血清脂联素、视黄醇结合蛋白4及中性粒细胞/淋巴细胞比值对代谢相关脂肪性肝炎的诊断价值
DOI: 10.12449/JCH260913
Value of serum adiponectin, retinol-binding protein 4, and neutrophil-to-lymphocyte ratio in the diagnosis of metabolic dysfunction-associated steatohepatitis
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摘要:
目的 分析血清脂联素(ADPN)、视黄醇结合蛋白4(RBP4)及中性粒细胞/淋巴细胞比值(NLR)对代谢相关脂肪性肝炎(MASH)的评估价值,为临床预防提供参考。 方法 选取2023年1月—2025年1月于山西医科大学第三医院就诊的代谢相关脂肪性肝病(MAFLD)患者为研究对象,采用Logistic回归分析MASH的预测因素,采用R语言rms程序包建立列线图,绘制受试者操作特征曲线(ROC曲线)、校准曲线及决策曲线分析(DCA)评估模型的准确性和实用性,并采用Pearson相关性分析各指标间的相关性。计数资料两组间比较采用χ2检验;符合正态分布的计量资料两组间比较采用成组t检验;不符合正态分布的计量资料两组间比较采用Mann-Whitney U检验。 结果 共纳入298例MAFLD患者,其中MASH患者95例,单纯性脂肪变性患者203例。多因素Logistic回归分析显示,丙氨酸氨基转移酶(ALT)、碱性磷酸酶(ALP)、RBP4、ADPN及NLR是MASH的独立影响因素(P值均<0.05)。根据以上因素构建列线图模型并进行评估,ROC曲线结果显示,模型的曲线下面积为0.985(95%置信区间:0.976~0.995),灵敏度为0.968,特异度为0.901。校准曲线结果显示,H-L拟合优度检验(χ2=2.905,P=0.940)提示该模型预测概率与实际概率之间的差异无统计学意义,表明该模型拟合性良好、预测准确度较高。DCA结果显示,当预测风险阈值>0.05时,该模型可获得净收益。Pearson相关性分析显示,MASH患者血清RBP4与ADPN呈负相关(r=-0.275,P<0.001),与NLR呈正相关(r=0.282,P<0.001);ADPN与NLR呈负相关(r=-0.221,P<0.001)。 结论 ALT、ALP、RBP4、ADPN及NLR是MASH发生的独立影响因素,临床应加强监测,早期识别高风险患者并及时干预,以降低其发病率及疾病进展风险。 Abstract:Objective To investigate the value of serum adiponectin (ADPN), retinol-binding protein 4 (RBP4), and neutrophil-to-lymphocyte ratio (NLR) in assessing metabolic dysfunction-associated steatohepatitis (MASH), and to provide a reference for clinical prevention. Methods A total of 298 patients with metabolic dysfunction-associated fatty liver disease (MAFLD) who attended The Third Hospital of Shanxi Medical University from January 2023 to January 2025 were enrolled as subjects. A Logistic regression analysis was used to investigate the predictive factors for MASH, and R language rms package was used to construct a nomogram. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis were used to evaluate model accuracy and practicality, and a Pearson correlation analysis was used to investigate the correlation between various indicators. The chi-square test was used for comparison of categorical data between groups; the independent-samples t test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups. Results A total of 298 MAFLD patients were enrolled, among whom there were 95 patients with MASH and 203 patients with simple steatosis. The multivariate Logistic regression analysis showed that alanine aminotransferase (ALT), alkaline phosphatase (ALP), RBP4, ADPN, and NLR were independent influencing factors for MASH (all P<0.05). A nomogram model was constructed based on the above factors, and the ROC curve analysis showed that the model had an area under the ROC curve of 0.985 (95% confidence interval: 0.976 — 0.995), with a sensitivity of 0.968 and a specificity of 0.901. The calibration curve analysis showed no significant difference between the predicted and actual probabilities