中国肝脏病杂志(电子版)
中國肝髒病雜誌(電子版)
중국간장병잡지(전자판)
CHINESE JOURNAL OF LIVER DISEASES(ELECTRONIC VERSION)
2015年
1期
86-90
,共5页
魏梅娟%张纯瑜%肖子鸿%张小曼%何彩婷%魏开鹏%潘兴南
魏梅娟%張純瑜%肖子鴻%張小曼%何綵婷%魏開鵬%潘興南
위매연%장순유%초자홍%장소만%하채정%위개붕%반흥남
肝纤维化%二元Logistic回归%诊断模型
肝纖維化%二元Logistic迴歸%診斷模型
간섬유화%이원Logistic회귀%진단모형
Hepatic ifbrosis%Binary logistic regression%Diagnosis model
目的:构建以“肝纤四项”为变量的诊断模型,并探讨该诊断模型对明显肝纤维化的诊断效能。方法选取485例乙型病毒性肝炎患者,随机分为建模组324例和验证组161例,采用放射免疫分析法检测建模组和验证组患者血清中HA、LN、PⅢNP、CⅣ的含量;采用二元Logistic回归分析法,以肝组织活检作为“金标准”,构建以“肝纤四项”为变量的诊断模型;采用受试者工作特征(ROC)曲线,评价该诊断模型的诊断效能;用独立的验证组检验该模型的诊断效率。结果在二元Logistic回归分析中,确定了3项与研究终点相关的独立预测指标(HA、PⅢNP和CIV),由这3个指标建立了诊断模型FSM,FSM=1.56 ln(HA)+0.92 ln(PⅢNP)+1.90 ln(CⅣ)-8.18。FSM用于预测明显肝纤维化具有较高的诊断价值,ROC曲线下面积(AUC)为0.85。该模型应用于验证组,其诊断明显肝纤维化的AUC同样为0.85。根据ROC曲线,用于预测明显肝纤维化时,FSM取10.8为排除界值,敏感性和阴性预测值分别为88.31%和69%;取12.6为诊断界值,特异性和阳性预测值分别为93.55%和95.3%。比较FSM模型与HA的诊断效能,FSM模型的约登指数、阳性似然比、敏感性、特异性和准确率均高于HA,两者的AUC差异有统计学意义(Z =2.06,P <0.05)。结论本研究所建立的“肝纤四项”联合检测FSM模型,一定程度上提高了诊断效能。将该模型应用于预测明显肝纤维化,可使65%~70%无或轻度肝纤维化乙型肝炎患者避免“肝组织活检”。作为一种非创伤性检查手段,该模型可用于动态监测乙型肝炎患者肝纤维化进程。
目的:構建以“肝纖四項”為變量的診斷模型,併探討該診斷模型對明顯肝纖維化的診斷效能。方法選取485例乙型病毒性肝炎患者,隨機分為建模組324例和驗證組161例,採用放射免疫分析法檢測建模組和驗證組患者血清中HA、LN、PⅢNP、CⅣ的含量;採用二元Logistic迴歸分析法,以肝組織活檢作為“金標準”,構建以“肝纖四項”為變量的診斷模型;採用受試者工作特徵(ROC)麯線,評價該診斷模型的診斷效能;用獨立的驗證組檢驗該模型的診斷效率。結果在二元Logistic迴歸分析中,確定瞭3項與研究終點相關的獨立預測指標(HA、PⅢNP和CIV),由這3箇指標建立瞭診斷模型FSM,FSM=1.56 ln(HA)+0.92 ln(PⅢNP)+1.90 ln(CⅣ)-8.18。FSM用于預測明顯肝纖維化具有較高的診斷價值,ROC麯線下麵積(AUC)為0.85。該模型應用于驗證組,其診斷明顯肝纖維化的AUC同樣為0.85。根據ROC麯線,用于預測明顯肝纖維化時,FSM取10.8為排除界值,敏感性和陰性預測值分彆為88.31%和69%;取12.6為診斷界值,特異性和暘性預測值分彆為93.55%和95.3%。比較FSM模型與HA的診斷效能,FSM模型的約登指數、暘性似然比、敏感性、特異性和準確率均高于HA,兩者的AUC差異有統計學意義(Z =2.06,P <0.05)。結論本研究所建立的“肝纖四項”聯閤檢測FSM模型,一定程度上提高瞭診斷效能。將該模型應用于預測明顯肝纖維化,可使65%~70%無或輕度肝纖維化乙型肝炎患者避免“肝組織活檢”。作為一種非創傷性檢查手段,該模型可用于動態鑑測乙型肝炎患者肝纖維化進程。
목적:구건이“간섬사항”위변량적진단모형,병탐토해진단모형대명현간섬유화적진단효능。방법선취485례을형병독성간염환자,수궤분위건모조324례화험증조161례,채용방사면역분석법검측건모조화험증조환자혈청중HA、LN、PⅢNP、CⅣ적함량;채용이원Logistic회귀분석법,이간조직활검작위“금표준”,구건이“간섬사항”위변량적진단모형;채용수시자공작특정(ROC)곡선,평개해진단모형적진단효능;용독립적험증조검험해모형적진단효솔。결과재이원Logistic회귀분석중,학정료3항여연구종점상관적독립예측지표(HA、PⅢNP화CIV),유저3개지표건립료진단모형FSM,FSM=1.56 ln(HA)+0.92 ln(PⅢNP)+1.90 ln(CⅣ)-8.18。FSM용우예측명현간섬유화구유교고적진단개치,ROC곡선하면적(AUC)위0.85。해모형응용우험증조,기진단명현간섬유화적AUC동양위0.85。근거ROC곡선,용우예측명현간섬유화시,FSM취10.8위배제계치,민감성화음성예측치분별위88.31%화69%;취12.6위진단계치,특이성화양성예측치분별위93.55%화95.3%。비교FSM모형여HA적진단효능,FSM모형적약등지수、양성사연비、민감성、특이성화준학솔균고우HA,량자적AUC차이유통계학의의(Z =2.06,P <0.05)。결론본연구소건립적“간섬사항”연합검측FSM모형,일정정도상제고료진단효능。장해모형응용우예측명현간섬유화,가사65%~70%무혹경도간섬유화을형간염환자피면“간조직활검”。작위일충비창상성검사수단,해모형가용우동태감측을형간염환자간섬유화진정。
