MRI Quantification of Placebo Effect in Nonalcoholic Steatohepatitis Clinical Trials.


Background Several early-phase clinical trials for the treatment of nonalcoholic steatohepatitis (NASH) use liver fat content as measured with the MRI-derived proton density fat fraction (PDFF) for a primary outcome. These trials have shown relative reductions in liver fat content with placebo treatment alone, a phenomenon termed "the placebo effect." This phenomenon confounds the results and limits generalizability to future trials. Purpose To quantify the effect of placebo treatment on change in the absolute PDFF value and to identify variables associated with this observed change. Materials and Methods This is a secondary analysis of prospectively collected data from seven early phase clinical trials that included participants with a diagnosis of NASH based on MRI and/or liver biopsy who received placebo treatment. The primary outcome was a greater than or equal to 30% relative reduction in PDFF after placebo treatment. Normalization of PDFF, relative change in alanine aminotransferase (ALT) level, and normalization of ALT level were also examined. An exploratory linear mixed-effects model was used to estimate an overall change in absolute PDFF and to explore parameters associated with this response. Results A total of 187 participants (median age, 52 years [IQR, 43-60 years]; 114 women) who received placebo treatment were evaluated. A greater than or equal to 30% relative reduction in baseline PDFF was seen in 20% of participants after 12 weeks of placebo treatment (10 of 49), 9% of participants after 16 weeks (two of 22), and 28% of participants after 24 weeks (34 of 122). A repeated-measures linear mixed-effects model estimated a decrease of 2.3 units (median relative reduction of 13%) in absolute PDFF values after 24 weeks of placebo treatment (95% CI: 3.2, 1.4; P < .001). Conclusion In this analysis of 187 participants, a clinically relevant decrease in PDFF was observed with placebo treatment. Based on the study model, assuming an absolute PDFF decrease of approximately 3 units (upper limit of 95% CI) to account for this "placebo effect" in sample size calculations for future clinical trials is suggested. Clinical trial registration nos. NCT01066364, NCT01766713, NCT01963845, NCT02443116, NCT02546609, NCT02316717, and NCT02442687 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Yoon in this issue.






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Publication Info

Nedrud, Marybeth A, Mohammad Chaudhry, Michael S Middleton, Cynthia A Moylan, Reginald Lerebours, Sheng Luo, Alfredo Farjat, Cynthia Guy, et al. (2022). MRI Quantification of Placebo Effect in Nonalcoholic Steatohepatitis Clinical Trials. Radiology. p. 220743. 10.1148/radiol.220743 Retrieved from

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Cynthia Ann Moylan

Associate Professor of Medicine

My research interests focus on the study of chronic liver disease and primary liver cancer, particularly from metabolic dysfunction associated steatotic liver disease (MASLD), formerly called nonalcoholic fatty liver disease (NAFLD).  As part of the MASLD Research Team at Duke, we are investigating the role of environmental contaminants, epigenetics, and genetics on the development of advanced fibrosis and liver cancer from MASLD and other chronic liver diseases.  We are also interested in understanding risks for progressive liver disease including developmental programming and in utero exposures and have been investigating these risks through studies of the Newborn Epigenetics Study (NEST).  The long term goal of our research is to develop non-invasive biomarkers to identify those patients at increased risk for cirrhosis and end stage liver disease in order to risk stratify patients as well as to develop better preventative and therapeutic strategies.


Reginald (Gino) Lerebours

Biostatistician II

Education: Masters Degree, Biostatistics. Harvard University. 2017
Bachelors Degree, Statistics. North Carolina State University. 2015

Overview:  Gino currently collaborates with researchers, residents, and clinicians in the Departments of Surgery, Radiology and Infectious Diseases. His main research interests and experience are in statistical programming, data management, statistical modeling, statistical consulting and statistical education.

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