Rare distant metastases to pancreas, liver, and lung as initial presentation of mixed tall cell and columnar cell variants of papillary thyroid cancer
Bibliographic record
Abstract
Summary: The most common sites of distant metastases of papillary thyroid carcinoma (PTC) are lung and bone. Widespread distant metastases of PTC are rare and associated with poor overall prognosis. Metastases to sites such as liver and pancreas are extremely rare, and literature is sparse on overall survival. In this report, we present a 57-year-old man whose initial presentation of PTC was with pancreatic, liver, and lung metastases, and subsequently developed metastases to bone and brain. He underwent a total thyroidectomy, neck dissection, and tracheal resection. Pathology revealed a predominant columnar cell variant PTC with focal areas of tall cell variant, and genomic sequencing showed both PIK3CA and BRAF gene mutations. Radioactive iodine ablation with I-131 did not show any uptake in metastatic sites and he had progression of the metastases within 6 months. Therefore, therapy with lenvatinib was initiated for radioactive iodine refractory disease. Our patient has tolerated the lenvatinib well, and all his sites of metastases decreased in size. His liver and pancreatic lesions took longer to respond but showed response 6 months after initiation of lenvatinib, and he remains on full dose lenvatinib 18 months into treatment. Learning points: Papillary thyroid carcinoma (PTC) usually metastasizes to lung and bone but can rarely occur in many other sites. Patients with distant metastases have significantly worse long-term prognosis. Lenvatinib can be an effective treatment of radioactive iodine refractory PTC with rare sites of distant metastases. Lenvatinib can be an effective treatment of PTC with BRAF V600E and PIK3CA mutation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".