Leon A. Adams, Richard K. Sterlinga
Accurate identification of liver disease severity and fibrosis stage is paramount in the management of those with chronic liver disease. In the past, this was often done by liver biopsy. However, due to it’s invasiveness and risks of bleeding, pain, and sampling error, non-invasive assessment of liver disease has gained increasing attention over the last decade. Non-invasive tests can be divided into serum tests and imaging tests. Although standard “liver function” tests, such as alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are inaccurate when used alone, several models have been developed that use them in combination with other markers of advanced liver disease, such as platelet count. Of those models that utilize routine, readily available tests, the AST-Platelet Ratio Index (APRI) and FIB-4 have gained the most attention[
[1]x[1]Shaheen, A.A. and Myers, R.P. Diagnostic accuracy of the aspartate aminotransferase-to-platelet ratio index for the prediction of hepatitis C-related fibrosis: a systematic review. Hepatology. 2007; 46: 912–921
Crossref | PubMed | Scopus (244)See all References,
[2]x[2]Sterling, R.K., Lissen, E., Clumeck, N., Sola, R., Correa, M.C., Montaner, J. et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology. 2006; 43: 1317–1325
Crossref | PubMed | Scopus (707)See all References]. Both APRI and FIB-4 have high specificity and negative predictive value’s (NPV) for advanced fibrosis or cirrhosis[
[1]x[1]Shaheen, A.A. and Myers, R.P. Diagnostic accuracy of the aspartate aminotransferase-to-platelet ratio index for the prediction of hepatitis C-related fibrosis: a systematic review. Hepatology. 2007; 46: 912–921
Crossref | PubMed | Scopus (244)See all References,
[2]x[2]Sterling, R.K., Lissen, E., Clumeck, N., Sola, R., Correa, M.C., Montaner, J. et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology. 2006; 43: 1317–1325
Crossref | PubMed | Scopus (707)See all References]. However, both have only moderate positive predictive values (PPV) and many patients fall in between the upper and lower cut-offs giving an indeterminate result. More complex serum panels have been developed including Fibrosure/Fibrotest[
3x[3]Imbert-Bismut, F., Ratziu, V., Pieroni, L., Charlotte, F., Benhamou, Y., and Poynard, T. Biochemical markers of liver fibrosis in patients with hepatitis C virus infection: a prospective study. The Lancet. 2001; 357: 1069–1075
Abstract | Full Text | Full Text PDF | PubMed | Scopus (1101)See all References]
[3] and Fibrometer[
4x[4]Cales, P., Boursier, J., Ducancelle, A., Oberti, F., Hubert, I., Hunault, G. et al. Improved fibrosis staging by elastometry and blood test in chronic hepatitis C. Liver Int. 2014; 34: 907–917
Crossref | PubMed | Scopus (8)See all References]
[4], which may offer additional accuracy compared to APRI or FIB-4 but have extra cost. In addition, the alternative non-invasive imaging tests, such as vibration controlled transient elastrography (VCTE)[
5x[5]Sandrin, L., Fourquet, B., Hasquenoph, J.M., Yon, S., Fournier, C., Mal, F. et al. Transient elastography: a new noninvasive method for assessment of hepatic fibrosis. Ultrasound Med Biol. 2003; 29: 1705–1713
Abstract | Full Text | Full Text PDF | PubMed | Scopus (1349)See all References]
[5] or magnetic resonance elastrography (MRE)[
6x[6]Wang, Q.B., Zhu, H., Liu, H.L., and Zhang, B. Performance of magnetic resonance elastography and diffusion-weighted imaging for the staging of hepatic fibrosis: A meta-analysis. Hepatology. 2012; 56: 239–247
Crossref | PubMed | Scopus (91)See all References]
[6] are generally only available in specialized centers, leaving many with chronic liver disease inadequately assessed. Because one serum or imaging test alone does not provide 100% sensitivity and specificity, there has been an attempt to combine tests, either performed together or sequentially[
[4]x[4]Cales, P., Boursier, J., Ducancelle, A., Oberti, F., Hubert, I., Hunault, G. et al. Improved fibrosis staging by elastometry and blood test in chronic hepatitis C. Liver Int. 2014; 34: 907–917
Crossref | PubMed | Scopus (8)See all References,
[7]x[7]Petta, S., Vanni, E., Bugianesi, E., Di Marco, V., Camma, C., Cabibi, D. et al. The combination of liver stiffness measurement and NAFLD fibrosis score improves the noninvasive diagnostic accuracy for severe liver fibrosis in patients with nonalcoholic fatty liver disease. Liver Int. 2015; 35: 1566–1573
