Individual evaluation

I dare to write to you because I have great doubts of interpretation, about how to translate the evidence from Mendelian randomization, randomized controlled studies and observational evidence as a set of statistical data to an individual view of risk, in which all variables change together all the time.

That is, can I infer that since LDL is causal according to medical societies, any increase in this marker will increase risk at the individual level in a blood test?

That the risk goes up if everything stays the same except that LDL, tells me little, given that as we know all states will change completely and therefore would not be comparable. am I right?

Doctors say all the time, LDL the lower the better most of the time, but is it possible or correct to deduce this in each person with existing tests?

What reading/book do you recommend to draw accurate conclusions on this particular topic and concept?

Thanks in advance for any answers that will help me understand these surely very basic concepts for you .

You might find this other thread and the some of the cited papers useful: Risk based treatment and the validity of scales of effect

Primary care physicians routinely try to estimate patients’ future risk for adverse cardiac events (e.g., MI) using risk calculators. While imperfect, they are the best we can do in everyday practice at this time. This site provides several options for risk calculators:

The physician enters a patient’s risk factors into the calculator (e.g., age, smoking status, blood pressure (treated or not), diabetes status, lipid levels) and the calculator estimates the 10 year risk of MI for a patient who is not taking a statin. You can then repeat the risk estimation if the patient were to start taking a statin. You can change various risk parameters to see how estimated future MI risk changes (e.g., you can show the patient how his risk would go down if he were to stop smoking).

Hope this helps.


Thank you very much, I will read this post carefully. I know in detail the risk calculators, but I am sure I will get a lot from these documents.

The question or my point would be more on:

  • Is it scientific to state that LDL the lower the better whenever possible because it is a causal effect, with observational triangulation, randomized controlled studies and Mendelian randomization, from an individual and cardiovascular point of view?


I’m not sure I’d phrase things quite this way, since patients are the ones who make the ultimate decisions about their health, not the physician. The patient will decide whether the estimated benefit of a long-term preventive therapy outweighs his/her personal “dysutility” with regard to taking a pill. I have patients with coronary stents who still refuse to take a statin in spite of discussions with me and multiple cardiologists. Conversely, I have other patients whose estimated future MI risk is at the low end of the moderate range who immediately jump at the chance to start a statin because they want to do everything possible to decrease their future risk (or know someone who died a premature death from coronary disease).

There is some emerging evidence that cumulative lifetime exposure to LDL is an important consideration, such that starting LDL-lowering treatment earlier in life could generate larger longer-term benefits than waiting until later in life. But getting huge swathes of young, otherwise healthy patients to start taking any pill for preventive purposes would likely be a hard sell (except in the case of familial hypercholesterolemia).

If you are expressing uncertainty as to whether LDL actually lies on the causal pathway in the development of atherosclerosis, I don’t think there’s any remaining doubt that this is the case. The evidence is overwhelming.


But we are talking more about whether or not it is a scientific claim based on proven facts.

What I mean again is that assuming the hypothesis of LDL causation. In an individual X that statement would be as much as saying that any state LDL-c below another any state with a higher LDL will lead to a better end result.

I consider that an illogical mantra with the existing evidence, assuming causality as a starting basis of course.

Thank you for your kindness in answering

We know without a doubt that taking a drug (statin) that is intended to lower LDL lowers cardiovascular event probability even for mildly elevated LDL.


Wouldn’t that viewpoint be to set aside the existing pleiotropies of statins? Or that in the few studies with isolated high LDL it seems that the effects are other, as in 4s post hoc, or TNT for example?

Could we be facing a Simpson’s paradox with the information available so far? Is Mendelian randomization still subject to this bias? Yes, from my point of view, but you are much more aware of these limitations and in-depth knowledge.