ObjectiveTo establish a diagnosis model combining four serum markers of hepatic ifbrosis (HA, LN,PⅢNP,CⅣ) and assess the diagnostic performance of model aimed to discriminate between patients with and without signiifcant hepatic ifbrosis in patients with hepatitis B.Methods Total of485 patients with hepatitis B were randomly divided into an estimation group (324 cases) and a validation group (161 cases). The serum levels of HA, LN, PⅢNP and CⅣ were measured by radiommunoassay in all patients and liver biopsy was used as the gold standard. A binary logistic regression model was established combining four serum markers and applied to the validation group to test its accuracy. The diagnostic value of the model was assessed by the receiver operating characteristic (ROC) curves.ResultsBinary logistic regression identiifed HA, PⅢNP and CⅣ as independent predictors of ifbrosis. We constructed a model named FSM combining HA, PⅢNP and CⅣ that proved useful to identify patients with or without significant hepatic fibrosis in patients with hepatitis B. FSM=1.56 ×ln(HA)+0.92 ×ln(PⅢNP)+1.9 ×ln(CⅣ)-8.18. The area under the ROC curve (AUC) was 0.85 for predicting signiifcant ifbrosis. In validation group, the AUC was also 0.85 for predicting significant fibrosis. Using optimized cutoff values, the sensitivity and negative predictive value of predicting the absence of significant fibrosis (FSM<10.8) were 88.31% and 69%,while the speciifcity and positive predictive value of predicting the presence of signiifcant ifbrosis (FSM≥12.6) were 93.55% and 95.3%. Comparing the FSM diagnostic model and HA, the Youden’s index, positive likelihood ratio, sensitivity, speciifcity and accuracy of FSM model were higher than those of HA, and AUC had signiifcant difference between the two (Z=2.06,P<0.05).ConclusionsThe FSM model established in this study improved the diagnostic performance. It can make the 65%-70% patients without signiifcant hepatic ifbrosis to avoid “liver biopsy”. As a noninvasive method, it can be employed for monitoring the progression of hepatic ifbrosis.