Bauvin Pierre, Delacôte Claire, Lassailly Guillaume, Ntandja Wandji Line Carolle, Gnemmi Viviane, Dautrecque Flavien, Louvet Alexandre, Caiazzo Robert, Raverdy Violeta, Leteurtre Emmanuelle, Pattou François, Deuffic-Burban Sylvie, Mathurin Philippe
Univ. Lille, Inserm, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, Lille, France.
Hôpital Claude Huriez, Services Maladies de l'Appareil Digestif, CHRU Lille, Lille, France.
Liver Int. 2021 Jan;41(1):91-100. doi: 10.1111/liv.14650.
BACKGROUND & AIMS: Severely obese patients are a growing population at risk of non-alcoholic fatty liver disease (NAFLD). Considering the increasing burden, a predictive tool of NAFLD progression would be of interest. Our objective was to provide a tool allowing general practitioners to identify and refer the patients most at risk, and specialists to estimate disease progression and adapt the therapeutic strategy.
This predictive tool is based on a Markov model simulating steatosis, fibrosis and non-alcoholic steatohepatitis (NASH) evolution. This model was developped from data of 1801 severely obese, bariatric surgery candidates, with histological assessment, integrating duration of exposure to risk factors. It is then able to predict current disease severity in the absence of assessment, and future cirrhosis risk based on current stage.
The model quantifies the impact of sex, body-mass index at 20, diabetes, age of overweight onset, on progression. For example, for 40-year-old severely obese patients seen by the general practitioners: (a) non-diabetic woman overweight at 20, and (b) diabetic man overweight at 10, without disease assessment, the model predicts their current risk to have NASH or F3-F4: for (a) 5.7% and 0.6%, for (b) 16.1% and 10.0% respectively. If those patients have been diagnosed F2 by the specialist, the model predicts the 5-year cirrhosis risk: 1.8% in the absence of NASH and 6.0% in its presence for (a), 10.3% and 26.7% respectively, for (b).
This model provides a decision-making tool to predict the risk of liver disease that could help manage severely obese patients.
重度肥胖患者群体不断壮大，面临非酒精性脂肪性肝病（NAFLD）风险。鉴于负担日益加重，NAFLD进展的预测工具将备受关注。我们的目标是提供一种工具，使全科医生能够识别并转诊风险最高的患者，使专科医生能够评估疾病进展并调整治疗策略。
该预测工具基于马尔可夫模型，模拟脂肪变性、纤维化和非酒精性脂肪性肝炎（NASH）的演变。该模型是根据1801例重度肥胖、拟行减肥手术且经组织学评估的患者数据开发的，纳入了危险因素暴露时间。然后，它能够在没有评估的情况下预测当前疾病严重程度，并根据当前阶段预测未来肝硬化风险。
该模型量化了性别、20岁时的体重指数、糖尿病、超重起始年龄对疾病进展的影响。例如，对于全科医生接诊的40岁重度肥胖患者：（a）20岁时超重的非糖尿病女性，以及（b）10岁时超重的糖尿病男性，在未进行疾病评估的情况下，该模型预测他们当前患NASH或F3-F4的风险：（a）分别为5.7%和0.6%，（b）分别为16.1%和10.0%。如果这些患者被专科医生诊断为F2，该模型预测5年肝硬化风险：（a）在无NASH时为1.8%，有NASH时为6.0%；（b）分别为10.3%和26.7%。
该模型提供了一种决策工具，用于预测肝病风险，有助于管理重度肥胖患者。
