Zhu Huiling, Zheng Mengyao, He Haiyu, Lei Hongtao, Tai Wenlin, Yang Jinhui, Song Zhengji
Department of Gastroenterology, Second Affiliated Hospital of Kunming Medical University, Kunming, China.
School of Public Health, Kunming Medical University, Kunming, China.
Sci Rep. 2024 Dec 28;14(1):31369. doi: 10.1038/s41598-024-82854-1.
Ursodeoxycholic acid (UDCA) is the first-line treatment for primary biliary cholangitis (PBC), but 20-40% of patients do not respond well to UDCA. We aimed to develop and validate a prognostic model for the early prediction of patients who nonresponse to UDCA. This retrospective analysis was conducted among patients with primary biliary cholangitis(N = 257) to develop a predictive model for early-stage nonresponse to ursodeoxycholic acid (UDCA) therapy. The model's reliability was subsequently confirmed through external validation in an independent cohort(N = 71). Multivariate cox regression analysis was used to evaluate variables that were significant in the univariate analysis. Total cholesterol, alkaline phosphatase (ALP), and neutrophil-to-lymphocyte ratio (NLR) were the three independent risk factors associated with early biochemical nonresponse to UDCA treatment. Based on these factors, we established a predictive model that possessed good discriminative ability, as reflected by an AUC of 0.862(95%CI = 0.813-0.911). The ROC curve of the external validation set calculated the AUC of 0.916(95%CI:0.823-1.000). In summary, we developed an early predictive model that could identify potential nonresponse factors to UDCA at baseline, which could facilitate risk evaluation and stratification for PBC patients. The NLR and total cholesterol provided a supplementary means for effectively managing PBC patients.
熊去氧胆酸(UDCA)是原发性胆汁性胆管炎(PBC)的一线治疗药物,但20%-40%的患者对UDCA反应不佳。我们旨在开发并验证一种用于早期预测对UDCA无反应患者的预后模型。这项回顾性分析在原发性胆汁性胆管炎患者(N = 257)中进行,以建立对熊去氧胆酸(UDCA)治疗早期无反应的预测模型。随后通过在一个独立队列(N = 71)中的外部验证确认了该模型的可靠性。采用多变量cox回归分析来评估在单变量分析中有显著意义的变量。总胆固醇、碱性磷酸酶(ALP)和中性粒细胞与淋巴细胞比值(NLR)是与UDCA治疗早期生化无反应相关的三个独立危险因素。基于这些因素,我们建立了一个具有良好鉴别能力的预测模型,AUC为0.862(95%CI = 0.813 - 0.911)即反映了这一点。外部验证集的ROC曲线计算出AUC为0.916(95%CI:0.823 - 1.000)。总之,我们开发了一种早期预测模型,该模型可以在基线时识别出对UDCA潜在的无反应因素,这有助于对PBC患者进行风险评估和分层。NLR和总胆固醇为有效管理PBC患者提供了一种补充手段。