Suppr超能文献

基于阳性淋巴结对数优势比构建和验证新型列线图以预测甲状腺乳头状癌的预后:一项回顾性队列研究

Construction and validation of novel nomograms based on the log odds of positive lymph nodes to predict the prognosis of papillary thyroid cancer: a retrospective cohort study.

作者信息

Jing Saisai, Song Jiazhao, Di Yupeng, Xiao Jiajia, Ma Jianke, Wu Zimiao

机构信息

Department of Oncology, Affiliated Cixi Hospital, Wenzhou Medical University, Cixi, Zhejiang, China.

Department of Radiotherapy, Air Force Medical Center, Air Force Medical University, Beijing, China.

出版信息

Front Endocrinol (Lausanne). 2025 Mar 7;16:1411426. doi: 10.3389/fendo.2025.1411426. eCollection 2025.

Abstract

OBJECTIVE

This study aims to assess the long-term prognostic significance of the log odds of positive lymph nodes (LODDS) in patients diagnosed with papillary thyroid cancer (PTC) and to develop a novel nomogram for predicting long-term overall survival (OS).

METHODS

The cohort was randomly divided at a ratio of 7:3 from the Surveillance, Epidemiology, and End Results (SEER) database. Additionally, patient data from a medical center in China served as an external validation cohort. Nomograms were constructed using data from the training cohort and subsequently validated using both internal and external validation cohorts to predict 120- and 180-month OS in PTC patients. The predictive performance and clinical utility of the nomogram were assessed using various metrics, including the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), Integrated Discriminant Improvement Index (IDI), and Net Reclassification Improvement Index (NRI).

RESULTS

LODDS is an independent prognostic factor for PTC, a nomogram demonstrating high accuracy in predicting long-term OS. The C-index values, and time-dependent area under the curve (AUC) indicated well discriminatory ability of the nomogram. Calibration plots exhibited high concordance, while DCA, NRI, and IDI analyses revealed superior performance of the nomogram compared to AJCC staging system.

CONCLUSION

The clinical prediction model incorporating LODDS exhibits robust predictive performance, aiding in the assessment of long-term prognosis post-surgery in PTC patients. It serves as a valuable adjunct to the AJCC system, offering a scientific basis for guiding interventions and rehabilitation strategies for PTC patients following surgery.

摘要

目的

本研究旨在评估诊断为乳头状甲状腺癌(PTC)患者的阳性淋巴结对数优势比(LODDS)的长期预后意义,并开发一种用于预测长期总生存期(OS)的新型列线图。

方法

该队列从监测、流行病学和最终结果(SEER)数据库中以7:3的比例随机划分。此外,来自中国一家医疗中心的患者数据作为外部验证队列。使用来自训练队列的数据构建列线图,随后使用内部和外部验证队列进行验证,以预测PTC患者120个月和180个月的总生存期。使用各种指标评估列线图的预测性能和临床实用性,包括一致性指数(C指数)、时间依赖性受试者工作特征(ROC)曲线、校准曲线、决策曲线分析(DCA)、综合判别改善指数(IDI)和净重新分类改善指数(NRI)。

结果

LODDS是PTC的独立预后因素,列线图在预测长期总生存期方面显示出高准确性。C指数值和时间依赖性曲线下面积(AUC)表明列线图具有良好的辨别能力。校准图显示出高度一致性,而DCA、NRI和IDI分析显示列线图的性能优于美国癌症联合委员会(AJCC)分期系统。

结论

纳入LODDS的临床预测模型具有强大的预测性能,有助于评估PTC患者术后的长期预后。它是AJCC系统的有价值辅助工具,为指导PTC患者术后的干预和康复策略提供科学依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/15b8/11925767/429e99b648b6/fendo-16-1411426-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验