Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer
Yongfeng Ding1,2, Zhuochao Mao1, Jiaying Ruan1
1Cancer Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Background And Objectives:
The clinicopathological risk factors to predict recurrence of papillary thyroid cancer (PTC) patients remain controversial.
Methods:
PTC patients treated with thyroidectomy between January 1997 and December 2011 at the First Affiliated Hospital of Zhejiang University (Zhejiang cohort) were included. Multivariate Cox regression analysis was conducted to identify independent recurrence predictors. Then, the nomogram model for predicting probability of recurrence was built.
Results:
According to Zhejiang cohort (N = 1,697), we found that the 10-year event-free survival (EFS) rates of PTC patients with early-stage (TNM stages I, II, and III) were not well discriminated (91.6%, 89.0%, and 90.7%; P=0.768). The multivariate Cox model identified age, bilaterality, tumor size, and nodal status as independent risk factors for tumor recurrence in PTC patients with TNM stages I-III. We then developed a nomogram with the C-index 0.70 (95% CI, 0.64 to 0.76), which was significantly higher (P < 0.0001) than the AJCC staging system (0.52). In the validation group, the C-index remained at a similar level.
Conclusions:
In this study, we build up a new recurrence predicting system and establish a nomogram for early-stage PTC patients. This prognostic model may better predict individualized outcomes and conduct personalized treatments.
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