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Response to Primary Biliary Cholangitis Treatment: Influencing Factors and the Role in Prognosis Prediction
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摘要:目的 探索血脂异常的原发性胆汁性胆管炎（primary biliary cholangitis, PBC）患者对熊去氧胆酸（ursodeoxycholic acid, UDCA）治疗应答不佳的影响因素、预后特点。方法 回顾性收集2009年1月−2022年3月在四川大学华西医院治疗的512例确诊为PBC的患者。根据UDCA治疗应答情况分为完全应答组（n=305）和UDCA应答不佳组（n=207），对比两组患者的资料，预测影响应答的不利因素。受试者工作特征（receiver operating characteristic, ROC）曲线下面积（area under the curve, AUC）确定血清总胆固醇（total cholesterol, TC）的临界值，分析患者基线实验室检查指标、治疗后应答的差异。根据临界值将患者分为TC≥5.415 mmol/L组与TC<5.415 mmol/L组，并使用UK-PBC、GLOBE评分评估两组预后的差异。结果 UDCA应答不佳组的基线谷丙转氨酶（alanine aminotransferase, ALT）、谷草转氨酶（aspartate aminotransferase, AST）、总胆红素（total bilirubin, TB）、碱性磷酸酶（alkaline phosphatase, ALP）、γ-谷氨酰转肽酶（gamma-glutamyl transferase, GGT）、甘油三酯（triglyceride, TG）、TC、高密度脂蛋白胆固醇（high-density lipoprotein cholesterol, HDL-C）和低密度脂蛋白胆固醇（low-density lipoprotein cholesterol, LDL-C）较完全应答组升高（P均<0.05），白蛋白水平下降（P=0.012）。logistic回归模型多因素分析提示TC〔 比值比（odds ratio, OR）=1.501，95%置信区间（confidence interval, CI）：1.275～1.767，P<0.01〕和ALP（OR=1.005，95%CI：1.003～1.006，P<0.01）是影响应答的独立风险因素。ROC曲线分析提示TC≥5.415 mmol/L的PBC患者预后更差（AUC：0.727，95%CI：0.680～0.775，敏感性63.8%，特异性76.4%）。另外，高TC组（TC≥5.415 mmol/L）治疗1年时的UK-PBC风险评分高于低TC组（TC<5.415 mmol/L），差异有统计学意义（P<0.01）。结论 高胆固醇血症是PBC患者对UDCA应答不佳的一个独立风险因素。当基线血清TC≥5.415 mmol/L时，PBC患者对UDCA治疗的应答及预后较差。Abstract:Objective To examine the influencing factors and prognostic features of poor response to ursodeoxycholic acid (UDCA) treatment in primary biliary cholangitis (PBC) patients with dyslipidemia.Methods A retrospective study was conducted, covering 512 patients who had a confirmed diagnosis of PBC, and who received treatment at West China Hospital, Sichuan University between January 2009 and March 2022. According to their actual response to UDCA treatment, patients were divided into two groups, UDCA full-response group (n=305) and UDCA non-responding group (n=207). The data from the two groups were compared to predict the adverse factors influencing patient response and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, identify the cut-off value of total cholesterol (TC), and analyze the differences in baseline laboratory test findings and the rate of responses to treatment. According to the TC cut-off value, patients were divided into a group with TC≥5.415 mmol/L and another group with TC<5.415 mmol/L. In addition, differences in the prognosis of the two groups were assessed by comparing the UK-PBC and GLOBE scores.Results The baseline data, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TB), alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), triglycerides (TG), TC, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), were significantly increased in the UDCA non-responding group compared to those in the full-response group (all P<0.005), while the albumin level of the UDCA non-responding group was decreased compared to that of the full-response group (P=0.012). Findings of multi-factor logistic regression analysis suggested that TC (odds ratio [OR]=1.501, 95% confidence interval [CI]: 1.275-1.767, P<0.01) and ALP (OR=1.005, 95% CI: 1.003-1.006, P<0.01) were independent risk factors influencing patient response. The ROC curve analysis suggested worse prognosis for patients with TC≥5.415 mmol/L (AUC: 0.727, 95% CI: 0.680-0.775, 63.8% sensitivity, 76.4% specificity). In addition, the UK-PBC risk score at 1 year of treatment was higher in the high-TC group (TC≥5.415 mmol/L) than that in the low-TC group (TC<5.415 mmol/L) (P<0.05).Conclusions Hypercholesterolemia is an independent risk factor for poor response to UDCA in PBC patients. When the baseline TC is equal to or higher than 5.415 mmol/L, PBC patients have a relatively poor response to UDCA and poor prognosis.
