The Enhanced Liver Fibrosis (ELF) Panel: Analyte Stability Under Common Sample Storage Conditions Used in Clinical Practice

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1 The Enhanced Liver Fibrosis (ELF) Panel: Analyte Stability Under Common Sample Storage Conditions Used in Clinical Practice Oliver J. Kennedy, 1 Julie Parkes, 1,2 Sudeep Tanwar, 2 Paul Trembling, 2 and William M. Rosenberg 2,3 * Background: The enhanced liver fibrosis (ELF) blood test has recently been recommended by the National Institute for Health and Care Excellence to test for advanced fibrosis in nonalcoholic fatty liver disease. The ELF test involves calculating a score from the concentrations of serum biomarkers: tissue inhibitor of matrix metalloproteinases-1 (TIMP-1), aminoterminal propeptide of procollagen type III (P3NP), and hyaluronic acid (HA). Blood samples for the ELF score are often acquired in primary care and may be stored before analysis. However, the effect of preanalytical storage on the ELF test is not known. Methods: We conducted experiments to assess the stabilities of the ELF score, P3NP, HA, and TIMP-1 under mediumto long-term storage at 80 C, repeated freeze-thawing, and refrigeration at 4 C for days. Results: Mean TIMP-1 concentrations increased during medium- to long-term storage (+16.5%) and refrigeration (+4.9%), but were stable during freeze-thawing. Mean P3NP concentrations were stable under medium- to long-term storage, but increased during refrigeration (+7.4%) and freeze-thawing (+9.3%). Mean HA concentrations decreased during medium- to long-term storage ( 12.3%) but were stable during refrigeration and freeze-thawing. Despite changes in biomarker concentrations, the changes in the mean ELF score were not clinically significant and not >0.1 U (0.7%). Conclusions: The ELF score was stable, with no clinically significant changes under common storage conditions. These findings demonstrate that the ELF score is robust in situations where analysis may be delayed. IMPACT STATEMENT The ELF test is an accurate test for liver fibrosis. Knowledge of sample stability during handling and storage is important. We investigated the effect of time, temperature, and storage conditions on test performance. ELF test results are remarkably consistent despite prolonged storage at a range of temperatures and after freeze-thaw cycles. The effects of perturbations of individual components of the test and their influence on the ELF result are explained. Users of the ELF test can have confidence that prolonged sample storage, variation in temperature, and thawing cycles before testing will have little influence on ELF test reliability. 1 Primary Care & Population Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK; 2 Institute for Liver and Digestive Health, Institute of Immunity and Transplantation, Division of Medicine, University College London, Royal Free Hospital, London, UK; 3 iqur Limited, London, UK. *Address correspondence to this author at: University College London, U3/262 UCL Medical School, Royal Free Hospital, Pond Street, London NW3 2PF, UK. Fax ; w.rosenberg@ucl.ac.uk. May : JALM 1 Copyright 2017 by American Association for Clinical Chemistry.

