Abstract
目的 慢性乙型肝炎(CHB)患者进展期肝纤维化的发生,显著增加了肝硬化及肝癌风险,早期诊断是改善其预后的关键。基于此,构建血清Ⅲ型胶原N端前肽(PRO-C3)联合血小板计数(PLT)的模型,以期提升对CHB患者进展期肝纤维化的诊断效能。 方法 纳入2017年10月15日至2021年12月30日于南京大学医学院附属鼓楼医院及苏州市第五人民医院接受过肝脏活组织检查的CHB初治患者资料。使用logistic回归分析法分析CHB患者进展期肝纤维化的危险因素,并构建无创模型;采用受试者操作特征曲线、决策曲线对模型效能进行评估,DeLong检验用于评估各无创评分之间的受试者操作特征曲线下面积(AUC)是否有统计学意义。 结果 本研究共纳入324例患者资料,其中进展期肝纤维化患者为83例(25.6%)。多因素logistic回归分析结果显示,PRO-C3(比值比=1.04,P<0.01)与PLT(比值比=0.99,P=0.04)是CHB患者发生进展期肝纤维化的独立危险因素。基于PRO-C3联合PLT构建的进展期肝纤维化诊断模型在训练队列中的AUC为0.80[95%置信区间:0.74~0.85],其AUC显著高于纤维化4因子(0.67,95%置信区间:0.60~0.73,P<0.01)与天冬氨酸转氨酶与血小板比值指数(0.71,95%置信区间:0.65~0.77,P=0.02),且与上述无创评分的AUC比较,差异有统计学意义。此外,该联合模型在不同临床亚组,如性别、年龄、丙氨酸转氨酶水平、HBeAg状态及HBV DNA水平中诊断效能稳定(AUC:0.73~0.84)。在验证队列中,本联合模型在诊断CHB进展期肝纤维化的AUC为0.84(95%置信区间:0.75~0.91),在上述亚组中同样收获良好的诊断效能(AUC:0.78~0.94)。 结论 血清PRO-C3联合PLT构建的无创诊断模型,对CHB相关进展期肝纤维化具有良好的诊断价值,其效能优于纤维化4因子和天冬氨酸转氨酶与血小板比值指数等常用无创评分。该模型简便、可靠,为临床无创诊断CHB相关肝纤维化提供了新的临床工具。
Keywords: 慢性乙型肝炎, 无创性诊断, 肝纤维化, 血清Ⅲ型胶原N端前肽, 进展期纤维化
Abstract
Objective The development of advanced liver fibrosis in patients with chronic hepatitis B (CHB) significantly increases the risk of cirrhosis and liver cancer; therefore, early diagnosis is crucial for improving prognosis. Accordingly, this study established a diagnostic model combining serum N-terminal pro-peptide of type Ⅲ collagen (PRO-C3) and platelet count (PLT) to enhance the diagnostic performance for advanced liver fibrosis in CHB patients. Methods This study included CHB patients who had not received prior treatment and underwent liver biopsy at the Drum Tower Hospital affiliated with the Medical School of Nanjing University and Suzhou Fifth People's Hospital between October 15, 2017, and December 30 2021. Logistic regression analysis was used to identify risk factors for advanced liver fibrosis in patients with CHB and to establish a non-invasive model. The model's performance was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis, while the DeLong test was employed to assess whether differences in the areas under the receiver operating characteristic curves (AUCs) among the non-invasive scores were statistically significant. Results Data from a total of 324 patients were included in the study, of whom 83 patients (25.6%) had advanced liver fibrosis. Multivariate logistic regression analysis revealed that PRO-C3 (odds ratio=1.04, P<0.01) and PLT (odds ratio=0.99, P=0.04) were independent occurrence risk factors for advanced liver fibrosis in patients with CHB. The diagnostic model for advanced liver fibrosis based on PRO-C3 combined with PLT had an area under the receiver operating characteristic curve (AUC) of 0.80 (95% confidence interval [CI], 0.74-0.85) in the training cohort, which was significantly higher than that of the Fibrosis-4 index (FIB-4) (AUC, 0.67; 95%CI, 0.60-0.73; P<0.01) and the aspartate aminotransferase-to-platelet ratio index (APRI) (AUC, 0.71; 95%CI, 0.65-0.77; P=0.02). The differences in AUCs between the diagnostic model and the aforementioned non-invasive scores were statistically significant. Furthermore, the combined model demonstrated stable diagnostic performance across various clinical subgroups, including gender, age, alanine aminotransferase levels, HBeAg status, and HBV DNA levels (AUC: 0.73-0.84). The combined model and the aforementioned subgroups achieved favorable diagnostic performance in the validation cohort for advanced liver fibrosis in patients with CHB, with an AUC of 0.84 (95%CI, 0.75-0.91) and (AUC: 0.78-0.94), respectively. Conclusion The non-invasive diagnostic model established by combining serum PRO-C3 and PLT shows favorable diagnostic value for CHB-related advanced liver fibrosis, and its performance is superior to commonly used non-invasive scores such as the Fibrosis-4 index and the aspartate aminotransferase-to-platelet ratio index. This simple and reliable model may provide a new clinical tool for the non-invasive diagnosis of CHB-related liver fibrosis.
