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Record W4322719691 · doi:10.1089/thy.2022.0672

Malignancy Risk of Thyroid Nodules That Are Not Classifiable by the American Thyroid Association Ultrasound Risk Stratification System: A Systematic Review and Meta-Analysis

2023· review· en· W4322719691 on OpenAlexaff
Daniel Kwon, Marta Kulich, Wendy J. Mack, Rodrigo Martinez Monedero, Eri Joyo, Trevor E. Angell

Bibliographic record

VenueThyroid · 2023
Typereview
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsInstitute of Population and Public Health
FundersNational Center for Advancing Translational SciencesNational Institutes of Health
KeywordsRisk stratificationMedicineThyroid nodulesMeta-analysisThyroidMalignancyUltrasoundOncologyInternal medicineRadiology

Abstract

fetched live from OpenAlex

Background: Sonographic evaluation is fundamental to thyroid nodule assessment. The American Thyroid Association (ATA) ultrasound risk stratification system (USRSS) is widely used, but the appearance of some nodules has been considered nonclassifiable (NC-ATA). The risk of malignancy (RoM) of NC-ATA nodules varies widely between studies, leading to uncertainty in clinical management. The aim of this study was to comprehensively evaluate the prevalence and malignancy risk of NC-ATA nodules. Methods: A systematic review was performed searching PubMed/MEDLINE and EMBASE to identify original studies of thyroid nodules classified using the ATA USRSS from 2016 to 2022 and reporting the outcome of NC-ATA nodules. Meta-analysis was conducted to obtain pooled RoM estimates and meta-regression sensitivity analyses were used to explore sources of between-study heterogeneity. Results: Of 6377 screened studies, 135 underwent full-text review, and 16 studies reporting 21,271 nodules were included. Within these, the pooled prevalence of NC-ATA nodules was 7.8% (1872 nodules; [confidence interval; CI 5.1–11.1]). The pooled RoM estimate for NC-ATA nodules was 20.3% [CI 13.0–28.7] and there was significant heterogeneity between studies ( I 2 = 92.8%, p < 0.001). NC-ATA nodule RoM estimates were significantly different by study type: single-center versus multicenter studies (24.8% vs. 12.3%, respectively, p = 0.031) and study design: retrospective versus prospective studies (25.1% vs. 8.5%, respectively, p = 0.003). No significant difference was observed in RoM based on inclusion of <1 cm nodules or geographic region. Meta-regression analysis showed study design and use of surgical histology for diagnostic criteria contributed significantly to differences in the reported RoM estimates. Conclusion: In this first meta-analysis comprehensively assessing the RoM of NC-ATA nodules, the malignancy risk was found to be comparable with the current ATA USRSS intermediate suspicion category. Significant heterogeneity was observed between studies and limits the interpretation of these results. In future iterations of the ATA USRSS that seek into incorporate categorization of NC-ATA nodules, these meta-analysis data may help to inform proper malignancy risk stratification. The study protocol was registered on PROSPERO, the international prospective register of systematic reviews (CRD42020182498), on July 14, 2020.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0170.041
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.068
GPT teacher head0.327
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations11
Published2023
Admission routes1
Has abstractyes

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