2 ELF Panel: Sample Stability Under Storage Hepatic fibrosis most commonly results from chronic high alcohol consumption, hepatitis B or C virus infection, and nonalcoholic fatty liver disease (NAFLD) 4 often associated with diabetes and metabolic syndrome (1). Fibrosis is usually asymptomatic but may eventually lead to cirrhosis. The end stage of cirrhosis is potentially fatal because of the complications of portal hypertension, such as hepatorenal syndrome, variceal bleeding, and spontaneous bacterial peritonitis. Cirrhosis is also the most important risk factor for hepatocellular carcinoma (2), a leading cause of cancer deaths worldwide with a 5-year survival of <20% (3). The best-established predictor for adverse clinical outcomes in patients with fibrosis is histological stage (4). Traditionally, histological stage has been determined by assessment of liver tissue obtained by needle biopsy. However, there are significant disadvantages to needle biopsy, such as sampling error, the need for specialist interpretation, interobserver variability in assessment, and potentially serious side effects for patients including pain and hemorrhage (5). In view of these disadvantages, noninvasive methods of assessing liver fibrosis, including blood tests and transient elastography, have generated recent interest. Noninvasive blood tests include measuring direct serum biomarkers involved in liver fibrogenesis or extracellular matrix degradation, all of which are indicators of liver fibrosis. The enhanced liver fibrosis (ELF) test is a wellestablished noninvasive test for liver fibrosis that includes serum biomarkers: tissue inhibitor of matrix metalloproteinases-1 (TIMP-1), aminoterminal propeptide of procollagen type III (P3NP), and hyaluronic acid (HA) (6). The concentrations of these biomarkers are used to calculate an ELF score, which indicates the histological stage of fibrosis (7) and is superior to biopsy for predicting clinical outcomes (8). The ELF score also has utility as a sensitive screening test for advanced fibrosis and cirrhosis (8), and its use may reduce the need for biopsy by over 60% (9). A major advantage of the ELF score over biopsy is that it is calculated from a simple blood sample, which can be collected in any healthcare setting (e.g., primary care). However, the sample must be analyzed in a clinical laboratory. Thus, samples may undergo a period of storage before analysis. It is known that storage, such as refrigeration and freezing, can affect the concentrations of serum biomarkers (10), but it is not known if and to what extend the ELF score is affected by these preanalytical factors. Preanalytical sample stability of sera used for ELF testing is particularly pertinent following the publication of National Institute for Health and Care Excellence (NICE) guidance number 49 (11), which recommends the use of the ELF test to stage liver fibrosis in NAFLD with many patients being seen in primary care and variable delays before sample analysis. Our study is the first to investigate the storage stability of samples used to measure the ELF score and its constituent biomarkers, TIMP-1, P3NP, and HA, which informs the implementation of the ELF score in clinical practice. MATERIALS AND METHODS Collection of samples and measurement of biomarker stabilities We conducted experiments to assess the stabilities of the ELF score and its constituent serum biomarkers P3NP, HA, and TIMP-1 under storage conditions commonly found in clinical practice: medium- to long-term storage at 80 C (experiment 1), freeze-thawing (experiment 2), and DOI: /jalm American Association for Clinical Chemistry 4 Nonstandard abbreviations: NAFLD, nonalcoholic fatty liver disease; ELF, enhanced liver fibrosis; TIMP-1, tissue inhibitor of matrix metalloproteinases-1; P3NP, aminoterminal propeptide of procollagen type III; HA, hyaluronic acid; NICE, National Institute for Health and Care Excellence. 2 JALM :06 May 2017