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乳腺癌是女性最常见的恶性肿瘤[1]，早期预后较好，中晚期乳腺癌治疗仍面临严峻挑战[2]。不同病理类型的乳腺癌预后不同，其中雌激素受体、孕激素受体以及表皮生长因子受体2表达较低或不表达的三阴性乳腺癌侵袭性强、异质性高，其临床预后较差，缺乏特异性治疗手段[2]。围刺属于中医传统外治疗法，是以病变部位为中心，沿病变边缘包围性针刺，具有疏通气血之效。前期研究发现，围刺可抑制肿瘤生长，其与化疗药物联合可增强抗肿瘤效应[3-6]。此外，围刺可显著提高小鼠乳腺癌肿瘤部位紫杉醇药物浓度，围刺及其与化疗药物的协同抗肿瘤作用与肿瘤微血管正常化密切相关[7]。肿瘤微血管正常化是指通过促进肿瘤异常血管的结构与功能向正常血管转化，以增强血管运输能力、改善肿瘤组织灌注、纠正酸性乏氧微环境，促使药物更高效地输送至肿瘤细胞，从而提高抗肿瘤疗效。本研究拟通过构建4T1小鼠乳腺癌皮下移植瘤模型，观察电针围刺诱导肿瘤微血管正常化的作用。
1. 材料与方法
1.1 实验动物与细胞株
来源于BALB/c小鼠的4T1乳腺癌细胞株（中国医学科学院肿瘤医院肿瘤研究所细胞库）。6～8周龄SPF级雌性Balb/c小鼠54只，体质量16～18 g（动物合格证号：SCXK2016-0006），饲养于北京中医药大学和平街校区动物室SPF级实验室。本研究过程严格遵守北京中医药大学医学与实验动物伦理委员要求（伦理编号：BUCM-4-2021060701-2085）。
1.2 试剂和仪器
贝伐珠单抗注射液（上海罗氏制药有限公司，中国），CD31、α-肌动蛋白（alpha smooth muscle actin, α-SMA）、缺氧诱导因子1α（hypoxia-inducible factor 1-alpha, HIF-1α）抗体（Abcam，美国），RPMI-1640培养基、胎牛血清、胰蛋白酶（Thermo，美国），扫描电子显微镜（无锡创辉测量技术有限公司，中国），一次性无菌针灸针（0.18 mm×15 mm）、SDZ-V系列电子低频针疗仪（华佗牌，中国），组织脱水机、组织包埋机、切片机（樱花株式会社，日本），CO2培养箱（Thermo，美国），生物数字显微镜（Leica，德国）。
1.3 实验方法
1.3.1 小鼠乳腺癌皮下移植瘤模型构建
小鼠4T1乳腺癌细胞株用含10%胎牛血清、1%青霉素-链霉素培养于37 ℃、体积分数为5%CO2的培养箱。取对数生长期4T1细胞，于小鼠左侧大腿外侧皮下接种肿瘤细胞悬液0.1 mL（约1×106个细胞），构建BALB/c小鼠乳腺癌皮下移植瘤模型[8]。判断小鼠移植瘤模型成功的标准：H&E病理证实组织为乳腺癌，且肿瘤体积大小约200 mm3[9]。
1.3.2 实验分组及取材
以小鼠肿瘤体积为协变量，将造模成功的乳腺癌模型小鼠随机分为荷瘤组（tumor-bearing group, TG）、电针围刺组（electroacupuncture tumor-bearing group, EATG）和贝伐单抗组（bevacizumab tumor-bearing group, BTG），每组18只。TG组不进行干预；BTG组腹腔注射10 mg/kg贝伐单抗[10]，作为阳性对照组；EATG组进行围刺治疗：小鼠经2%戊巴比妥钠（3 mL/kg）腹腔注射麻醉后，采用一次性无菌针灸针在距瘤体边界约5 mm瘤周与体表呈60°角度向瘤根方向进针，深度约5 mm；采用低频针疗仪以疏密波交替刺激30 min（疏波频率3～4 Hz，串长5 s；密波频率15～20 Hz，串长10 s），刺激强度以动物未出现明显肢体颤抖为宜[7]。分别在干预前（D0）、干预后第3天（D3）、干预后第5天（D5）各组取6只小鼠，用2%戊巴比妥钠（3 mL/kg）腹腔注射麻醉后处死，完整剥离肿瘤组织，将肿瘤组织分别固定于10%甲醛溶液和2.5%戊二醛溶液，用于组织病理学检测和扫描电镜检测。
1.3.3 免疫荧光检测和电镜观察
肿瘤组织经石蜡包埋后制备5～10 μm石蜡切片，依次用二甲苯脱蜡，梯度乙醇脱水后，柠檬酸缓冲液修复抗原，3%过氧化氢室温30 min阻断内源性过氧化物酶的活性，3%山羊血清封闭抗原，加入CD31/α-SMA、HIF-1α抗体（1∶1000）4 ℃孵育过夜。加入荧光二抗，室温避光孵育1 h，PBS洗3次，DAPI溶液室温避光孵育10 min，PBS洗3次，甘油封片，荧光显微镜下任意选取3个视野采集图像。采用Image J软件对荧光强度进行定量分析。
