Suboptimal reliability of liver biopsy evaluation has implications for randomized clinical trials
Abstract
Background & aims Liver biopsies are a critical component of pivotal studies in non-alcoholic steatohepatitis (NASH), constituting inclusion criteria, risk stratification factors and endpoints. We evaluated the reliability of NASH Clinical Research Network scoring of liver biopsies in a NASH clinical trial. Methods Digitized slides of 678 biopsies from 339 patients with paired biopsies randomized into the EMMINENCE study - examining a novel insulin sensitizer (MSDC-0602K) in NASH - were read independently by 3 hepatopathologists blinded to treatment code and scored using the NASH CRN histological scoring system. Various endpoints were computed from these scores. Results Inter-reader linearly weighted kappas were 0.609, 0.484, 0.328, and 0.517 for steatosis, fibrosis, lobular inflammation, and ballooning, respectively. Inter-reader unweighted kappas were 0.400 for the diagnosis of NASH, 0.396 for NASH resolution without worsening fibrosis, and 0.366 for fibrosis improvement without worsening NASH. In the current study, 46.3% of the patients included in the study based on 1 hepatopathologist's qualifying reading were deemed not to meet the study's histologic inclusion criteria by at least 1 of the 3 hepatopathologists. The MSDC-0602K treatment effect was lowest for those histologic features with lower inter-reader reliability. Simulations show that the lack of reliability of endpoints and inclusion criteria can drastically reduce study power - from >90% in a well-powered study to as low as 40%. Conclusions The reliability of hepatopathologists' liver biopsy evaluation using currently accepted criteria is suboptimal. This lack of reliability may affect NASH pivotal studies by introducing patients who do not meet NASH study entry criteria, misclassifying fibrosis subgroups, and attenuating apparent treatment effects. Lay summary Since liver biopsy analysis plays such an important role in clinical studies of non-alcoholic steatohepatitis, it is important to understand the reliability of hepato-pathologist readings. We examined both inter- and intra-reader variability in a large data set of paired liver biopsies from a clinical trial. We found very poor inter-reader and modest intra-reader variability. This result has important implications for entry criteria, fibrosis stratification, and the ability to measure a treatment effect in clinical trials.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A phase 2 RCT investigating reversible FASN inhibitor TVB-2640 in people with MASLD showed moderate reduction in steatosis and increase in circulating adiponectin, without effects on body weight and unchanged circulating triglyceride levels.
“A phase 2 RCT investigating the reversible FASN inhibitor TVB-2640 in people with MASLD showed a moderate reduction in steatosis and an increase in circulating adiponectin, notably without effects on body weight as well as unchanged circulating triglyceride levels [227].”
From Obesity and MASLD: Is weight loss the (only) key to treat metabolic liver disease? (2024) · cites this paper as [227]
Cites
The Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148 · see citing works
Self-citationMeasuring nominal scale agreement among many raters.
Fleiss, J. L. (1971) · Psychological Bulletin · doi:10.1037/h0031619 · Cited by 8,733 · see citing works
Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention
Younossi, Z., Anstee, Q. M., Marietti, M., Hardy, T., Henry, L., Eslam, M., George, J., & Bugianesi, E. (2018) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/nrgastro.2017.109 · Cited by 5,249 · see citing works
Sampling Variability of Liver Biopsy in Nonalcoholic Fatty Liver Disease
Ratziu, V., Charlotte, F., Heurtier, A., Gombert, S., Giral, P., Bruckert, E., Grimaldi, A., Capron, F., & Poynard, T. (2005) · Gastroenterology · doi:10.1053/j.gastro.2005.03.084 · Cited by 2,106 · 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
Mukhopadhyay, S., Feldman, M. D., Abels, E., Ashfaq, R., Beltaifa, S., Cacciabeve, N. G., Cathro, H. P., Cheng, L., Cooper, K., Dickey, G. E., et al. (2018) · American Journal of Surgical Pathology · doi:10.1097/pas.0000000000000948 · Cited by 399 · see citing works
