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  • Title: Construction and Validation of a Nomogram Based on the Log Odds of Positive Lymph Nodes to Predict the Prognosis of Medullary Thyroid Carcinoma After Surgery.
    Author: Tang J, Jiang S, Gao L, Xi X, Zhao R, Lai X, Zhang B, Jiang Y.
    Journal: Ann Surg Oncol; 2021 Aug; 28(8):4360-4370. PubMed ID: 33469797.
    Abstract:
    BACKGROUND: This study aimed to explore the prognostic impact that the log odds of positive lymph nodes (LODDS) has on medullary thyroid cancer (MTC) and to develop a nomogram incorporating LODDS to predict the cancer-specific survival (CSS) of MTC. METHODS: Data from 1110 MTC patients after total thyroidectomy were collected from the Surveillance, Epidemiology, and End Results (SEER) database and divided into training and validation cohorts. The prognostic efficiency of N status from the American Joint Committee on Cancer (AJCC) staging system, the number of positive lymph nodes (PLNN), and LODDS were compared using the Harrell concordance index (C-index), the Akaike information criterion (AIC), and area under the receiver operating characteristic (ROC) curve (AUC). A multivariate Cox analysis was performed to determine the independent prognostic factors, and a nomogram based on LODDS was constructed. The nomogram's performance was assessed with the C-index, AUC, calibration curves, and decision curve analysis (DCA). RESULTS: Among the three lymph node (LN) staging systems, LODDS showed the highest accuracy in predicting CSS for MTC. In the training cohort, the C-index of the LODDS-based nomogram was 0.895. The AUCs were 0.949, 0.917, 0.925, and 0.901 for predicting 1-, 3-, 5- and 10-year CSS, respectively. The calibration plots and DCA showed the superior clinical applicability of the nomogram. These results were verified in the validation cohort. CONCLUSIONS: As an independent prognostic factor for MTC, LODDS demonstrated superior prognostic efficiency over N status and PLNN. This LODDS-based nomogram yielded better performance than the AJCC tumor-node-metastasis (TNM) staging system in predicting CSS after surgery for MTC.
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