用2.5%戊二醛溶液充分固定肿瘤组织，梯度酒精脱水后真空干燥，IB-3型真空离子镀膜仪中喷金镀膜，放入扫描电子显微镜载物台上，加速电压15 kV，低真空（40 Pa）模式下观察并采集图像。
1.4 统计学方法
实验数据采用SAS 9.3软件进行统计分析，计量资料表达以
$ \bar x \pm s $ 表示。多组独立计量资料，若满足正态分布并符合方差齐性标准，则执行单因素方差分析，若不能同时满足正态分布相符和方差齐性，则执行Welch检验。P<0.05为差异有统计学意义。2. 结果
2.1 皮下移植瘤模型构建情况
细胞接种7 d后可在皮下触及小米粒大小的肿瘤，瘤体逐渐增大，质硬。HE染色证实其为增殖异常活跃的乳腺癌细胞。所有小鼠皮下移植瘤生长情况基本一致，第14～16天肿瘤体积约200 mm3，造模成功率100%。
2.2 围刺对肿瘤生长的影响
实验期间所有小鼠均无明显异常。干预后第 3 天（D3）、第 5 天（D5）肿瘤体积均较实验干预前增加（ P<0.05），第 5 天（D5）肿瘤体积均较第 3 天（D3）增加（ P<0.05），相同时间点组间肿瘤体积无明显差异（P>0.05）（表1）。
表 1 不同时间点小鼠肿瘤生长情况（n=6）Table 1. Comparison of the tumor volume at different time points (n=6)Time Tumor volume/mm3 TG BTG EATG D0 376.89±53.42 376.82±56.66 387.28±63.43 D3 428.42±41.78# 437.80±30.17# 423.10±31.43# D5 527.50±76.22* 538.20±53.22* 539.76±78.38* TG: tumor-bearing group; BTG: bevacizumab tumor-bearing group; EATG: electroacupuncture tumor-bearing group. # P<0.05, vs. D0 in the same group; * P<0.05, vs. D3 in the same group. 2.3 围刺对CD31、α-SMA、HIF-1α表达的影响
CD31、α-SMA分别为血管内皮细胞、周细胞标记物。由图1可见，干预前（D0）各组CD31、α-SMA表达水平无明显差异（P>0.05）。干预后第3天（D3），EATG组与BTG组CD31表达水平均显著降低（P<0.01），α-SMA表达水平明显增加（P<0.01）。干预后第5天（D5），EATG组与BTG组CD31表达水平仍低于TG组（P<0.01），α-SMA表达水平仍高于TG组（P<0.05）。EATG组CD31表达水平在D5较D3有所增加，但差异不显著（P>0.05），EATG组α-SMA表达水平在D5、D3均无明显差异。干预后第3（D3）、5天（D5）EATG组与BTG组α-SMA、CD31表达水平均无明显差异（P>0.05）。
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图 1 围刺对肿瘤组织CD31、α-SMA表达的影响。×200Figure 1. Effect of peritumoral electroacupuncture on the expression of CD31 and α-SMA in the tumor tissue. ×200The red fluorescence represents positive expression of CD31, the green fluorescence represents positive expression of α-SMA, and the blue fluorescence represents the nucleus. * P<0.05, ** P<0.01, vs. TG. Image J software was used for semi-quantitative analysis.HIF-1α为缺氧诱导因子，可反映肿瘤组织乏氧情况。由图2可见，干预前（D0），各组HIF-1α表达水平无明显差异（P>0.05）；干预后第3天（D3），第5天（D5）EATG组、BTG组HIF-1α表达水平低于TG组（P<0.01），EATG组与BTG组HIF-1α表达水平无明显差异（P>0.05）；干预后第5天（D5），EATG组与BTG组HIF-1α表达水平较第3天（D3）有所增加，但差异不显著（P>0.05）。
