Construction and validation of a diagnostic model for high-risk papillary thyroid microcarcinoma based on the SEER database

Abstract:

Objective To investigate the risk predictors of high-risk papillary thyroid microcarcinoma（PTMC） and to construct and validate a reliable diagnostic nomogram model.Methods A retrospective analysis was performed on the clinicopathologic and ultrasound imaging data of patients with PTMC from the SEER database who underwent surgical treatment from 2004 to 2015（training set） and patients with thyroid micronodules treated in the Thyroid Treatment Center of Sichuan Provincial People’s Hospital from 2020 to 2022（external validation set）. In the validation set，the risk predictors of high-risk PTMC were analyzed using logistic regression； a diagnostic nomogram model was constructed，and an internal validation set and an external validation set were used for internal and external validation，respectively. An indirect assessment was performed according to the preoperative ultrasound imaging characteristics to examine the feasibility and reliability of preoperative ultrasound imaging characteristics in predicting high-risk PTMC.Results The training set included 1552 patients，and the external validation set included 516 patients. The independent risk factors for high-risk PTMC were sex（male），age（no more than 55），number of nodules（multikitchen），capsular invasion，and abnormal cervical lymph nodes（P<0.05）. The C-index of the constructed nomogram was 0.946. In the training set and the external validation set，the prediction results of the nomogram model were in good agreement with the actual results. The area under the ROC curve for diagnosing high-risk PTMC based on the ultrasound imaging characteristics was 0.931（95%CI=0.910-0.953），which had a high consistency with the diagnosis based on pathological characteristics（κ=0.611，P<0.05）.Conclusions The diagnostic model of high-risk PTMC constructed in this study has good predictive validity. The prediction of high-risk PTMC based on preoperative ultrasound imaging characteristics is clinically feasible and holds promise for clinical application.