Prognostic value of 18F-fluorodeoxyglucose-positron emission tomography in patients with differentiated thyroid carcinoma and circulating antithyroglobulin autoantibodies
Bibliographic record
Abstract
OBJECTIVE: To explore the prognostic value of F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) in radioiodine-negative patients with differentiated follicular cell-derived thyroid carcinoma with circulating antithyroglobulin autoantibodies (TgAb). METHODS: We retrospectively reviewed cases of all patients with differentiated thyroid cancer and increased TgAb referred for FDG-PET at Mayo Clinic, Rochester, Minnesota, from August 2001 to December 2004. PET findings were compared with results of other imaging and laboratory studies. Follow-up information was recorded until 19 December 2009. RESULTS: Of the 17 patients identified, PET results were true positive in 10 and false negative in two. In eight of these 12 patients with confirmed residual or recurrent disease, the increased TgAb level persisted and the disease progressed. In four of the 12 patients, TgAb decreased or disappeared after further treatment. In five patients, no residual or recurrent disease was found during follow-up. PET results were true negative in these five patients; TgAb disappeared spontaneously in four of these patients. CONCLUSIONS: Negative PET results were associated with the absence of active disease and disappearing TgAb over time. FDG-avid residual lesions were associated with more aggressive disease and persistently increased TgAb.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".