A pilot study examining Toronto-area family physician perspectives on thyroid neoplasm evaluation
Bibliographic record
Abstract
OBJECTIVE: The incidence of thyroid cancer (TC) is known to be very high in the Greater Toronto Area of Ontario, Canada. We performed a pilot survey study examining Toronto-area family physician (FP) perspectives on thyroid neoplasm evaluation (i.e. thyroid nodules [TNs] or thyroid cancer [TC]) in this region, to explore for potential factors leading to overdiagnosis. METHODS: We performed a cross-sectional mail-out written survey of a random sample of 300 FPs in active practice in the Greater Toronto Area (Markham and Brampton). RESULTS: The overall response rate was 22.3, 95% confidence interval (CI) 18.0, 27.4% (67/300); the effective response rate was 19.9, 95% CI 15.7, 24.9% (58/291), after excluding 6 FPs that reported TN evaluation was outside their scope of practice and three FPs with an invalid mailing address. There were no missing responses to questions. The demographic characteristics were as follows: 58.6% (34/58) from Markham, 55.2% (32/58) were female, 58.6% (34/58) were in practice > 10 years, and 32.8% (19/58) affiliated with a University. All FPs reported easy access to thyroid ultrasound (TUS). About half of FPs were concerned about overdiagnosis of TC and most did not believe that there was any TC survival advantage with routine screening TUS. Although appropriate indications for TUS were endorsed by most respondents (e.g. palpable TN, incidental TN on other imaging), inappropriate recommendations were observed in a third of FPs (19/57) who recommended TUS for abnormal thyroid blood tests about half of FPs (30/56) who endorsed biopsy of sub-centimeter nodules. About half of FPs (31/58) reported that their patients sometimes request medically unnecessary TUS. CONCLUSION: There are likely multiple complex factors leading to potential overdiagnosis of TC in primary care, including some physicians' knowledge gaps about appropriate indications for TN investigations as well as patients' requests and expectations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".