3 ELF Panel: Sample Stability Under Storage ARTICLE refrigeration at 4 C for days (experiment 3). The subjects were healthy males and females aged years and had fasted for at least 2himmediately before the samples were drawn. Blood samples were collected into gold top Vacutainer tubes (with gel for serum separation and a clot activator) by venipuncture of the antecubital fossa. The blood samples were allowed to clot adequately before centrifugation at 1500 g for 10 min at room temperature. The sera were collected and aliquoted into sterile polypropylene tubes for analysis, either immediately or after a period of storage, as described below. The sera were analyzed in accordance with the manufacturer's instructions using an Advia Centaur XP (SiemensHealthcare), and ELF scores were calculated using Eq. 1 below: ELF score ln [HA] ln[p3np] ln [TIMP1] (1) In the first experiment, sample stability under medium- to long-term storage at 80 C was assessed using samples collected from 10 subjects. Biomarker concentrations and ELF scores were determined at baseline by analyzing triplicate aliquots of serum from each participant immediately after collection. The remaining aliquots were stored at 80 C for a mean duration of 220 days (maximum: 498 days; minimum: 8 days). After thawing the sera, each aliquot was separated into test samples and biomarker concentrations, and ELF scores were measured in triplicate for each aliquot. The mean of the triplicates was compared against the mean at baseline for each biomarker and the ELF score. In the second experiment, the stability of biomarker/elf samples subjected to repeated freezethawing was investigated using sera collected and aliquoted from patients. We measured baseline biomarker concentrations and ELF scores by analyzing aliquots immediately after collection. The remaining aliquots were subjected to cycles, in which they were frozen for2hat 80 C, thawed to room temperature for 3 h, and then frozen again for a minimum of 2 h at 80 C. This cycle was repeated on consecutive days, with the first freeze-thaw cycle occurring on the day of sample collection. Biomarker concentrations and ELF scores were measured after each cycle in duplicate. The mean biomarker concentrations and ELF score were compared after each cycle against baseline. In the third experiment, biomarker/elf stabilities were assessed for samples refrigerated at 4 C for days using sera collected and aliquoted from patients and initially stored at 80 C. After thawing all the samples, biomarker concentrations and ELF scores were measured in duplicate on day 0 (i.e., baseline) and then again after 1, 2, and 4 days. The mean biomarker concentrations and ELF score on each day were compared to those measured on day 0. Statistical analysis and model For each experiment, absolute and percentage differences in the mean biomarker concentrations and ELF scores relative to baseline were calculated. Statistical significance of the differences was tested using a paired t-test (-tailed) and values of <0.05 were deemed to be statistically significant. A change in the ELF score of >0.5 was determined to be clinically significant. This result corresponds approximately to a 50% increase in the risk of a liver-related outcome, such as decompensated cirrhosis or hepatocellular cancer. It also approximates a quarter of the range of the moderate fibrosis category specified by the manufacturer (Siemens) in their instructions for use of the ELF test (<7.7 is none to mild, 7.7 to <9.8 is moderate, and 9.8 is severe ). In NICE guidance number 49, a diagnosis of advanced fibrosis is based on an ELF score of or above. Hence, our threshold for clinical significance is conservative given the range of possible ELF scores and the variations that would generally be required to result in a change in diagnosis or management. May : JALM 3

4 ELF Panel: Sample Stability Under Storage Table 1. Mean biomarker concentrations and ELF scores (SDs) from 10 patients before and after a periods of medium- to long-term storage at 80 C (mean: 220 days; maximum: 498 days; minimum: 8 days). a Initial After storage Score/concentration (SD), ng/ml Score/concentration (SD), ng/ml Difference (%) ELF 9.0 (1.1) 9.0 (1.0) 0.0 (0.0) TIMP (151.6) (176.6) 44.1 (16.5) P3NP 7.1 (3.6) 7.7 (3.3) 0.6 (8.7) HA 52.2 (39.6) 45.8 (39.0) 6.4 ( 12.3) a The absolute and percentage differences are relative to baseline. Statistically significant differences are in bold. The theoretical effect of biomarker instability was investigated using a computer model. This step involved first computing an ELF score from the mean concentrations of P3NP, HA, and TIMP-1 across all subjects participating in the experiments above. The absolute changes in the ELF score were then modeled while varying the concentrations of each individual biomarker up to ±20% but keeping the concentrations of the other biomarkers