Evidence map›Paper›PMID 36969066›Full record

ArticleFrontiers in oncology2023

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

Bingyu Ran, Jian Gong, Jingjie Shang, Feng Wei, Hao Xu

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Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Bingyu RanDepartment of Nuclear Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Jian GongDepartment of Nuclear Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Jingjie ShangDepartment of Nuclear Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Feng WeiDepartment of Nuclear Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Hao XuDepartment of Nuclear Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This 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. Methods: In 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. Results: The 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. Conclusion: We 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.

Indexed as

nomogramoverall survivalradioiodine therapySEERthyroid cancer

Identifiers

PMID36969066
PMCPMC10034318

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