Outcomes of Early Transition of Low-Risk Thyroid Cancer Patients from Specialist to Primary Care
Bibliographic record
Abstract
Background: Recently published clinical pathways for management of thyroid cancer outlined the criteria for transitioning low-risk patients to primary care within one to five years from diagnosis. However, discharge patterns among endocrinologists remain heterogeneous as there lacks a consensus regarding post-treatment care for thyroid cancer patients. Objective: This study described general characteristics and outcomes of thyroid cancer patients who were discharged from specialist care and transitioned to a primary care-based follow-up clinic. Methods: Thyroid cancer patients seen in the After Cancer Treatment Transition (ACTT) clinic at Women’s College Hospital (Toronto, Canada) were included in the study. Electronic medical records were reviewed between May and October 2021 to collect patient characteristics and outcomes. Descriptive statistics were calculated. Results: The study cohort included 148 thyroid cancer patients and 76% were female. All cases were papillary thyroid cancer and most diagnoses were classified as T2 (42%), N0 (55%), M0 (91%), and stage 1 (83%). Nearly all patients (n = 147) had complete thyroidectomy. Levels of thyroglobulin and thyroglobulin antibodies (TgAb) were low overall, with only 5% of the study cohort deemed TgAb positive. Mean levels of thyroid stimulating hormone (TSH) measured at 2 time points (1.37 mIU/L, 1.42 mIU/L) were within normal range. About 91% of the study cohort had normal TSH levels and 82% met target TSH levels. There were 2 cases of recurrence; however, investigation determined that they were not initially appropriate candidates for transition to primary care. Nearly 99% (n = 146) of patients had excellent response to therapy, showed no evidence of disease recurrence, and have not required re-referral to specialist care. Conclusions: These findings may reassure specialists that low-risk, stable thyroid cancer patients can be safely transitioned to primary care for post-treatment follow-up.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".