Development and validation of nomograms for predicting survival in differentiated thyroid cancer patients with or without radioiodine therapy

Abstract

ObjectiveThis study aimed to establish and validate the nomograms for predicting overall survival (OS) probabilities in differentiated thyroid cancer (DTC) patients who received and did not receive radioiodine therapy (RAI), respectively.MethodsIn this study, 11, 099 patients diagnosed with DTC in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2016 were selected. Whether they have RAI, they are divided into RAI (n=6427) and non-RAI (n=4672) groups. They were randomly assigned to either a training cohort (RAI: n=4498, non-RAI: n=3263) or a validation cohort (RAI: n=1929, non-RAI: n=1399) using R software to divide the patients in a 7-to-3 ratio randomly. Variables were selected using a backward stepwise method in a Cox regression model to determine the independent prognostic factors, which were then utilized to build two nomograms to predict the 5-, 8-, and 10-year OS probabilities in DTC patients with or without RAI. The concordance index (C‐index), the area under the time-dependent receiver operating characteristics curve (AUC), the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to evaluate the performance of our models.ResultsThe multivariate analyses demonstrated that birth of the year, race, histological type, tumor size, grade, TNM stage, lymph node dissections, surgery, and chemotherapy were risk factors for OS. Compared to the AJCC stage, the C‐index (RAI: training group: 0.911 vs. 0.810, validation group: 0.873 vs. 0.761; non-RAI: training group: 0.903 vs. 0.846, validation group: 0.892 vs. 0.808). The AUC values for the training cohort (RAI: 0.940, 0.933, and 0.942; non-RAI: 0.891, 0.884, and 0.852 for the 5-, 8-, and 10-year OS, respectively) and validation cohort (RAI: 0.855, 0.825, and 0.900, non-RAI: 0.867, 0.896, and 0.899), and the calibration plots of both two models all exhibited better performance. Additionally, the NRI and IDI further showed that they exhibited good 5-, 8-, and 10-year net benefits.ConclusionWe have established the prediction models of DTC patients with or without RAI respectively through various variables. The nomogram may be more targeted to guide clinical decisions in the future.

Development and validation of a nomogram for predicting lymph node metastasis in early gastric cancer

“…Numerous factors influence LNM in EGC, and the identified risk factors differ across studies. Consistently, the depth of tumor invasion and tumor size are significant predictors of LNM across almost all research[ 9 , 21 , 26 , 27 ]. Based on preoperative clinicopathological data, we identified risk factors for LNM in EGC patients, and the results showed that tumor size, tumor location, degree of differentiation and pathological type were independent predictive risk factors for LNM in EGC patients.…”

Diagnostic value of qualitative and quantitative parameters of contrast-enhanced ultrasound for differentiating differentiated thyroid carcinomas from benign nodules

“…Inclusion criteria were: (1) Those who signed the informed consent before CEUS examination; (2) The nodules could be completely displayed in one section on US; (3) The final pathological results after surgical excision were obtained. Exclusion criteria were the following: (1) CEUS showed no enhancement; (2) CEUS images were not clear; (3) The distance between the edge of the nodule (>50%) and the thyroid capsule was <3 mm.…”

“…Differentiated thyroid cancers (DTC) (1)including papillary thyroid carcinoma (PTC), follicular thyroid carcinoma (FTC), and their variant subtypes (2), are the most frequent endocrine malignancies, and the incidence increased rapidly in recent years. DTC usually has a good prognosis, and Iodine-131 therapy and thyroid inhibitors have been shown to be beneficial for patients 10year survival rates ranging from 80 to 95 percent (3,4). However, about 5%-20% of cases may have tumor biological variation due to gene mutation, resulting in different subtypes and poor prognosis, which may be related to the biological characteristics of highly invasive tumors (5).…”

Development and validation of nomogram for predicting lymph node metastasis in early gastric cancer

“…To date, there have been many studies globally on the characteristics and regularity of LNM in EGC, but there is still no accurate prediction model. An increasing number of scholars believe that nomograms are effective tools for predicting tumour progression and aiding clinical decision-making [5][6][7][8][9][10] Prediction models are widely used to predict diagnosis and evaluate prognosis [11,12] , tumour stage, recurrence, metastasis, patient survival, and therapeutic e cacy [13][14][15][16][17][18] , There have been numerous studies worldwide on nomograms for the prediction of LNM in EGC [19][20][21] . Cui [22] et al established a nomogram for predicting LNM in EGC, which included patient sex, tumour morphology, vascular invasion, lymphangiosarcoma thrombosis, tumour length, tumour invasion depth, and tumour differentiation degree.…”