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本帖最后由 StephenW 于 2011-4-8 20:28 编辑
Serum marker panelsSince present direct markers cannot satisfy yet the clinical need of measuring the fibrosis, an alternative approach turn out to be combining a number of serum markers to generate algorithms capable of evaluating fibrosis. A large number of panels have been studied by groups worldwide11–32 (Table 2).
Table 2. Studies of serum markers panels for assessment of liver fibrosis
Index, author, year, reference
| Patients (n) | CLD | Markers in panel | AUROC (T-V)† | - † The area under the receiver operating characteristic curves (AUROC) for the diagnosis of significant fibrosis (stage 2–4 by the METAVIR or Scheuer classification, 3–6 by the Ishak score). T-V, AUROC values of training group and validation group.
- ‡ ‡Differentiation cirrhosis from no cirrhosis.
- § Differentiation advanced fibrosis (Ishak 4–6) from mild to moderate fibrosis (Ishak 0–3).
- ¶ Differentiation advanced hepatic fibrosis (defined as F3–F4 by METAVIR) from milder (F0–F2).
A2M, α2-macroglobulin; AAR, AST/ALT ratio; ALP, alkaline phosphatase; ALT, alanine aminotransferase; apoA1, apolipoprotein A1; APRI, aspartate aminotransferase to platelet ration index; AST, aspartate aminotransferase; AUROC, area under the receiver operating characteristic curves; BMI, body mass index; CLD, chronic liver disease; GGT, γ-glutamyltransferase; HA, hyaluronic acid; HBV, hepatitis B virus; HCV, hepatitis C virus; NAFLD, Nonalcoholic fatty liver disease; HIV, human immunodeficiency virus; HOMA-IR, homeostasis model assessment insulin resistance (fast glucose × plasma gluc/22.5); Hpt, haptoglobin; INR, international normalized ratio; IV-7S, type IV collagen 7s domain; MMP-1, metalloproteinase 1; Mn-SOD, manganese superoxide dismutase; PCHE, pseudocholinesterase; PI, prothrombin index; PIIINP, N-terminal peptide of type β pro-collagen; PLT, platelet count; PT, prothrombin time; TB, total bilirubin; TC, total cholesterol; TG, triglycerides; TIMP-1, tissue inhibitor of metalloproteinase 1; β-NAG, N-acetyl β-glucosaminidase.
| AAR, Williams, 1988 | 177 | Mixed | AAR | n/a | PGA index, Poynard, 1991 | 624 | Alcohol | PT, GGT, apoA1 | n/a | PGAA index, Naveau, 1994 | 525 | Alcohol | PT, GGT, apoA1, A2M | n/a | CDS index, Bonacini, 1997 | 75 | HCV | PLT, AAR, PT | n/a | AP index, Poynard 1997 | 620 | HCV | Age, PLT | 0.763–0.690 | BAAT score, Ratziu 2000 | 93 | NAFLD | Age, BMI, ALT, TG | 0.84 | Fortunato, 2001 | 103 | HCV | Fibronectin, prothrombin, ALT, PCHE, Mn-SOD, β-NAG | n/a | Pohl, 2001 | 211 | HCV | AAR, PLT | n/a | FibroTest, Imbert-Bismut, 200111 | 339 | HCV | A2M, Hpt, GGT, ApoA1, bilirubin | 0.836–0.870 | Kaul, 200212 | 264 | HCV | PLT, AST, sex, spider nevi | n/a | Forns index, Forns, 200213 | 476 | HCV | Age, GGT, cholesterol, PLT | 0.86–0.81 | APRI, Wai, 200314 | 270 | HCV | AST, PLT | 0.80–0.88 | ELF-score, Rosenberg, 200415 | 1021 | Mixed | Age, HA, PIIINP, TIMP-1 | 0.804 | FIBROSpect II, Patel, 200416 | 696 | HCV | HA, TIMP-1, A2M | 0.831–0.823 | FPI, Sud, 200417 | 302 | HCV | Age, AST, TC, HOMA-IR, past alcohol intake | 0.84–0.77 | MP3, Leroy, 200418 | 194 | HCV | PIIINP, MMP-1 | 0.82 | HALT-C, Lok, 200519 | 1141 | HCV | PLT, AAR, INR | 0.78–0.81‡ | Hepascore, Adams, 200520 | 221 | HCV | Bilirubin, GGT, HA, A2M, age, sex | 0.85–0.82 | Fibrometer, Cales, 200521 | 383 | Mixed | PLT, PI, AST, A2M, HA, urea, age | 0.883–0.892 | SHASTA index, Kelleher, 200522 | 95 | HCV/HIV | HA,AST and albumin | 0.878 | Sakugawa, 200523 | 112 | NAFLD | IV-7S, HA | n/a | Hui, 200524 | 235 | HBV | BMI, PLT, albumin, TB, ALP | 0.803–0.765 | SLFG, Zeng, 200525 | 372 | HBV | A2M, age, GGT, HA | 0.84–0.77 | FIB-4, Sterling, 200626 | 832 | HCV/HIV | Age, AST, ALT, PLT | 0.765§ | Virahep-C, Fontana, 200627 | 399 | HCV | age, AST, ALP, PLT | 0.837–0.851 | Mohamadnejad, 200628 | 276 | HBV | HBV DNA levels, ALP, albumin, PLT, | 0.91–0.85 | FibroIndex, Koda, 200729 | 402 | HCV | PLT, AST, γ-globulin | 0.828–0.835 | Alsatie, 200730 | 286 | HCV | diabetes mellitus, PLT, AST, INR, bilirubin | 0.79–0.75¶ | Esmat, 200731 | 220 | HCV | HA, age | 0.84§ | NAFLD fibrosis score, Angulo, 200732 | 733 | NAFLD | Age, BMI, PLT, albumin, AAR, hyperglycemia | 0.88–0.82 |
