Evidence map›Paper›PMID 42015141›Full record

ArticleBMC endocrine disorders2026

Ultrasound-based nomogram for predicting central lymph node metastasis in papillary thyroid microcarcinoma.

Hong Huang, Lina Hu, Xuan Chen, Hui Luo

Abstract read
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Article in BMC endocrine disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Hong HuangShantou University Medical College, Shantou, Guangdong, 515041, China.
Lina HuDepartment of Hematology, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University:The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518020, China.
Xuan ChenDepartment of Endocrinology, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University: The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518020, China.
Hui LuoDepartment of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University: The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518020, China. 18126299810@163.com.

Funding

Heyuan Science Planning Projects 241106151472860
6 · The paper itself

Abstract

backgroundThis study aimed to develop a nomogram based on Ultrasound features for predicting the probability of central lymph node metastases (CLNM) in patients diagnosed with papillary thyroid microcarcinoma (PTMC).

methodsA total of 670 patients with histologically confirmed PTMC between 2021 and 2024 were included in this retrospective study and divided into the training (n = 469) and validation (n = 201) cohorts. Through least absolute shrinkage and selection operator (LASSO) regression analysis on the training cohort, we identified the most effective predictors. These predictors were then used to construct a nomogram. We evaluated the nomogram’s discrimination, calibration, and clinical usefulness in the validation cohort using receiver operating characteristic (ROC) analysis, calibration plots, and decision curve analysis.

resultsAfter applying LASSO and logistic regression screening with criteria for retaining non-zero coefficients, several factors were found to be independently linked to CLNM in PTMC patients. A nomogram model was subsequently developed to predict the risk of CLNM in PTMC patients based on the predictors. The AUC (C-statistic) of the nomogram was 0.73 (95% CI: 0.68–0.77) for the training cohort and 0.77 (95% CI: 0.70–0.83) for the validation cohort. Decision curve analysis (DCA) demonstrated that the model achieved a higher net benefit than the baseline strategy within the threshold probability ranges of 17%–88% in the training cohort and 10%–76% in the validation cohort.

conclusionsThis ultrasound-based nomogram, incorporating relevant clinical characteristics, holds promise as a valuable clinical instrument capable of furnishing essential information to guide treatment decisions.

trial registrationNot applicable.

Indexed as

Carcinoma, PapillaryLymphatic MetastasisNomogramsThyroid NeoplasmsAdultFemaleFollow-Up StudiesHumansMaleMiddle AgedPrognosisRetrospective StudiesUltrasonographyCentral lymph node metastases (CLNM)NomogramPapillary thyroid microcarcinoma (PTMC)Ultrasound-based

Identifiers

PMID42015141
PMCPMC13235074

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.