Prevalence of Differentiated High-Grade Thyroid Carcinoma Among Well-Differentiated Tumors: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The current edition of the World Health Organization (WHO) classification of endocrine tumors introduced grading for follicular cell-derived thyroid cancer. Tumors with necrosis and/or high mitotic count but not fulfilling the Turin criteria for poorly differentiated carcinoma will be reclassified as differentiated high-grade thyroid carcinoma (DHGTC). However, the impact of this reclassification has not been evaluated. In this study, we performed a systematic review and meta-analysis to estimate the prevalence of this new entry across thyroid tumor subtypes. Methods: In this systematic review and meta-analysis, studies reporting data on necrosis and/or mitoses in well-differentiated thyroid carcinoma (WDTC) were used to estimate the prevalence of DHGTC. Heterogeneity and potential publication bias were also evaluated. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed, and quality assessment was performed using a modification of the Newcastle–Ottawa scale. The study has been registered in the International Prospective Register of Systematic Reviews (PROSPERO, ID: CRD42022378716). Results: In clinically unselected patients, the prevalence of DHGTC in WDTC was 0.072 [95% confidence interval, CI, = 0.045–0.113]. The proportion of high-grade tumors greatly varied across growth patterns and subtypes. Overall, the prevalence of DHGTC was higher in follicular thyroid carcinoma (FTC; 0.146 [CI = 0.101–0.205]) than in papillary thyroid carcinoma (PTC; 0.059 [CI = 0.036–0.097]). Diffuse sclerosing, follicular, and classic subtype PTC had the lowest rates of high-grade features (i.e., 0.018 [CI = 0.004–0.084]; 0.036 [CI = 0.010–0.124]; and 0.042 [CI = 0.027–0.066], respectively), while a greater proportion of solid trabecular and histologically aggressive PTC could be reclassified as DHGTC (i.e., 0.154 [CI = 0.067–0.314] and 0.168 [CI = 0.108–0.252], respectively). Similar proportions were obtained for minimally and widely invasive FTC (i.e., 0.136 [CI = 0.058–0.287] and 0.152 [CI = 0.086–0.254], respectively). Finally, in a cohort of patients with poor prognosis (i.e., fatal cases, metastatic and radioiodine resistant tumors, cases with biochemical recurrence), the proportion of DHGTC was 0.287 [CI = 0.155–0.469]. Conclusions: Following the current WHO indications, some tumors will be reclassified as DHGTC. The proportion of tumors with high-grade features is relevant in FTC, solid trabecular, and histologically aggressive PTC subtypes. A remarkable enrichment in DHGTC among patients with poor prognosis confirms the negative impact of high-grade features on outcome.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.006 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".