Secondary malignancy following radiotherapy for thyroid eye disease
Bibliographic record
Abstract
AIM: To describe the first case of a secondary meningioma in a patient after radiation treatment for thyroid eye disease (TED). Secondarily to identify any additional cases of secondary malignancy resulting from radiotherapy for thyroid eye disease from our institutional experience. BACKGROUND: Thyroid eye disease (TED) is a self-limiting auto-immune disorder causing expansion of orbital soft tissue from deposition of glycosaminoglycans and collagen, leading to significant cosmetic and functional morbidity. Established management options for TED include: glucocorticosteroids, orbital radiotherapy, and surgical orbital decompression. Two large series on radiotherapy for TED have been reported without any cases of secondary malignancy. MATERIALS AND METHODS: The case of a patient with visual failure, found to have a sphenoid wing meningioma after previous TED radiotherapy is described. We then reviewed 575 patients with at least 3-year follow-up receiving radiotherapy for TED at British Columbia Cancer Agency to identify other possible secondary malignancies. RESULTS: The patient had postoperative improvement in her vision without any identified complications. Three additional cases of hematologic malignancy were identified. The calculated risk in our population of developing a radiation-induced meningioma after TED with at least 3 years of follow-up of is 0.17% (1/575); with hematopoetic malignancies the risk for secondary malignancy is 0.7% (4/575). CONCLUSIONS: Our calculated risk for secondary malignancy (0.17%, 0.7%) is similar to the reported theoretical risk published in the literature (0.3-1.2%). There is real risk for the development of a secondary malignancy after radiotherapy treatment of TED and treatment options should include consideration for this potential.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".