Discover and read the best of Twitter Threads about #observational
Most recents (6)
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...
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.
... 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...
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...
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👇
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...
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.
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.
1/
We've just confirmed the effectiveness of the Pfizer-BioNTech vaccine outside of randomized trials.
Details @NEJM: nejm.org/doi/full/10.10…
Yes, great news, but let's talk about methodological issues that arise when using #observational data to estimate vaccine effectiveness.
We've just confirmed the effectiveness of the Pfizer-BioNTech vaccine outside of randomized trials.
Details @NEJM: nejm.org/doi/full/10.10…
Yes, great news, but let's talk about methodological issues that arise when using #observational data to estimate vaccine effectiveness.
2/
A critical concern in observational studies of vaccine effectiveness is #confounding:
Suppose that people who get vaccinated have, on average, a lower risk of infection/disease than those who don't get vaccinated.
Then, even if the vaccine were useless, it'd look beneficial.
A critical concern in observational studies of vaccine effectiveness is #confounding:
Suppose that people who get vaccinated have, on average, a lower risk of infection/disease than those who don't get vaccinated.
Then, even if the vaccine were useless, it'd look beneficial.
3/
To adjust for confounding:
We start by identifying potential confounders.
For example: Age
(vaccination campaigns prioritize older people and older people are more likely to develop severe disease)
Then we choose a valid adjustment method. In our paper, we matched on age.
To adjust for confounding:
We start by identifying potential confounders.
For example: Age
(vaccination campaigns prioritize older people and older people are more likely to develop severe disease)
Then we choose a valid adjustment method. In our paper, we matched on age.
ATTN #CBD stakeholders: @US_FDA today holding scientific conf. on CBD/other #cannabinoids. I'll be live tweeting throughout. Not sure we'll get much insight on immediate path forward for consumer products but I'll share noteworthy observations. Agenda: bit.ly/3pHXU8V
I'll be paying particular attention to @DrAbernethyFDA's remarks at 9:05a (head of #FDA's #CBD Policy Working Group) and @DThrockmortonMD's keynote at 9:15a (one of Agency's principals for regulating R&D, manufacture & marketing of #cannabis & cannabis-derived #drug products).
BREAKING: Risk of #COVID19 hospitalization in 77,590 persons with #HIV by antiretroviral type:
TDF/FTC: 10.5
TAF/FTC: 20.3
ABC/3TC: 23.4
Other: 20.0
per 10,000 (Febr-April 2020)
WANTED: Randomized trials of TDF/FTC (Tenofovir/Emtricitabine)
doi.org/10.7326/M20-36…
TDF/FTC: 10.5
TAF/FTC: 20.3
ABC/3TC: 23.4
Other: 20.0
per 10,000 (Febr-April 2020)
WANTED: Randomized trials of TDF/FTC (Tenofovir/Emtricitabine)
doi.org/10.7326/M20-36…
That is, individuals on TDF/FTC had about half the risk of #COVID19 hospitalization than those on TAF/FTC or ABC/3TC.
Rate ratio 0.53 (95% CI 0.29, 0.95)
journals.lww.com/epidem/Citatio…
Any reasonable person should be concerned about confounding, so we did the following 3 things
👇
Rate ratio 0.53 (95% CI 0.29, 0.95)
journals.lww.com/epidem/Citatio…
Any reasonable person should be concerned about confounding, so we did the following 3 things
👇
1) We restricted the analysis to individuals younger than 60 years, who have the lowest prevalence of comorbidities.
Rate ratio of #COVID19 hospitalization: 0.55 (0.29–1.04) for TDF/FTC compared with TAF/FTC.
Confounding by comorbidities appears less likely now.
Rate ratio of #COVID19 hospitalization: 0.55 (0.29–1.04) for TDF/FTC compared with TAF/FTC.
Confounding by comorbidities appears less likely now.
#Causalinference that talks the talk and walks the walk.
Claim: "Continuing #breastcancer screening past age 75 doesn't reduce 8-year breast cancer mortality."
Emulation of a #TargetTrial led by @xabieradrian with Medicare data
doi.org/10.7326/M18-11…
Let the discussion start.
Claim: "Continuing #breastcancer screening past age 75 doesn't reduce 8-year breast cancer mortality."
Emulation of a #TargetTrial led by @xabieradrian with Medicare data
doi.org/10.7326/M18-11…
Let the discussion start.
@xabieradrian @AnnalsofIM @HarvardEpi @harvard_data @HarvardBiostats @HarvardChanSPH @CMSGov @CMSgovPress @MonganInstitute @MassGeneralNews 2)
Because there's so much talk about #causalinference around here.
Computer scientists, economists, statisticians... talk a lot about the merits of #DeepLearning, instrumental variables, or whatever their preferred methodology is.
Everybody: This is your chance to shine.
Because there's so much talk about #causalinference around here.
Computer scientists, economists, statisticians... talk a lot about the merits of #DeepLearning, instrumental variables, or whatever their preferred methodology is.
Everybody: This is your chance to shine.
3)
No more toy examples. A real world question:
"At what age should #breastcancer screening stop?"
Need to compare the mortality of women under two dynamic screening strategies using a database of insurance claims with time-varying treatments and confounders.
How'd you do it?
No more toy examples. A real world question:
"At what age should #breastcancer screening stop?"
Need to compare the mortality of women under two dynamic screening strategies using a database of insurance claims with time-varying treatments and confounders.
How'd you do it?