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图 2 围刺对肿瘤组织HIF-1α表达的影响。×200Figure 2. Effect of peritumoral electroacupuncture on the expression of HIF-1α in the tumor tissue. ×200The red fluorescence represents positive expression of HIF-1α and the blue fluorescence represents the nucleus. ** P<0.01, vs. TG.2.4 围刺对肿瘤微血管形态结构的影响
结合免疫荧光结果，我们进一步观察了干预后第3天肿瘤微血管的形态结构。HE染色显示各组肿瘤组织均可见微血管（图3）。采用扫描电镜观察肿瘤微血管形态发现，TG组新生血管管壁粗糙、有缺损、完整性差、管腔明显畸形，而EATG组和BTG组血管管壁完整性较好，管腔未出现明显变形（图4）。结果提示，围刺干预在一定程度上可改善肿瘤微血管形态和结构，使其形态结构趋于正常化。
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图 4 扫描电镜观察肿瘤微血管Figure 4. Observation of microvessels in the tumor tissue by scanning electron microscopeMagnification rates from left to right are ×1000, ×2000, and ×5000, with the arrows indicating the vascular wall.3. 讨论
血管正常化是促进肿瘤异常的血管向正常的血管转化的过程，其成为近年来肿瘤领域的研究热点[11-12]。相对于正常血管，肿瘤血管曲折迂回、基底膜松散、周细胞覆盖减少、血流灌注不足，并处于乏氧环境中。通过诱导肿瘤异常血管结构趋向正常化，以增加基底膜完整性、提高周细胞的覆盖水平、纠正失衡的微环境，以及改善血液循环水平，为药物进入肿瘤组织提供支持，从而可提高抗肿瘤效果[13]。围刺是指围病灶或围穴而刺的方法[14]，通常以施术部位为中心，进行多针单层或多层环状包围性针刺。针对肿瘤的围刺法可疏通经络，调节肿瘤局部经脉、络脉、浮络与皮部之间的联系[15]，其作用类似局部活血化瘀。研究表明，部分活血中药或中药有效成分可诱导肿瘤血管正常化，如当归可减少瘤内微血管密度，降低血管通透性，诱导肿瘤血管正常化[16]；丹参酮ⅡA促进血管周细胞生成，显著提高微血管壁完整性，抑制肿瘤新生血管，诱导血管正常化[17]。前期研究证实，围刺可增加肿瘤局部紫杉醇药物浓度，从而提高化疗药物抗肿瘤的效果[7]，但并不清楚围刺提高化疗药物效果是否与围刺诱导血管正常化有关。因此，本研究以4T1乳腺癌皮下移植瘤小鼠模型为研究对象，采用围刺治疗方式，探讨围刺诱导肿瘤微血管正常化的作用。
CD31为血小板-内皮细胞黏附分子，多表达于血管内皮细胞、血小板、白细胞，与血管形成密切相关，是内皮细胞常见标记物[18]。在乳腺癌组织中CD31显著上调，且CD31的高表达与肿瘤直径和TNM分期密切相关[19]。周细胞与内皮细胞构成血管壁，对血管具有稳定和支撑作用[20]。α-SMA表达于周细胞，但不表达于内皮细胞，可用α-SMA标记周细胞[21]。通过双荧光标记CD31/α-SMA观察微血管结构，评价肿瘤微血管密度和周细胞覆盖率[22-23]。本研究发现，电针围刺或小剂量贝伐单抗治疗后第3、5天肿瘤组织CD31的表达水平均明显下降，α-SMA表达水平显著增加，表明电针围刺和贝伐单抗均能降低微血管密度，促进周细胞的募集和覆盖，且该治疗作用具有一定的持续性效应，为课题组后期临床针药结合研究提供研究基础。
血管的结构异常引起血流紊乱、灌注不足，导致氧气无法正常供应，肿瘤局部微环境处于乏氧状态。HIF-1α是HIF-1的活性亚基，可反映肿瘤组织乏氧情况。在三阴性乳腺癌中，HIF-1α在癌组织的阳性率较癌旁组织显著增加，且与血管密度显著相关[24-25]。本研究发现，电针围刺、贝伐单抗治疗后第3、5天HIF-1α表达水平明显下降，表明电针围刺和贝伐单抗均可改善肿瘤乏氧状态。
血管功能的正常化依赖于血管结构的正常化。本研究进一步采用HE染色和扫描电镜观察肿瘤组织的微血管结构，发现电针围刺和贝伐单抗均可促进肿瘤微血管形成较完整的管壁，减少管腔畸形，从形态学上进一步验证电针围刺具有诱导肿瘤微血管正常化的作用。但本研究中电针围刺或小剂量贝伐单抗均未见明显抑瘤效应，这可能与电针围刺、贝伐单抗治疗频次少有关（仅治疗1次）。