Keywords: Chronic hepatitis B, Non-invasive diagnosis, Liver fibrosis, N-terminal propeptide of type Ⅲ collagen, Advanced fibrosis
全球现存慢性乙型肝炎(chronic hepatitis B,CHB)患者2.54亿人,其中约有超过20%的患者合并进展期肝纤维化[1-3]。因此,尽早识别进展期肝纤维化对于改善患者预后影响重大。我国指南主要推荐使用肝脏硬度值(liver stiffness measurement,LSM)、天冬氨酸转氨酶与血小板比值指数(aspartate transaminase to platelet ratio index,APRI)、纤维化4因子(fibrosis 4,FIB-4)指数等标志物对CHB患者的肝纤维化严重程度进行无创评估[4]。基于CHB患者肝活组织检查队列的分析结果显示,LSM、FIB-4、APRI识别进展期肝纤维化的受试者操作特征曲线下面积(area under the curve,AUC)分别为0.767、0.753、0.613;识别肝硬化的AUC为0.786、0.763、0.607 [5-6]。尽管 LSM、FIB-4及APRI在肝纤维化评估中具有一定参考价值,但其诊断效能整体仍处于中等水平,尚难以满足精准分层与临床决策的需求。
血清Ⅲ型胶原N端前肽(N-terminal propeptide of type Ⅲ collagen,PRO-C3)是Ⅲ型前胶原蛋白分解产生的片段,主要用于反映肝脏内胶原合成的活跃程度,与肝纤维化的发生显著相关[7]。我们前期工作发现PRO-C3与CHB显著肝纤维化(S2~S4期)、进展期肝纤维化(S3~S4期)显著相关[8]。在此基础上,本研究拟以PRO-C3为核心指标,联合易于获取的临床参数,建立一种简便、稳定且具有良好推广价值的血清学无创模型,用于提升CHB相关进展期肝纤维化的诊断效能。
资料与方法
1. 研究人群:本研究纳入了2017年10月15日至2021年12月30日期间就诊于南京大学医学院附属鼓楼医院及苏州市第五人民医院的324例接受过肝活组织检查的CHB初治患者,其中南京大学医学院附属鼓楼医院的227例患者作为训练队列,苏州市第五人民医院的97例患者作为验证队列。患者纳入标准如下:(1)年龄≥18岁;(2)均已签署肝脏穿刺活组织检查知情同意书;(3)乙型肝炎病毒表面抗原(hepatitis B surface antigen,HBsAg)或乙型肝炎病毒脱氧核糖核酸(hepatitis B virus deoxyribonucleic acid,HBV DNA)阳性6个月以上或临床诊断HBV持续感染[9];(4)肝脏活组织检查在抗病毒治疗前进行并留存相应结果。排除标准包括:(1)年龄<18岁;(2)合并丙型肝炎病毒、丁型肝炎病毒、巨细胞病毒、EB病毒等病毒共感染;或合并药物性、自身免疫性、胆汁淤积性或遗传性肝病;(3)合并肝细胞癌或其他恶性肿瘤。
2. 研究数据评估及收集:收集所有患者的性别、年龄等一般临床特征,丙氨酸转氨酶(alanine transaminase,ALT)、天冬氨酸转氨酶(aspartate transaminase,AST)、γ-谷氨酰转移酶(gamma glutamyltransferase,GGT)、碱性磷酸酶(alkaline phosphatase,ALP)、血小板(platelet,PLT)计数、血红蛋白(hemoglobin,Hb)、总胆红素(total bilirubin,TBil)、HBeAg状态、HBV DNA等血清生物化学指标,APRI评分和FIB-4评分等数据[10]。
