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Record W3013122178 · doi:10.1186/s40463-019-0397-9

Preoperative prediction of non-invasive follicular thyroid neoplasm with papillary-like nuclear features: A Canadian single-Centre experience

2020· article· en· W3013122178 on OpenAlexaffabout
Vincent Larouche, Marc Pusztaszeri, Sabin Filimon, Richard J. Payne, Michael P. Hier, Michael Tamilia

Bibliographic record

VenueJournal of Otolaryngology - Head and Neck Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineThyroid neoplasmThyroid carcinomaInternal medicineThyroid

Abstract

fetched live from OpenAlex

BACKGROUND: An international group of experts recommended reclassifying non-invasive follicular variant of papillary thyroid cancers (FVPTC) as 'non-invasive follicular thyroid neoplasm with papillary-like nuclear features' (NIFTP) in April 2016. The purpose of this study was to establish preoperative clinical, laboratory, ultrasonographic, and cytological variables, which can differentiate NIFTP from FVPTC. METHODS: We conducted a retrospective chart review of consecutive patients from a single institution evaluated between January 2012 and December 2017. 203 adult patients underwent lobectomy or total thyroidectomy for a FVPTC during that period. Each patient's medical chart was reviewed and information on pre-operative variables was recorded. An expert pathologist reviewed all surgical specimens and reclassified a subset of FVPTC as NIFTP according to the specific criteria. RESULTS: Overall, 44 patients were included in the NIFTP group and 159 in the non-NIFTP group. Mean age was 50.1 years in the NIFTP group and 50.7 in the non-NIFTP group. Most patients were female (86.4% (38/44) in the NIFTP group vs 79.8% (127/159) in the non-NIFTP group). More patients underwent lobectomy in the NIFTP group (50% (22/44) vs 16.4% (26/159) in the non-NIFTP group, p = < 0.0001). Less patients received radioactive iodine in the NIFTP group (31.8% (14/44) vs 52.2% (83/159) in the non-NIFTP group, p = 0.0177). Preoperative thyroglobulin levels were lower in NIFTP patients (Median 25.55 mcg/L +/- 67.8 vs 76.06 mcg/L +/- 119.8 in Non-NIFTP, p = 0.0104). NIFTP nodules were smaller (Mean size 22.97 mm +/- 12.3 vs 25.88 mm +/- 11.2 for non-NIFTP, p = 0.0448) and more often solid than non-NIFTP (93.2% (41/44) vs 74.8% (119/159) for non-NIFTP, p = 0.0067). 2017 ACR TIRADS nodule category of 1-4 on ultrasound had a negative predictive value and a sensitivity of 100% for NIFTP. ROC Curve Analysis demonstrated that a preoperative thyroglobulin level of 31.3 mcg/L had a sensitivity of 75% and a specificity of 62.5% to differentiate NIFTP from non-NIFTP cancers. CONCLUSION: Lower preoperative thyroglobulin levels, smaller nodule size, solid texture and 2017 ACR TIRADS Category of 1-4 are more strongly associated with NIFTP than FVPTC and can favour less invasive surgical options such as lobectomy.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.932

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.227
Teacher spread0.211 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations20
Published2020
Admission routes2
Has abstractyes

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