Repeated FIB-4 measurements can help identify individuals at risk of severe liver disease
Open accessAbstract
BACKGROUND & AIMS: It is unclear whether the identification of individuals at risk of cirrhosis using non-invasive tests can be improved by repeated measurements. Herein, we tested whether repeated measurements of fibrosis-4 index (FIB-4) could improve the identification of individuals at risk of severe liver disease. METHODS: Data were derived from the population-based Swedish AMORIS cohort with baseline examinations from 1985-1996. FIB-4 was calculated at 2 time points within 5 years. Thereafter, we associated changes in FIB-4 with outcomes. Incident severe liver disease data was ascertained through linkage to Swedish national registers until 2011. Hazard ratios (HRs) and CIs for outcomes were calculated using Cox regression. RESULTS: Of 126,942 individuals with available FIB-4 data, 40,729 (32.1%) underwent a second test within 5 years (mean interval 2.4 years). During 613,376 person-years of follow-up, 581 severe liver disease events were documented (0.95/1,000 person-years). An increase of 1 unit in FIB-4 was associated with an elevated risk of severe liver disease (adjusted hazard ratio [aHR] 1.81; 95% CI 1.67-1.96). Transitioning from a low- or intermediate- to a high-risk group was associated with an increased risk of severe liver disease compared with those consistently in the low-risk group (aHR 7.99 and 8.64, respectively). A particularly increased risk of severe liver disease was found in individuals defined as high risk at both tests (aHR 17.04; 95% CI 11.67-24.88). However, almost half of all events occurred in those consistently in the low-risk group. CONCLUSIONS: Repeated testing of FIB-4 within 5 years improves the identification of individuals at an increased risk of severe liver disease in the general population. However, the sensitivity is comparatively low and improved tests are needed for screening in a general population or primary care setting. LAY SUMMARY: The fibrosis-4 scoring system is often used to estimate the risk of advanced fibrosis in liver diseases. Herein, we found that changes in this score over time are associated with the risk of future severe liver disease in a population-based cohort. However, even if the prediction is improved by repeated testing, the overall ability of the score to predict future events is relatively low.
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Only a very small proportion of individuals developed liver-related events, despite one third of the population having intermediate or high FIB-4 on more than one occasion.
“only a very small proportion of individuals developed liver-related events, despite one third of the population having intermediate or high FIB-4 on > -1 occasion. 191”
From EASL-EASD-EASO Clinical Practice Guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD). (2024) · cites this paper as [191]
Up to 50% of individuals with liver events may have persistently low FIB-4.
“up to 50% of individuals with liver events may have persistently low FIB-4. 191”
From EASL-EASD-EASO Clinical Practice Guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD). (2024) · cites this paper as [191]
Cites
External review and validation of the Swedish national inpatient register
