Risk factors and predictive model for recurrence in papillary thyroid carcinoma: a single-center retrospective cohort study based on 955 cases - Li, Yin; Tian, Jiahe; Jiang, Ke; Wang, Zhongyu; Gao, Songbo; Wei, Keyang; Yang, Ankui; Li, Qiuli (Frontiers in Endocrinology, 2023)
The 2015 American Thyroid Association (ATA) guidelines proposed the recurrence risk stratification of differentiated thyroid carcinoma (DTC) including papillary thyroid carcinoma (PTC), but this stratification excluded the non–initial treatment patients with worse outcomes. This study aimed to explore potential risk factors for recurrence in PTC and develop a predictive model of recurrence for both in initial treatment and non–initial treatment patients with PTC.Methods: A total of 955 patients were included in this study. The differences between recurrence (−) and recurrence (+) were compared. The All 955 cases were randomized into two groups: the training group (671 cases) and the validation group (284 cases). All variables were selected by through This is a provisional file, not the final typeset article LASSO regression analysis. A nomogram was developed based on the results of univariate and multivariate logistic regression analysisanalyses. The performance of the nomogram was evaluated by discrimination and calibration.Results: Patient Age age ≥55 years, extraonodal extension (ENE), metastatic LN ratio (LNR) ＞0.5, and non–initial treatment were identified as potential recurrence risk factors for recurrence through LASSO regression analysis and univariate and multivariate analyses. The receiver operating characteristic curve (ROC curve) showed high efficiency, with an area under the ROC curve (AUC) of 0.819 (95% confidence interval [CI], 0.729-0.909) and 0.818 (95% CI, 0.670-0.909) in the training and validation groups, respectively. The calibration curve indicated that the nomogram had good consistency.In PTC patients with PTC, age ≥55 years, ENE, LNR ＞0.5, and non-initial treatment were potential associated withrisk factors for recurrence. The predictive model of recurrence was confirmed to be a practical and convenient tool for clinicians to accurately predict the recurrence of PTC.