Sanyal, A. J., Harrison, S. A., Ratziu, V., Abdelmalek, M. F., Diehl, A. M., Caldwell, S., Shiffman, M. L., Aguilar Schall, R., Jia, C., McColgan, B., et al. (2019) · Hepatology · doi:10.1002/hep.30664 · Cited by 390 · see citing works
Self-citationAssociation of histologic disease activity with progression of nonalcoholic fatty liver disease
Kleiner, D. E., Brunt, E. M., Wilson, L. A., Behling, C., Guy, C., Contos, M., Cummings, O., Yeh, M., Gill, R., Chalasani, N., et al. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.12565 · Cited by 372 · see citing works
Self-citationValidation of digital pathology imaging for primary histopathological diagnosis
Snead, D. R. J., Tsang, Y., Meskiri, A., Kimani, P. K., Crossman, R., Rajpoot, N. M., Blessing, E., Chen, K., Gopalakrishnan, K., Matthews, P., et al. (2016) · Histopathology · doi:10.1111/his.12879 · Cited by 238 · see citing works
Forlano, R., Mullish, B. H., Giannakeas, N., Maurice, J. B., Angkathunyakul, N., Lloyd, J., Tzallas, A. T., Tsipouras, M., Yee, M., Thursz, M. R., et al. (2020) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2019.12.025 · Cited by 142 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Non-alcoholic fatty liver disease
Powell, E. E., Wong, V. W.-S., & Rinella, M. (2021) · The Lancet · doi:10.1016/s0140-6736(20)32511-3 · Cited by 2,789 · see citing works
Cusi, K., Isaacs, S., Barb, D., Basu, R., Caprio, S., Garvey, W. T., Kashyap, S., Mechanick, J. I., Mouzaki, M., Nadolsky, K., et al. (2022) · Endocrine Practice · doi:10.1016/j.eprac.2022.03.010 · Cited by 1,021 · see citing works
Lomonaco, R., Godinez Leiva, E., Bril, F., Shrestha, S., Mansour, L., Budd, J., Portillo Romero, J., Schmidt, S., Chang, K.-L., Samraj, G., et al. (2021) · Diabetes Care · doi:10.2337/dc20-1997 · Cited by 354 · see citing works
Impact of non-invasive biomarkers on hepatology practice: past, present and future
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
Vali, Y., Lee, J., Boursier, J., Petta, S., Wonders, K., Tiniakos, D., Bedossa, P., Geier, A., Francque, S., Allison, M., et al. (2023) · The Lancet Gastroenterology & Hepatology · doi:10.1016/s2468-1253(23)00017-1 · Cited by 224 · see citing works
Self-citationMózes, F. E., Lee, J. A., Vali, Y., Alzoubi, O., Staufer, K., Trauner, M., Paternostro, R., Stauber, R. E., Holleboom, A. G., van Dijk, A.-M., et al. (2023) · The Lancet Gastroenterology & Hepatology · doi:10.1016/s2468-1253(23)00141-3 · Cited by 214 · see citing works
Self-citationBoursier, 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
Anstee, Q. M., Neuschwander-Tetri, B. A., Wai-Sun Wong, V., Abdelmalek, M. F., Rodriguez-Araujo, G., Landgren, H., Park, G. S., Bedossa, P., Alkhouri, N., Tacke, F., et al. (2024) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2023.04.003 · Cited by 179 · see citing works
Self-citationRinella, M. E., Dufour, J.-F., Anstee, Q. M., Goodman, Z., Younossi, Z., Harrison, S. A., Loomba, R., Sanyal, A. J., Bonacci, M., Trylesinski, A., et al. (2022) · Journal of Hepatology · doi:10.1016/j.jhep.2021.10.029 · Cited by 164 · see citing works
Obesity and MASLD: Is weight loss the (only) key to treat metabolic liver disease?
Huttasch, M., Roden, M., & Kahl, S. (2024) · Metabolism · doi:10.1016/j.metabol.2024.155937 · Cited by 169 · see citing works
Noninvasive assessment of liver fibrosis in NAFLD
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
Castera, L., Laouenan, C., Vallet-Pichard, A., Vidal-Trécan, T., Manchon, P., Paradis, V., Roulot, D., Gault, N., Boitard, C., Terris, B., et al. (2023) · Diabetes Care · doi:10.2337/dc22-2048 · Cited by 136 · see citing works
Tamaki, N., Munaganuru, N., Jung, J., Yonan, A. Q., Loomba, R. R., Bettencourt, R., Ajmera, V., Valasek, M. A., Behling, C., Sirlin, C. B., et al. (2022) · Gut · doi:10.1136/gutjnl-2021-324264 · Cited by 130 · see citing works
Loomba, R., Ratziu, V., Harrison, S. A., Loomba, R., McFarlane, S. C., Tamaki, N., Ratziu, V., Abdelmalek, M. F., Rinella, M. E., Anstee, Q. M., et al. (2022) · Gastroenterology · doi:10.1053/j.gastro.2021.10.051 · Cited by 127 · see citing works
Self-citationNaoumov, N. V., Brees, D., Loeffler, J., Chng, E., Ren, Y., Lopez, P., Tai, D., Lamle, S., & Sanyal, A. J. (2022) · Journal of Hepatology · doi:10.1016/j.jhep.2022.06.018 · Cited by 115 · see citing works
Self-citationWhy Do So Many Nonalcoholic Steatohepatitis Trials Fail?
