Division of Gastroenterology and Hepatology, Stanford University Medical Center, Stanford, California.
Liver Int. 2019 Apr;39(4):655-666. doi: 10.1111/liv.14009. Epub 2018 Dec 18.
BACKGROUND & AIM: Renal impairment is associated with chronic hepatitis B (CHB). To overcome prior study design differences, we used propensity score matching to balance the non-CHB and CHB cohorts and generalized linear modelling (GLM, models using probit and logit linking functions for complex models) to evaluate the effect of CHB, treatment and cirrhosis on renal function.
A retrospective cohort (1996-2017) from one U.S. university medical centre. Included patients had ≥12 months of serial creatinine laboratories and a baseline estimated glomerular filtration rate (eGFR, by the Modification of Diet in Renal Disease Study equation) ≥60 mL/min/1.73 m . Propensity score matching was performed using age, sex, ethnicity, diabetes, hypertension and baseline eGFR. GLM was performed to generate adjusted mean eGFR over time.
Adjusted mean eGFR was significantly higher for non-CHB vs. untreated CHB patients (eGFR 87.4 vs. 85.6, P= 0.004, n = 580, median follow-up = 82 months). A significant difference in adjusted mean eGFR between untreated vs. entecavir (ETV)-treated CHB patients (eGFR 85.1 vs. 83.5, P= 0.02, n = 340, median follow-up = 70 months) was found among non-cirrhotic CHB. Among treated CHB, there was no difference in adjusted mean eGFR between non-cirrhotic vs. cirrhotic patients (eGFR 77.0 vs. 76.5; P= 0.66, n = 112, median follow-up = 58 months).
After PSM and GLM, the significant predictors for worsening renal function were age, hypertension and diabetes mellitus but not CHB, ETV or cirrhosis. However, given small sample size, data regarding the use of ETV in patients with cirrhosis should be interpreted with caution and requires additional investigation.
肾功能损害与慢性乙型肝炎（CHB）相关。为了克服先前研究设计的差异，我们使用倾向评分匹配来平衡非 CHB 和 CHB 队列，并使用广义线性模型（GLM，对于复杂模型使用概率和对数链接函数的模型）来评估 CHB、治疗和肝硬化对肾功能的影响。
这是一项来自美国一所大学医疗中心的回顾性队列研究（1996-2017 年）。纳入的患者有≥12 个月的连续肌酐实验室检查和基线估计肾小球滤过率（eGFR，通过肾脏病饮食改良方程）≥60 mL/min/1.73 m 。使用年龄、性别、种族、糖尿病、高血压和基线 eGFR 进行倾向评分匹配。GLM 用于生成随时间调整的平均 eGFR。
与未经治疗的 CHB 患者相比，非 CHB 患者的调整后平均 eGFR 显著更高（eGFR 87.4 与 85.6，P=0.004，n=580，中位随访时间=82 个月）。在非肝硬化 CHB 患者中，未经治疗的 CHB 与恩替卡韦（ETV）治疗的 CHB 患者之间的调整后平均 eGFR 存在显著差异（eGFR 85.1 与 83.5，P=0.02，n=340，中位随访时间=70 个月）。在接受治疗的 CHB 患者中，非肝硬化与肝硬化患者的调整后平均 eGFR 无差异（eGFR 77.0 与 76.5；P=0.66，n=112，中位随访时间=58 个月）。
在进行 PSM 和 GLM 后，肾功能恶化的显著预测因素是年龄、高血压和糖尿病，而不是 CHB、ETV 或肝硬化。然而，鉴于样本量较小，应谨慎解读关于肝硬化患者使用 ETV 的数据，并需要进一步研究。
