of adolescent and young adult (AYA) patients with cancer (those aged 15-39 years) diagnosed at a distant stage of disease did not significantly change between 1975 and 2004. It has been hypothesized that a lack of health insurance may be a significant risk factor for a diagnosis of distant-stage disease among AYA patients, but to the authors' knowledge this has not been examined in a national sample. METHODS: The National Cancer Data Base, a hospital-based cancer registry, was used to obtain data regarding incident cancer cases among patients aged 15 years to 39 years who were diagnosed between 2004 and 2010. After all exclusions, a total of 285,448 cases were available for analysis; all AYA cancer sites were included. A retrospective study was conducted to assess the association between insurance status and stage of disease at diagnosis. RESULTS: After adjusting for age, race/ethnicity, facility type, ZIP code-based income and education levels, and US Census region, it was found that among males, uninsured patients were 1.51 times more likely to be diagnosed at a distant stage of disease compared with patients with private insurance (95% confidence interval, 1.46-1.55). Among females, the effect of insurance was stronger, with uninsured patients found to be 1.86 times more likely to be diagnosed at a distant stage (95% confidence interval, 1.79-1.94). The effect of insurance status was substantially stronger for malignancies that are more amenable to early detection (melanoma, thyroid carcinoma, breast carcinoma, genitourinary carcinoma), and substantially weaker for those that are less amenable to early detection (lung carcinoma, adrenocortical carcinoma, Wilms tumor). CONCLUSIONS: In a large national sample of AYA patients with cancer, insurance status was found to be a strong independent risk factor for distant-stage disease at the time of diagnosis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".