David Nunan Profile picture
Sep 30, 2019 6 tweets 4 min read Read on X
You’re going to hear a lot about red meat tomorrow. @AnnalsofIM has published 4 SRs & recommendation from Gordon Guyatt & others.

Here was my take for @SMC_London

And an old thread that is relevant here. Image
@AnnalsofIM @SMC_London Also, folk might like to see the reactions of other ‘experts’ here:

@AnnalsofIM @SMC_London In particular, Rod Jackson’s (Auckland) comments chime with me: ImageImage
Let’s not forget that the latest #redmeat studies do not recommend eating MORE meat!

They just don’t have much confidence in the evidence they reviewed that underpins the observed small increased risk with eating 3-4+ servings per week.
Just realised could have phrased some things a bit better.
When I (& others) say “small benefits”, what we mean is that only a few people (out of many, say 1000) see the benefit. That’s not to say that the health outcome(s) that benefit are not important, especially to you.

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More from @dnunan79

Feb 29
Lots of takes on this. Many are what people have anyway regardless of this paper, such is the general diet/nutrition discourse, and particularly around UPF.

For those of you interested in what an actual evidence-based approach to this paper looks like, buckle up🧵

1/
In my view it is a good example of pervasive issue in the way most medical/health research is interpreted, and this even includes the authors themselves.

What’s the issue?

IGNORING UNCERTAINTY!

2/
A key function of a systematic review is to inform as to how certain we can be that the available data provides an observable truth.

There are different methods a review team can take. One of the most commonly used in med/health research is GRADE.

3/ Image
Read 26 tweets
Sep 22, 2022
"It's going to protect YOU..."
"It will reduce YOUR risk of a heart attack, cancer, diabetes etc".

We see this all the time when it comes to medical treatments and health interventions.

I'm going to show why 99.9% of the time this type of phrasing/framing ("YOU/R") is wrong🧵
When people hear these phrases with "YOU" / "YOUR" in them, it's most likely they will perceive the benefits & risks of treatment/intervention in relation to their own personal benefit/risk. The thing is, we do not, & cannot, know your own personal benefit/risk.
The vast majority of the time we only have information on groups of people (samples). Benefits/risks in this context relate to the numbers of people (with a similar health profile) among the group who either do or do not experience a given health outcome.

An example to help...
Read 17 tweets
Feb 8, 2022
ON MISINFORMATION

Here's the thing. You cannot police it in a fair, reproducible & representative way.

The reason being is the lines between misinformation and genuine uncertainty soon become blurred.
Trust me, I tried.

(ps. does this tweet count as misinformation)
I mean, look at Twitters own criteria.
"...widely available, authoritative sources'

Trouble is these sources are dealing mainly with evidence/information in the Green zone.
Lots of examples of the difficulty in this area.

Here's @cochranecollab being censored for spreading "harmful false information" (for the 2nd time)
Read 9 tweets
Apr 22, 2021
So here's the thing with this. I posted a tweet out of frustration of seeing an organisation promote evidence from a commentary piece as if it were proof a question had been answered. No uncertainty. Proof.
/1
The same organisation didn't mention a systematic review attempting to answer the same question (which happened to show uncertainty). Yes, the organisation was aware of the review's existence.
This signals, to me, an agenda. It's also a good example of the state of things.
/2
The state of things in relation to evidence and "evidence-based". It's a state I worry about, hence the original tweet.
This isn't about the topic/question. It's about the principle. Of promoting selected information as if it is proven fact, ignoring info that might contest.
/3
Read 15 tweets
Feb 5, 2021
Our latest publication revisits a well-known problem: reporting of relative effect estimates without absolute effects in journal publications of clinical trials:

ebm.bmj.com/content/early/…

🧵on this issue
("nah, show me the findings": )
First an intro to the problem. A practical example is probably best here. Take a look at the image. How many more people are at increased risk bowel cancer? Image
I'll be nice by making it multiple choice:
Read 46 tweets
Jan 2, 2021
Lots of folk already commented on “1 or 2 dose”. One thing that comes up often is “efficacy”, followed by numbers like “80%”, 95%”. In many cases, it reads as if folk think this is how much YOUR chance of getting the virus is reduced by. That’s incorrect.
These figures are actually the relative risk reduction (RRR) of infection with the vaccine. Eg. 2000 people without Covid-19 - 1000 vaccinated (group 1), 1000 not vaccinated (group 2).
200 people (20%) in group 2 get Covid-19
10 people (1%) in group 1 get Covid-19
= 95% RRR
The absolute effect is 19% (difference between 1% and 19%).

Another way of putting it = in 1000 people who don’t have Covid and are not vaccinated, 200 will catch it.
If the same 1000 people had the vaccine, 10 would get it, meaning 190 will be spared.
Read 11 tweets

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