Stratification of patients in NASH clinical trials: A pitfall for trial success

Abstract

Identifying the most effective therapeutic intervention in patients with NAFLD is challenging. Precise stratification in clinical trials is key to ensuring the inclusion of patients who will benefit (and not those who will be harmed) and/or in whom the natural history can be improved. Clinical trials in NAFLD can provide useful information about the individual components that underlie this complex metabolic disorder and the concomitant medications that could interfere with responses to an experimental intervention. However, to date, clinical trial reporting for NAFLD has been suboptimal, limiting our understanding. Frequently dysmetabolic comorbidities and/or daily habits are not reported or adequately accounted for. Herein, we suggest new strategies to integrate the spectra of comorbidities usually present in patients with NAFLD, accounting for the impact of lifestyle, to develop personalised therapeutic approaches. First, the mechanism of action of the drug being explored should be considered. Second, the same proportion of patients with relevant metabolic comorbidities should be maintained from phase II to III clinical trials, if such comorbidities are expected to impact on the treatment response. Third, innovative trial designs, such as the adaptative, umbrella or basket strategies, could be used to increase the efficiency of clinical trials, potentially benefiting patients while reducing costs and enhancing the likelihood of finding a real benefit of the therapy being studied. Finally, alcohol intake and daily exercise should be assessed objectively not only in the screening period but also during follow-up.

Perspectives on Precision Medicine Approaches to NAFLD Diagnosis and Management

“…Also, artificial intelligence tools to integrate and analyze big data as well as to develop algorithms combining the information through machine learning strategies [187][188][189] may be of help to better stratifying patients and defining tailored treatment strategies. A more accurate phenotyping of patients may also allow for grouping into more homogenous categories in clinical trials leading to more granular data on the efficacy of drugs in well-defined patient subgroups [26,190]. Finally, artificial intelligence tools and high-performance computing could be useful to link biological information to health data in electronic medical records, thus advancing the discovery of novel associations using data-mining analysis.…”

Historical narrative from fatty liver in the nineteenth century to contemporary NAFLD – Reconciling the present with the past

“…Differences in NAFLD phenotypes and genotypes, alcohol consumption, diet, exercise, severity of metabolic comorbidity, use of concomitant medications and adverse events in clinical trial participants are likely to influence both treatment responses and interpretations of NASH clinical trial results. 80 …”

Insights into Nonalcoholic Fatty-Liver Disease Heterogeneity

“…Also, adoption of innovative trials designs to study novel NAFLD treatments, such as the adaptative, umbrella, or basket strategies, could be useful to improve trial efficiency. 12,23 Fig. 2 The differential contribution of genetic/epigenetic, environmental and metabolic factors deters a significant interpatient variation regarding the major driver of disease.…”