Regional variation in cancer‐directed surgery and mortality among women with epithelial ovarian cancer in the medicare population
Bibliographic record
Abstract
BACKGROUND: Regional differences in health services can point to disparities in access to healthcare. The authors performed a population-based cohort study to examine differences in ovarian cancer treatment and mortality according to geographic region. METHODS: The Surveillance, Epidemiology, and End Results (SEER)-Medicare database was used to identify 4589 women aged ≥65 years with ovarian cancer diagnosed between 1998 and 2002 who had Medicare claims filed from 1998 to 2005. Hospital Referral Region (HRR) was assigned according to patient zip code. The authors calculated the proportion of women in each HRR who underwent cancer-directed surgery. With HRR as the predictor of interest, mortality and the receipt of cancer-directed surgery were described in multivariate analyses. RESULTS: Among 4589 women with ovarian cancer, 3286 underwent cancer-directed surgery. The receipt of cancer-directed surgery varied by HRR (range, 53%-88%). Women were less likely to undergo cancer-directed surgery if they were older, nonwhite, had higher stage disease, or had more comorbidities. For example, white women were more likely to undergo such surgery (odds ratio, 1.41; 95% confidence interval, 1.10-1.82) compared with all nonwhite women. HRR was a significant predictor of cancer-directed surgery (P = .01). A significant correlation was observed between HRR and all-cause mortality (P = .02); however, after adjusting for cancer-directed surgery, that correlation was no longer significant (P = .10). CONCLUSIONS: There was regional variation in mortality among Medicare recipients with ovarian cancer, and access to cancer-directed surgery explained some of that variation. Improving access to high-quality cancer surgery for ovarian cancer may improve outcomes, particularly for minorities and for older women.
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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) | 0.001 | 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 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".