Adjuvant Radioactive Iodine Ablation in Tall Cell Subtype Papillary Thyroid Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction Tall cell subtype papillary thyroid cancer (TCS-PTC) is associated with aggressive disease features and worse patient outcomes. It remains unclear whether adjuvant radioactive iodine (RAI) ablation following thyroidectomy is associated with improved survival in TCS-PTC. The purpose of this review and meta-analysis was to determine whether adjuvant RAI was associated with improved survival in patients with TCS-PTC. Methods We included any study design that investigated survival outcomes in adult patients diagnosed with TCS-PTC who underwent either thyroidectomy following by adjuvant RAI or thyroidectomy alone. We searched MEDLINE, EMBASE, Scopus, and CENTRAL databases from inception with no restrictions. All screening and review stages were performed in duplicate. Risk of bias was evaluated using ROBINS-I and certainty of evidence were evaluated using GRADE. Meta-analysis was performed using a random effects model and we calculated pooled hazard ratios (HRs), where applicable. All analyses were performed in RevMan 5.3 (Cochrane, UK). Results Seven nonrandomized studies were included with 9611 TCS-PTC patients, of which 6296 (65.5%) underwent adjuvant RAI. All studies were at high risk of bias. Based on low certainty evidence, we found that adjuvant RAI was possibly associated with improved overall survival in TCS-PTC (HR = 0.60, 95% confidence interval: 0.42-0.85). This benefit was maintained in studies that performed propensity score matching, but we did not find a significant association with tumor size. Sensitivity analysis to remove studies with potentially overlapping data changed the HR to 0.74 (95% CI: 0.46-1.19) with considerable heterogeneity (I 2 = 70%). Based on very low certainty evidence, we were uncertain where adjuvant RAI was associated with cancer-specific or recurrence-free survival. Conclusions Adjuvant RAI may be associated with improved overall survival in TCS-PTC, but future high-quality randomized studies with risk stratification are needed.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.027 |
| Bibliometrics | 0.004 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".