Reanalyzing Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients (EMPAREG) using Longitudinal Targeted Maximum Likelihood Estimation (LTMLE) analysis

Lead Investigator: Christian Torp-Peteresen, North Zealand Hospital
Title of Proposal Research: Reanalyzing Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients (EMPAREG) using Longitudinal Targeted Maximum Likelihood Estimation (LTMLE) analysis
Vivli Data Request: 10055
Funding Source: EU grant Project Reddie
Potential Conflicts of Interest: None

Summary of the Proposed Research:

This project will be conducted to present the findings of a clinical trial in a way that’s useful for future users of a new drug. In clinical trials, researchers assess the benefits and positive effects/outcomes of a new treatment by comparing how well participants who receive the treatment fare against those who receive a control or placebo (a substance that has no therapeutic benefit). However, these trials can underestimate the real benefit of treatment because in all trials some participants stop taking the treatment.

The treatment being studied, Sodium-Glucose Cotransporter 2 (SGLT2) inhibitors, involves medications that help lower blood sugar levels in people with diabetes, a health condition where the body has trouble regulating blood sugar levels. The drug works by blocking a specific protein, Sodium-Glucose Cotransporter 2 protein. The aim of the proposed analysis is to analyze how continuous use of SGLT2 inhibitors over different durations (1 year, 2 years, etc.) benefits patients compared to not receiving treatment at all. The reason why we are investigating SGLT2 inhibitors is the widespread use of the drug, with the goal of being able to give more interpretable results for the patients using this medication. Therefore we are using data from the EMPAREG trial which established the effect and safety of SGLT2 inhibitors.

The analysis method used is called longitudinal targeted maximum likelihood estimation. This technique allows researchers to estimate what the outcomes would have been if all participants had stayed on treatment consistently, despite breaks or discontinuations in the real data. This study is crucial because it assesses whether the ‘intention to treat’ analysis typically used in clinical trials can accurately guide patients who want to understand the long-term benefits of treatment, beyond what’s observed during the trial itself. To achieve this, the researchers need to reanalyze the data collected during the clinical trial.

Intention-to-treat is a statistical principle used in randomized clinical trials (RCTs) to evaluate patients based on the group they were randomly assigned to, regardless of whether they received the intended treatment or followed the protocol- including those who dropped ed out of the trial, switched treatments, or didn’t adhere to the treatment regimen.

Requested Studies:

A Phase III, Multicentre, International, Randomised, Parallel Group, Double Blind Cardiovascular Safety Study of BI 10773 (10 mg and 25 mg Administered Orally Once Daily) Compared to Usual Care in Type 2 Diabetes Mellitus Patients With Increased Cardiovascular Risk
Data Contributor: Boehringer Ingelheim
Study ID: NCT01131676
Sponsor ID: 1245.25