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Original research
Clinical utility of 30% relative decline in MRI-PDFF in predicting fibrosis regression in non-alcoholic fatty liver disease
  1. Nobuharu Tamaki1,2,
  2. Nagambika Munaganuru1,
  3. Jinho Jung1,
  4. Aed Qas Yonan1,
  5. Rohan R Loomba1,3,
  6. Richele Bettencourt1,
  7. Veeral Ajmera1,
  8. Mark A Valasek4,
  9. Cynthia Behling4,
  10. Claude B Sirlin5,
  11. Rohit Loomba1,6
  1. 1NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, California, USA
  2. 2Department of Gastroenterology and Hepatology, Musashino Red Cross Hospital, Musashino, Japan
  3. 3Cathedral Catholic High School, San Diego, California, USA
  4. 4Department of Pathology, University of California San Diego, La Jolla, California, USA
  5. 5Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, California, USA
  6. 6Department of Family Medicine and Public Health, University of California San Diego, La Jolla, California, USA
  1. Correspondence to Professor Rohit Loomba, Department of Medicine, University of California San Diego, La Jolla CA 92037, USA; roloomba{at}ucsd.edu

Abstract

Objective Emerging data suggest that a 30% relative decline in liver fat, as assessed by MRI-proton density fat fraction (MRI-PDFF), may be associated with Non-Alcoholic Fatty Liver Disease Activity Score improvement, but the association between decline in MRI-PDFF and fibrosis regression is not known. Therefore, we aimed to examine the association between ≥30% relative decline in MRI-PDFF and fibrosis regression in non-alcoholic fatty liver disease (NAFLD).

Design This prospective study included 100 well-characterised patients with biopsy-proven NAFLD with paired contemporaneous MRI-PDFF assessment at two time points. MRI-PDFF response was defined as ≥30% relative decline in MRI-PDFF. The primary outcome was ≥1 stage histological fibrosis regression.

Results The median (IQR) age was 54 (43–62) years and body mass index was 31.9 (29–36) kg/m2. In multivariable-adjusted logistic regression analysis (adjusted for age, gender, diabetes status, race/ethnicity, interval between biopsies, gamma-glutamyl transferase, liver stiffness by magnetic resonance elastography and change in platelet counts), MRI-PDFF response was an independent predictor of fibrosis regression with an adjusted OR of 6.46 (95% CI 1.1 to 37.0, p=0.04). The proportion of patients with MRI-PDFF response with fibrosis regression, no change in fibrosis and fibrosis progression was 40.0%, 24.6% and 13.0%, respectively, and the proportion of patients with MRI-PDFF response increased with fibrosis regression (p=0.03).

Conclusion ≥30% reduction in MRI-PDFF in early phase trials can provide a useful estimate of odds of ≥1 stage improvement in fibrosis. These data may be helpful in sample size estimation in non-alcoholic steatohepatitis trials.

  • nonalcoholic steatohepatitis
  • liver imaging

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. Data can be provided upon request to credible investigators on verification for patient confidentiality.

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Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. Data can be provided upon request to credible investigators on verification for patient confidentiality.

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Footnotes

  • Contributors NT: analysis and interpretation of data, drafting of the manuscript, critical revision of the manuscript, obtained funding, approved final submission. NM: drafting of the manuscript, critical revision of the manuscript, approved final submission. JJ, AQY, RRL. RB, MAV, CB, CBS: data analysis, critical revision of the manuscript, approved final submission. VA: data analysis, drafting of the manuscript, critical revision of the manuscript, obtained funding, approved final submission. RL: study concept and design, analysis and interpretation of data, drafting of the manuscript, critical revision of the manuscript, obtained funding, study supervision, approved final submission.

  • Funding RL received funding support from NIEHS (5P42ES010337), NCATS (5UL1TR001442), DOD PRCRP (W81XWH-18-2-0026), NIDDK (U01DK061734, R01DK106419, R01DK121378, R01DK124318, P30DK120515), NHLBI (P01HL147835) and NIAAA (U01AA029019). VA received funding support from NIDDK (K23DK119460). NT received funding support from the Uehara Memorial Foundation (201940021).

  • Competing interests RL serves as a consultant or advisory board member for Alnylam/Regeneron, Arrowhead Pharmaceuticals, AstraZeneca, Bird Rock Bio, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Cirius, CohBar, Conatus, Eli Lilly, Galmed, Gemphire, Gilead, Glympse Bio, GNI, GRI Bio, Inipharm, Intercept, Ionis, Janssen, Merck, Metacrine, NGM Biopharmaceuticals, Novartis, Novo Nordisk, Pfizer, Prometheus, Promethera, Sanofi, Siemens and Viking Therapeutics. In addition, his institution has received grant support from Allergan, Boehringer Ingelheim, Bristol Myers Squibb, Cirius, Eli Lilly and Company, Galectin Therapeutics, Galmed Pharmaceuticals, GE, Genfit, Gilead, Intercept, Grail, Janssen, Madrigal Pharmaceuticals, Merck, NGM Biopharmaceuticals, NuSirt, Pfizer, pH Pharma, Prometheus and Siemens. He is also co-founder of Liponexus. CBS reports grants from GE, Siemens, Philips, Bayer and Gilead; personal consultation fees from Blade, Boehringer and Epigenomics; consultation under the auspices of the University to AMRA, BMS, Exact Sciences, GE Digital and IBM Watson; lab service agreements from Enanta, Gilead, ICON, Intercept, NuSirt, Shire, Synageva and Takeda; and royalties or honoraria from Wolters Kluwer and Medscape, respectively, for educational materials, outside the submitted work. The other authors disclose no conflicts.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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