stable. To simulate an unlikely worst-case scenario, changes in the ELF score were modeled while varying the concentrations of all biomarkers simultaneously in the same direction and by the same magnitude (±20%). All analyses were performed in Mathematica (Version 10, Wolfram Research). Experiment 2 Table 2 shows mean biomarker concentrations and ELF scores before and after freeze-thaw cycles (experiment 2). Fig. 2 illustrates the percentage differences compared to baseline. The mean ELF score and concentrations of TIMP-1 and HA were not significantly different after any of the freezethaw cycles. The mean concentrations of P3NP were significantly different after the first (+9.3%) and third freeze-thaw cycle (+6.8), but not after the second. The maximum change in an individual's ELF score after the third cycle compared to baseline was 0.2 U, while the minimum was <0.1 U. RESULTS Experiment 1 Table 1 and Fig. 1 show mean serum concentrations of P3NP, HA, TIMP-1, and ELF scores before and after medium- to long-term storage at 80 C (experiment 1). The mean ELF score and concentration of P3NP after medium- to long-term storage were not significantly different from baseline. However, the mean concentrations of TIMP-1 and HA differed significantly by 16.5% and 12.3%, respectively. The maximum change in an individual's ELF score from baseline was 0.2 U, while the minimum was <0.1 U. Fig. 1. Percentage changes in the mean ELF score and concentrations of TIMP-1, P3NP, and HA in samples from patients before and after storage at 80 C. The mean ELF varied by <0.1%. 4 JALM :06 May 2017

5 ELF Panel: Sample Stability Under Storage ARTICLE Table 2. Mean biomarker concentrations and ELF scores (SDs) from 5 patients before and after 3 freeze-thaw cycles. a Stability during freeze-thawing Initial First freeze-thaw Second freeze-thaw Third freeze-thaw ng/ml (SD) ELF 9.4 (1.3) 9.4 (1.3) 0.0 (0.0) 9.3 (1.3) 0.1 ( 0.9) 9.3 (1.3) 0.0 ( 0.4) TIMP (63.7) (52.1) 4.0 ( 1.7) (50.8) 9.9 ( 4.1) (47.1) 10.2 ( 4.2) P3NP 7.9 (2.7) 8.6 (2.8) 0.7 (9.3) 8.1 (2.6) 0.2 (2.7) 8.4 (2.7) 0.5 (6.8) HA (142.1) 99.9 (124.3) 10.9 ( 9.9) 95.8 (117.8) 15.1 ( 13.6) 98.2 (121.4) 12.6 ( 11.4) a The absolute and percentage differences are relative to baseline. Statistically significant differences are in bold. Fig. 2. Percentage changes in the mean ELF score and concentrations of TIMP-1, P3NP, and HA in samples from patients after freeze-thaw cycles. The ELF score was not significantly different from baseline after any of the cycles. Experiment 3 Table 3 shows mean biomarker concentrations and ELF scores over days refrigerated at 4 C (experiment 3). Fig. 3 illustrates the percentage changes compared to baseline. The mean ELF scores after 2 and 4 days were not significantly different from day 0. The mean ELF score after 1 day was significantly different, but the corresponding absolute difference was 0.1 U and therefore is not considered to be clinically relevant. The mean concentrations of TIMP-1 and P3NP were significantly different after 1 day, but not after 2 or 4 days. There was no statistically significant difference in mean HA on any of the days. On the fourth day of refrigeration, the maximum change in an individual's ELF score compared to baseline was 0.2 U, while the minimum was <0.1 U. Fig. 4 illustrates modeled changes in the ELF score with changing concentrations of P3NP, HA, and TIMP-1. The ELF score was more sensitive to reductions in biomarker concentrations than increases. With isolated reductions of 20% in concentrations of P3NP, HA, and TIMP-1 (i.e., with one May : JALM 5

6 ELF Panel: Sample Stability Under Storage Table 3. Mean biomarker concentrations and ELF scores (SDs) from 6 patients over 4 days of refrigeration at 4 C. a Stability in a refrigerator at 4 C Day 0 After 1 day After 2 days After 4 days ng/ml (SD) ELF 9.7 (1.6) 9.8 (1.6) 0.1 (0.7) 9.7 (1.6) < 0.1 ( 0.1) 9.7 (1.6) <0.0 ( 0.5) TIMP (85.6) (83.1) 13.1 (4.9) (81.0) 2.4 ( 0.9) (94.6) 10.1 ( 3.8) P3NP 12.8 (10.6) 13.8 (11.3) 0.9 (7.4) 13.2 (10.7) 0.4 (3.2) 13.4 (11.0) 0.6 (4.7) HA (169.2) (168.5) <0.1 (<0.1) (162.2) 4.6 ( 3.7) (163.9) 5.4 ( 4.3) a The absolute and percentage differences are relative to baseline. Statistically significant differences are in bold. Fig. 3. Percentage change in the mean ELF score and concentrations of TIMP-1, P3NP, and HA in patients during days of refrigeration at 4 C. The ELF score was significantly