Ludvigsson, J. F., Andersson, E., Ekbom, A., Feychting, M., Kim, J.-L., Reuterwall, C., Heurgren, M., & Olausson, P. O. (2011) · BMC Public Health · doi:10.1186/1471-2458-11-450 · Cited by 5,055 · see citing works
Sterling, R. K., Lissen, E., Clumeck, N., Sola, R., Correa, M. C., Montaner, J., S. Sulkowski, M., Torriani, F. J., Dieterich, D. T., Thomas, D. L., et al. (2006) · Hepatology · doi:10.1002/hep.21178 · Cited by 5,021 · see citing works
Wai, C.-T., Greenson, J. K., Fontana, R. J., Kalbfleisch, J. D., Marrero, J. A., Conjeevaram, H. S., & Lok, A. S.-F. (2003) · Hepatology · doi:10.1053/jhep.2003.50346 · Cited by 4,406 · see citing works
Angulo, P., Hui, J. M., Marchesini, G., Bugianesi, E., George, J., Farrell, G. C., Enders, F., Saksena, S., Burt, A. D., Bida, J. P., et al. (2007) · Hepatology · doi:10.1002/hep.21496 · Cited by 3,198 · see citing works
Angulo, P., Kleiner, D. E., Dam-Larsen, S., Adams, L. A., Bjornsson, E. S., Charatcharoenwitthaya, P., Mills, P. R., Keach, J. C., Lafferty, H. D., Stahler, A., et al. (2015) · Gastroenterology · doi:10.1053/j.gastro.2015.04.043 · Cited by 2,987 · see citing works
Transient elastography: a new noninvasive method for assessment of hepatic fibrosis
Sandrin, L., Fourquet, B., Hasquenoph, J.-M., Yon, S., Fournier, C., Mal, F., Christidis, C., Ziol, M., Poulet, B., Kazemi, F., et al. (2003) · Ultrasound in Medicine & Biology · doi:10.1016/j.ultrasmedbio.2003.07.001 · Cited by 2,734 · see citing works
The Swedish personal identity number: possibilities and pitfalls in healthcare and medical research
Ludvigsson, J. F., Otterblad-Olausson, P., Pettersson, B. U., & Ekbom, A. (2009) · European Journal of Epidemiology · doi:10.1007/s10654-009-9350-y · Cited by 2,407 · see citing works
Ekstedt, M., Hagström, H., Nasr, P., Fredrikson, M., Stål, P., Kechagias, S., & Hultcrantz, R. (2015) · Hepatology · doi:10.1002/hep.27368 · Cited by 2,287 · see citing works
Self-citationSingh, S., Allen, A. M., Wang, Z., Prokop, L. J., Murad, M. H., & Loomba, R. (2015) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2014.04.014 · Cited by 1,748 · see citing works
Eddowes, P. J., Sasso, M., Allison, M., Tsochatzis, E. A., Anstee, Q. M., Sheridan, D. A., Guha, I. N., Cobbold, J., Deeks, J. J., Paradis, V., et al. (2019) · Gastroenterology · doi:10.1053/j.gastro.2019.01.042 · Cited by 1,425 · see citing works
The Swedish cause of death register
Brooke, H. L., Talbäck, M., Hörnblad, J., Johansson, L. A., Ludvigsson, J. F., Druid, H., Feychting, M., & Ljung, R. (2017) · European Journal of Epidemiology · doi:10.1007/s10654-017-0316-1 · Cited by 1,382 · see citing works
Self-citationThe completeness of the Swedish Cancer Register – a sample survey for year 1998
Barlow, L., Westergren, K., Holmberg, L., & Talbäck, M. (2008) · Acta Oncologica · doi:10.1080/02841860802247664 · Cited by 1,240 · see citing works
Self-citationLudvigsson, J. F., Svedberg, P., Olén, O., Bruze, G., & Neovius, M. (2019) · European Journal of Epidemiology · doi:10.1007/s10654-019-00511-8 · Cited by 1,118 · see citing works
Hagström, H., Nasr, P., Ekstedt, M., Hammar, U., Stål, P., Hultcrantz, R., & Kechagias, S. (2017) · Journal of Hepatology · doi:10.1016/j.jhep.2017.07.027 · Cited by 1,067 · see citing works
Self-citationMcPherson, S., Hardy, T., Henderson, E., Burt, A. D., Day, C. P., & Anstee, Q. M. (2014) · Journal of Hepatology · doi:10.1016/j.jhep.2014.11.034 · Cited by 1,059 · see citing works
Age as a confounding factor for the accurate non-invasive diagnosis of advanced NAFLD fibrosis
