Author:
Wang Wenlong,Bai Ning,Li Xinying
Abstract
BackgroundThe current TNM classification that simply classifies differentiated thyroid carcinoma (DTC) patients younger than 55 years into stage I and stage II based on the presence or absence of distant metastases has been questioned. In this study, we reexamined the impact of T status and N status on prognosis and then developed a new prediction model to improve the predictability of cancer-specific survival (CSS) in young patients.Materials and methodsKaplan–Meier method was applied to calculate the CSS. Multivariable Cox proportional hazards models were used to assess the impact of T status and N status on CSS after adjustment for known covariates. The area under the receiver operating characteristic curve (AUC), C-index, Bayesian information criterion (BIC), and Akaike information criterion (AIC) were calculated to compare model performance.ResultsA total of 9,242 DTC patients younger than 55 years were enrolled in the study. After adjusting for gender, age at diagnosis, race, pathology subtype, N stage, and M stage, T3 disease [hazard ratio (HR): 3.78, P = 0.006] and T4 disease (HR: 7.96, P < 0.001) remain independent predictors of CSS. Similarly, the 10-year CSS rate of N1b disease (HR: 3.78, P < 0.001) was significantly higher than that of N0 disease after adjustment. Moreover, Kaplan–Meier survival analysis showed that the 10-year CSS of stage II disease in younger patients with DTC showed a sharp decrease compared with that in older patients with DTC (74.47% vs. 98.43%, P < 0.001). Furthermore, a modified TNM staging system based on significantly prognostic T stage and N stage was established, which showed better performance than the current TNM staging system (P < 0.05). The new prediction model is also applicable to papillary thyroid carcinoma patients and follicular thyroid carcinoma patients.ConclusionsThis is the first study to question the rationality of the current TNM staging system for patients younger than 55 years and successfully develop a new prognostic model, which improves prognostic stratification and guides individualized management.
Subject
Endocrinology, Diabetes and Metabolism
Cited by
2 articles.
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