患者血清PRO-C3水平使用Nordic Bioscience公司酶联免疫吸附测定试剂盒(nordicPRO-C3™,96T)检测。按照说明书要求将生物素化抗原(1∶100)、辣根过氧化物酶偶联抗体(1∶100)、洗涤液(1∶50),血清样品(1∶1)稀释,对照品用0.5 mL蒸馏水溶解,标准品使用孵育缓冲液以1.5倍梯度稀释用于制备标准曲线。在链霉亲和素包被板孔中加生物素化抗原,于18~22 ℃孵育30 min后使用洗涤液洗涤5次。随后在待测定孔中加入标准品、血清样品、对照品,检测孔中加入稀释的辣根过氧化物酶偶联抗体,2~8 ℃振荡孵育20 h,洗涤后加四甲基联苯胺显色液避光孵育15 min,检测孔加100 μL 0.18 mol/L硫酸终止液,以酶标仪650 nm为参考、450 nm读取吸光度;以标准品吸光度和对应浓度拟合曲线,插值法计算样PRO-C3浓度,单位为ng/mL。本试剂盒由丹麦诺迪克生物科学公司赠送(非商用,仅供研究使用)。
本研究收集的肝组织病理学评分是由两家医院的病理科专家依照Scheuer's评分系统评估每一位患者的肝纤维化程度,Scheuer's评分系统将无纤维化定义为S0,汇管区扩大为S1,汇管区纤维化伴纤维化间隔形成为S2,纤维间隔伴小叶结构紊乱为S3,S4为可能或肯定的肝硬化。本研究将S3及以上级别(S3~S4)定义为进展期肝纤维化。
3. 统计学方法:采用SPSS软件(26.0版本)进行数据分析.计量资料的分布采用Kolmogorov-Smirnov检验进行评估,对于正态分布和非正态分布的数据,分别使用均值±标准差(
±s)或中位数及四分位数M(Q1,Q3)描述;计数资料使用频数及百分比描述。对于两组间的差异性分析,非正态分布者应用Mann-Whitney U检验,正态分布者应用t检验,分类变量用χ2检验明确组间差异。单因素及多因素logistic回归分析评估CHB患者发生进展期肝纤维化(S3~S4期)的危险因素并构建诊断模型。受试者操作特征(receiver operating characteristic,ROC)曲线、灵敏度、特异度、阳性预测值(positive predictive value,PPV)、阴性预测值(negative predictive value,NPV)用于评估诊断模型对进展期肝纤维化的识别能力。决策曲线分析(decision curve analysis,DCA)用于评估模型的临床净收益。DeLong检验用于评估各无创评分之间的AUC差异是否有统计学意义。此外,研究在不同性别、年龄(≥40岁)、ALT升高(>40 U/L)、HBeAg状态、高病毒载量(HBV DNA≥4 log10 IU/mL)组别的CHB患者中验证了诊断模型的诊断效能。所有分析均以P<0.05为差异有统计学意义。
结果
1. 队列基线特征:本研究纳入的324例CHB初治患者,男性206例(63.6%),女性118例(36.4%),年龄39.0(32.0,47.0)岁,S0~S2期患者242例(74.4%),S3~S4期患者83例(25.6%)。与S0~S2组患者相比,S3~S4期患者的血清PRO-C3水平[50.8(33.9,67.0) ng/mL]显著高于S0~S2期[19.5(12.1,35.7) ng/mL,P<0.01]。此外,S3~S4期患者的ALT、AST、GGT、ALP、TBil、FIB-4指数及APRI评分均显著升高,PLT水平显著降低(P<0.01);性别、年龄、HBeAg阳性率及HBV DNA载量在两组间差异无统计学意义(表1)。
表1.
