Comparison of diagnostic yield of core-needle and fine-needle aspiration biopsies of thyroid lesions: Systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Thyroid nodular disease is one of the most commonly observed medical conditions. Cytological evaluation of the specimens obtained with fine-needle aspiration biopsy (FNAB) is the most accurate tool for selecting nodules which should be further surgically removed. A major limitation of this method is the high occurrence of non-diagnostic results. This indicates the need for improvement of the thyroid biopsy technique. The aim of this meta-analysis was to compare the diagnostic value of thyroid core-needle biopsies (CNBs) and FNABs. MATERIALS AND METHODS: PubMed/MEDLINE, Cochrane Library, Scopus, Cinahl, Academic Search Complete, Web of Knowledge, PubMed Central, PubMed Central Canada and Clinical Key databases were searched. Risk ratios (RRs) of non-diagnostic results were meta-analysed using the random-effects model. RESULTS: Eleven studies were included in the quantitative analysis. CNB yielded significantly more diagnostic results - the pooled risk ratio (RR) of gaining a non-diagnostic result was 0.27 (p<0.0001). For lesions with one previous non-diagnostic FNAB, RR was 0.22 (p<0.0001). CONCLUSIONS: CNB seems to be a valuable diagnostic technique yielding a higher proportion of diagnostic results than conventional FNAB. It is also significantly more effective in case of nodules with a prior non-diagnostic result of FNAB results than repeated FNABs. KEY POINTS: • Core-needle biopsy yields a higher proportion of diagnostic results than fine-needle biopsy. • Core-needle biopsies may decrease the amount of unnecessary thyroidectomies. • Probability of gaining non-diagnostic result using core-needle biopsy is almost four times lower.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".