These panels are mainly based on two kinds of markers, direct and indirect. Direct markers are those directly linked to the modifications in ECM metabolism, such as hyaluronic acid and PIIINP. Indirect markers include a broad range of blood tests which have no direct link with liver fibrosis. They reflect liver dysfunction or other phenomena caused by fibrosis rather than fibrosis per se. Generally speaking, indexes including direct markers, such as the Fibrometer, may perform with greater accuracy, but indexes composed by only indirect markers are effective as well, and are usually more useful because they are based on routine blood tests that are easy to be performed in a general laboratory.
The diagnostic value of the models was assessed by calculating the area under the receiver operating characteristic curves (AUROC). Most studies reported an AUROC > 0.80 in differentiating significant fibrosis (fibrosis spread out the portal tract with septa) from no/mild fibrosis (no fibrosis or portal fibrosis without septa). Improved performance with a higher AUROC value was shown in differentiating between no cirrhosis and cirrhosis. But it must be underlined that the AUROC values in Table 2 each came from differently designed studies and are not suitable for making a comparison. Some well designed validation studies were done in the last 2 years, which may give us more reliable results.33,34
There are still some limitations of these marker panels to be considered. First, the design of every study differed in population characteristics, patient selection, significant fibrosis prevalence, blood test inclusion, biochemical measurement and liver histological assessment, which resulted in various panels with different markers and parameters. The agreement among these indexes is poor and a validation study is needed to choose a proper panel and cut-off value for clinical use. Second, none of the studies controlled for the degree of necro-inflammatory activity, most of the panels include markers likely to reflect or be affected by inflammation in the liver, which is much more mobile than fibrosis stage. Third, the formulas can easily fail because many markers included will be influenced by extrahepatic diseases or conditions such as inflammation, hemolysis, cholestasis, hypercholesterolaemia and renal failure. Finally, few of the studies include treated patients. It is not clear whether these indexes are suitable for assessing treatment response. However, a few studies by Poynard et al. suggested that FibroTest (BioLiveScale, Angers, France) could also be used as surrogate markers of the histological impact of treatments in patients infected by HCV and HBV.35
These indexes, in their current form, are not able to give us the exact stage of fibrosis in most studies. Their main value is to reduce the need for a liver biopsy by distinguishing significant fibrosis from no/mild fibrosis, and showing the presence of cirrhosis. It does not seem appropriate to completely replace liver biopsy with serum marker panels at the present time, but it can be anticipated that these indexes will become very useful in the clinical management of CLD by offering an attractive alternative to liver biopsy, as they are non-invasive, convenient, and inexpensive, and may allow the dynamic assessment of fibrosis. Validation in larger cohorts of patients with different CLD is needed before an index is proposed for extensive clinical use.
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