Target trial emulation for causal inference using observational data in neurology.

Area of Science:

• Neurology
• Epidemiology
• Biostatistics

Background:

• Clinical questions in neurology are often causal, but observational studies traditionally focus on associations, leading to biases.
• Existing biases include inappropriate covariate adjustment, temporal misalignment, immortal-time bias, and susceptible depletion.

Purpose of the Study:

• To introduce target trial emulation as a practical approach for causal inference in neurology using observational data.
• To provide a framework for designing observational studies that align with randomized trial protocols.

Main Methods:

• Target trial emulation involves specifying an ideal randomized trial protocol and then emulating it with observational data.
• Key elements include defining eligibility, treatment strategies, time zero, follow-up, outcomes, and causal contrasts.
• Utilizes causal inference tools like counterfactual reasoning, causal diagrams, and g-methods.

Main Results:

• Target trial emulation reduces design-related bias in observational studies.
• This approach clarifies causal questions and establishes a transparent foundation for real-world evidence.
• Validation studies show good concordance between emulated trials and randomized controlled trials, including in multiple sclerosis research.

Conclusions:

• Target trial emulation is a valuable complement to randomized evidence in neurology.
• It is particularly useful for addressing causal questions that are difficult or impossible to study via randomization.
• This methodology has the potential to significantly enhance causal inference in neurological research.