Factors favouring early nodal recurrence in papillary thyroid carcinoma (PTC)
Bibliographic record
Abstract
2110 Objectives Following surgical treatment of PTC, the use of adjuvant therapy with radioiodine ablation, and degree of TSH suppression, will depend on the patient9s risk of recurrent disease. The demographic and histologic features associated with early recurrence in PTC are not well understood. We have attempted to determine the factors associated with recurrence within five years of initial diagnosis. Methods A retrospective cohort study of PTC patients treated and followed at a single tertiary centre. 263 patients with PTC were examined using a fixed time window restriction protocol to identify 81 recurrent and 182 non-recurrent patients. All were treated and followed at a single center for the duration of the study.Demographic, histologic, surgical and adjuvant treatment data were collected on all patients and examined for univariate and multivariate correlations with recurrent PTC. Risk factors for recurrent PTC are defined by patient age, sex and tumour histologic characteristics. Results In the patient cohorts defined by tumours of similar size and with similar treatment regimes, it was clear that recurrent disease was favoured in younger patients ( Conclusions Patients at risk of early recurrence of PTC may be identified by young age, lymph node metastases and extra-thyroidal extension
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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 | 0.000 |
| 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 | 0.000 |
| 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".