MACE RCT Simulation

Definitions of terms and abbreviations

Term or Abbreviation	Definition	Note
IHD	Ischemic Heart Disease	Cause of cardiovascular mortality
LDL-C	Low Density Lipoprotein Cholesterol	Risk Factor
MACE	Major Adverse Cardiovascular Events	Composite outcome typically including cardiovascular death, myocardial infarction, and stroke
MASH	Metabolic Dysfunction-Associated Steatohepatitis	Updated nomenclature for NASH
MASLD	Metabolic dysfunction–Associated Steatotic Liver Disease	Spectrum of liver disease ranging from simple steatosis to MASH; a term gradually replacing NAFLD.
NAFLD	Non-Alcoholic Fatty Liver Disease	Spectrum of liver disease ranging from simple steatosis to NASH
NASH	Non-Alcoholic Steatohepatitis	Also referred to as MASH (metabolic dysfunction-associated steatohepatitis)
RCT	Randomized Controlled Trial	Study design

1. Background

Elevated low-density lipoprotein cholesterol (LDL-C) is a well-established causal risk factor for atherosclerotic cardiovascular disease, including ischemic heart disease (IHD) and ischemic stroke. Despite the availability of statins and other lipid-lowering therapies, a substantial fraction of patients at elevated cardiovascular risk do not achieve guideline-recommended LDL-C targets, motivating the development of novel LDL-C-lowering agents.

Non-alcoholic steatohepatitis (NASH), now more commonly referred to as metabolic dysfunction-associated steatohepatitis (MASH), is an increasingly prevalent condition characterized by hepatic inflammation and fibrosis in the setting of metabolic syndrome. Patients with NASH and significant liver fibrosis carry a metabolic risk profile that differs from the general population in important ways: they have higher rates of insulin resistance, dyslipidemia, obesity, and systemic inflammation. These comorbidities place NASH patients at substantially elevated risk of cardiovascular events. Indeed, cardiovascular disease is the leading cause of death in patients with non-alcoholic fatty liver disease (NAFLD), surpassing liver-related mortality in all but the most advanced stages of fibrosis.

The randomized controlled trial (RCT) that this concept model simulates will enroll patients with a to-be-determined level of liver fibrosis (e.g., fibrosis stage F2–F3) and elevated LDL-C. Because this trial focuses on a population selected for hepatic fibrosis, the enrolled participants are expected to have a metabolic risk profile that is meaningfully different from the general population. In particular, they may have higher baseline rates of major adverse cardiovascular events (MACE) due to the clustering of cardiometabolic risk factors associated with NASH. Understanding these differences is critical for several reasons.

First, it is useful to understand what fraction of the general population would meet the trial’s inclusion criteria, as this determines the generalizability of the trial findings and the potential market size for the intervention.

Second, it is important to estimate how MACE rates in the trial population might differ from general population rates. If the trial population has meaningfully higher baseline MACE risk, the trial may be better powered to detect a treatment effect, but the absolute risk reduction observed may not translate directly to lower-risk populations. Conversely, if the trial population has lower baseline MACE risk, the trial may need to recruit an unexpectedly large sample of study participants to be likely to detect the treatment effect.

This simulation will model the trial population, the randomization to treatment and control arms, LDL-C trajectories under the experimental agent, and the downstream incidence of MACE (cardiovascular death, myocardial infarction, and ischemic stroke) to inform trial design and expected outcomes.

2. Modeling Aims and Objectives

The aim of this simulation is to estimate the effect of the experimental LDL-C-lowering agent on MACE incidence under trial conditions.

3. Concept Model Diagram

The concept model diagram will represent the trial population, the randomization to treatment and control arms, LDL-C exposure, and downstream MACE outcomes.

4. Vivarium Modeling Components

The simulation will include cause models for cardiovascular outcomes, a risk exposure model for LDL-C, a risk effect linking LDL-C to MACE, and an intervention model representing the experimental agent.

5. Back of the Envelope Calculations

Back of the envelope calculations to estimate the expected effect size and required trial size will be added here.

6. Limitations

Known limitations of the simulation, including assumptions about adherence, response heterogeneity, and trial design simplifications, will be documented here.

7. References

References supporting the model design and parameters will be listed here.