Regional Differences in Opinions on Adjuvant Radioactive Iodine Treatment of Thyroid Carcinoma within Canada and the United States
Bibliographic record
Abstract
OBJECTIVE: To identify regional differences in recommendations for radioactive iodine remnant ablation (RRA) in early stage well-differentiated thyroid carcinoma (WDTC) within Canada and the United States. DESIGN: A cross-sectional written survey of a sample of physicians in specialties potentially involved in thyroid cancer care was performed in 2006. Participants were asked if they recommended RRA for a hypothetical 38-year-old woman with a solitary, 1.6-cm papillary carcinoma resected by total thyroidectomy. Exploratory regional comparisons were performed using Student t tests or analysis of variance. The regions studied were western Canada, eastern Canada (Ontario, the Maritimes), Quebec, the northeastern United States, the western and midwestern United States, and the southern United States. In a secondary multivariable logistic regression analysis, we explored potential relationships between individual respondent characteristics RRA recommendations. MAIN OUTCOME: Agreement with case-based RRA recommendations was measured on a Likert scale of 1 to 7 (7 = strongest agreement). RESULTS: The effective response rate was 56.3% (486/864). There were significant differences in RRA recommendations among the regions studied (F = 11.99, 5 df, p < 0.001); national boundaries did not explain regional variations. For the sample case, the strongest support for RRA was in Quebec and the southern United States, intermediate support in eastern Canada and the northeastern United States, and the least support in western Canada and the western and midwestern United States. Academic affiliation and surgical specialty were independently inversely associated with strong RRA recommendations. CONCLUSIONS: There are significant regional differences in physician-based RRA recommendations in early stage WDTC within Canada and the United States. Physician specialty and practice characteristics may influence RRA recommendations.
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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 | 0.000 |
| 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".