An evidence‐based review of poorly differentiated thyroid cancer
Bibliographic record
Abstract
BACKGROUND: Poorly differentiated thyroid cancer (PDTC) presents the endocrinologist and surgeon with challenges of recognition and treatment given the lack of consensus on histopathologic definition and limited literature on surgical and nonsurgical treatment. METHODS: We offer an operational pathologic definition for PDTC, which should help guide future work in this area. Poorly differentiated thyroid cancer should include insular and trabecular variants but should not include solid type lesions (included by other workers) or more differentiated tumors that may have poor prognosis such as tall cell, columnar, diffuse sclerosing, and oncocytic lesions. Systematic evidence-based literature reviews focusing on two questions were carried out: (1) is PDTC associated with an intermediate prognosis relative to anaplastic and WDTC? and (2) What are the postoperative treatment options for poorly differentiated thyroid cancer? CONCLUSIONS: We have found level IV evidence that PDTC is intermediate between WDTC and anaplastic cancers in terms of prognosis. It represents a disease where appropriate administration of aggressive treatment not typically necessary for routine WDTC and not effective for anaplastic disease may uniquely result in substantial benefit. Limited level IV data show conflicting results regarding 131I treatment benefit. Given lack of morbidity and potential for benefit, we recommend that 131I therapy be considered in all patients postoperatively. Recommendation regarding external beam radiotherapy (XRT) is based primarily on extrapolation from studies in forms of poor-prognosis WDTC where substantial data exist regarding treatment benefit. We recommend that external beam treatment be considered in all patients with PDTC with T3 tumors without distant metastasis, all patients with T4 tumors, and all patients with regional lymph node involvement.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".