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基于 BRAF(V600E) 与淋巴细胞亚群的列线图在 C-TIRADS 3 类及以上结节中鉴别良性病变与甲状腺乳头状癌的价值

英文原题:Value of a BRAF(V600E) and lymphocyte subset-based nomogram for discriminating benign lesions from papillary thyroid carcinoma in C-TIRADS 3 and higher nodules.

PubMed 2025/08/15(内容时间) Front Endocrinol (Lausanne) Q1 · IF 5.7(JCR 2025)

研究概要

BRAF V600E-淋巴细胞亚群列线图在 C-TIRADS 3+ 甲状腺结节中区分良性病变与 PTC 方面展现出稳健的临床实用性,其诊断效能优于传统风险分层系统。

中文摘要

背景:BRAF V600E突变和淋巴细胞亚群可能与甲状腺乳头状癌(PTC)相关。本研究建立并验证了一种列线图模型,用于定量预测C-TIRADS 3类及以上甲状腺结节的恶性风险,为中度或高度可疑结节的精准诊断和治疗提供参考。 方法:这项回顾性研究分析了210例C-TIRADS 3类甲状腺结节患者,根据细针穿刺活检(FNAB)结果分为良性组和PTC组。系统收集所有患者的临床及实验室参数。使用最小绝对收缩和选择算子(LASSO)回归进行变量筛选,并通过方差膨胀因子评估多重共线性(VIF<5)。随后将显著预测因子纳入多变量列线图。调整潜在混杂变量后,采用二元Logistic回归识别PTC独立风险因素。通过1,000次Bootstrap重复抽样进行内部验证,评估模型预测准确性、临床实用性和区分能力。并与传统C-TIRADS分类系统进行比较分析,评估相对性能。 结果:良性甲状腺结节与PTC在年龄、BRAF V600E基因型、NK细胞计数、NK细胞比例、CD4+ T细胞比例,以及超声特征(包括大小、回声、成分、边界和形态)方面存在显著差异(P<0.05)。通过LASSO回归和共线性诊断筛选出5个变量用于构建列线图:年龄、BRAF V600E基因型、NK细胞计数、NK细胞比例和CD4+ T细胞比例。模型具有优异区分能力(AUC=0.861,C-index=0.861)、良好的校准度(Hosmer-Lemeshow=6.72,P=0.57),且准确性优于随机预测(Brier评分=0.1061,P<0.05)。决策曲线分析证实,该模型在相关概率阈值范围内具有临床实用性。最终比较分析显示,新列线图的诊断性能优于C-TIRADS系统(AUC:0.862 vs. 0.752;P<0.01)。 结论:BRAF V600E-淋巴细胞亚群列线图对C-TIRADS 3类及以上甲状腺结节中良性病变和PTC的鉴别具有稳健的临床实用性,诊断性能优于传统风险分层系统。

展开英文摘要原文

BACKGROUND: The BRAF V600E mutation and lymphocyte subsets may be associated with papillary thyroid carcinoma (PTC). This study established and validated a nomogram model to quantitatively predict the malignant risk of papillary thyroid carcinoma in thyroid nodules classified as C-TIRADS category 3 or higher, providing a reference for precise diagnosis and treatment of these moderately or highly suspicious nodules. METHODS: This retrospective study analyzed 210 patients with thyroid nodules (C-TIRADS 3), stratified by fine-needle aspiration biopsy (FNAB) results into benign and PTC groups. Clinical and laboratory parameters were systematically collected for all patients. Variable selection was performed using least absolute shrinkage and selection operator (LASSO) regression, with multicollinearity assessed using variance inflation factors (VIF < 5). Subsequently, significant predictors were incorporated into a multivariate nomogram. Binary logistic regression analysis was employed to identify independent risk factors for PTC following adjustment for potential confounding variables. Internal validation was performed using bootstrap resampling (1,000 iterations) to assess the model's predictive accuracy, clinical utility, and discriminative ability. Comparative analysis was conducted against the conventional C-TIRADS classification system to evaluate relative performance. RESULTS: Significant differences were observed between benign thyroid nodules and PTC in age, BRAF V600E genotype, natural killer (NK) cell counts, NK cell percentages, CD4+ T cell percentages, and ultrasound characteristics including size, echogenicity, composition, boundary, and morphology (P < 0.05). Five variables, including age, BRAF V600E genotype, NK cell counts, NK cell%, and CD4+ T cell%, were selected through LASSO regression with collinearity diagnostics for nomogram construction. The model demonstrated excellent discrimination (AUC=0.861, C-index=0.861), good calibration (Hosmer-Lemeshow =6.72, P=0.57), and superior accuracy compared to random prediction (Brier score=0.1061, P<0.05). Decision curve analysis confirmed its clinical utility across relevant probability thresholds. Finally, the comparative analysis demonstrated superior diagnostic performance of the novel nomogram relative to the C-TIRADS system (AUC: 0.862 vs. 0.752; P<0.01). CONCLUSION: The BRAF V600E -lymphocyte subset nomogram demonstrates robust clinical utility for discriminating benign lesions from PTC in C-TIRADS 3+ thyroid nodules, offering superior diagnostic performance to conventional risk stratification systems.

论文信息

作者
Zhang W、Zeng S、Dou J、Yu C
单位
Department of Endocrinology, Chaohu Affiliated Hospital of Anhui Medical University, Hefei,&#xa0;China.China
期刊
Frontiers in endocrinology2025
原文标识
PubMed 40895621 · DOI 10.3389/fendo.2025.1608222