Crossref | PubMed | Scopus (15)See all References,
[8]x[8]Sebastiani, G., Halfon, P., Castera, L., Pol, S., Thomas, D.L., Mangia, A. et al. SAFE biopsy: a validated method for large-scale staging of liver fibrosis in chronic hepatitis C. Hepatology. 2009; 49: 1821–1827
Crossref | PubMed | Scopus (124)See all References,
[9]x[9]Wong, G.L., Chan, H.L., Choi, P.C., Chan, A.W., Yu, Z., Lai, J.W. et al. Non-invasive algorithm of enhanced liver fibrosis and liver stiffness measurement with transient elastography for advanced liver fibrosis in chronic hepatitis B. Aliment Pharmacol Ther. 2014; 39: 197–208
Crossref | PubMed | Scopus (20)See all References,
[10]x[10]Wong, G.L., Wong, V.W., Choi, P.C., Chan, A.W., and Chan, H.L. Development of a non-invasive algorithm with transient elastography (Fibroscan) and serum test formula for advanced liver fibrosis in chronic hepatitis B. Aliment Pharmacol Ther. 2010; 31: 1095–1103
Crossref | PubMed | Scopus (70)See all References,
[11]x[11]Zarski, J.P., Sturm, N., Guechot, J., Paris, A., Zafrani, E.S., Asselah, T. et al. Comparison of nine blood tests and transient elastography for liver fibrosis in chronic hepatitis C: the ANRS HCEP-23 study. J Hepatol. 2012; 56: 55–62
Abstract | Full Text | Full Text PDF | PubMed | Scopus (85)See all References,
[12]x[12]Demir, M., Lang, S., Nierhoff, D., Drebber, U., Hardt, A., Wedemeyer, I. et al. Stepwise combination of simple noninvasive fibrosis scoring systems increases diagnostic accuracy in nonalcoholic fatty liver disease. J Clin Gastroenterol. 2013; 47: 719–726
Crossref | PubMed | Scopus (9)See all References,
[13]x[13]Bourliere, M., Penaranda, G., Ouzan, D., Renou, C., Botta-Fridlund, D., Tran, A. et al. Optimized stepwise combination algorithms of non-invasive liver fibrosis scores including Hepascore in hepatitis C virus patients. Aliment Pharmacol Ther. 2008; 28: 458–467
Crossref | PubMed | Scopus (37)See all References,
[14]x[14]Castera, L., Sebastiani, G., Le Bail, B., de Ledinghen, V., Couzigou, P., and Alberti, A. Prospective comparison of two algorithms combining non-invasive methods for staging liver fibrosis in chronic hepatitis C. J Hepatol. 2010; 52: 191–198
Abstract | Full Text | Full Text PDF | PubMed | Scopus (128)See all References,
[15]x[15]Boursier, J., Vergniol, J., Sawadogo, A., Dakka, T., Michalak, S., Gallois, Y. et al. The combination of a blood test and Fibroscan improves the non-invasive diagnosis of liver fibrosis. Liver Int. 2009; 29: 1507–1515
Crossref | PubMed | Scopus (66)See all References]. Thus, the rationale for the study by Boursier and colleagues published in the current issue of the
Journal of Hepatology was to develop such a test as part of an algorithm to more accurately and easily identify advanced liver disease[
16x[16]Boursier J, de Ledinghen V, Leroy V, Anty R, Francque S, Salmon D, et al. A stepwise algorithm using a at-a-glance first-line test for the non-invasive diagnosis of advanced liver fibrosis and cirrhosis. Journal of Hepatology 2017;Epub ahead of print.See all References]
[16].
To that goal, the study aimed to develop and validate a stepwise algorithm that could be easily used by all providers to facilitate detection of advanced fibrosis in those with chronic liver disease. The cohort studied consisted of 3754 subjects with chronic liver disease who had undergone liver biopsy and VCTE, who were divided 2:1 into a derivation and validation set. They initially evaluated the utility of both APRI and FIB-4 as an initial screening test. Because FIB-4 outperformed APRI (higher sensitivity), they used it to compare to their new “first line test” which included age, gender, gamma-GT (GGT), AST, platelet count, and prothrombin time (PT). Each of these variables was assigned a number (0-4 depending on the variable and cut off) in the “
easy
LIver
Fibrosis
Test (eLIFT), with a score of at least 8 providing 80% sensitivity for advanced fibrosis. In a core group of 1946 subjects, they found that while FIB-4 and eLIFT had similar sensitivity (77-78%), eLIFT had higher specificity (91%), NPV (79%), and PPV (91%) with fewer false positive results than FIB-4, especially in those over age 60. They concluded that eLIFT was better than FIB-4 as a general screening test.