324例患者总队列基本信息
| 人群特征 | 总队列(n=324) | S0~S2组(n=242) | S3~S4组(n=83) | P值 |
|---|---|---|---|---|
| 男性[n(%)] | 206(63.6) | 156(64.7) | 50(60.2) | 0.46 |
| 年龄(岁)a | 39.0(32.0,47.0) | 39.0(33.0,47.0) | 39.0(32.0,48.0) | 0.72 |
| ALT(U/L)a | 39.0(24.9,62.7) | 39.0(24.1,60.2) | 40.0(27.0,79.0) | <0.01 |
| AST(U/L)a | 26.0(20.0,37.8) | 24.0(20.0,33.0) | 32.0(25.0,48.0) | <0.01 |
| GGT(U/L)a | 28.3(17.0,42.2) | 26.0(16.2,40.8) | 36.0(22.0,64.0) | <0.01 |
| ALP(U/L)a | 63.2(49.6,79.9) | 61.3(47.1,88.1) | 72.0(57.0,94.0) | <0.01 |
| PLT(109/L)a | 166.5(136.0,208.8) | 177.0(146.0,217.0) | 143.0(109.0,177.0) | <0.01 |
| Hb(g/L)a | 146.0(132.3,158.0) | 145.0(131.0,156.0) | 150.0(137.0,164.0) | 0.04 |
| TBil(μmol/L)a | 12.7(9.2,17.2) | 11.9(8.7,16.4) | 14.6(11.4,18.7) | <0.01 |
| HBeAg阳性[n(%)] | 136(42.0) | 145(60.2) | 43(51.8) | 0.11 |
| HBV DNA (log10 IU/mL)a | 4.0(3.0,7.0) | 4.0(2.0,7.0) | 4.0(3.0,6.0) | 0.23 |
| PRO-C3(ng/mL)a | 27.4(13.2,48.4) | 19.5(12.1,35.7) | 50.8(33.9,67.0) | <0.01 |
| FIB-4指数a | 1.1(0.7,1.7) | 0.9(0.7,1.5) | 1.4(1.0,2.4) | <0.01 |
| APRI评分a | 0.4(0.3,0.7) | 0.3(0.2,0.5) | 0.7(0.4,0.9) | <0.01 |
| 肝纤维化程度[n(%)]a | - | |||
| S0~S2 | 241(74.4) | 242(100.0) | 0(0) | |
| S3~S4 | 83(25.6) | 0(0) | 83(100.0) | |
注:a 计量资料使用M(Q1,Q3)描述;P值为S0~S2组别与S3~S4组别间差异性比较的结果;ALT为丙氨酸转氨酶;AST为天冬氨酸转氨酶;GGT为γ-谷氨酰转移酶;ALP为碱性磷酸酶;PLT为血小板计数;Hb为血红蛋白;TBil为总胆红素;PRO-C3为Ⅲ型胶原N端前肽;FIB-4为纤维化-4因子;APRI为天冬氨酸转氨酶与血小板比值指数
2. 进展期肝纤维化危险因素分析:单因素logistic回归进行数据分析显示:GGT[比值比(odds ratio,OR)=1.02,95%置信区间(confidence interval,CI):1.01~1.02,P<0.01]、ALP(OR=1.02,95%CI:1.00~1.03,P<0.01)、PLT(OR=0.99,95%CI:0.98~1.00,P<0.01)及PRO-C3(OR=1.04,95%CI:1.03~1.06,P<0.01)均与进展期肝纤维化显著相关。将上述4个变量纳入多因素logistic回归分析,结果显示PLT(OR=0.99,95%CI:0.98~1.00,P=0.04)及PRO-C3(OR=1.04,95%CI:1.02~1.05,P<0.01)为CHB患者进展期肝纤维化的独立危险因素。基于PRO-C3和PLT构建的诊断模型为Logit(P)=ln[P/(1-P)]=-1.190+0.038×(PRO-C3)-0.007×(PLT)(表2)。
表2.
