Department of Hepatology, The First Hospital of Jilin University, Changchun, Jilin, China.
Department of Gastroenterology, Qingdao Municipal Hospital, Qingdao, China.
Front Immunol. 2023 Mar 16;14:1152294. doi: 10.3389/fimmu.2023.1152294. eCollection 2023.
The aim of this study was to develop a noninvasive prediction model for histological stages in PBC that is simple, easy to implement, and highly accurate.
A total of 114 patients with PBC were included in this study. Demographic, laboratory data and histological assessments were collected. The independent predictors of histological stages were selected to establish a noninvasive serological model. The scores of 22 noninvasive models were calculated and compared with the established model.
This study included 99 females (86.8%) and 15 males (13.2%). The number of patients in Scheuer's stage 1, 2, 3 and 4 was 33 (29.0%), 34 (29.8%), 16 (14.0%), and 31 (27.2%), respectively. TBA and RDW are independent predictors of PBC histological stages. The above indexes were used to establish a noninvasive model-TR score. When predicting early histological change (S1) or liver fibrosis and cirrhosis (S3-S4), the AUROC of TR score were 0.887 (95% CI, 0.809-0.965) and 0.893 (95% CI, 0.816-0.969), higher than all of the other 22 models included in this study. When predicting cirrhosis (S4), its AUROC is still as high as 0.921 (95% CI, 0.837-1.000).
TR score is an easy, cheap and stable noninvasive model, without complex calculation formulas and tools, and shows good accuracy in diagnosing the histological stages of PBC.
本研究旨在开发一种简单、易于实施且高度准确的非侵入性预测 PBC 组织学分期的模型。
本研究共纳入 114 例 PBC 患者。收集了人口统计学、实验室数据和组织学评估。选择独立的预测因素来建立非侵入性血清学模型。计算了 22 种非侵入性模型的评分并与建立的模型进行了比较。
本研究包括 99 名女性（86.8%）和 15 名男性（13.2%）。Scheuer 分期 1、2、3 和 4 的患者数量分别为 33 例（29.0%）、34 例（29.8%）、16 例（14.0%）和 31 例（27.2%）。TBA 和 RDW 是 PBC 组织学分期的独立预测因素。使用上述指标建立了一种非侵入性模型-TR 评分。当预测早期组织学变化（S1）或肝纤维化和肝硬化（S3-S4）时，TR 评分的 AUROC 为 0.887（95%CI，0.809-0.965）和 0.893（95%CI，0.816-0.969），高于本研究纳入的所有其他 22 种模型。当预测肝硬化（S4）时，其 AUROC 仍然高达 0.921（95%CI，0.837-1.000）。
TR 评分是一种简单、廉价且稳定的非侵入性模型，无需复杂的计算公式和工具，在诊断 PBC 的组织学分期方面具有良好的准确性。