Subsequently, they determined what should be the “second line test” by comparing APRI, FIB-4, liver stiffness by VCTE, and Fibrometer (with or without VCTE) and found that Fibrometer
VCTE had the highest number of biopsies avoided (81%). A new algorithm was proposed with eLIFT as the initial screening test followed by Fibrometer
VCTE in those with an eLIFT score ≥ 8 for confirmation. Using this two-step strategy, 46% of patients (33% with eLIFT score <8 and 14% with eLIFT ≥ 8 but Fibrometer
VCTE <0.384) would not need to see a specialist thus avoiding liver biopsy or additional testing. This two-step approach found that 34% had advanced fibrosis (eLIFT >8 and Fibrometer
VCTE ≥ 0.715) leaving only 19% with an indeterminate result that might go on to liver biopsy. This combined strategy worked better than FIB-4 or Fibrometer
VCTE alone in identifying those with advanced fibrosis. Finally, they followed 1275 patients longitudinally (median follow-up 2.9 years) to determine if the eLIFT-Fibrometer
VCTE strategy could predict liver-related and all-cause mortality. Although eLIFT and FIB-4 had similar performance for all-cause mortality, Fibrometer
VCTE had the best performance for predicting liver-related mortality.
This study has several strengths; the large patient population enabled comparison of several methods of fibrosis assessment and detected relatively small differences in test performance. Furthermore, the proposed algorithm was accurate across a wide spectrum liver disease increasing applicability and attractiveness to implement in the community. In addition, eLIFT and Fibrometer
VCTE were demonstrated to be prognostic of liver related outcomes, re-enforcing the appropriateness to use them as tests to guide patient management. Nevertheless, the eLIFT test utilizes some serum tests that may not be routinely ordered by community physicians, such as prothrombin time, which in itself may suffer inter-laboratory variability. In addition, the use of AST and GGT in the eLIFT algorithm, resulted in a reduction in specificity in the setting of alcoholic liver disease. Nevertheless, this was resolved when combined with the Fibrometer
VCTE. The Fibrometer
VCTE was developed using the M probe, which provides higher values than the XL probe and has a lower success rate in obesity, limiting applicability in this population. For these reasons, independent validation will be important to confirm the accuracy of the eLIFT-FM
VCTE algorithm.
Lastly, the study population was not identified from the general population, and so caution should be exercised in trying to extrapolate this algorithm to screen for fibrosis in the general population.
Combining non-invasive algorithms is an attractive way of increasing diagnostic accuracy for liver fibrosis, however uncertainty exists on the best way to combine tests and which tests to use. For example, tests may be used concurrently with discordant results leading to a diagnostic biopsy. Alternatively two modalities may be combined into one diagnostic formula, or thirdly, tests may be used sequentially, with the first being a screening test and the second used following an indeterminate screen or as a confirmatory test for a positive screening test. The approach by Boursier utilizes a combination of firstly, a two-step approach using eLIFT as a screening test and Fibrometer
VCTE as the confirmatory test, which in itself combines VCTE and a serum test[
16x[16]Boursier J, de Ledinghen V, Leroy V, Anty R, Francque S, Salmon D, et al. A stepwise algorithm using a at-a-glance first-line test for the non-invasive diagnosis of advanced liver fibrosis and cirrhosis. Journal of Hepatology 2017;Epub ahead of print.See all References]
[16]. Thus, this approach requires three non-invasive tests to be performed, adding to the complexity and cost.