训练队列中CHB患者进展期肝纤维化的单因素及多因素logistic回归分析结果
| 变量 | 单因素分析 | 多因素分析 | ||
|---|---|---|---|---|
| OR(95%CI) | P值 | OR(95%CI) | P值 | |
| 年龄(岁) | 1.01(0.98~1.04) | 0.49 | ||
| 性别 | ||||
| 女性 | 参照组 | 0.21 | ||
| 男性 | 0.69(0.38~1.23) | |||
| HBeAg状态 | ||||
| 阴性 | 参照组 | 0.58 | ||
| 阳性 | 1.18(0.66~2.08) | |||
| HBV DNA(log10 IU/mL) | 1.04(0.93~1.16) | 0.49 | ||
| ALT(U/L) | 1.00(0.99~1.00) | 0.99 | ||
| AST(U/L) | 1.00(0.99~1.00) | 0.68 | ||
| GGT(U/L) | 1.02(1.01~1.02) | <0.01 | 1.01(1.00~1.02) | 0.10 |
| ALP(U/L) | 1.02(1.00~1.03) | <0.01 | 1.00(1.00~1.01) | 0.41 |
| PLT(109/L) | 0.99(0.98~1.00) | <0.01 | 0.99(0.98~1.00) | 0.04 |
| Hb(g/L) | 1.02(1.00~1.03) | 0.07 | ||
| TBil(μmol/L) | 1.00(0.98~1.02) | 0.83 | ||
| PRO-C3(ng/mL) | 1.04(1.03~1.06) | <0.01 | 1.04(1.02~1.05) | <0.01 |
注:CHB为慢性乙型肝炎;OR为比值比;95%CI为95%置信区间;ALT为丙氨酸转氨酶;AST为天冬氨酸转氨酶;GGT为γ-谷氨酰转移酶;ALP为碱性磷酸酶;PLT为血小板计数;Hb为血红蛋白;TBil为总胆红素;PRO-C3为Ⅲ型胶原N端前肽
3. PRO-C3联合PLT模型与其他无创血清学模型的诊断效能比较:训练队列的ROC曲线结果(图1A)显示,PRO-C3联合PLT、PRO-C3、FIB-4、APRI诊断进展期肝纤维化的AUC分别为:0.80(95%CI:0.74~0.85)、0.78(95%CI:0.72~0.83)、0.67(95%CI:0.60~0.73)、0.71(95%CI:0.65~0.77),且PRO-C3联合PLT模型的PPV(59.5%)及NPV(88.1%)均高于其他模型(表3)。DeLong检验显示PRO-C3联合PLT模型诊断进展期肝纤维化的AUC显著高于FIB-4(P<0.01)、APRI(P<0.02)。PRO-C3联合PLT模型在验证队列(图1B)中AUC为0.84(95%CI:0.75~0.91),同样高于其他模型。
图1. 不同模型诊断进展期肝纤维化的受试者操作特征曲线 3A为训练队列;3B为验证队列.

注:PRO-C3为Ⅲ型胶原N端前肽;PLT为血小板计数;FIB-4为纤维化4因子;APRI为天冬氨酸转氨酶与血小板比值指数
表3.
各模型诊断慢性乙型肝炎初治患者进展期肝纤维化的效能
| 诊断模型 | AUC | 95%CI | 截断值 | 灵敏度(%) | 准确度(%) |
阳性 预测值(%) |
阴性 预测值(%) |
DeLong检验 (P值)a |
|---|---|---|---|---|---|---|---|---|
| PRO-C3联合PLT | 0.80 | 0.74~0.85 | 0.30 | 74.63 | 78.75 | 59.52 | 88.11 | - |
| PRO-C3 | 0.78 | 0.72~0.83 | 35.70 | 76.12 | 72.50 | 53.68 | 87.88 | 0.17 |
| FIB-4 | 0.67 | 0.60~0.73 | 1.89 | 41.79 | 87.50 | 58.33 | 78.21 | <0.01 |
| APRI | 0.71 | 0.65~0.77 | 0.47 | 65.67 | 71.87 | 49.44 | 83.33 | 0.02 |
注:aDeLong检验用于评估PRO-C3联合PLT模型与其他诊断模型间AUC的差异;AUC为曲线下面积;CI为置信区间;PRO-C3为Ⅲ型胶原N端前肽;PLT为血小板计数;FIB-4为纤维化4因子;APRI为天冬氨酸转氨酶与血小板比值指数
DCA结果显示,在训练队列及验证队列中,PRO-C3联合PLT模型的净收益高于PRO-C3、FIB-4及APRI评分,提示其在肝纤维化临床决策中的应用价值更优(图2)。
图2. 不同模型诊断慢性乙型肝炎初治患者进展期纤维化的决策曲线 2A训练队列;2B为验证队列.

注:PRO-C3为Ⅲ型胶原N端前肽;PLT为血小板计数;FIB-4为纤维化4因子;APRI为天冬氨酸转氨酶与血小板比值指数;All为队列全部患者均接受肝纤维化进一步评估;None为队列全部患者均未接受肝纤维化进一步评估
4. PRO-C3联合PLT模型与LSM诊断效能比较:LSM是当前诊断肝纤维化最常用的影像手段之一,其诊断价值已得到广泛认可。为进一步探究PRO-C3联合PLT模型与LSM在诊断效能上的差异,本研究从总队列中筛选出167例有LSM数据的患者,运用ROC曲线对上述两种模型的效能进行了比较。结果显示,PRO-C3联合PLT诊断进展期肝纤维化的AUC为0.84(95%CI:0.74~0.91),LSM为0.71(95%CI:0.59~0.80)(图3)。
图3. PRO-C3联合PLT、LSM诊断进展期肝纤维化的ROC.

