Construction of a nomogram model based on biomarkers for liver metastasis in non-small cell lung cancer.

IF 2.3 3区医学 Q3 ONCOLOGY Thoracic Cancer Pub Date : 2024-09-01 Epub Date: 2024-08-04 DOI:10.1111/1759-7714.15417

Tian Zhang, Yajuan Zhang, Yunfeng Ni, Xiaohui Jia, Yanlin Li, Ziyang Mao, Panpan Jiang, Xiaolan Fu, Min Jiao, Lili Jiang, Wenjuan Wang, Hui Guo, Ying Zan, Mengjie Liu

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Abstract

Background: Patients with non-small cell lung cancer (NSCLC) with liver metastasis have a poor prognosis, and there are no reliable biomarkers for predicting disease progression. Currently, no recognized and reliable prediction model exists to anticipate liver metastasis in NSCLC, nor have the risk factors influencing its onset time been thoroughly explored.

Methods: This study conducted a retrospective analysis of 434 NSCLC patients from two hospitals to assess the association between the risk and timing of liver metastasis, as well as several variables.

Results: The patients were divided into two groups: those without liver metastasis and those with liver metastasis. We constructed a nomogram model for predicting liver metastasis in NSCLC, incorporating elements such as T stage, N stage, M stage, lack of past radical lung cancer surgery, and programmed death ligand 1 (PD-L1) levels. Furthermore, NSCLC patients with wild-type EGFR, no prior therapy with tyrosine kinase inhibitors (TKIs), and no prior radical lung cancer surgery showed an elevated risk of early liver metastasis.

Conclusion: In conclusion, the nomogram model developed in this study has the potential to become a simple, intuitive, and customizable clinical tool for assessing the risk of liver metastasis in NSCLC patients following validation. Furthermore, it provides a framework for investigating the timing of metachronous liver metastasis.

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根据非小细胞肺癌肝转移的生物标志物构建提名图模型

背景：非小细胞肺癌（NSCLC）肝转移患者的预后较差，目前尚无可靠的生物标志物来预测疾病的进展。目前，还没有公认可靠的预测模型来预测非小细胞肺癌肝转移，也没有深入探讨影响肝转移发生时间的风险因素：本研究对两家医院的434名NSCLC患者进行了回顾性分析，以评估肝转移的风险和时间以及几个变量之间的关联：结果：患者被分为两组：无肝转移组和有肝转移组。我们构建了一个预测NSCLC肝转移的提名图模型，将T分期、N分期、M分期、既往未接受过肺癌根治术以及程序性死亡配体1（PD-L1）水平等因素纳入其中。此外，表皮生长因子受体野生型、既往未接受过酪氨酸激酶抑制剂（TKIs）治疗、既往未接受过肺癌根治手术的NSCLC患者发生早期肝转移的风险较高：总之，本研究开发的提名图模型经过验证后，有望成为一种简单、直观、可定制的临床工具，用于评估NSCLC患者的肝转移风险。此外，它还为研究肝转移的时间提供了一个框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Thoracic Cancer ONCOLOGY-RESPIRATORY SYSTEM

CiteScore

5.20

自引率

3.40%

发文量

439

审稿时长

2 months

期刊介绍： Thoracic Cancer aims to facilitate international collaboration and exchange of comprehensive and cutting-edge information on basic, translational, and applied clinical research in lung cancer, esophageal cancer, mediastinal cancer, breast cancer and other thoracic malignancies. Prevention, treatment and research relevant to Asia-Pacific is a focus area, but submissions from all regions are welcomed. The editors encourage contributions relevant to prevention, general thoracic surgery, medical oncology, radiology, radiation medicine, pathology, basic cancer research, as well as epidemiological and translational studies in thoracic cancer. Thoracic Cancer is the official publication of the Chinese Society of Lung Cancer, International Chinese Society of Thoracic Surgery and is endorsed by the Korean Association for the Study of Lung Cancer and the Hong Kong Cancer Therapy Society. The Journal publishes a range of article types including: Editorials, Invited Reviews, Mini Reviews, Original Articles, Clinical Guidelines, Technological Notes, Imaging in thoracic cancer, Meeting Reports, Case Reports, Letters to the Editor, Commentaries, and Brief Reports.