Prediction of liver fibrosis and cirrhosis in chronic hepatitis B infection by serum proteomic fingerprinting: A pilot study

被引:97
作者
Poon, TCW
Hui, AY
Chan, HLY
Ang, IL
Chow, SM
Wong, N
Sung, JJY
机构
[1] Chinese Univ Hong Kong, Prince Wales Hosp, Dept Med & Therapeut, Shatin, Hong Kong, Peoples R China
[2] Chinese Univ Hong Kong, Prince Wales Hosp, Dept Anat & Cellular Pathol, Shatin, Hong Kong, Peoples R China
关键词
D O I
10.1373/clinchem.2004.041764
中图分类号
R446 [实验室诊断]; R-33 [实验医学、医学实验];
学科分类号
1001 ;
摘要
Background: Most noninvasive predictive models of liver fibrosis are complicated and have suboptimal sensitivity. This study was designed to identify serum proteomic signatures associated with liver fibrosis and to develop a proteome-based fingerprinting model for prediction of liver fibrosis. Methods: Serum proteins from 46 patients with chronic hepatitis B (CHB) were profiled quantitatively on surface-enhanced laser desorption/ionization (SELDI) ProteinChip arrays. The identified liver fibrosis-associated proteomic fingerprint was used to construct an artificial neural network (ANN) model that produced a fibrosis index with a range of 0-6. The clinical value of this index was evaluated by leave-one-out cross-validation. Results: Thirty SELDI proteomic features were significantly associated with the degree of fibrosis. Cross-validation showed that the ANN fibrosis indices derived from the proteomic fingerprint strongly correlated with Ishak scores (r = 0.831) and were significantly different among stages of fibrosis. ROC curve areas in predicting significant fibrosis (Ishak score :3) and cirrhosis (Ishak score greater than or equal to5) were 0.906 and 0.921, respectively. At 89% specificity, the sensitivity of the ANN fibrosis index in predicting fibrosis was 89%. The sensitivity for prediction increased with degree of fibrosis, achieving 100% for patients with Ishak scores >4. The accuracy for prediction of cirrhosis was also 89%. Inclusion of International Normalized Ratio, total protein, bilirubin, alanine transaminase, and hemoglobin in the ANN model improved the predictive power, giving accuracies >90% for the prediction of fibrosis and cirrhosis. Conclusions: A unique serum proteomic fingerprint is present in the sera of patients with fibrosis. An ANN fibrosis index derived from this fingerprint could differentiate between different stages of fibrosis and predict fibrosis and cirrhosis in CHB infection. (C) 2005 American Association for Clinical Chemistry.
引用
收藏
页码:328 / 335
页数:8
相关论文
共 31 条
[1]   Evaluation of liver fibrosis: A concise review [J].
Afdhal, NH ;
Nunes, D .
AMERICAN JOURNAL OF GASTROENTEROLOGY, 2004, 99 (06) :1160-1174
[2]  
[Anonymous], 1998, MMWR Recomm Rep, V47, P1
[3]   Genomic data sampling and its effect on classification performance assessment [J].
Azuaje, F .
BMC BIOINFORMATICS, 2003, 4 (1)
[4]   Sampling variability of liver fibrosis in chronic hepatitis C [J].
Bedossa, P ;
Dargère, D ;
Paradis, V .
HEPATOLOGY, 2003, 38 (06) :1449-1457
[5]   Hepatocellular carcinoma: Diagnosis and treatment [J].
Befeler, AS ;
Di Bisceglie, AM .
GASTROENTEROLOGY, 2002, 122 (06) :1609-1619
[6]   Analysis of serum proteomic patterns for early cancer diagnosis: Drawing attention to potential problems [J].
Diamandis, EP .
JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2004, 96 (05) :353-356
[7]   Point - Proteomic patterns in biological fluids: Do they represent the future of cancer diagnostics? [J].
Diamandis, EP .
CLINICAL CHEMISTRY, 2003, 49 (08) :1272-1275
[8]   The role of liver biopsy in chronic hepatitis C [J].
Dienstag, JL .
HEPATOLOGY, 2002, 36 (05) :S152-S160
[9]   Risk factors for the rising rates of primary liver cancer in the United States [J].
El-Serag, HB ;
Mason, AC .
ARCHIVES OF INTERNAL MEDICINE, 2000, 160 (21) :3227-3230
[10]   Identification of chronic hepatitis C patients without hepatic fibrosis by a simple predictive model [J].
Forns, X ;
Ampurdanès, S ;
Llovet, JM ;
Aponte, J ;
Quintó, L ;
Martínez-Bauer, E ;
Bruguera, M ;
Sánchez-Tapias, JM ;
Rodés, J .
HEPATOLOGY, 2002, 36 (04) :986-992