Massimo Pinzani
Correspondence to
Professor Massimo Pinzani, Dipartimento di Medicina Interna, Center for Research, Higher Education and Transfer “DENOThe”, Università degli Studi di Firenze, Viale G.B. Morgagni, 85, Firenze, Florence 50134, Italy; m.pinzani@dmi.unifi.it
Published Online First 29 June 2010
The development of non-invasive methods, particularly serum markers and transient elastography, for the evaluation of fibrosis progression and their validation for use in clinical practice certainly represents a relevant advancement in hepatology. Although non-invasive methods were designed to predict the fibrotic stage of chronic liver diseases (CLDs) and, ultimately, replace liver biopsy in clinical practice, there is now a large consensus on the use of these methods as cross-sectional discriminators of three major stages: absence or very limited fibrosis, advanced fibrosis/cirrhosis and the stage in between these two extremes, often referred to as the ‘gray area’. Overall, the application of these methods, alone or in combination, reduces the number of liver biopsies by at least 50%.
Serum markers for the prediction of the stage of liver fibrosis are grouped in two categories: (a) ‘direct markers’ reflecting the shedding into the systemic circulation of peptides involved in the accumulation of fibrillar extracellular matrix (fibrogenesis); involved in its degradation (fibrolysis); or involved, more generally, in tissue inflammation, and (b) ‘indirect markers’ a mixture of common biochemical abnormalities found in CLDs and clinical parameters. The predictive ability of several possible combinations of these markers is enhanced by their inclusion in a mathematic algorithm. At present, most of the information on serum markers is associated with their diagnostic accuracy for a given fibrotic stage. As shown in figure 1, each individual marker included in the algorithms proposed so far coincides with a specific phase of disease progression. Accordingly, what becomes evident is that the wider the selection two or more markers (ie, ALT and platelet count), the lower will be the ability to differentiate between intermediate stages, which indeed remain a ‘gray area’. In addition, since the development of fibrosis and the underlying prevalent mechanism differs in different CLDs, the combination of different markers in a specific algorithm may be more efficient in predicting the fibrotic stage in one type of CLD and less efficient in another. These and other related problems indicate that further understanding is needed of both the limitations and the potential advantages of each method in a particular clinical setting. In addition and importantly, it is now mandatory to explore the value of serum markers beyond their cross-sectional ability and to understand whether or not they might be clinically useful as prognostic markers.
Figure 1
Relationship between biochemical parameters included in different diagnostic algorithms and different phases of disease progression in chronic liver diseases. F0–F4 refer to the METAVIR score for chronic hepatitis C.
The ‘Enhanced’ Liver Fibrosis (ELF) panel, once termed ‘European’, originated from a major effort of several European experts in hepatic fibrogenesis that led to a large multicentre study involving several European hospitals, mainly in the UK, the results of which were published in 2004. The study included more than 1000 patients with different CLDs, and the ELF panel was tested for its cross-sectional ability to detect the stage of fibrosis. A key finding of the original study was a higher sensitivity and negative predictive value for CLD characterised by initial sinusoidal fibrosis such as non-alcoholic steatohepatitis (NASH), post-transplant chronic HCV hepatitis and haemochromatosis. In retrospect, this is not surprising since the three markers included in the ELF panel—that is, hyaluronic acid (HA), the N-terminal pro-peptide of collagen type III and tissue inhibitor of metalloproteinase-1 (TIMP-1), are typical of ongoing fibrogenesis mostly at sinusoidal levels (capillarisation of sinusoids), as illustrated in figure 1. Accordingly, the ELF panel has so far been validated for detection of the stage of fibrosis in adult and paediatric cohorts of patients with non-alcoholic fatty liver disease (NAFLD)/NASH.
The ability of the ELF panel to predict clinical outcomes was reported in a retrospective study performed in a cohort of patients with primary biliary cirrhosis. The study showed that the prognostic performance of ELF was significantly better than the model for end-stage liver disease (MELD) or the Mayo Risk (R) score. In the paper by Parkes and coworkers published in this issue of Gut (in this issue), the performance of the ELF panel in predicting clinical outcomes was evaluated with a 7-year follow-up of part of the original cohort encompassing patients with CLDs of a range of causes. The authors report that ELF was at least accurate as liver biopsy in predicting liver-related outcomes. In particular, a one point increase in ELF in adjusted models was associated with a twofold increase in the risk of a liver-related outcome.
The results of this study add to the scarce documentation on the ability of serum markers to function as prognostic indicators. Promising results derived from studies that evaluated the performance of the Fibrotest panel (FT) in predicting clinical outcomes in chronic hepatitis C, chronic hepatitis B and alcoholic liver disease.8–10 In these studies, FT performed significantly better than histology and other panels, particularly APRI and the Forns indexes. In a recently published study, Nunes and coworkers showed that serum markers such as HA, the APRI index, Fib-4, and YKL-40 can individually predict liver-related mortality independently of Child–Pugh and MELD scores in a population of HCV-infected patients with and without HIV co-infection.
The study by Parkes and coworkers is, however, the first study employing a panel of ‘direct’ markers with high levels of prospective patient follow-up for a sufficient number of years. In addition, it is the first study in a cohort of patients with CLDs of mixed aetiologies that is representative of much hepatology clinical practice. It is unfortunate that the authors of this work could not evaluate in parallel the performance of FT or other panels in the same cohort.
A key concept is emerging from these studies, even though they are few and characterised by intrinsic biases, particularly the lack of serial determinations over the period of observation. Serum markers and other non-invasive methodologies have the major limitation of being compared with an imperfect ‘gold standard’—that is, liver biopsy, when used for their cross-sectional ability to predict a certain fibrosis stage. However, their potential for predicting clinical outcomes seems to be better than that of liver biopsy probably because they reflect the ongoing pathophysiological processes and functions that a biopsy cannot detect. Thus it is important to consider carefully the individual parameters that are included in the panel under consideration, and particularly their pathophysiological and clinical meaning in the progression of a given fibrogenic CLD (figure 1). For example, on the one hand, inclusion of parameters indicative of hepatocellular failure or portal hypertension (ie, bilirubin, albumin, platelet count), which have themselves an immediate prognostic value, will add only limited value to the evaluation of clinical outcomes over several years. On the other hand, parameters reflecting phases of the fibrogenic process characterised by inflammation and active fibrogenesis (ie, HA, procollagens, metalloproteinases, TIMP-1, α2 macroglobulin, YLK-40), which are present in the whole range of disease pathophysiology, would probably perform better than ‘end-stage’ markers or very variable markers such as transaminases in evaluation of outcome.
Secondary, yet relevant, information emerging from the study of Parkes and coworkers is that the markers included in the ELF panel may overestimate mortality since they may reflect extrahepatic abnormal extracellular matrix turnover—that is, cardiovascular disease or other chronic inflammatory disorders. This is definitely a limitation that needs to be considered when dealing with aged populations where clinical outcomes become more frequent.
Footnotes
Competing interests None.
Provenance and peer review Commissioned; not externally peer reviewed.
References
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