Oncocytic Papillary Thyroid Carcinoma and Oncocytic Poorly Differentiated Thyroid Carcinoma: Clinical Features, Uptake, and Response to Radioactive Iodine Therapy, and Outcome
Bibliographic record
Abstract
Objective: The main objective of this study was to review the clinicopathologic characteristics and outcome of patients with oncocytic papillary thyroid carcinoma (PTC) and oncocytic poorly differentiated thyroid carcinoma (PDTC). The secondary objective was to evaluate the prevalence and outcomes of RAI use in this population. Methods: Patients with oncocytic PTC and PDTC who were treated at a quaternary cancer centre between 2002 and 2017 were retrospectively identified from an institutional database. All patients had an expert pathology review to ensure consistent reporting and definition. The cumulative incidence function was used to analyse locoregional failure (LRF) and distant metastasis (DM) rates. Univariable analysis (UVA) was used to assess clinical predictors of outcome. Results: In total, 263 patients were included (PTC [n=218], PDTC [n=45]) with a median follow up of 4.4 years (range: 0 = 26.7 years). Patients with oncocytic PTC had a 5/10-year incidence of LRF and DM, respectively, of 2.7%/5.6% and 3.4%/4.5%. On UVA, there was an increased risk of DM in PTC tumors with widely invasive growth (HR 17.1; p<0.001), extra-thyroidal extension (HR 24.95; p<0.001), angioinvasion (HR 32.58; p=0.002), focal dedifferentiation (HR 19.57, p<0.001), and focal hobnail cell change (HR 8.67, p=0.042). There was additionally an increased risk of DM seen in male PTC patients (HR 5.5, p=0.03).The use of RAI was more common in patients with larger tumors, angioinvasion, and widely invasive disease. RAI was also used in the management of DM and 43% of patients with oncocytic PTC had RAI-avid metastatic disease. Patients with oncocytic PDTC had a higher rate of 5/10-year incidence of LRF and DM (21.4%/45.4%; 11.4%/40.4%, respectively). Patients with extra-thyroidal extension had an increased risk of DM (HR 5.52, p=0.023) as did those with angioinvasion. Of the patients with oncocytic PDTC who received RAI for the treatment of DM, 40% had RAI-avid disease. Conclusion: We present a large homogenous cohort of patients with oncocytic PTC and PDTC, with consistent pathologic reporting and definition. Patients with oncocytic PTC have excellent clinical outcomes and similar risk factors for recurrence as their non-oncocytic counterparts (angioinvasion, large tumor size, extra-thyroidal extension, and focal dedifferentiation). Compared with oncocytic PTCs, the adverse biology of oncocytic PDTCs is supported with increased frequency of DM and lower uptake of RAI.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".