Published in:
Open Access
01-12-2024 | Thyroid Cancer | Research
A nomogram for predicting adverse pathologic features in low-risk papillary thyroid microcarcinoma
Authors:
Lei Gong, Ping Li, Jingjing Liu, Yan Liu, Xinghong Guo, Weili Liang, Bin Lv, Peng Su, Kai Liang
Published in:
BMC Cancer
|
Issue 1/2024
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Abstract
Background
Identifying risk factors for adverse pathologic features in low-risk papillary thyroid microcarcinoma (PTMC) can provide valuable insights into the necessity of surgical or non-surgical treatment. This study aims to develop a nomogram for predicting the probability of adverse pathologic features in low-risk PTMC patients.
Methods
A total of 662 patients with low-risk PTMC who underwent thyroid surgery were retrospectively analyzed in Qilu Hospital of Shandong University from May 2019 to December 2021. Logistic regression analysis was used to determine the risk factors for adverse pathologic features, and a nomogram was constructed based on these factors.
Results
Most PTMC patients with these adverse pathologic features had tumor diameters greater than 0.6 cm (p < 0.05). Other factors (age, gender, family history of thyroid cancer, history of autoimmune thyroiditis, and BRAFV600E mutation) had no significant correlation with adverse pathologic features (p > 0.05 each). The nomogram was drawn to provide a quantitative and convenient tool for predicting the risk of adverse pathologic features based on age, gender, family history of thyroid cancer, autoimmune thyroiditis, tumor size, and BRAFV600E mutation in low-risk PTMC patients. The areas under curves (AUC) were 0.645 (95% CI 0.580–0.702). Additionally, decision curve analysis (DCA) and calibration curves were used to evaluate the clinical benefits of this nomogram, presenting a high net benefit.
Conclusion
Tumor size > 0.60 cm was identified as an independent risk factor for adverse pathologic features in low-risk PTMC patients. The nomogram had a high predictive value and consistency based on these factors.