Miguel Hernán Profile picture
May 30, 2018 5 tweets 3 min read Read on X
Today Mendelian Randomization (MR) is usually implemented as a form of instrumental variable (IV) estimation.

Aware that valid #IVestimation requires strong assumptions, MR advocates often retreat to the position that MR numerical estimates need not be taken seriously...
Their position: The goal of MR is to "test causality". MR studies aren't designed to yield a valid numerical IV estimate of causal effect. MR studies are designed to answer a yes/no question: Is the causal null hypothesis true?

But retreating to *null testing* is problematic...
1) If the goal of MR is simply to test the null, then why use #IVestimation at all? MR papers should just report the association between the genetic trait (proposed IV) and the outcome.

This is the routine approach in RCTs to test the null. It’s called intent-to-treat approach.
2) If the goal of MR is simply to test the null, we don't need #IVestimation but we still need an IV.

That is, all criticisms of genetic traits as IVs continue to apply even if the goal is redefined as "just testing the null." See recent discussion here
3) "Retreating to null testing" raises other serious problems when, as in most MR studies, the underlying exposure is time-varying. Even if the genetic trait were a true IV!

Sonja Swanson, Jeremy Labrecque (@radarlake) and I discuss IV null testing here:
link.springer.com/article/10.100…

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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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