Ultrasound Surveillance for Thyroid Malignancies in Survivors of Childhood Cancer Following Radiotherapy: A Single Institutional Experience
Bibliographic record
Abstract
BACKGROUND: Survivors of childhood cancer (SCC) who have received radiotherapy to the head, neck, and upper thorax are at higher risk of developing subsequent thyroid malignancies. As part of the post treatment long-term follow-up protocol, the current Children's Oncology Group guideline recommends surveillance by annual palpation; however, thyroid nodules are difficult to detect by physical examinations alone, and potentially malignancy-harboring nodules may be undetected. Since thyroid ultrasound is a sensitive and noninvasive procedure, it was incorporated in our institutional follow-up protocol. The aim of this study was to examine the outcome of ultrasound screening in this high-risk population. The following describes our experience from 2007 to 2013. METHODS: A retrospective chart review was conducted on survivors enrolled in our follow-up program. SCC who have received direct or scattered radiation to the thyroid gland, and who were ≥10 years from the diagnosis of primary childhood cancer were considered to be at-risk. RESULTS: Seventy-eight survivors met the inclusion criteria and were screened. Thyroid ultrasound detected thyroid nodule(s) in 46 patients (59%), 17 of which had nodule(s) between 5 and 10 mm (22%), and 15 patients had nodules ≥10 mm (19%). Fourteen patients (18%) underwent fine-needle aspiration biopsy. Six patients (8%) underwent surgery, and 5 (6%) had confirmed papillary carcinoma. At the time of the first ultrasound, thyroid nodules of various sizes were found. However, over time, these nodules demonstrated slow growth rates. CONCLUSIONS: Incorporation of thyroid ultrasound into routine follow-up of high-risk SCC may aid in the detection of thyroid malignancies that are not clinically apparent. The use of ultrasound allows detailed characterization of the thyroid nodule and reliable monitoring of nodule progression. In SCC without suspicious nodule(s), it may be reasonable to perform screening ultrasounds less frequently due to the slow growth rate of thyroid nodules. However, in those with suspicious features, surgical work-up resulted in the removal of a high number of malignancies, with few unnecessary surgeries and complications.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".