以上研究表明电针围刺可通过降低微血管密度、促进周细胞覆盖以诱导肿瘤血管结构的正常化，并改善肿瘤组织乏氧状态，这将为后期探索电针围刺诱导血管正常化机制及其与化疗药物协同抗肿瘤研究提供重要依据。
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图 1 患者纳入排除及分析流程图
Figure 1. Flowchart of the patient inclusion and exclusion process
PBC: primary biliary cholangitis; TC: total cholesterol.
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图 2 ROC曲线分析
Figure 2. Analysis of ROC curves
The abbreviations are explained in the note to Table 1.
表 1 应答组与应答不佳组基线临床特征比较
Table 1 Comparison of baseline clinical characteristics of the responding and non-responding groups
Variable Responders (n=305) Nonresponders (n=207) P (Female/male)/case 268/37 183/24 0.854 Age/yr., $\bar x \pm s $ 53.13±11.24 52.57±10.09 0.566 TB/(μmol/L), median (IQR) 15.0 (8.9) 19.2 (19.9) 0.005 ALT/(IU/L), median (IQR) 45.0 (47.5) 68.0 (61.0) <0.001 AST/(IU/L), median (IQR) 48.0 (38.0) 73.0 (49.0) 0.003 ALB/(g/L), median (IQR) 45.2 (5.6) 43.7 (6.3) 0.012 GLB/(g/L), median (IQR) 32.7 (7.7) 33.6 (6.9) 0.375 ALP/(IU/L), median (IQR) 157 (132) 307 (243) <0.001 GGT/(IU/L), median (IQR) 145 (204) 310 (417) <0.001 TG/(mmol/L), median (IQR) 1.20 (0.64) 1.33 (0.85) 0.003 TC/(mmol/L), median (IQR) 4.83 (1.25) 5.93 (2.05) <0.001 HDL-C/(mmol/L), median (IQR) 1.57 (0.61) 1.76 (0.89) 0.004 LDL-C/(mmol/L), median (IQR) 2.61 (1.04) 3.06 (1.33) <0.001 PLT/(×109 L－1), median (IQR) 147 (109) 153 (100) 0.652 AMA (+)/case (%) 180 (59.0) 120 (57.9) 0.814 Cirrhosis/case (%) 79 (25.9) 45 (21.7) 0.281 Fib-4 (median [IQR]) 2.55 (3.49) 3.06 (3.17) 0.726 ABRI (median [IQR]) 0.99 (1.39) 1.38 (1.25) 0.782 TB: total bilirubin; ALT: alanine aminotransferase; AST: aspartate aminotransferase; ALB: albumin; GLB: globulin; ALP: alkaline phosphatase; GGT: gamma-glutamyl transferase; TG: triglyceride; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; PLT: platelet; AMA: anti-mitochondrial antibody; Fib-4: fibrosis score; APRI: aspartate aminotransferase/platelet ratio index. 