McPherson, S., Hardy, T., Dufour, J.-F., Petta, S., Romero-Gomez, M., Allison, M., Oliveira, C. P., Francque, S., Van Gaal, L., Schattenberg, J. M., et al. (2017) · American Journal of Gastroenterology · doi:10.1038/ajg.2016.453 · Cited by 945 · see citing works
Vilar‐Gómez, E., & Chalasani, N. (2017) · Journal of Hepatology · doi:10.1016/j.jhep.2017.11.013 · Cited by 608 · see citing works
Hagström, H., Talbäck, M., Andreasson, A., Walldius, G., & Hammar, N. (2020) · Gastroenterology · doi:10.1053/j.gastro.2019.09.008 · Cited by 182 · see citing works
Self-citationVergniol, J., Boursier, J., Coutzac, C., Bertrais, S., Foucher, J., Angel, C., Chermak, F., Hubert, I. F., Merrouche, W., Oberti, F., et al. (2014) · Hepatology · doi:10.1002/hep.27069 · Cited by 128 · see citing works
Risk Factors for Severe Liver Disease in Patients With Type 2 Diabetes
Björkström, K., Franzén, S., Eliasson, B., Miftaraj, M., Guðbjörnsdóttir, S., Lagerros, Y. T., Svensson, A., & Hagström, H. (2019) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2019.04.038 · Cited by 73 · see citing works
Self-citationCohort Profile: The AMORIS cohort
Walldius, G., Malmström, H., Jungner, I., Fairé, U. D., Lambe, M. P., Hemelrijck, M. V., & Hammar, N. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw333 · Cited by 61 · see citing works
Self-citationChalasani, N., Abdelmalek, M. F., Loomba, R. S., Kowdley, K. V., McCullough, A. J., Dasarathy, S., Neuschwander‐Tetri, B. A., Terrault, N. A., Ferguson, B., Shringarpure, R., et al. (2018) · Liver International · doi:10.1111/liv.13974 · Cited by 58 · see citing works
Liver Fibrosis as Assessed by the FIB-4 Index in Patients with Type 2 Diabetes (T2DM)
FILOZOF, C. M., JONES, S., & Goldstein, B. J. (2018) · Diabetes · doi:10.2337/db18-1570-p · Cited by 6 · see citing works
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Rinella, M. E., Neuschwander-Tetri, B. A., Siddiqui, M. S., Abdelmalek, M. F., Caldwell, S., Barb, D., Kleiner, D. E., & Loomba, R. (2023) · Hepatology · doi:10.1097/hep.0000000000000323 · Cited by 2,667 · see citing works
Tacke, F., Horn, P., Wai-Sun Wong, V., Ratziu, V., Bugianesi, E., Francque, S., Zelber-Sagi, S., Valenti, L., Roden, M., Schick, F., et al. (2024) · Journal of Hepatology · doi:10.1016/j.jhep.2024.04.031 · Cited by 2,210 · see citing works
Kanwal, F., Shubrook, J. H., Adams, L. A., Pfotenhauer, K., Wai-Sun Wong, V., Wright, E., Abdelmalek, M. F., Harrison, S. A., Loomba, R., Mantzoros, C. S., et al. (2021) · Gastroenterology · doi:10.1053/j.gastro.2021.07.049 · Cited by 618 · see citing works
Natural history and progression of metabolic dysfunction-associated steatotic liver disease
Hagström, H., Shang, Y., Hegmar, H., & Nasr, P. (2024) · The Lancet Gastroenterology & Hepatology · doi:10.1016/s2468-1253(24)00193-6 · Cited by 310 · see citing works
Self-citationLin, H., Lee, H. W., Yip, T. C.-F., Tsochatzis, E., Petta, S., Bugianesi, E., Yoneda, M., Zheng, M.-H., Hagström, H., Boursier, J., et al. (2024) · JAMA · doi:10.1001/jama.2024.1447 · Cited by 250 · see citing works
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Anstee, Q. M., Castera, L., & Loomba, R. (2022) · Journal of Hepatology · doi:10.1016/j.jhep.2022.03.026 · Cited by 224 · see citing works