Thank you @ESMD for referring to my previous post and alerting me to this discussion. In addition to specific questions about LDL-cholesterol as a modifiable risk factor for atheromatous disease, you @Novato_Deseoso seem to be raising issues about the nature of causation and how to design experiments to test for it. You must not forget that the link between lipids and vascular events was established because hypotheses about formation of the underlying atheroma suggested the link in the first place. An important text about casual inference is: Hern´an MA, Robins JM. Causal Inference: What If. Boca Raton: Chapman & Hall/CRC, 2022. There is a free downloadable version here: Causal Inference: What If (the book) | Miguel Hernan's Faculty Website | Harvard T.H. Chan School of Public Health

According to my understanding of causal inference, an important concept is that of a ‘modifiable risk factor’. A RCT on statins should show not only a lowering in incidence of vascular events but also a corresponding reduction in the LDL-cholesterol if the latter reflects the underlying causal mechanism. We can expect the risk reduction to be proportional to the pre-treatment LDL-cholesterol value as suggested by @f2harrell. However, we would not expect to see a reduction of other risk factors for vascular events such as age or the blood pressure. When we calculate the effect of reduction in vascular events due to statins, we should only do so via the lowering effect on LDL-cholesterol and what the new risk is due to the new, lowered LDL-cholesterol.

If there are other risk factors (e.g., old age, high BP) then we can’t expect a statin to reduce these and their effect on risk of vascular events as well. However, this is what some tools do such as: 3. These multivariable risk factors work by adding individual risks where patient’s risk score = intercept + (bsex×sex) + (bage×age) + (bBP×BP) + (bLDL×LDL) etc.) when bsex, bage, bBP, and bLDL are regression coefficients that describe how a patient’s values of the predictor variables affect risk. Treatment only affects the relevant values of sex, age, BP and LDL (only the LDL in this case). By applying the risk reduction from statins to the overall risk we are also assuming that statins change sex, reduce age and BP as well as the LDL-cholesterol. If you wish to base the risk of vascular events on other risk factors related to LDL-cholesterol, I suppose you need to build these into your multivariable risk calculation and estimate the effect of statins on them…


Thank you very much for your valuable contributions.

In the triangulation that is often made of observational, RCT and Mendelian, I think we make the mistake of ecological associations, which leads us to a very biased perspective of what may actually be happening, from my limited ability to assess the limitations of the studies compared to you.

We have studies where polygenic indices completely eliminate any association with LDL, which is very telling.

Could we be looking at a simple projection that picks up all the time people with birth matches that if you pour gasoline on them they burn, and conversely those that you don’t pour gasoline on them don’t burn, and mixing it with people with lipid triad so extraordinarily present in society?

For example, Velican’s studies of very slight morphological modifications could be among others, those matches, which I understand is undetectable by any type of study, since it would only be the match of the group where we pour more gasoline.

Than you

I’m not sure about this statement…

Most physicians were not trained to interpret regression equations (me included). So most of us have to trust that many eminently qualified statisticians were involved in the development of risk calculators that have been used globally for decades, and in advising physicians about how best to “transport” the results of RCTs to the patients we see in clinic. While not impossible, it seems, to me at least, quite implausible that we’ve all been doing things wrong for the past 25 years.

For whatever it’s worth, this is how I conceptualize the causal path:

:new: I’m thinking of all this using the framework shown in figure 10 of this publication:

I’m really trying to understand your concerns, Huw, and I wonder if the underlying causal diagram is the main point of contention. I sense that you perceive an inconsistency between how CV risk factors are treated in the process of estimating an individual patient’s future MI risk, versus how we conceptualize the potential “relative treatment effect” of statins.

Specifically, you seem to be viewing CV risk factors as “prognostic” factors, such that non-lipid risk factors (e.g., smoking/HTN/DM2/age) would not be expected to biologically “modify” the relative treatment effect of statins (e.g., the HR) in a statin RCT. In contrast, my conceptualization above treats the non-lipid risk factors as both “prognostic” and “predictive” [a view that seems, to me, to be more in keeping with our current biologic understanding of the interactivity of various CV risk factors].

I sense that you are troubled by what you perceive to be a “bait-and-switch” with regard to how the medical community estimates potential statin benefits. I think you’re saying that if we are going to treat non-lipid risk factors as strictly “prognostic” for the purpose of estimating a patient’s future MI risk (i.e, no arrow from the other CV risk factors toward " :arrow_up:plaque stability/ :arrow_down:plaque progression"), then we shouldn’t act like treating a patient with a “good” LDL with a statin could, under any circumstances, be expected to confer much CV protection (?) In contrast, as discussed previously, I tend to view the underlying known biology as strongly supportive of a view of LDL as interactive with the other risk factors, as though some patients will just “tolerate” a given LDL level better than others, depending on the presence/absence of other risk factors. While you seem to view the proposed interactivity of CV risk factors as post-hoc rationalization that is being used to bolster the perceived benefits of statins in primary prevention contexts, I view the interactivity as strongly supported biologically.


