Endocrinologist-Perceived Factors Affecting the Transition of Thyroid Cancer Patients from Specialist to Primary Care Postcancer Treatment in Ontario, Canada
Bibliographic record
Abstract
Background: Thyroid cancer patient discharge patterns from specialists are heterogeneous, with some specialists following patients for a longer period of time than others. With no well-established transitional plan, such as in breast and colorectal cancer, primary care physicians play a variable role in long-term thyroid cancer care. The objective of this study was to examine endocrinologist-perceived factors affecting the transition of care for thyroid cancer patients through a qualitative and quantitative survey of practicing endocrinologists in Ontario, Canada. Methods: All eligible practicing endocrinologists in Ontario were invited to participate in the study, via an email with an embedded survey link. Consent was assumed if the physician completed the survey. The survey collected physician demographics and asked a series of Likert-scale and open-ended questions on their views regarding transitioning care of their thyroid cancer patients. Quantitative analysis was based on mode and variability. Qualitative analysis was completed using inductive thematic analysis. Results: Seventy physicians completed the survey, with a response rate of 35.5%. Based on the responses to the Likert-scale questions, there was a lack of consensus in terms of discharging criteria for patients who had low-risk papillary thyroid cancer, stable thyrotropin levels, multiple nonthyroid-related comorbidities, and hemithyroidectomy with no disease recurrence. The majority of endocrinologists responded that the main factors affecting discharge included whether the primary care physician was able to follow their recommendations, whether the primary care physician could appropriately adjust levothyroxine doses, and whether the patient was confident that their primary care physician could manage their thyroid cancer follow-up. Themes extracted from the open-ended question also indicated that the main factors affecting the transition of care were related to the primary care physician, the patient, the imaging interpretation, and the discharge guidelines. Conclusion: The lack of consensus among endocrinologists affects the transition of patient care, and there is a need to provide clear and accurate information to primary care physicians and thyroid cancer patients on postcancer treatment care. Efforts should be sought to standardize discharge and long-term care.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".