基于纤维蛋白原与中性粒细胞比值的Nomogram预测宫颈癌和2型糖尿病患者淋巴结转移的新方法

IF 2.5 4区 医学 Q3 ONCOLOGY
Cancer Management and Research Pub Date : 2025-05-10 eCollection Date: 2025-01-01 DOI:10.2147/CMAR.S510815
Hongying Kuang, Dongxia Yang, Ruoyao Lin, Yaling Tang, Yongli Luo, Shuwen Wang, Tingting Xia, Ge Lou, Hong Chen
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引用次数: 0

摘要

背景:糖尿病患者中宫颈癌发病率的上升是一个值得关注的问题,对全世界的健康状况和生活质量产生了深远的影响。在诊断为早期宫颈癌的患者中,淋巴结受累程度已成为影响复发风险和生存结果的关键预后因素。因此,准确预测盆腔淋巴结转移对于准确评估预后至关重要。术前淋巴结转移的识别是制定个性化治疗策略的关键因素。研究表明,炎症标志物如中性粒细胞、淋巴细胞和纤维蛋白原对癌症进展和预后评估有重要影响。在这方面,我们提出纤维蛋白原与中性粒细胞比率(FNR)作为评估宫颈癌合并2型糖尿病患者盆腔淋巴结转移的创新和有前途的生物标志物。方法:选取在厦门大学附属第一医院就诊的141例宫颈癌合并2型糖尿病患者为研究对象。将患者随机分为训练组(n=98)和验证组(n=43),比例为7:3。进行单因素和多因素logistic回归分析,以确定独立的危险因素,并根据这些发现建立预后模型。对模型的有效性进行了评价。结果:与使用单一生物标志物相比,结合FNR、甘油三酯、最大直径和总蛋白等多种因素的nomogram预测2型糖尿病和宫颈癌患者盆腔淋巴结转移的潜力更大。结论:FNR作为一种综合性的生物标志物,在鉴别宫颈癌合并糖尿病患者淋巴结转移风险增高方面具有更全面、更可靠的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Nomogram Based on Fibrinogen-to-Neutrophil Ratio as a Novel Predictor of Lymph Node Metastasis in Patients with Cervical Cancer and Type 2 Diabetes Mellitus.

Background: The rising incidence of cervical cancer among individuals with diabetes is a matter of significant concern, presenting profound implications for the health status and quality of life worldwide. In patients diagnosed with early-stage cervical cancer, the extent of lymph node involvement has emerged as a critical prognostic factor influencing recurrence risk and survival outcomes. Therefore, the precise prediction of pelvic lymph node metastasis is essential for an accurate assessment of prognosis. The preoperative identification of lymph node metastasis constitutes a pivotal element in the formulation of personalized treatment strategies. It has been demonstrated that inflammatory markers such as neutrophils, lymphocytes, and fibrinogen significantly contribute to cancer progression and prognostic evaluations. In this regard, we propose the fibrinogen-to-neutrophil ratio (FNR) as an innovative and promising biomarker for evaluating pelvic lymph node metastasis in cervical cancer patients with type 2 diabetes.

Methods: The study was conducted on 141 patients diagnosed with cervical cancer and concomitant type 2 diabetes, who were treated at the First Affiliated Hospital of Xiamen University. The patients were randomly divided into a training set (n=98) and a validation set (n=43), with a ratio of 7:3. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors, and a prognostic model was established based on these findings. The model's effectiveness was evaluated.

Results: A nomogram that integrates multiple factors, including FNR, triglycerides, maximum diameter, and total protein, demonstrates superior potential in predicting pelvic lymph node metastasis in patients with type 2 diabetes and cervical cancer, compared to the use of a single biomarker.

Conclusion: As a comprehensive biomarker, FNR shows significant potential in offering a more thorough and reliable approach for identifying cervical cancer patients with diabetes who are at an elevated risk of lymph node metastasis.

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来源期刊
Cancer Management and Research
Cancer Management and Research Medicine-Oncology
CiteScore
7.40
自引率
0.00%
发文量
448
审稿时长
16 weeks
期刊介绍: Cancer Management and Research is an international, peer reviewed, open access journal focusing on cancer research and the optimal use of preventative and integrated treatment interventions to achieve improved outcomes, enhanced survival, and quality of life for cancer patients. Specific topics covered in the journal include: ◦Epidemiology, detection and screening ◦Cellular research and biomarkers ◦Identification of biotargets and agents with novel mechanisms of action ◦Optimal clinical use of existing anticancer agents, including combination therapies ◦Radiation and surgery ◦Palliative care ◦Patient adherence, quality of life, satisfaction The journal welcomes submitted papers covering original research, basic science, clinical & epidemiological studies, reviews & evaluations, guidelines, expert opinion and commentary, and case series that shed novel insights on a disease or disease subtype.
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