Introduction to target trial emulation: Worked

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Introduction to target trial emulation: Worked

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Introduction to target trial emulation: Worked example Susan Hoffman, MPH Department of Epidemiology Emory University SPER Methods Workshop June 17, 2024 Follow along! https:github.comssb214SPER24 2 Study background Caniglia, et al.

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Introduction to target trial emulation: Worked example Susan Hoffman, MPH
Department of Epidemiology
Emory University SPER Methods Workshop
June 17, 2024

Follow along! https://github.com/ssb214/SPER24 2

Study background Caniglia, et al. (2023) – on GitHub
Exposure: Antibiotic initiation at or after 24 weeks gestation through 36 weeks gestation
Outcome: Preterm delivery 3

Causal contrast Intention to treat effect
The effect of being assigned to treatment, not the effect of the treatment itself
No confounders 4

Causal contrast Observational analogue of the intention to treat effect
Now, we need to control for confounders (in this example, maternal age, parity, and HIV status)
The risk ratio is the estimate of interest 5

“Data” structure 6

Code overview https://github.com/ssb214/SPER24

Step 1: estimate a RR for each target trial within week 24-36 8

General model for weeks 24-36 9

Quick note: Families and links 10

Sequential target trials within each week 11

Pulling results 12

Step 2: estimate RR for pooled results across weeks 24-36 13

Pooled model 14

Pooled results Now we have the Beta estimates for the model, but because people can be present in more than one trial, we need to use the bootstrap for SE 15

The bootstrap https://engineering.atspotify.com/2022/03/comparing-quantiles-at-scale-in-online-a-b-testing/ 16

The bootstrap 17

The bootstrap 18

The bootstrap 19

Pooled results 20

21

Questions? 22 Email: ssbucke@emory.edu

Introduction to target trial emulation: Worked

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