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Record W1602610616 · doi:10.1089/thy.2013.0191

Serum Thyroglobulin Improves the Sensitivity of the McGill Thyroid Nodule Score for Well-Differentiated Thyroid Cancer

2013· article· en· W1602610616 on OpenAlex
Patrick Scheffler, V. I. Forest, Rébecca Leboeuf, Anca Florea, Michael Tamilia, Noah Sands, Michael P. Hier, Alexander Mlynarek, Richard J. Payne

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThyroid · 2013
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsUniversité de MontréalHôpital Notre-DameMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineThyroglobulinThyroid cancerMalignancyThyroidNodule (geology)CancerThyroidectomyBiopsyInternal medicineGastroenterology

Abstract

fetched live from OpenAlex

BACKGROUND: The McGill Thyroid Nodule Score (MTNS) is a scoring system devised to help physicians to assess the preoperative risk that a thyroid nodule is malignant. It uses 22 different known risk factors for thyroid cancer (radiation exposure, microcalcifications on ultrasound, positive HBME-1 stain on biopsy, etc.) and attributes a percentage risk that the nodule is malignant. Recently, preoperative thyroglobulin (Tg) levels have been shown to correlate with the risk of malignancy. The aim of this study was to incorporate Tg levels into the already established MTNS. METHODS: This is a retrospective analysis of 184 thyroidectomy patients at the McGill University Thyroid Cancer Center. Patients with preoperative Tg levels were included in the study, and patients with incidental papillary microcarcinoma without extrathyroidal extent on final pathology were excluded. MTNS scores were calculated for all patients. Preoperative Tg levels of 75 ng/mL added one point to the MTNS, and levels of 187.5 ng/mL added two points. The new system is named MTNS+. RESULTS: Malignancy rates were calculated for each MTNS+ score. Patients with a score of 0-1 were <5% at risk of malignancy. The malignancy rate for scores of 2-3 was 14.29%, followed by 28.95% for scores of 4-6, 32.65% for scores of 7-8, 64.86% for scores of 9-11, 71.43% for scores of 12-14, 78.57% for scores of 15-18, and 92.31% for scores of 19-22. All patients (five of five) with an MTNS+ score of 23 or more had a malignant final pathology result. Patients with scores greater than eight had a relative risk of 2.5 [CI 1.79-3.49] of malignancy compared to patients with lower scores. MTNS+ showed good specificity at higher scores, with 89%, 96%, and 100% at scores above 11, 14, and 20 respectively. Compared to MTNS, adding Tg levels did not improve positive predictive values (PPV) or specificity, but improved sensitivity by 7.89% for scores greater than eight, and by up to 10.48% for scores greater than seven. CONCLUSION: This study shows that adding Tg to the MTNS increases the sensitivity of this scoring system. Moreover, it suggests that a combined scoring system such as the MTNS+ can accurately stratify the risk of well-differentiated malignancy in patients with thyroid nodules.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.255
Teacher spread0.239 · 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