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A nomogram for predicting adverse pathologic features in low-risk papillary thyroid microcarcinoma.

BMC cancer 2024 Vol.24(1) p. 244

Gong L, Li P, Liu J, Liu Y, Guo X, Liang W, Lv B, Su P, Liang K

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[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 t

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  • p-value p < 0.05
  • 95% CI 0.580-0.702

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BibTeX ↓ RIS ↓
APA Gong L, Li P, et al. (2024). A nomogram for predicting adverse pathologic features in low-risk papillary thyroid microcarcinoma.. BMC cancer, 24(1), 244. https://doi.org/10.1186/s12885-024-12012-3
MLA Gong L, et al.. "A nomogram for predicting adverse pathologic features in low-risk papillary thyroid microcarcinoma.." BMC cancer, vol. 24, no. 1, 2024, pp. 244.
PMID 38389061

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 BRAF 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 BRAF 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.

MeSH Terms

Humans; Nomograms; Proto-Oncogene Proteins B-raf; Retrospective Studies; Thyroid Neoplasms; Risk Factors; Thyroiditis, Autoimmune; Carcinoma, Papillary

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