Tro!
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Replying to @ethanjweiss @DoctorTro and
I'm curious what you'd say,
@ethanjweiss. The "reverse causality" hypothesis doesn't really work in this case, as these are all very elevated LDL-C levels 16 years prior... and likely not a coincidence they match up with high HDL and low TG, no?2 replies 0 retweets 3 likes -
Replying to @DaveKeto @ethanjweiss and
The obvious answer would be survivorship bias of some description. People who survive to 100 are weird in many ways!
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Replying to @GidMK @ethanjweiss and
... and yet, they are surprising near uniform in the triad thus far. I’m excited to see upcoming centenarians and how much/little we see this phenomenon continue.
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Replying to @GidMK @ethanjweiss and
I want to see how common the triad is in centenarians (High LDL, high HDL, low TG) when tested a decade and a half earlier.
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Replying to @DaveKeto @ethanjweiss and
But you'd still be seeing survivorship bias there. You're seeing the people who, for whatever reason, can be in that state and live for a long time. Doesn't say much about the rest of the population imo
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Replying to @GidMK @ethanjweiss and
Survivorship bias makes sense if we were testing these 100/101 year olds a year earlier. But I'm emphasizing these markers (high LDL, high HDL, low TG) were taken 15 years earlier when they were age 84/85. The other 118 of those 84/85 taken at that time are not centenarians.
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Replying to @DaveKeto @ethanjweiss and
Well, the sample size is still tiny. But even so, the case-control you're suggesting would definitely be open to survivorship bias, because you're selecting people who have lived a very long time. More appropriate to start at, say 50, and see how many make it to 100
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Replying to @GidMK @ethanjweiss and
Technically, the sample size is 124 of those 84/85 in the NHANES dataset. The five are the ones who have categorically survived to 100 and are still alive at last check.
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Mmmm but for this kind of study 124 is still far too few. You'd want at least that many cases, and then link to 2-3x as many matched controls. Even then, it's going to be biased, but at least you'd be able to make some statistical comparisons
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Replying to @GidMK @ethanjweiss and
I don’t disagree. But as an epi guy, you know what it means when correlations are running counter to expectations of a given hypothesis of causality. If we’re seeing more and more people who test decades earlier with the triad showing greater longevity, this would be powerful.
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Replying to @DaveKeto @ethanjweiss and
Not necessarily. I mean, firstly, depends on what you mean by "more and more". Another 5 would be an interesting statistical blip, another 100 might be worth investigating
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