Miguel Hernán Profile picture
Nov 10, 2019 5 tweets 6 min read Read on X
1/
Suppose you want to extend causal inferences from a randomized trial to a target population.

Is that #transportability or #generalizability?

Issa Dahabreh and I propose an answer in this brief commentary in the European Journal of Epidemiology:
ncbi.nlm.nih.gov/pubmed/31218483 Image
2/
For those interested in methods for extending inferences from randomized trials to a target population:

Take a look at our tutorial
arxiv.org/pdf/1805.00550…
(soon to appear in Statistics in Medicine)

You will find identification conditions AND three estimation approaches. Image
3/
Want more?

This article in @Biometrics_ibs considers estimators to generalize inferences from individuals in randomized trials to all trial-eligible individuals:
ncbi.nlm.nih.gov/pubmed/30488513

And this article in @EpidemiologyLWW clears some confusions:
journals.lww.com/epidem/fulltex…
@Biometrics_ibs @EpidemiologyLWW 4/

Do you—like @yudapearl below—prefer to express your #generalizability assumptions using causal diagrams?

No problem. Led by Issa Dahabreh, here
arxiv.org/abs/1906.10792
we use graphs to examine the conditions for generalizability of causal inferences from a #randomized trial. Image
5/

Also, so much talk about extending results from #randomizedtrials to a target population.

But so little guidance on how to design data collection.

Here we provide a unified description of study designs for #transportability and #generalizability.
pubmed.ncbi.nlm.nih.gov/33324969/ Image

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More from @_MiguelHernan

Jun 19, 2023
1/
One day everyone will recognize #selectionbias due to a #collider and the world will be a better place.

This time observational studies found a higher risk of omicron reinfection after a 3rd dose of #COVID19 vaccine. As usual, alarms went off.

Can you see the obvious bias? Image
2/
Those who receive a booster and get infected are, on average, more susceptible to infection than those who don't receive a booster and get infected.

So no surprise than those who receive a booster and get infected are more likely to get reinfected.

Led by @susanamcorella...
3/
... we described the bias @bmj_latest with simulations + real data.

We show that a vaccine booster will be associated with higher reinfection risk even if the booster has no harmful effect.

Now the good news: Preventing this #selectionbias is easy...
bmj.com/content/381/bm…
Read 6 tweets
Apr 13, 2022
1/
Our findings on a fourth dose (2nd booster) of the Pfizer-BioNTech #COVID19 vaccine are now published.

Compared with 3 doses only, a fourth dose had 68% effectiveness against COVID-19 hospitalization during the Omicron era in persons over 60 years of age.

Interestingly...
2/
... this is yet another example of the need for good #observational studies that emulate a #TargetTrial.

Would it be better to have a real randomized trial? Yes

Do we have a randomized trial? No

Will we have a randomized trial? Perhaps, but too late for a timely decision.
3/
Last year, observational evidence was also used to recommend a first vaccine booster.

Our and others' studies provided evidence on the booster's protection against hospitalization after infection with Delta:


Policy makers listened. Lives were saved...
Read 8 tweets
Dec 3, 2021
1/
We emulated a target trial of two #COVID19 mRNA vaccines in the largest healthcare system in the US.

Both vaccines were similarly effective, with Moderna slightly better than Pfizer-BioNTech.

But that isn't the most important conclusion of our study.

2/
Spring of 2020: #COVID19 vaccines are developed.

October 2020: Results from randomized trial are announced.
businesswire.com/news/home/2021…

~6 months from development to evaluation of effectiveness.

Utterly impressive. Unprecedented.

Kudos to the pharmaceutical industry.

Now...
3/
December 2020: Vaccines become available.

December 2021: Where are the big randomized trials for COMPARATIVE effectiveness?

1 year, still *crickets*

Billions of taxpayer dollars and we don’t get to know which vaccine is better and safer?

Not so impressive, pharma industry.
Read 6 tweets
Aug 25, 2021
1/
Vaccine safety: We compared excess adverse events after #COVID19 vaccination (Pfizer-BioNTech) and after documented #SARSCoV2 infection.

nejm.org/doi/full/10.10…

Take-home message: Low excess risk of adverse events after vaccination, higher after infection.

Some thoughts👇
2/
Preferring #SARSCoV2 infection over vaccination has become even harder. (Remember: infection also increases the risk of severe disease/death)

This is a good illustration of how #randomized trials and #observational studies complement each other for better #causalinference...
3/
The original #randomized trial estimated vaccine effectiveness to prevent symptomatic infection, but was too small to quantify vaccine safety.

That's what #observational studies do.

Now a different sort of question: Why could we do this study in the first place?

2 reasons.
Read 8 tweets
Mar 18, 2021
1/

Many countries are vaccinating their elderly. Can we relax control measures now?

No.

Even with 50% of elderly vaccinated, uncontrolled #SARSCOV2 transmission may overrun the healthcare system.

We explain @AMJPublicHealth today, led by @_gmales
ajph.aphapublications.org/doi/10.2105/AJ…
2/

Data from Madrid, Spring 2020:

Critical care requirements peaked at 5 times the usual capacity.

Hospitals managed to increase ICU capacity by 3-fold.

Heroic but, sadly, insufficient.

The healthcare system collapsed. Not everybody who needed critical care received it.
3/

If 50% of the elderly had been vaccinated, critical care requirements still would have peaked at almost 4 times the usual capacity.

Greater than the ICU capacity of any country in the world.

Only a prolonged lockdown could return ICU requirements to normal.

One last thing:
Read 4 tweets
Mar 12, 2021
@ProfMattFox 1/
The odds ratio from a case-control study is an unbiased estimator of the

a. odds ratio in the underlying cohort when we sample controls among non-cases

b. rate ratio in the underlying cohort when we use with incidence density sampling

No rare outcome assumption required.
@ProfMattFox 2/
Because the odds ratio is approximately equal to the risk ratio when the outcome is rare, the odds ratio from a case-control study approximates the risk ratio in the underlying cohort when we sample controls among non-cases and the outcome is rare.

But...
@ProfMattFox 3/
... for an unbiased estimator of the risk ratio (regardless of the outcome being rare), we need a case-base design, not a classical case-control design.

Of course, all of the above only applies to time-fixed treatments or exposures.

As for the causal interpretation...
Read 5 tweets

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