Tapper Elliot B, Zhang Peng, Garg Rohan, Nault Tori, Leary Kate, Krishnamurthy Venkat, Su Grace L
Division of Gastroenterology and Hepatology, University of Michigan, Ann Arbor, Michigan.
Institute for Healthcare Policy and Innovation, Ann Arbor, Michigan.
JHEP Rep. 2019 Dec 5;2(1):100061. doi: 10.1016/j.jhepr.2019.11.005. eCollection 2020 Feb.
BACKGROUND & AIMS: Body composition, particularly sarcopenia, is associated with mortality in patients with decompensated cirrhosis undergoing transplant evaluation. Similar data are limited for non-transplant eligible or compensated patients.
A total of 274 patients with cirrhosis were followed prospectively for ≤5 years after a CT scan. We utilized Analytic Morphomics® to measure body composition (fat, muscle, and bone) which was rendered into relative values (percentiles) in relation to a reference population. The model for end-stage liver disease (MELD) score was used as a reference model for survival prediction. We validated our models in a separate cohort.
Our cohort had a mean Child-Pugh score of 7.0 and a mean MELD of 11.3. The median follow-up time was 5.05 years. The proportion of patients alive at 1, 3 and 5 years was 86.5%, 68.0%, and 54.3%; 13 (4.6%) underwent liver transplantation. Child-Pugh B/C ( A) cirrhosis was associated with decreased muscle, subcutaneous, and visceral fat area but increased subcutaneous/visceral fat density. Decreased normal density muscle mass was associated with mortality (hazard ratio [HR] 0.984, <0.001) as well as visceral and subcutaneous fat density (HR 1.013 and 1.014, respectively, <0.001). Models utilizing these features outperformed MELD alone for mortality discrimination in both the derivation and validation cohort, particularly for those with compensated cirrhosis (C-statistics of 0.74 0.58). Using competing risk analysis, we found that subcutaneous fat density was most predictive of decompensation (subdistribution HR 1.018, = 0.0001).
The addition of body composition features to predictive models improves the prospective determination of prognosis in patients with cirrhosis, particularly those with compensated disease. Fat density, a novel feature, is associated with the risk of decompensation.
Am I at high risk of getting sicker and dying? This is the key question on the mind of patients with cirrhosis. The problem is that we have very few tools to help guide our patients, particularly if they have early cirrhosis (without symptoms like confusion or fluid in the belly). We found that how much muscle and fat the patient has and what that muscle or fat looks like on a CT scan provide helpful information. This is important because many patients have CT scans and this information is hiding in plain sight.
身体组成，尤其是肌肉减少症，与接受移植评估的失代偿期肝硬化患者的死亡率相关。对于不符合移植条件或处于代偿期的患者，类似的数据有限。
对274例肝硬化患者在CT扫描后进行了为期≤5年的前瞻性随访。我们使用Analytic Morphomics®测量身体组成（脂肪、肌肉和骨骼），并将其转化为相对于参考人群的相对值（百分位数）。终末期肝病模型（MELD）评分用作生存预测的参考模型。我们在一个单独的队列中验证了我们的模型。
我们的队列平均Child-Pugh评分为7.0，平均MELD评分为11.3。中位随访时间为5.05年。1年、3年和5年时存活患者的比例分别为86.5%、68.0%和54.3%；13例（4.6%）接受了肝移植。Child-Pugh B/C（A）级肝硬化与肌肉、皮下和内脏脂肪面积减少但皮下/内脏脂肪密度增加有关。正常密度肌肉量减少与死亡率相关（风险比[HR]0.984，P<0.001），以及内脏和皮下脂肪密度（HR分别为1.013和1.014，P<0.001）。在推导队列和验证队列中，利用这些特征的模型在死亡率判别方面优于单独的MELD模型，尤其是对于代偿期肝硬化患者（C统计量为0.74对0.58）。使用竞争风险分析，我们发现皮下脂肪密度最能预测失代偿（亚分布HR 1.018，P = 0.0001）。
在预测模型中加入身体组成特征可改善肝硬化患者预后的前瞻性判定，尤其是代偿期疾病患者。脂肪密度作为一个新特征，与失代偿风险相关。
我病情加重和死亡的风险高吗？这是肝硬化患者心中的关键问题。问题在于我们几乎没有工具来帮助指导患者，特别是如果他们患有早期肝硬化（没有如意识模糊或腹水等症状）。我们发现患者的肌肉和脂肪量以及CT扫描上的肌肉或脂肪外观能提供有用信息。这很重要，因为许多患者都进行CT扫描，而这些信息就隐藏在眼前。
