With #TargetTrial emulation becoming increasingly popular, it's important to understand what it can and cannot do.

In this podcast with JAMA Statistical Editor Roger Lewis, I discuss our commentary "Target Trial Emulation: A Framework for Causal Inference From Observational Data"
https://jamanetwork.com/journals/jama/article-abstract/2799678

We talk about how explicit emulation of a target trial can 1) improve causal inference from observational databases and 2) extend the inferences from randomized trials.
https://edhub.ama-assn.org/jn-learning/audio-player/18877235

2/
We described this bias with simulations + real data.

We show that a vaccine booster will be associated with higher reinfection even if the booster has no harmful effect.
https://www.bmj.com/content/381/bmj-2022-074404.full

The good news: Preventing this self-inflicted #selectionbias is easy: Specify the #TargetTrial that the observational analysis tries to emulate.

Here the (unethical) target trial requires forced infection, so observational analyses will be biased unless they adjust for susceptibility to infection.

For multidrug-resistant #tuberculosis, the optimal duration of bedaquiline treatment is unknown.

Our #TargetTrial emulation: Bedaquiline for more than 6 months doesn't increase the probability of success.

Cloning+censoring+#IPweighting

https://www.atsjournals.org/doi/10.1164/rccm.202211-2125OC

#TargetTrial and observational data for cancer research. #epitwitter #epiverse
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RT @_MiguelHernan
The European Organisation for Research and Treatment of Cancer (@EORTC) endorses #TargetTrial emulation with #RWD.

An organization with unmatched expertise in the design of #randomizedtrials embraces their explicit emulation when using observational data.
https://www.ejcancer.com/article/S0959-8049(23)00149-1/fulltext
https://twitter.com/_MiguelHernan/status/1638259606072750094

Observational studies are often the only option to
estimate effects of interventions during #pregnancy.

Thinking of emulating a #TargetTrial during pregnancy using healthcare databases?

Here we review challenges and propose solutions to common biases 👇
https://pubmed.ncbi.nlm.nih.gov/36722806/

#oncology

RT @MiguelHernan: 1/

Problem: The best therapies for advanced pancreatic #cancer (Folfirinox, GN) haven't been compared in a head-to-head randomized trial due to cost and commercial barriers.

We emulated a #TargetTrial using observational data: Folfirinox is a bit better

https://www.sciencedirect.com/science/article/pii/S1047279722003088?dgcid=coauthor

Because randomized trials are great only when they exist.

Without trials, high-quality observational data + explicit #TargetTrial emulation is our best chance to help

people make the treatment decisions they must make

until we convince companies/funders to pay for the trial.

1/

Problem: The best therapies for advanced pancreatic #cancer (Folfirinox, GN) haven't been compared in a head-to-head randomized trial due to cost and commercial barriers.

We emulated a #TargetTrial using observational data: Folfirinox is a bit better

https://www.sciencedirect.com/science/article/pii/S1047279722003088?dgcid=coauthor

I just spent the last hour with a brilliant young anesthesiologist imagining potential good questions in management of #IntraoperativeHypotension in #CardiacSurgery

I used @SPT_MD's example of specification and emulation of a #TargetTrial to help really clarify the questions of interest, and let me tell you, @SPT_MD's way of thinking is great

1/
Our summary of #TargetTrial emulation is out.

We illustrate it with another observational success:

A survival benefit of #tocilizumab in critically ill #COVID19 patients was quantified using observational data before a randomized trial confirmed it.
👇

https://jamanetwork.com/journals/jama/fullarticle/2799678

My #introduction:

I repurpose observational #RealWorldData into scientific evidence for the prevention and treatment of human disease. At #CAUSALab, we often do so by explicitly emulating a #TargetTrial. Other times we analyze #RandomizedTrials.

I teach #causalinference methods at the #Harvard T.H. Chan School of #PublicHealth. My online course #CausalDiagrams and “Causal Inference" #WhatIfBook (with James Robins) are free. See my profile.

#epidemiology #epiverse
#statistics
#datascience
#AI

The reflex to indiscriminately stratify and adjust on covariates is strong in biomedical research. I face this so often, especially with clinician-scientist collaborators.

The analyses and models that arise from this, in fact, often do not well represent how exposures and treatments exert their effect in reality.

A #TargetTrial approach crystallizes when, where, and how co-variates should be treated.

Take this great illustration from Target Trial originator @MiguelHernan where he explains the study design choices for study on COVID vaccine booster effectiveness:

https://fediscience.org/@MiguelHernan/109331025655365201

#epidemiology #biostatistics #epitwitter #statstodon #epiVerse @epiVerse