Risk factor analysis and prediction model for papillary thyroid carcinoma with lymph node metastasis

Area of Science:

• Oncology
• Radiology
• Medical Informatics

Background:

• Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer.
• Lymph node metastasis (LNM) is a critical prognostic factor in PTC.
• Accurate prediction of LNM is essential for effective treatment planning.

Purpose of the Study:

• To identify clinical and ultrasound factors associated with LNM in PTC.
• To develop and validate a nomogram for predicting LNM in PTC patients.
• To enhance personalized clinical decision-making for PTC management.

Main Methods:

• Retrospective analysis of 252 PTC patients.
• Univariate and multivariate logistic regression to identify risk factors.
• Development and validation of a predictive nomogram using ROC curves, calibration curves, DCA, and clinical impact curves.

Main Results:

• Significant differences in age, sex, tumor size, and ultrasound characteristics (hypoechoic halo, capsule invasion, lymph node microcalcification/hyperechoic area, contrast PI/AUC) were observed between LNM and non-LNM groups.
• Age, sex, thyroid capsule invasion, and lymph node microcalcification were identified as independent predictors of LNM.
• The developed nomogram demonstrated excellent predictive accuracy (ROC 0.800, accuracy 0.757, Kappa 0.508) with good calibration and clinical utility.

Conclusions:

• Age, sex, thyroid capsule invasion, and lymph node microcalcification are significant risk factors for LNM in PTC.
• The visualized nomogram provides a valuable tool for clinicians to predict LNM risk preoperatively.
• This nomogram can aid in personalized treatment strategies for PTC patients.