I don’t think you’ll find any serious scientist who doubts the role of LDL in atherogenesis. There are many “bad actors” (including a very small number of medical professionals who have, unfortunately, very loud voices) who have built lucrative careers around sowing doubt about the role of LDL in atherogenesis by appealing to the conspiracy-minded segment of the population (which is not small). They are, without a doubt, responsible for countless premature deaths from coronary disease globally. Primary care practitioners and cardiologists fight hard to counter these highly pernicious forces every day in clinic. These grifters should be assigned to console the children of patients who have dropped dead prematurely from an MI that might have been prevented if only they hadn’t read a screed from “that famous doctor (insert bad actor MD or PhD of choice) on the Internet.”


Very much in agreement, that is why recent findings are so relevant and many recent discussions and perspectives.

My point has nothing to do with what you indicate in this sentence. But there are many, many points that outweigh already at this point LDL which is clearly off under APO B or Non-HDL-c, not to mention Lp(a) or high draft opinions like Libby’s who is far from being a denialist.

But my question is more about statistical plausibility and evaluation of the existing science and the limits of each type of study, than about the existing evidence which I know quite deeply and follow on a daily basis. Thank you very much for participating

I try to go deeper into these questions about the existing gaps in the types of research available to us in this specific subject.

Hi again Erin

I agree with your conceptual diagram. However, if the risk from young age, non-diabetic status, non-smoking status and normotension was 4% and that from pre-treatment LDL-C was 5% then on the additive scale the total risk would be 4%+5% = 9%. On a statin the new risk would be still 4% from the 4 risk factors but 5% x 0.6 = 3% from a risk reduction of 0.6 from high dose statin. Therefore, the new risk by applying a risk reduction on the additive scale would be 4%+3% = 7%. However, by applying the risk reduction to all risk factors, the new risk on statin treatment would be 0.6(4%+5%) = 4% x0.6 + 5%x0.6 = 2.4%+3% = 5.4%, lower than the 7% and therefore exaggerating the risk reduction in that patient.

I am not saying that statins are not important in preventing vascular events or do not work. Far from it. If I was presented with someone with a high risk of vascular event and a high HbA1c, a high BP but a low LDL-cholesterol, then I would persuade the patient to allow me to help to improve diabetic and BP control and focus on this at least initially. I do not believe that much would be gained from offering a statin as the risk reduction would be small when calculated on the additive scale (unless there is a RCT that contradicts this). I would not burden the patient with another pill. However, if the LDL-cholesterol was also high or the patient was already known to have had a vascular event, then I would add a statin because the expected risk reduction would be greater. Also, if a 75-year-old person with an inevitably high risk of a vascular event in the next 10 years had a low LDL-cholesterol, low BP, and no diabetes etc, I would not recommend medication.

As far as I understand, this is how most physicians would have been reasoning over the past 25 years. In this sense they would not assume that they should treat a high risk of vascular event with a statin irrespective of its cause(s). You seem to assume that there is a very strong interaction between non-lipid based risk factors (e.g. age) and lipid-based risk factors, which should be modelled by an effect on all the risk factors (which if untrue would potentially increase sales of statins unjustifiably). However, as far as I can understand, the way that multivariable risk factors are calculated assumes that there is no such interaction at all so that there is independence between risk factors (maybe @f2harrell could comment on this). Perhaps the truth lies in between. Establishing such a truth would be very difficult as we discovered by looking at the literature previously (Risk based treatment and the validity of scales of effect - #12 by HuwLlewelyn).

Hi Huw

I would put this patient on a statin and would prioritize getting him on a statin and controlling his BP over controlling his blood sugar (though I would also put him on an SGLT-2 inhibitor and/or GLP-1 agonist if he needed something to bring his sugar down).

I think we’ll have to agree to disagree on this point.

