Pretreatment prediction of response to ursodeoxycholic acid in primary biliary cholangitis: development and validation of the UDCA Response Score.
Pretreatment prediction of response to ursodeoxycholic acid in primary biliary cholangitis: development and validation of the UDCA Response Score.
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DOI：
10.1016/s2468-1253(18)30163-8
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发表时间：
2018-09
期刊：
影响因子：
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通讯作者：
Italian PBC Study Group and the UK–PBC Consortium
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作者：
Carbone M;Nardi A;Flack S;Carpino G;Varvaropoulou N;Gavrila C;Spicer A;Badrock J;Bernuzzi F;Cardinale V;Ainsworth HF;Heneghan MA;Thorburn D;Bathgate A;Jones R;Neuberger JM;Battezzati PM;Zuin M;Taylor-Robinson S;Donato MF;Kirby J;Mitchell-Thain R;Floreani A;Sampaziotis F;Muratori L;Alvaro D;Marzioni M;Miele L;Marra F;Giannini E;Gaudio E;Ronca V;Bonato G;Cristoferi L;Malinverno F;Gerussi A;Stocken DD;Cordell HJ;Hirschfield GM;Alexander GJ;Sandford RN;Jones DE;Invernizzi P;Mells GF;Italian PBC Study Group and the UK–PBC Consortium
目前的指南提倡对原发性胆汁性胆管炎（PBC）进行逐步的疾病改善治疗：所有患者开始熊去氧胆酸（UDCA）单药治疗，随后考虑对UDCA生化反应不足的患者进行二线治疗，常规的UDCA反应不足的时间为12个月。然而，这种方法的一个潜在限制是，风险最高的患者最终等待有效治疗的时间最长。在本研究中，我们试图确定是否可以使用治疗前临床参数准确预测UDCA的反应，以便探索治疗分层的替代方法。我们对2，703例UDCA治疗患者的治疗前变量进行了logistic回归分析，以得出UDCA缓解的最佳拟合模型，定义为ALPT 12 < 1.67×ULN。我们在来自意大利的外部PBC队列（n=460）中验证了该模型。最后，我们通过寻找模型预测与PBC肝活检（n = 20）的关键组织学特征（如胆道损伤和纤维化）之间的相关性，探索了模型的生物学可行性。以下治疗前参数与UDCA缓解概率较低相关：高ALP（p<0.0001），胆红素升高（p=0.0003），转氨酶降低（TA，p=0.0012），年轻（p<0.0001），从诊断到开始UDCA的时间间隔较长（治疗时滞，p<0.0001），ALP从诊断开始恶化（ΔALP，p<0.0001）。基于这些变量，我们得出了UDCA缓解的预测评分：在外部验证中，AUROC为0.83（0.79-0.87）。在PBC肝活检中，URS与导管反应（DR）和中间肝细胞（IH）相关。我们推导并外部验证了一个基于治疗前变量的模型，该模型可准确预测UDCA的缓解。与DR和IH的关联提供了表面效度。因此，该模型为探索PBC治疗分层的替代方法提供了基础。医学研究理事会（MR/L001489/1）;米兰比可卡大学。资助者在研究设计、数据收集和分析、出版决定或手稿编写中没有任何作用。
Current guidelines advocate a step-wise approach to disease-modifying treatment of primary biliary cholangitis (PBC): all patients begin treatment with ursodeoxycholic acid (UDCA) monotherapy – and those with inadequate biochemical response to UDCA are subsequently considered for second-line therapies, the conventional period to demonstrate inadequate UDCA response being 12 months. A potential limitation with this approach, however, is that patients at highest risk end up waiting longest for effective treatment. In this study, we sought to determine whether UDCA response can be accurately predicted using pre-treatment clinical parameters, so that alternative approaches to treatment stratification might be explored. We undertook logistic regression analysis of pre-treatment variables in 2,703 UDCA-treated patients to derive the best-fitting model of UDCA response, defined as ALPT12 < 1.67×ULN. We validated the model in an external PBC cohort from Italy (n=460). Finally, we explored the biological plausibility of the model by looking for correlation between model predictions and key histological features on PBC liver biopsies (n = 20), such as biliary injury and fibrosis. The following pre-treatment parameters were associated with lower probability of UDCA response: higher ALP (p<0.0001), higher bilirubin (p=0.0003), lower transaminases (TA, p=0.0012), younger age (p<0.0001), longer interval from diagnosis to the start of UDCA (treatment time lag, p<0.0001), and worsening of ALP from diagnosis (ΔALP, p<0.0001). Based on these variables, we derived a predictive score of UDCA response: In external validation, the AUROC was 0.83 (0.79-0.87). In PBC liver biopsies, the URS was associated with ductular reaction (DR) and intermediate hepatocytes (IH). We have derived and externally validated a model based on pre-treatment variables that accurately predicts UDCA response. Association with DR and IH provides face validity. Thus, this model provides a basis to explore alternative approaches to treatment stratification in PBC. Medical Research Council (MR/L001489/1); University of Milan-Bicocca. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.