注:PRO-C3为Ⅲ型胶原N端前肽;PLT为血小板计数;LSM为肝脏硬度值;ROC为受试者操作特征曲线
5. PRO-C3联合PLT模型对不同亚组患者进展期肝纤维化的诊断效能:为了验证PRO-C3联合PLT模型对不同亚组CHB患者的进展期肝纤维化的诊断效能,在男性、女性、年龄<40岁、年龄>40岁、ALT正常、ALT>40 U/L、HBeAg阴性与阳性、HBV DNA≥4 log10 IU/mL及<4 log10 IU/mL的CHB患者中分别验证PRO-C3联合PLT模型对不同亚组CHB患者的进展期肝纤维化的诊断效能。结果显示,在训练队列(图4A)中PRO-C3联合PLT模型在所有亚组中的AUC均高于0.70,在HBV DNA<4 log10 IU/mL的患者中AUC可达0.84。在验证队列中,中PRO-C3联合PLT模型在所有亚组中的AUC均高于0.75,在HBeAg阳性的患者中AUC最高(0.94)(图4B)。
图4. PRO-C3联合PLT模型对不同亚组慢性乙型肝炎患者进展期肝纤维化的诊断效能 4A为训练队列;4B为验证队列.

注:ALT为丙氨酸转氨酶;AUC为曲线下面积
讨论
本研究结果显示PRO-C3及PLT是CHB患者发生进展期肝纤维化的危险因素,基于PRO-C3和PLT构建的诊断模型对进展期肝纤维化具有良好的效能(AUC=0.80),优于单独使用PRO-C3以及FIB-4、APRI等无创模型。
肝纤维化以细胞外基质过度积累为主要特征。在细胞外基质形成过程中,PRO-C3是一种由含血小板反应蛋白基序的解整合素样金属蛋白酶2释放的Ⅲ型胶原蛋白N端前肽,其血清学水平可间接反映肝纤维化进展,现已被诸多研究证实可作为诊断多种病因相关肝纤维化的关键血清标志物[11-13]。Tang等[14]在代谢相关脂肪性肝病的肝活组织检查队列中明确了PRO-C3在排除进展期肝纤维化中具有良好的准确性。在酒精性肝病中,PRO-C3在肝纤维化、肝脏相关事件等的发生中同样具有良好的诊断效力[15-16]。本研究进一步发现,在CHB患者中,血清PRO-C3水平是诊断进展期肝纤维化的独立预测因子。
PLT是人体外周血中关键的血细胞成分,其合成主要受肝脏合成的血小板生成素调节。对于肝纤维化患者而言,肝功能受损可导致血小板生成素合成减少,继发的门静脉高压促使脾脏淤血和脾功能亢进增强,多重机制共同导致了PLT数量的减少[17-18]。诸多临床研究认为PLT水平可间接反映肝纤维化的严重程度,在HBeAg阴性且ALT正常的CHB患者中,随着纤维化加重PLT逐渐下降,基于PLT构建的诊断模型[如血小板-门静脉宽度比(AUC=0.75)、血小板-脾脏厚度比(AUC=0.79)可有效评估早期进展期肝纤维化[19]。Daniels等[20]将PLT、PRO-C3和年龄、糖尿病患病情况联合构建的无创诊断模型ADAPT评分,在非酒精性脂肪性肝病患者的肝纤维化诊断中可显示出比单一PRO-C3更优的诊断效能(训练队列及验证队列AUC:0.86~0.87)。在酒精性肝病队列中,PRO-C3及ADAPT在检测晚期肝纤维化方面也具有较高的准确性,组合评分的诊断效力同样优于单一指标[16]。在CHB患者中,我们发现使用PRO-C3和PLT构建的联合模型(训练队列及验证队列AUC分别为0.80、0.84)在诊断进展期肝纤维化中的效能显著优于PRO-C3(训练队列及验证队列AUC分别为0.78、0.78),这与Fernández-Garibay等[18]在其他肝病中观察到的趋势一致。
除了优于传统的血清学诊断模型外,本模型与LSM相比,在诊断进展期肝纤维化中也展现出了良好的效能。对于医疗资源受限、难以开展影像学检查的地区,PRO-C3联合PLT可作为早期识别CHB进展期肝纤维化的重要替代手段。相较于影像学手段,本模型虽在即时反映肝纤维化的动态变化方面存在不足,但血清指标的检测不会因操作者经验不足、受试者肥胖、肋间隙狭窄等因素干扰[21],这些优势可保障诊断结果的稳定性。
本模型在诊断效能上存在优势,对于实现大规模临床推广仍存在部分局限性。PRO-C3在临床上并非常规检测项目,且诊断成本高于FIB-4等其他血清学模型。因此,临床实践中可采取分层应用策略,优先采用传统简易模型进行基层初筛,而对于需进一步明确诊断的患者,再使用本模型进行精准评估。此外,本研究样本数量有限,后续仍需在大样本、多中心、多病种的慢性肝病队列中不断验证和优化本模型的诊断效能。
综上所述,PRO-C3联合PLT构建的无创模型对CHB患者进展期肝纤维化具有良好的诊断效能。目前CHB相关指南已推荐采用无创血清学评分对患者肝纤维化进行筛查,本研究构建的联合模型可为该指南推荐提供一种新的选择。
利益冲突
所有作者声明不存在利益冲突
引用本文:
白雪, 朱莉, 郑明华, 等. 血清Ⅲ型胶原N端前肽联合血小板诊断慢性乙型肝炎相关肝纤维化的临床研究[J]. 中华肝脏病杂志, 2026, 34(9):878-885. DOI: 10.3760/cma.j.cn501113-20260130-00051.
Funding Statement
新发突发与重大传染病防控国家科技重大专项(2025ZD01906404);江苏省自然科学基金(BK20231118);沐新慢乙肝科研基金(MX202406,MX202581)
Prevention and Control of Emerging and Major Infectious Diseases -National Science and Technology Major Project (2025ZD01906404); Natural Science Foundation of Jiangsu Province (BK20231118); Muxin Scientific Research Foundation for Chronic Hepatitis B (MX202406, MX202581)
参考文献