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表 2 影响UDCA应答的多因素logistic回归分析
Table 2 Logistic regression analysis of multiple factors affecting UDCA response
Parameter β SE P OR 95% CI TB/(μmol/L) −0.001 0.004 0.853 0.999 0.991-1.007 ALT/(IU/L) −0.002 0.004 0.634 0.998 0.990-1.006 AST/(IU/L) −0.002 0.005 0.611 0.998 0.998-0.993 ALB/(g/L) −0.041 0.017 0.015 0.960 0.929-0.992 ALP/(IU/L) 0.005 0.001 <0.001 1.005 1.003-1.006 GGT/(IU/L) <0.001 0.001 0.906 1.000 0.999-1.001 TG/(mmol/L) 0.069 0.160 0.667 1.071 0.783-1.465 TC/(mmol/L) 0.406 0.083 <0.001 1.501 1.275-1.767 HDL-C/(mmol/L) 0.003 0.250 0.991 1.003 0.615-1.636 LDL-C/(mmol/L) −0.217 0.247 0.380 0.805 0.496-1.306 The abbreviations are explained in the note to Table 1. β: regression coefficient; SE: standard error; OR: odds ratio; CI: confidence interval.
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表 3 低TC组与高TC组临床特征比较
Table 3 Comparison of clinical features of the low TC and the high TC groups
Variable TC<5.415 mmol/L (n=308) TC≥5.415 mmol/L (n=204) P (Female/male)/case 270/38 181/23 0.716 Age/yr., $\bar x \pm s$ 53.2±11.4 52.3±9.6 0.328 TB/(μmol/L), median (IQR) 15.4 (10.7) 17.0 (16.4) 0.012 ALT/(IU/L), median (IQR) 45.0 (41.0) 70.5 (68.7) <0.001 AST/(IU/L), median (IQR) 51.0 (39.7) 71.5 (51.7) 0.011 ALB/(g/L), median (IQR) 44.6 (5.9) 44.4 (5.8) 0.889 GLB/(g/L), median (IQR) 33.1 (7.8) 32.9 (6.7) 0.736 ALP/(IU/L), median (IQR) 172.5 (149.0) 298.0 (252.2) <0.001 GGT/(IU/L), median (IQR) 145.0 (204.0) 336.5 (429.2) <0.001 TG/(mmol/L), median (IQR) 1.14 (0.60) 1.54 (0.93) <0.001 TC/(mmol/L), median (IQR) 4.55 (1.08) 6.29 (1.63) <0.001 HDL-C/(mmol/L), median (IQR) 1.53 (0.61) 1.93 (0.96) <0.001 LDL-C/(mmol/L), median (IQR) 2.38 (0.85) 3.49 (1.09) <0.001 PLT/(×109 L－1), median (IQR) 136.0 (105.7) 171.5 (94.7) 0.001 AMA (+)/case (%) 184 (59.7) 116 (56.9) 0.518 Cirrhosis/case (%) 76 (24.7) 48 (23.5) 0.767 Fib-4 (median [IQR]) 2.94 (4.02) 2.55 (2.15) 0.259 ABRI (median [IQR]) 1.08 (1.49) 1.24 (1.27) 0.976 Response (+)/case (%) 233.0 (75.6) 72.0 (35.3) <0.010 The abbreviations are explained in the note to Table 1. Continuous variables are presented as the median (interquartile range) and categorical variables, percentages.
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表 4 低TC组与高TC组UK-PBC评分比较
Table 4 Comparison of the UK-PBC risk scores between low TC and the high TC groups
Predicted time UK-PBC risk score, median (IQR) P TC<5.415 (mmol/L)
(n=308)TC≥5.415 (mmol/L)
(n=204)5 years 0.011 (0.017) 0.014 (0.028) <0.01 10 years 0.036 (0.057) 0.046 (0.090) <0.01 15 years 0.066 (0.102) 0.084 (0.158) <0.01 Data are expressed as the median (interquartile range).
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表 5 低TC组与高TC组GLOBE评分比较
Table 5 Comparison of the GLOBE scores between the low TC and the high TC groups
Predicted time GLOBE score, median (IQR) P TC<5.415 (mmol/L)
(n=308)TC≥5.415 (mmol/L)
(n=204)3 years 0.960 (0.058) 0.959 (0.053) 0.315 5 years 0.930 (0.100) 0.928 (0.092) 0.320 10 years 0.824 (0.233) 0.819 (0.211) 0.320 15 years 0.707 (0.350) 0.699 (0.312) 0.312 Data are presented as the median (interquartile range).
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