A nomogram based on the characteristics of metastatic lymph nodes to predict papillary thyroid carcinoma recurrence.

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A nomogram based on the characteristics of metastatic lymph nodes to predict papillary thyroid carcinoma recurrence.

Thyroid. 2018 Feb 14;:

Authors: Lei J, Zhong J, Li Z, Wei T, Gong R, Zhu J

Abstract
BACKGROUND AND AIMS: The extent of metastatic LN invasion was not considered in the postoperative stratification of the recurrence risk of papillary thyroid carcinoma (PTC) in the 2015 American Thyroid Association (ATA) guidelines, and the recommended risk stratification cannot be applied to individuals. A nomogram based on these risk factors was developed based on the risk factors to predict individual recurrence risk.
PATIENTS AND METHODS: Data from 1788 PTC patients at the West China Hospital and 306 cases from the Shang Jin Nan Fu Hospital between August 2013 and July 2015 were included in our study. The 1788 cases were randomized into two groups: the training set (896 cases) and the testing set (896 cases), 306 cases were used as the external evaluation set.
RESULTS: Univariate and multivariate analyses identified the following independent prognostic factors associated with recurrence in the three independent sets and the combined set (all P values <0.01): lymph node invasion in the capsule or organ, >5 metastatic LNs, and a largest metastatic LN diameter >3 cm. Importantly, PTC patients showed significantly different recurrence rates depending on the extent of LN invasion in the three sets and in the combined set (all P values <0.001). The nomogram was developed based on the risk factors in the training set and was validated in the independent testing and validation sets.
CONCLUSION: The largest LN metastasis diameter, number of metastatic LNs, and the extent of extranodal invasion had significant prognostic value for predicting the risk of recurrence. Our nomogram based on the characteristics of the thyroidal PTC lesion and metastatic LNs showed good prediction of recurrence in individual PTC patients.

PMID: 29439612 [PubMed - as supplied by publisher]

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