Is it time to reconsider lobectomy in low‐risk paediatric thyroid cancer?
Bibliographic record
Abstract
OBJECTIVE: Current guidelines recommend total thyroidectomy for nearly all children with well-differentiated thyroid cancer (WDTC). These guidelines, however, derive from older data accrued prior to current high-resolution imaging. We speculate that there is a subpopulation of children who may be adequately treated with lobectomy. DESIGN: Retrospective analysis of prospectively maintained database. PATIENTS: Seventy-three children with WDTC treated between 2004 and 2015. MEASUREMENTS: We applied two different risk-stratification criteria to this population. First, we determined the number of patients meeting American Thyroid Association (ATA) 'low-risk' criteria, defined as disease grossly confined to the thyroid with either N0/Nx or incidental microscopic N1a disease. Second, we defined a set of 'very-low-risk' histopathological criteria, comprising unifocal tumours ≤4 cm without predefined high-risk factors, and determined the proportion of patients that met these criteria. RESULTS: Twenty-seven (37%) males and 46 (63%) females were included in this study, with a mean age of 13·4 years. Ipsilateral- and contralateral multifocality were identified in 27 (37·0%) and 19 (26·0%) of specimens. Thirty-seven (51%) patients had lymph node metastasis (N1a = 18/N1b = 19). Pre-operative ultrasound identified all cases with clinically significant nodal disease. Of the 73 patients, 39 (53·4%) met ATA low-risk criteria and 16 (21·9%) met 'very-low-risk' criteria. All 'very-low-risk' patients demonstrated excellent response to initial therapy without persistence/recurrence after a mean follow-up of 36·4 months. CONCLUSIONS: Ultrasound and histopathology identify a substantial population that may be candidates for lobectomy, avoiding the risks and potential medical and psychosocial morbidity associated with total thyroidectomy. We propose a clinical framework to stimulate discussion of lobectomy as an option for low-risk patients.
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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 | 0.001 |
| 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) | 0.007 | 0.008 |
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; both teacher heads agree on what is shown here.
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".