ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2025
[A multi-molecular predictive model for lymph node metastasis in papillary thyroid carcinoma based on machine learning algorithms].
Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2025. 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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Abstract
objectivesAccurate preoperative evaluation of lymph node metastasis (LNM) status in patients with papillary thyroid carcinoma (PTC) is essential for the development of individualized diagnosis and treatment strategies; however, the predictive performance of current clinical approaches remains limited. This study aims to identify key molecular biomarkers associated with LNM in PTC, construct LNM-risk prediction models using machine learning (ML) algorithms, and assess their potential value in supporting clinical decision-making.
methodsTranscriptomic data from 507 PTC patients were obtained from The Cancer Genome Atlas (TCGA). After rigorous quality control, 50 patients with unknown lymph node status (N-stage) were excluded, leaving 457 eligible patients [229 with no LNM (N0) and 228 with LNM (N1)]. Patients were randomly stratified into a training set (
resultsEdgeR combined with LASSO regression identified 11 signature genes associated with LNM in PTC:
conclusionsThe optimized multi-molecular logistic regression model (Model 2) built on 11 signature genes can effectively predict lymph node metastasis risk in PTC patients, demonstrating robust cross-sex stability, strong compatibility across multiple ML algorithms, and potential clinical utility as a preoperative decision-support tool for lymph node status assessment and personalized treatment planning.
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