- 1.World Health Organization, Guidelines for the prevention, diagnosis , care and treatment for people with chronic hepatitis B infection:policy brief [R]. Geneva: WHO, 2024. [PubMed] [Google Scholar]
- 2.Easterbrook PJ ,Luhmann N ,Bajis S ,et al. WHO 2024 hepatitis B guidelines:an opportunity to transform care[J]. Lancet Gastroenterol Hepatol, 2024,9(6):493-495. DOI: 10.1016/S2468-1253(24)00089-X. [DOI] [PubMed] [Google Scholar]
- 3.van VLM ,Patmore LA ,Feld JJ ,et al. Association of metabolic comorbidities with fibrosis severity and fibrosis regression in patients with chronic hepatitis B[J]. Clin Gastroenterol Hepatol, 2026,24(1):121-130.e12. DOI: 10.1016/j.cgh.2025.04.024. [DOI] [PubMed] [Google Scholar]
- 4.中华医学会肝病学分会 . 肝硬化临床诊治管理指南(2025 版)[J]. 中华肝脏病杂志, 2025,33(10):958-976. DOI: 10.3760/cma.j.cn501113-20250728-00298. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Fan R ,Li G ,Yu N ,et al. aMAP score and its combination with liver stiffness measurement accurately assess liver fibrosis in chronic hepatitis B patients[J]. Clin Gastroenterol Hepatol, 2023,21(12):3070-3079.e13. DOI: 10.1016/j.cgh.2023.03.005. [DOI] [PubMed] [Google Scholar]
- 6.Rui F ,Xu L ,Yeo YH ,et al. Machine learning-based models for advanced fibrosis and cirrhosis diagnosis in chronic hepatitis B patients with hepatic steatosis[J]. Clin Gastroenterol Hepatol, 2024,22 (11):2250-2260.e 12. DOI: 10.1016/j.cgh.2024.06.014. [DOI] [PubMed] [Google Scholar]
- 7.Hansen JF ,Juul NM ,Nyström K ,et al. PRO-C3:a new and more precise collagen marker for liver fibrosis in patients with chronic hepatitis C[J]. Scand J Gastroenterol, 2018,53(1):83-87. DOI: 10.1080/00365521.2017.1392596. [DOI] [PubMed] [Google Scholar]
- 8.Chen Q ,Zheng MH ,Zhu L ,et al. Superior diagnostic efficacy of n-terminal propeptide of type iii collagen and golgi protein 73 for detection of fibrosis in chronic hepatitis B patients[J]. Med Comm, 2025, 6(6):e70236. DOI: 10.1002/mco2.70236. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.中华医学会肝病学分会, 中华医学会感染病学分会 . 慢性乙型肝炎防治指南(2022年版)[J]. 中华肝脏病杂志, 2022, 30(12):1309-1331. DOI: 10.3760/cma.j.cn501113-20221204-00607. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Kim WR ,Berg T ,Asselah T ,et al. Evaluation of APRI and FIB-4 scoring systems for non-invasive assessment of hepatic fibrosis in chronic hepatitis B patients[J]. J Hepatol, 2016,64(4):773-780. DOI: 10.1016/j.jhep.2015.11.012. [DOI] [PubMed] [Google Scholar]
