Diffuse sclerosing variant papillary thyroid carcinoma has worse survival than classic papillary thyroid carcinoma: a meta-analysis
Bibliographic record
Abstract
Diffuse sclerosing variant (DSV) of papillary thyroid carcinomais a rare form of thyroid cancer that demonstrates more aggressive histopathology than classical papillary thyroid carcinoma (c-PTC); however, if this leads to worse survival is debated. Many DSVs are driven by fusion events which are of recent clinical importance due to the advent of targeted RET inhibitors. A systematic search and meta-analysis of the literature was performed to compare outcomes of disease-specific mortality (DSM), metastatic and recurrent disease and the incidence of fusion events between DSV and c-PTC to July 2022. The Newcastle-Ottawa Quality Assessment studies was used to assess quality. An odds ratio (OR) was utilised to measure outcomes with 95% CIs. The Preferred Reporting Items for Systematic Reviews and Meta-analysis guideline was followed. Seventeen studies were included with 874 DSV patients compared to 76,013 c-PTC patients. DSV patients had worse DSM (OR=2.50, 95% CI 1.39-4.51) and presented with a higher rate of metastatic lymph nodes (OR = 5.85, 95% CI 2.73-12.53) and more distant metastases (OR = 3.83, 95% CI 2.17-6.77). DSV patients had higher odds of recurrent disease (OR = 3.23, 95% CI 2.00-5.23) and overall distant metastasis (OR = 2.70, 95% CI 1.74-4.17). Rates of RET fusion alterations for DSV ranged from 25 to 83%. DSV has a worse prognosis than c-PTC with higher rates of recurrent disease and distant metastasis. The high prevalence of RET fusions offers the potential to improve outcomes for patients with DSV.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.045 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".