> nobody ever reports confidence intervals

But the article[0], in PNAS, has confidence intervals.

[0] http://www.pnas.org/content/early/2018/07/31/1800097115

They don't report it in their abstract, which is all the majority of HN has access to. As a result any conclusions reached will be unfounded. (Unless someone gets the paper and tells us what it said, which is what the linked article's authors were supposed to be doing...)

Edit: The thing is that in the abstract no form of statistical indicator was reported. That plus its absence from the linked article means that unless someone here can get access to the paper our discussion is in vain.

As much as people like to talk about how P values are not useful and debate what values we should use, I don't think there's an especially compelling reason to choose confidence intervals over P values, or complain that one is appropriate and the other is not. They both measure the relationship between statistical likelihood and parameter values. P values fix the parameter values and measure the statistical likelihood, confidence intervals fix the statistical likelihood and measure the parameter values. So if you ask for confidence intervals and they give you a P-value, well you have a confidence interval it just won't be a nice round number like 95% or 99%.

It's kind of like complaining that you ordered 1 kg of water but were delivered 1 l, and insisting that everyone measure water by weight rather than volume. Don't read too much into that analogy, but the relationship between P values and confidence intervals is of a broadly similar nature.

Knowing there are over 500k patients in the sample, you can calculate the error bars.

Well, ideally you would know more than just the number of patients. The roughest estimate would be to compute the expected variance of a binomial distribution with N=120e3 and P=0.12, which gives a standard deviation of 0.00094, so a difference of 0.5% is well over 5 standard deviations out. Not quite good enough for particle physics, but you're damn right it's good enough for medicine.

Now you just have to look at group sizes, possible confounding factors, etc...

Also a p-value would be nice.

Click on the link to the actual study, you will see P values right there in the abstract.