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I would not disagree strongly with you as the evidence is very flimsy on these issues. I would give my reasoning and suggestions to the patient, who might well ask for a statin for a low LDL-cholesterol as you would recommend. However, if we accept the assumptions and reasoning used to construct multivariable risk scores, then to apply them logically, we should estimate the risk reduction based on the statin’s effect on lipids alone and not also on an assumption that statins reduce age, BP etc (an assumption that the risk calculators do not make). If the risk calculation were to be changed to take into account some way that age, BP etc modify the effect of statins on vascular risk, then that would be a different matter.

"Interpretation: Atorvastatin 10 mg daily is safe and efficacious in reducing the risk of first cardiovascular disease events, including stroke, in patients with type 2 diabetes without high LDL-cholesterol."

“For primary prevention, most trials and meta-analyses have demonstrated a significant benefit of statin therapy in reducing cardiovascular events in those with diabetes.”

Primary prevention for people with and without type 2 diabetes


offer atorvastatin 20 mg for the primary prevention of CVD to people who have a 10-year QRISK3 score of 10% or more. [2023]

Statin Treatment Recommendations

  1. The following are guideline recommendations for statin treatment:
  • Patients ages 20-75 years and LDL-C ≥190 mg/dl, use high-intensity statin without risk assessment.
  • T2DM and age 40-75 years, use moderate-intensity statin and risk estimate to consider high-intensity statins. Risk-enhancers in diabetics include ≥10 years for T2DM and 20 years for type 1 DM, ≥30 mcg albumin/mg creatinine, eGFR

“This meta-analysis is the largest in terms of pooling results from the largest number of articles and sample size. The main results indicate that statin use in patients with diabetes is associated with a reduced risk of CVD events and ischemic stroke in primary and secondary prevention, but is not associated with reduced all-cause mortality in either group”

Esential “The mechanism by which statins reduce the risk of CVD and stroke in diabetes is related to the potential protection of endothelial cell injuries induced by hyperglycemia”

“Diabetes may increase systemic inflammation, and increased inflammation and coronary calcification may counteract the effects of statins in patients with diabetes. Therefore, it seems reasonable to explain the negative results for mortality in patients with statin use and diabetes”

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This will be my final contribution to this thread. Since I don’t sense that anybody here is open to having his/her mind changed at this point, continuing to lob citations back and forth likely isn’t productive. More importantly, this discussion isn’t about statistics (the purpose of this forum).

From the paper you cite:

“Elevated inflammation and coronary plaque progression have been proposed in statin users [[42]”

I don’t find this statement credible. A more widely accepted explanation:

“Statin therapy appears to accelerate the process of transforming a potentially highly metabolically active plaque to a more inert state. Specifically, statin therapy is associated with a decrease in low-attenuation and fibro-fatty plaque volumes and an increase in high-density and 1K volumes. Higher calcium density is associated with slowed plaque progression…

This present analysis supports findings from the above literature, i.e., suggesting a role of statin therapy in accelerating plaque transformation from noncalcified to calcified content and thus aiding plaque stabilization.”

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I asked statistical questions, because it was not my intention to debate evidence in lipidology which I would be happy to do because it is a subject I study, but as you say it is not the right forum.

My questions remain open in the sense of the gaps or limitations of each of the evidences we consider to causality (observational, Mendelian and RCT), and the plausibility of the existing evidences showing the ideas I commented.

How do these three lines of evidence eliminate the possibility that it is one or more characteristics present in both groups that react with exposure and are inert in the absence of exposure?

Thank you all very much again

I’m sorry Erin. It was the above statement of yours that I was focussing on. If as you suggest, you replace ‘smoking’ with with ‘no smoking’, you get a risk reduction by repeating the ‘Mayo’ calculation. If you similarly replace the untreated lipid profile with a new improved lipid profile after treatment with a statin, you usually get a smaller risk reduction by repeating the calculation than that provided by the Mayo clinic site by clicking on ‘intervention’. Also a young person with a very low risk lipid profile but severe hypertension gets a surprising 40% risk reduction on a statin. None of these calculators include the risk from the presence of coronary artery plaque.

None of the studies on diabetics (e.g., Colhoun et al) summarise the absolute risk reductions for different baseline risks for each LDL-cholesterol value or of the overall kind provided by the Mayo clinic site. The whole thing is rather muddied (which is why I think that the evidence for making individual decisions is flimsy), leaving physicians to have to muddle through or over-simplify matters.