Access to Care and Outcomes for Neuroendocrine Tumours: Does Socioeconomic Status Matter?
Bibliographic record
Abstract
Introduction: Neuroendocrine tumours (NETS) are a poorly understood malignancy lacking standardized care. Differences in socioeconomic status (SES) might worsen the effect of non-standardized care. We examined the effect of SES on NET peri-diagnostic care patterns and outcomes. Methods: In this population-based cohort study, NET cases identified from a provincial cancer registry (1994–2009) were divided into low (1st and 2nd income quintiles) and high (3rd, 4th, and 5th quintiles) SES groups. We compared peri-diagnostic health care utilization (–2 years to +6 months), metastatic recurrence, and overall survival (os) between the groups. Results: Of 4966 NET patients, 38.3% had a low SES. Neither the primary NET sites (p = 0.15), nor the metastatic presentation (p = 0.31) differed. Patients with low SES had a higher mean number of physician visits (20.1 ± 19.9 vs. 18.1 ± 16.5, p = 0.001) and imaging studies (56 ± 50 vs. 52 ± 44, p = 0.009) leading to the NET diagnosis. Rates of primary tumour resection (p = 0.14), hepatectomy (p = 0.45), systemic therapy (p = 0.38), and liver embolization (p = 0.13) did not differ with SES. In the low-SES group, metastatic recurrence was more likely (41.1% vs. 37.6%, p = 0.01) during a median follow-up of 61.7 months, and the 10-year os was inferior (47.1% vs. 52.2%, p < 0.01). Low SES was associated with worse os (hazard ratio: 1.16; 95% confidence interval: 1.06 to 1.26) after adjustment for age, sex, comorbidity burden, primary NET site, and rural living. Conclusions: Low SES was associated with more physician visits and imaging before a NET diagnosis, but not with more advanced stage at presentation nor with an effect on the pattern of therapy. Long-term outcomes were inferior in the low-SES group. These data can help to inform the design of health care delivery for NETS.
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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".