different from baseline after 1 day, although the absolute difference was 0.1 U only. The ELF score was not significantly different after 3 or 4 days. biomarker varied while the others held constant), the modeled reductions in the ELF score were 0.2 U, 0.2 U, and 0.1 U, respectively. As such, the ELF score was most sensitive to changes in HA concentration and least sensitive to P3NP. As expected, Fig. 4. Modeled changes in any ELF score with isolated and simultaneous changes in biomarkers HA, P3NP, or TIMP-1 of up to ±20%. With isolated changes, the ELF score did not vary by >0.2 U. Even with simultaneous changes in the same direction, the ELF score varied by 0.4 U only. 6 JALM :06 May 2017

7 ELF Panel: Sample Stability Under Storage ARTICLE the ELF score was more sensitive to simultaneous changes in all biomarkers. However, even with simultaneous reductions of 20%, the absolute change in the ELF score was 0.4 U only and, as such, was not clinically significant. The absolute change in the ELF score per percentage change in biomarker concentrations was the same irrespective of the initial biomarker concentrations (and, thus, ELF score) used in the model. DISCUSSION This is the first study to investigate the extent to which the ELF score and its constituent serum biomarkers (TIMP-1, P3NP, and HA) are affected by storage conditions commonly found in clinical practice. In all our experiments, there were statistically significant changes in at least one biomarker concentration. However, the changes did not follow a consistent pattern (e.g., P3NP during the freeze-thaw cycles, as is explained below) and, thus, may have been statistical or methodological effects rather than real changes in concentrations. Notwithstanding, in our experiments, the mean TIMP-1 concentrations increased with statistical significance after medium- to long-term storage at 80 C and after 1 day of refrigeration, but were stable across freeze-thaw cycles. Previous studies evaluating the stability of TIMP-1 in sera are inconsistent, with increasing (12), decreasing (13), and unchanged (14) concentrations being reported. The reason for this inconsistency is unclear and should be investigated in future studies. In our experiments, P3NP was stable under medium- to long-term storage conditions, but increased with statistical significance after the first and third, but not second, freeze-thaw cycle and during one of the days refrigerated. As mentioned above, the variation did not follow a clear pattern and, thus, may not have represented real changes in concentrations. This interpretation (i.e., that the changes were not real) is supported by a previous study (15), which reported no significant differences in P3NP concentrations after months at 20 C, freeze-thaw cycle, and day refrigeration. In our experiments, HA concentrations were stable during freeze-thawing and refrigeration but decreased during medium- to long-term storage. We are unaware of any previous studies reporting the stability of HA under similar conditions. Notwithstanding the biomarkers' variable stability, we demonstrated for the first time that the ELF score was stable within the bounds of clinical significance during medium- to long-term storage in a freezer at 80 C, freeze-thaw cycles, and after refrigeration over days at 4 C. The mean ELF score did not vary by >0.1 U (0.7%) in any of our experiments. The individuals' ELF scores varied by a maximum of 0.2. Given that these changes are not clinically significant, our findings provide further supportive evidence for the use of the ELF score, such as that set out in the NICE clinical guidance on screening in NAFLD. In addition, our results provide reassurance where the ELF algorithm has been applied to measurements from nonproprietary/non-siemens P3NP/TIMP/HA assays, which may not have been stability tested (16). Using a computer model, we showed that a typical ELF score would not vary by >0.5 U even with simultaneous increases or decreases in biomarker concentrations of up to ±20%. The stability of the ELF score in the face of changes in the concentrations of the constituent biomarkers is explained with reference to the ELF algorithm shown in Eq. 1. The ELF score varies according to the logarithm of each biomarker concentration multiplied by a number smaller than 1 (e.g.,.751 ln[p3np]). For example, a 10-fold increase in the concentration of a biomarker would increase the ELF score by <1 U. The reciprocal changes in HA decreasing and TIMP-1 increasing with storage may diminish any effects of medium- to long-term storage on the calculated ELF score. There are limitations to our findings that may restrict their applicability to clinical practice. First, we did not investigate stability at room tempera- May : JALM 7

