血清miRNA提升多变量指数检验在附件肿块分诊中的准确性

Serum miRNA improves the accuracy of a multivariate index assay for triage of an adnexal mass

GYNECOLOGIC ONCOLOGY

影响因子:4.1

分区:医学2区 Top / 妇产科学1区肿瘤学2区

发表日期:2024 Nov

作者: James W Webber, Laura Wollborn, Sudhanshu Mishra, Allison F Vitonis, Daniel W Cramer, Ryan T Phan, Todd C Pappas, Konrad Stawiski, Wojciech Fendler, Dipanjan Chowdhury, Kevin M Elias

DOI: 10.1016/j.ygyno.2024.08.008

摘要

为了确定结合血清microRNA、蛋白质生物标志物和元数据的多模态检测是否能改善附件肿块的分诊评估。对来自468名训练对象（其中191例癌症病例和277例良性附件肿块对照或健康对照）的血清样本，分析了七种蛋白质生物标志物和180种miRNA。循环分析物数据与年龄和绝经状态（元数据）结合，构建神经网络模型以分类样本为病例或对照。采用十折交叉验证的前向回归最小化模型的维度同时最大化病例与对照之间的线性分离。模型验证分别使用内部（44例病例和56例对照）和外部验证集（51例病例和59例对照）。总体研究人群为678名受试者，包括286例病例和392例对照。其中，绝经前的受试者占43%（290人）。10个miRNA组成的检测面板在结合蛋白质和元数据时表现最佳。联合模型在内部验证（AUC=0.9；95% CI 0.81-0.95）和外部验证（AUC=0.95；95% CI 0.90-0.98）中均优于仅使用miRNA或蛋白质加元数据（不含miRNA）。在外部验证中，联合模型总体敏感性为92%，特异性为80%，早期和晚期癌症的敏感性分别为80%和100%，包括早期浆液性卵巢癌的78%和早期非浆液性癌的82%。一种结合miRNA、蛋白质生物标志物、年龄和绝经状态的多模态检测方法，有助于改善附件肿块的手术分诊。

Abstract

To determine whether a multimodal assay combining serum microRNA with protein biomarkers and metadata improves triage assessment of an adnexal mass.Serum samples from 468 training subjects (191 cancer cases and 277 benign adnexal mass controls or healthy controls) were analyzed for seven protein biomarkers and 180 miRNA. Circulating analyte data were combined with age and menopausal status (metadata) into a neural network model to classify samples as cases or controls. Forward regression with ten-fold cross-validation minimized the dimensionality of the model while maximizing linear separation between cases and controls. Model validation proceeded using both internal (44 cases and 56 controls) and external validation sets (51 cases and 59 controls).The total study population comprised 678 subjects, including 286 cases and 392 controls. Overall, 290 (43%) of the subjects were premenopausal. A panel of 10 miRNA delivered optimal performance when combined with protein and metadata features. The combined model improved the Receiver Operator Characteristic Area Under the Curve (ROC AUC) on the internal (AUC = 0.9; 95% CI 0.81-0.95) and external validation sets (AUC = 0.95; 95% CI 0.90-0.98) compared to miRNA alone or proteins plus metadata (without miRNA). On external validation, the combined model offered 92% sensitivity at 80% specificity overall, with 80% and 100% sensitivity for early and late-stage cancers, respectively, including 78% sensitivity for early-stage, serous ovarian cancers and 82% sensitivity for early-stage, non-serous cancers.A multimodal assay combining miRNA with protein biomarkers, age, and menopausal status improves surgical triage of an adnexal mass.