Ratziu, V., & Friedman, S. L. (2023) · Gastroenterology · doi:10.1053/j.gastro.2020.05.046 · Cited by 88 · see citing works
Emerging role of genomic analysis in clinical evaluation of lean individuals with NAFLD
Vilarinho, S., Ajmera, V., Zheng, M., & Loomba, R. (2021) · Hepatology · doi:10.1002/hep.32047 · Cited by 85 · see citing works
Antifibrotic therapy in nonalcoholic steatohepatitis: time for a human-centric approach
Brennan, P. N., Elsharkawy, A. M., Kendall, T. J., Loomba, R., Mann, D. A., & Fallowfield, J. A. (2023) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-023-00796-x · Cited by 68 · see citing works
Tamaki, N., Ahlholm, N., Luukkonen, P. K., Porthan, K., Sharpton, S. R., Ajmera, V., Kono, Y., Dave, S., Ahmed, A., Sundaram, V., et al. (2022) · Journal of Clinical Investigation · doi:10.1172/jci162513 · Cited by 69 · see citing works
Iyer, J. S., Juyal, D., Le, Q., Shanis, Z., Pokkalla, H., Pouryahya, M., Pedawi, A., Stanford-Moore, S. A., Biddle-Snead, C., Carrasco-Zevallos, O., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-03172-7 · Cited by 54 · see citing works
Self-citationNing, Y., Zhou, I. Y., Roberts, J. D., Rotile, N. J., Akam, E., Barrett, S. C., Sojoodi, M., Barr, M. N., Punshon, T., Pantazopoulos, P., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abq6297 · Cited by 47 · see citing works
Loomba, R., Amangurbanova, M., Bettencourt, R., Madamba, E., Siddiqi, H., Richards, L., Behling, C., Sirlin, C. B., Gottwald, M. D., Feng, S., et al. (2024) · Gut · doi:10.1136/gutjnl-2023-331401 · Cited by 43 · see citing works
The future of incretins in the treatment of obesity and non-alcoholic fatty liver disease
Andreasen, C. R., Andersen, A., & Vilsbøll, T. (2023) · Diabetologia · doi:10.1007/s00125-023-05966-9 · Cited by 44 · see citing works
NAFLD and NASH biomarker qualification in the LITMUS consortium – Lessons learned
Rasmussen, D. G. K., Anstee, Q. M., Torstenson, R., Golding, B., Patterson, S. D., Brass, C., Thakker, P., Harrison, S., Billin, A. N., Schuppan, D., et al. (2023) · Journal of Hepatology · doi:10.1016/j.jhep.2022.11.028 · Cited by 41 · see citing works
Self-citationHarris, S. J., Smith, N., Hummer, B., Schreibman, I. R., Faust, A. J., Geyer, N. R., Chinchilli, V. M., Sciamanna, C., Loomba, R., & Stine, J. G. (2024) · Liver International · doi:10.1111/liv.15769 · Cited by 31 · see citing works
Authors, & Collaborators: (2022) · Zeitschrift für Gastroenterologie · doi:10.1055/a-1880-2388 · Cited by 30 · see citing works
Loomba, R., Daniel, P. C.-Y. N., Amangurbanova, M., Bettencourt, R., Madamba, E., Siddiqi, H., Richards, L., Gottwald, M. D., Feng, S., Margalit, M., et al. (2026) · Hepatology · doi:10.1097/hep.0000000000001396 · Cited by 17 · see citing works
- Authors
- Davison, B. A., Harrison, S. A., Cotter, G., Alkhouri, N., Sanyal, A., Edwards, C., Colca, J. R., Iwashita, J., Koch, G. G., & Dittrich, H. C.
- Affiliations
- Momentum Research (US)
- University of Oxford (GB)
- Texas Liver Institute (US)
- Virginia Commonwealth University (US)
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Davison, Beth A.
- ORCID
- Venue
- Journal of Hepatology
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 73
- Issue
- 6
- Pages
- 1322-1332
- ISSN
- 0168-8278 (ISSN-L)
- OpenAlex
- W3038092240
- Cited by
- 448
- References
- 10
- Citations by year
- 2026: 70 · 2025: 58 · 2024: 81 · 2023: 83 · 2022: 78 · 2021: 62 · 2020: 16
- FWCI
- 42.85
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Hepatology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Cirius Therapeutics
- Topics
- Health Sciences › Medicine › Epidemiology › Liver Disease Diagnosis and Treatment
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- liver biopsy, nonalcoholic steatohepatitis, inter-reader reliability, histological scoring, fibrosis assessment, steatosis, lobular inflammation, ballooning, study power, insulin sensitizers, paired biopsies
- MeSH terms
- Acetophenones, Biopsy, Diabetes Mellitus, Type 2, Female, Humans, Hypoglycemic Agents, Insulin Resistance, Liver, Liver Cirrhosis, Male, Middle Aged, Prognosis, Research Design, Reproducibility of Results, Disease Progression, Risk Assessment, Thiazolidinediones, Non-alcoholic Fatty Liver Disease
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review