In addition to the current study, a range of alternative combination strategies have been examined (outlined in
Table 1Table 1), primarily among patients with chronic hepatitis C (CHC)[
[7]x[7]Petta, S., Vanni, E., Bugianesi, E., Di Marco, V., Camma, C., Cabibi, D. et al. The combination of liver stiffness measurement and NAFLD fibrosis score improves the noninvasive diagnostic accuracy for severe liver fibrosis in patients with nonalcoholic fatty liver disease. Liver Int. 2015; 35: 1566–1573
Crossref | PubMed | Scopus (15)See all References,
[8]x[8]Sebastiani, G., Halfon, P., Castera, L., Pol, S., Thomas, D.L., Mangia, A. et al. SAFE biopsy: a validated method for large-scale staging of liver fibrosis in chronic hepatitis C. Hepatology. 2009; 49: 1821–1827
Crossref | PubMed | Scopus (124)See all References,
[9]x[9]Wong, G.L., Chan, H.L., Choi, P.C., Chan, A.W., Yu, Z., Lai, J.W. et al. Non-invasive algorithm of enhanced liver fibrosis and liver stiffness measurement with transient elastography for advanced liver fibrosis in chronic hepatitis B. Aliment Pharmacol Ther. 2014; 39: 197–208
Crossref | PubMed | Scopus (20)See all References,
[14]x[14]Castera, L., Sebastiani, G., Le Bail, B., de Ledinghen, V., Couzigou, P., and Alberti, A. Prospective comparison of two algorithms combining non-invasive methods for staging liver fibrosis in chronic hepatitis C. J Hepatol. 2010; 52: 191–198
Abstract | Full Text | Full Text PDF | PubMed | Scopus (128)See all References,
[15]x[15]Boursier, J., Vergniol, J., Sawadogo, A., Dakka, T., Michalak, S., Gallois, Y. et al. The combination of a blood test and Fibroscan improves the non-invasive diagnosis of liver fibrosis. Liver Int. 2009; 29: 1507–1515
Crossref | PubMed | Scopus (66)See all References,
[16]x[16]Boursier J, de Ledinghen V, Leroy V, Anty R, Francque S, Salmon D, et al. A stepwise algorithm using a at-a-glance first-line test for the non-invasive diagnosis of advanced liver fibrosis and cirrhosis. Journal of Hepatology 2017;Epub ahead of print.See all References,
[17]x[17]Sebastiani, G., Halfon, P., Castera, L., Mangia, A., Di Marco, V., Pirisi, M. et al. Comparison of three algorithms of non-invasive markers of fibrosis in chronic hepatitis C. Aliment Pharmacol Ther. 2012; 35: 92–104
Crossref | PubMed | Scopus (29)See all References,
[18]x[18]Boursier, J., de Ledinghen, V., Zarski, J.P., Fouchard-Hubert, I., Gallois, Y., Oberti, F. et al. Comparison of eight diagnostic algorithms for liver fibrosis in hepatitis C: new algorithms are more precise and entirely noninvasive. Hepatology. 2012; 55: 58–67
Crossref | PubMed | Scopus (63)See all References,
[19]x[19]Crisan, D., Radu, C., Lupsor, M., Sparchez, Z., Grigorescu, M.D., and Grigorescu, M. Two or more synchronous combination of noninvasive tests to increase accuracy of liver fibrosis assessement in chronic hepatitis C; results from a cohort of 446 patients. Hepat Mon. 2012; 12: 177–184
Crossref | PubMedSee all References]. These have included the SAFE algorithm which sequentially combines APRI and Fibrotest[
8x[8]Sebastiani, G., Halfon, P., Castera, L., Pol, S., Thomas, D.L., Mangia, A. et al. SAFE biopsy: a validated method for large-scale staging of liver fibrosis in chronic hepatitis C. Hepatology. 2009; 49: 1821–1827
Crossref | PubMed | Scopus (124)See all References]
[8], sequential APRI and Hepascore[
13x[13]Bourliere, M., Penaranda, G., Ouzan, D., Renou, C., Botta-Fridlund, D., Tran, A. et al. Optimized stepwise combination algorithms of non-invasive liver fibrosis scores including Hepascore in hepatitis C virus patients. Aliment Pharmacol Ther. 2008; 28: 458–467
Crossref | PubMed | Scopus (37)See all References]
[13], concurrent Fibrotest and Fibroscan[
14x[14]Castera, L., Sebastiani, G., Le Bail, B., de Ledinghen, V., Couzigou, P., and Alberti, A. Prospective comparison of two algorithms combining non-invasive methods for staging liver fibrosis in chronic hepatitis C. J Hepatol. 2010; 52: 191–198
Abstract | Full Text | Full Text PDF | PubMed | Scopus (128)See all References]