- 11.Caussy C ,Bhargava M ,Villesen IF ,et al. Collagen formation assessed by n-terminal propeptide of type 3 procollagen is a heritable trait and is associated with liver fibrosis assessed by magnetic resonance elastography[J]. Hepatology, 2019,70(1):127-141. DOI: 10.1002/hep.30610. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Karsdal MA ,Nielsen SH ,Leeming DJ ,et al. The good and the bad collagens of fibrosis-their role in signaling and organ function[J]. Adv Drug Deliv Rev, 2017,121:43-56. DOI: 10.1016/j.addr.2017.07.014. [DOI] [PubMed] [Google Scholar]
- 13.Genovese F ,Gonçalves I ,Holm Nielsen S ,et al. Plasma levels of PRO-C3, a type Ⅲ collagen synthesis marker, are associated with arterial stiffness and increased risk of cardiovascular death[J]. Atherosclerosis, 2024,388:117420. DOI: 10.1016/j.atherosclerosis.2023.117420. [DOI] [PubMed] [Google Scholar]
- 14.Tang LJ ,Ma HL ,Eslam M ,et al. Among simple non-invasive scores, Pro-C3 and ADAPT best exclude advanced fibrosis in Asian patients with MAFLD[J]. Metabolism, 2022,128:154958. DOI: 10.1016/j.metabol.2021.154958. [DOI] [PubMed] [Google Scholar]
- 15.Johansen S ,Israelsen M ,Villesen IF ,et al. Validation of scores of PRO-C3 to predict liver-related events in alcohol-related liver disease[J]. Liver Int,2023,43(7):1486-1496. DOI: 10.1111/liv.15595. [DOI] [PubMed] [Google Scholar]
- 16.Madsen BS ,Thiele M ,Detlefsen S ,et al. PRO-C3 and ADAPT algorithm accurately identify patients with advanced fibrosis due to alcohol-related liver disease[J]. Aliment Pharmacol Ther, 2021,54(5):699-708. DOI: 10.1111/apt.16513. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Peck-Radosavljevic M. Thrombocytopenia in chronic liver disease[J]. Liver Int, 2017, 37(6):778-793. DOI: 10.1111/liv.13317. [DOI] [PubMed] [Google Scholar]
- 18.Fernández-Garibay VM ,Ramírez-Mejia MM ,Ponciano-Rodriguez G ,et al. The mechanisms behind thrombocytopenia in patients with portal hypertension and chronic liver disease[J]. J Clin Transl Hepatol, 2025,13(11):986-991. DOI: 10.14218/jcth.2025.00279. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Feng M, Lei L, Xu J, et al. Platelet-to-Portal vein width ratio and platelet-to-spleen thickness ratio can be used to predict progressive liver fibrosis among patients with hbv infection with hbeag-negativity and a normal alt level[J]. Front Med,2022,9:837898. DOI: 10.3389/fmed.2022.837898. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Daniels SJ ,Leeming DJ ,Eslam M ,et al. ADAPT: an algorithm incorporating pro-c3 accurately identifies patients with nafld and advanced fibrosis[J]. Hepatology,2019,69(3):1075-1086. DOI: 10.1002/hep.30163. [DOI] [PubMed] [Google Scholar]
- 21.葛启超, 陆伦根. 肝纤维化的影像学评价:新技术的进步和挑战[J]. 中华肝脏病杂志, 2025,33(10):923-927. DOI: 10.3760/cma.j.cn501113-20250710-00272. [DOI] [PMC free article] [PubMed] [Google Scholar]
