Development and validation of a competitive risk model for the progression of papillary microcarcinoma of the thyroid—based on the Surveillance, Epidemiology, and End Results database and real-world study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: The overall clinical treatment outcomes and prognosis for papillary thyroid microcarcinoma (PTMC) are generally favorable; however, some patients develop occult metastases in the central lymph nodes, which are often closely associated with distant metastases, disease recurrence, and poor prognosis. This study aimed to construct a competitive risk model for the progression of PTMC based on the Surveillance, Epidemiology, and End Results (SEER) database and to clinically validate it. Methods: We conducted a retrospective search of the SEER database for medical records of patients diagnosed with PTMC between 2016 and 2022. Patients were divided into progression (n=176) and non-progression groups (n=1,050) based on the presence or absence of metastasis. Using the progression of papillary microcarcinoma of the thyroid as the target event, we performed a multivariate analysis using the Fine-Gray competitive risk model. A nomogram model was constructed based on the identified independent risk factors, and the predictive performance of the nomogram model was evaluated using the C-index, receiver operating characteristic (ROC) curve, and calibration curve. Results: Multivariate analysis indicated that age, gender, tumor size, and tumor focality were independent predictors of PTMC progression (P<0.05). Based on the above variables, the C-index values for the training and testing sets of the nomogram model were 0.615 and 0.604, respectively, and the area under the curve (AUC) values of the ROC curves were 0.704 and 0.697, respectively. This indicates that the nomogram model demonstrates good agreement between the predicted and actual probabilities and possesses a certain degree of discriminatory power. Conclusions: Advanced age, male gender, tumor size ≥5 mm, and multifocal tumors are risk factors for PTMC progression. The nomogram model constructed based on these factors demonstrated a certain degree of discriminatory ability; when applied clinically, it can provide valuable data for the early identification of high-risk patients likely to experience progression.
Source: Translational Cancer Research
Authors: Fang Xiong, Juan Liu, Ke Gong
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7224120635