A Nomogram for Predicting Lung Metastasis in Papillary Thyroid Cancer Patients Aged Less Than 55 Years

用于预测55岁以下乳头状甲状腺癌患者肺转移的列线图

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Abstract

HIGHLIGHTS: A nomogram predicting lung metastasis in patients with papillary thyroid cancer was developed and validated. Our study focused on patients under 55 years old, revealing the genetic factors linked to lung metastasis in this younger group. Young patients with the BRAF V600E mutation are less likely to develop lung metastasis. OBJECTIVE: To develop and validate a nomogram for predicting the risk of lung metastasis in patients under 55 years old with papillary thyroid cancer (PTC). METHODS: A total of 243 patients under 55 years old with PTC were retrospectively collected from January 2017 to June 2020 and randomly divided into a training group (n = 170) and a validation group (n = 73) in a 7:3 ratio. Genetic testing data and clinical information were compiled, and univariate and multivariate binary logistic regression analyses were performed. Based on the results, a nomogram predicting the risk of lung metastasis was constructed using the training cohort. The nomogram's performance was assessed using calibration curves, decision curve analysis (DCA), the concordance index (C-index), and the area under the receiver operating characteristic (ROC) curve (AUC) in both the training and validation groups. RESULTS: T stage, unilateral thyroid involvement, TERT mutation, and BRAF mutation were identified as independent prognostic factors and were used to construct the nomogram. The C-index of the model was 0.89 in the training group and 0.88 in the validation group. The AUC, DCA, and calibration curves demonstrated favorable predictive accuracy. Using a cut-off value of 0.229, the nomogram achieved a sensitivity of 0.829 and a specificity of 0.793. CONCLUSION: A nomogram with strong predictive performance has been successfully developed and validated, which may assist clinicians in estimating the risk of lung metastasis in young patients with PTC.

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