[14] and combining Fibrometer and Fibroscan into one diagnostic model[
15x[15]Boursier, J., Vergniol, J., Sawadogo, A., Dakka, T., Michalak, S., Gallois, Y. et al. The combination of a blood test and Fibroscan improves the non-invasive diagnosis of liver fibrosis. Liver Int. 2009; 29: 1507–1515
Crossref | PubMed | Scopus (66)See all References]
[15]. In non-alcoholic fatty liver disease, concurrent Fibroscan and NAFLD Fibrosis Score and sequential FIB4 and BARD have been proposed[
[7]x[7]Petta, S., Vanni, E., Bugianesi, E., Di Marco, V., Camma, C., Cabibi, D. et al. The combination of liver stiffness measurement and NAFLD fibrosis score improves the noninvasive diagnostic accuracy for severe liver fibrosis in patients with nonalcoholic fatty liver disease. Liver Int. 2015; 35: 1566–1573
Crossref | PubMed | Scopus (15)See all References,
[12]x[12]Demir, M., Lang, S., Nierhoff, D., Drebber, U., Hardt, A., Wedemeyer, I. et al. Stepwise combination of simple noninvasive fibrosis scoring systems increases diagnostic accuracy in nonalcoholic fatty liver disease. J Clin Gastroenterol. 2013; 47: 719–726
Crossref | PubMed | Scopus (9)See all References], whilst in chronic hepatitis B, a combination of concurrent ALT with Fibroscan followed by the Enhanced Liver Fibrosis Score or the Forns index has been examined[
[9]x[9]Wong, G.L., Chan, H.L., Choi, P.C., Chan, A.W., Yu, Z., Lai, J.W. et al. Non-invasive algorithm of enhanced liver fibrosis and liver stiffness measurement with transient elastography for advanced liver fibrosis in chronic hepatitis B. Aliment Pharmacol Ther. 2014; 39: 197–208
Crossref | PubMed | Scopus (20)See all References,
[10]x[10]Wong, G.L., Wong, V.W., Choi, P.C., Chan, A.W., and Chan, H.L. Development of a non-invasive algorithm with transient elastography (Fibroscan) and serum test formula for advanced liver fibrosis in chronic hepatitis B. Aliment Pharmacol Ther. 2010; 31: 1095–1103
Crossref | PubMed | Scopus (70)See all References] Overall, these studies demonstrate an increase in diagnostic accuracy and higher predictive values with multiple non-invasive tests compared with single tests, particularly for the determination of moderate degrees of fibrosis (e.g. METAVIR F2+).
Table 1Cross-sectional studies (n>200) examining the accuracy of combination non-invasive fibrosis tests in the prediction of advanced fibrosis or cirrhosis.
Author | n | Liver Disease | Outcome | Algorithms | Diagnostic Accuracy | Sensitivity | Specificity | NPV | PPV |
Boursier 2009 | 332 | Mixed | Cirrhosis | APRI → Fibrotest | 80% | 44% | 93% | 81% | 71% |
| | | | Fibrotest + Fibroscan | 94% | 89% | 96% | 96% | 90% |
| | | | Fibrometer / Fibroscan | 91% | 75% | 97% | 91% | 91% |
Sebastiani 2009 | 2035 | HCV | Cirrhosis | APRI → Fibrotest | 92% | 90% | 93% | 56% | 99% |
Castera 2010 | 302 | HCV | Cirrhosis | APRI → Fibrotest | 89% | 86% | 90% | 94% | 78% |
| | | | Fibrotest + Fibroscan | 96% | 89% | 98% | 96% | 95% |
Sebastiani 2012 | 1013 | HCV | Cirrhosis | APRI → Fibrotest | 91% | 82% | 92% | 98% | 57% |
| | | | APRI + Fibrotest. | 94% | 73% | 97% | 96% | 73% |
Boursier 2012 | 1785 | HCV | Cirrhosis | APRI → Fibrotest | 89% | 61% | 93% | 95% | 56% |
| | | | Fibrotest + Fibroscan | 94% | 86% | 95% | 98% | 76% |
| | | | Fibrometer / Fibroscan | 87% | - | - | - | - |
Crisan 2012 | 446 | HCV | Advanced fibrosis | APRI + FIB4 + Fibrometer | 89% | 84% | 91% | 94% | 76% |
| | | | APRI + FIB4 + Fibrotest | 85% | 88% | 83% | 95% | 68% |
| | | | APRI + FIB4 + Fibroscan | 86% | 62% | 100% | 59% | 100% |
Wong 2014 | 323 | HBV | Advanced fibrosis | Fibroscan + ELF | - | 65-66% | 86-92% | 79-80% | 76-85% |
Petta 2014 | 321 | NAFLD | Advanced fibrosis | Fibroscan + FIB4 | - | 42-85% | 97-100% | 91-98% | 71-100% |
| | | | Fibroscan + NFS | - | 25-83% | 100% | 93-99% | 100% |
| | | | FIB4 + NFS | - | 14-35% | 100% | 88-91% | 100% |
Boursier 2017 | 1946 | Mixed | Advanced fibrosis | eLIFT → Fibrometer/Fibroscan | - | 78% | 91% | 79% | 91% |