8 ELF Panel: Sample Stability Under Storage ture, over long periods of refrigeration (e.g., 7 days and above), or for more than freeze-thaw cycles. Determining stability under those conditions would provide further useful evidence for designing a protocol for preanalytical processing. In addition, we only tested sample stability during refrigeration after the samples had first been frozen for a period at 80 C and then thawed. It is possible that this prior freezethawing affected subsequent stability during refrigeration. However, there is no clear mechanism by which this would occur, especially since the biomarkers/elf score are relatively unaffected by freeze-thawing, as is demonstrated by the results from experiment 1. In conclusion, the ELF score is stable under common storage conditions, such as medium- to longterm at 80 C, at least freeze-thaw cycles, and after storage at 4 C in refrigeration for days. Our findings are important, since they demonstrate the preanalytical stability of serum samples used for ELF testing and the capacity of the ELF test to accommodate changes in the constituent biomarkers attributable to the ELF algorithm. These properties mean that the ELF test is suitably robust for reliable use in situations where there may be delays in the analysis of samples with storage at a range of temperatures such as in primary care settings and when samples are analyzed in batches after storage as in clinical trials. Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 4 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; (c) final approval of the published article; and (d) agreement to be accountable for all aspects of the article thus ensuring that questions related to the accuracy or integrity of any part of the article are appropriately investigated and resolved. Authors Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Employment or Leadership: W.M. Rosenberg, iqur Limited. Consultant or Advisory Role: W.M. Rosenberg, Siemens Healthineers. Stock Ownership: W.M. Rosenberg, iqur Limited. Honoraria: W.M. Rosenberg, Siemens Healthineers. Research Funding: This work was funded by iqur Limited and supported by researchers at the National Institute for Health Research Biomedical Research Centre University College London Hospitals. Expert Testimony: None declared. Patents: None declared. Role of Sponsor: No sponsor was declared. Acknowledgments: W.M. Rosenberg is a National Institute for Health Research (NIHR) Senior Investigator and a member of the Leeds NIHR Diagnostic Evidence Cooperative. REFERENCES 1. Friedman SL. Liver fibrosis from bench to bedside. J Hepatol 2003;38(Suppl 1):S El-Serag HB, Rudolph KL. Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology 2007;132: Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin 2011;61: Poynard T, Ratziu V, Benmanov Y, Di Martino V, Bedossa P, Opolon P. Fibrosis in patients with chronic hepatitis C: detection and significance. Semin Liver Dis 2000;20: Myers RP, Fong A, Shaheen AA. Utilization rates, complications and costs of percutaneous liver biopsy: a population-based study including 4275 biopsies. Liver Int 2008;28: Rosenberg WM, Voelker M, Thiel R, Becka M, Burt A, Schuppan D, et al. Serum markers detect the presence of liver fibrosis: a cohort study. Gastroenterology 2004; 127: Nobili V, Parkes J, Bottazzo G, Marcellini M, Cross R, Newman D, et al. Performance of ELF serum markers in predicting fibrosis stage in pediatric non-alcoholic fatty liver disease. Gastroenterology 2009;136: Parkes J, Roderick P, Harris S, Day C, Mutimer D, Collier J, et al. Enhanced liver fibrosis test can predict clinical outcomes in patients with chronic liver disease. Gut 2010;59: Cales P, Laine F, Boursier J, Deugnier Y, Moal V, Oberti F, et al. Comparison of blood tests for liver fibrosis specific or not to NAFLD. J Hepatol 2009;50: Lee JE, Kim SY, Shin SY. Effect of repeated freezing and thawing on biomarker stability in plasma and serum samples. Osong Public Health Res Perspect 2015;6: JALM :06 May 2017

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