Boursier, J., Hagström, H., Ekstedt, M., Moreau, C., Bonacci, M., Cure, S., Ampuero, J., Nasr, P., Tallab, L., Canivet, C. M., et al. (2022) · Journal of Hepatology · doi:10.1016/j.jhep.2021.12.031 · Cited by 206 · see citing works
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Sanyal, A. J., Castera, L., & Wong, V. W.-S. (2023) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2023.03.042 · Cited by 157 · see citing works
Cholankeril, G., Kramer, J. R., Chu, J., Yu, X., Balakrishnan, M., Li, L., El-Serag, H. B., & Kanwal, F. (2023) · Journal of Hepatology · doi:10.1016/j.jhep.2022.10.035 · Cited by 119 · see citing works
Definition of healthy ranges for alanine aminotransferase levels: a 2021 update
Valenti, L., Pelusi, S., Bianco, C., Ceriotti, F., Berzuini, A., Iogna Prat, L., Trotti, R., Malvestiti, F., D’Ambrosio, R., Lampertico, P., et al. (2021) · Hepatology Communications · doi:10.1002/hep4.1794 · Cited by 77 · see citing works
Ndumele, C. E., Rodriguez, F., Dixon, D. L., Khan, S. S., Mukherjee, D., Bajaj, M., Bangalore, S., Bozkurt, B., Breathett, K., Clarke, S. L., et al. (2026) · JACC · doi:10.1016/j.jacc.2026.03.056 · Cited by 90 · see citing works
Zhang, X., Yip, T. C.-F., Wong, G. L.-H., Leow, W.-X., Liang, L. Y., Lim, L.-L., Li, G., Ibrahim, L., Lin, H., Lai, J. C. T., et al. (2023) · Gut · doi:10.1136/gutjnl-2023-330269 · Cited by 55 · see citing works
Canivet, C. M., Costentin, C., Irvine, K. M., Delamarre, A., Lannes, A., Sturm, N., Oberti, F., Patel, P. J., Decaens, T., Irles‐Depé, M., et al. (2023) · Hepatology · doi:10.1002/hep.32665 · Cited by 49 · see citing works
Authors, & Collaborators: (2022) · Zeitschrift für Gastroenterologie · doi:10.1055/a-1880-2388 · Cited by 30 · see citing works
Rutledge, S. M., Soper, E. R., Ma, N., Pejaver, V., Friedman, S. L., Branch, A. D., Kenny, E. E., Belbin, G. M., & Abul-Husn, N. S. (2023) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2022.12.025 · Cited by 22 · see citing works
- Authors
- Hagström, H., Talbäck, M., Andreasson, A., Walldius, G., & Hammar, N.
- Affiliations
- Karolinska University Hospital (SE)
- Karolinska Institutet (SE)
- Corresponding author
- Hagström, Hannes
- Venue
- Journal of Hepatology
- Publisher
- Elsevier BV
- Published
- 2020-11
- Volume
- 73
- Issue
- 5
- Pages
- 1023-1029
- ISSN
- 0168-8278 (ISSN-L)
- OpenAlex
- W3040545282
- Cited by
- 199
- References
- 23
- Citations by year
- 2026: 23 · 2025: 36 · 2024: 38 · 2023: 30 · 2022: 46 · 2021: 23 · 2020: 3
- FWCI
- 18.27
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Hepatology (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Intercept Pharmaceuticals
- Stockholms Läns Landsting
- AstraZeneca
- Gilead Sciences
- Topics
- Health Sciences › Medicine › Epidemiology › Liver Disease Diagnosis and Treatment
- Health Sciences › Medicine › Hepatology › Liver Disease and Transplantation
- Health Sciences › Medicine › Hepatology › Liver Diseases and Immunity
- Keywords
- FIB-4, liver fibrosis, liver cirrhosis, severe liver disease, repeated measures, non-invasive risk prediction, liver disease screening, risk stratification, AMORIS cohort, general population screening, primary care screening
- MeSH terms
- Aged, Aged, 80 and over, Biopsy, Female, Follow-Up Studies, Humans, Liver, Liver Cirrhosis, Male, Middle Aged, Prognosis, Risk Factors, Severity of Illness Index, Sweden, Biomarkers, Comorbidity, Incidence, Disease Progression, Non-alcoholic Fatty Liver Disease
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