based on the Hosmer-Lemeshow goodness-of-fit test (χ2=2.905, P=0.940), suggesting that the model had good fit and high predictive accuracy. The decision curve analysis showed that the model achieved net benefit when the risk threshold was >0.05. The Pearson correlation analysis showed that in MASH patients, serum RBP4 was negatively correlated with ADPN (r=-0.275, P<0.001) and was positively correlated with NLR (r=0.282, P<0.001), and ADPN was negatively correlated with NLR (r=-0.221, P<0.001). Conclusion ALT, ALP, RBP4, ADPN, and NLR are independent influencing factors for MASH. It is necessary in clinical practice to enhance monitoring, identify high-risk patients as early as possible, and provide timely intervention, so as to reduce the incidence rate of MASH and the risk of disease progression. -
表 1 两组临床资料及实验室指标比较
Table 1. Comparison of clinical data and laboratory indicators between the two groups
因素 MASH组(n=95) SFL组(n=203) 统计值 P值 性别[例(%)] χ2=0.473 0.492 男 55(57.89) 126(62.07) 女 40(42.11) 77(37.93) 年龄(岁) 51.36±6.59 50.24±6.95 t=1.318 0.189 BMI(kg/m2) 26.86±4.21 24.93±4.07 t=3.773 <0.001 吸烟史[例(%)] χ2=0.165 0.685 是 52(54.74) 106(52.22) 否 43(45.26) 97(47.78) 伴糖尿病[例(%)] χ2=0.521 0.471 是 44(46.32) 85(41.87) 否 51(53.68) 118(58.13) 伴高血压[例(%)] χ2=0.336 0.562 是 46(48.42) 91(44.83) 否 49(51.58) 112(55.17) ALT(U/L) 45.23±11.57 30.31±9.68 t=11.633 <0.001 AST(U/L) 24.22±6.59 23.09±6.13 t=1.448 0.149 ALP(U/L) 101.39±12.27 82.37±10.43 t=13.850 <0.001 GGT(U/L) 63.58±11.23 66.16±12.65 t=1.699 0.090 TBil(μmol/L) 14.00(12.00~16.00) 14.00(12.00~16.00) Z=-0.797 0.425 DBil(μmol/L) 5.00(4.00~7.00) 5.00(4.00~7.00) Z=-0.368 0.713 TG(mmol/L) 3.45±1.10 3.21±0.95 t=1.931 0.055 TC(mmol/L) 5.23±0.98 5.18±0.99 t=0.408 0.684 HDL-C(mmol/L) 1.22±0.30 1.28±0.32 t=1.538 0.125 LDL-C(mmol/L) 3.84±0.91 3.63±0.91 t=1.856 0.064 ADPN(μg/mL) 9.13±2.05 11.58±2.43 t=8.510 <0.001 RBP4(mg/L) 25.00(22.00~27.00) 19.00(17.00~22.00) Z=-10.625 <0.001 NLR 1.65±0.45 1.21±0.35 t=9.204 <0.001 PLT(×109/L) 7.00(6.00~8.00) 7.00(6.00~8.00) Z=-1.256 0.209 注:MASH,代谢相关脂肪性肝炎;SFL,单纯性脂肪变性;BMI,体重指数;ALT,丙氨酸氨基转移酶;AST,天冬氨酸氨基转移酶;ALP,碱性磷酸酶;GGT,γ-谷氨酰转移酶;TBil,总胆红素;DBil,直接胆红素;TG,甘油三酯;TC,总胆固醇;HDL-C,高密度脂蛋白胆固醇;LDL-C,低密度脂蛋白胆固醇;ADPN,脂联素;RBP4,视黄醇结合蛋白4;NLR,中性粒细胞/淋巴细胞比值;PLT,血小板。
表 2 MASH预测指标的Logistic多因素分析
Table 2. Multi-factor analysis of MASH predictors
自变量 B值 SE Wald P值 OR 95%CI BMI 0.005 0.067 0.005 0.945 0.995 0.873~1.135 ALT 0.112 0.031 13.295 <0.001 1.118 1.053~1.188 ALP 0.142 0.033 18.011 <0.001 1.152 1.079~1.230 ADPN -0.550 0.146 14.181 <0.001 0.577 0.434~0.768 RBP4 0.502 0.108 21.752 <0.001 1.651 1.337~2.039 NLR 3.911 1.004 15.192 <0.001 49.971 6.991~357.209 常量 -28.798 5.246 30.134 0.002 <0.001 — 注:BMI,体重指数;ALT,丙氨酸氨基转移酶;ALP,碱性磷酸酶;ADPN,脂联素;RBP4,视黄醇结合蛋白4;NLR,中性粒细胞/淋巴细胞比值;MASH,代谢相关脂肪性肝炎;OR,比值比;CI,置信区间;SE,标准误。
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