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Relative Risk vs Absolute Risk Reduction

Relative Risk vs Absolute Risk Reduction

I have written often and spoken repeatedly to so many of my patients about relative versus absolute risk.  This is so widespread in the medical literature, scientific literature and even in all advertising.  I am always waiting for that “aha moment” when you understand how relative risk management is chicanery.  It is used to sell you product.  To amplify, inflate or conflate results.

I am prompted to write this blog by a recent meta-analysis published in JAMA Neurology May 13, 2019 with the title Frequency of Intracranial Hemorrhage With Low-Dose Aspirin in Individuals Without Symptomatic Cardiovascular Disease A Systematic Review and Meta-analysisSounds ominous, doesn’t it?  Low-dose aspirin, increasing the risk of brain hemorrhage?  Especially to all of you are using low-dose aspirin (81 mg) as a preventive measure.

In June 2015, I had previously published on my own analysis of all the major statin studies showing negligible benefit.   So let’s expand upon this discussion.  Let me bombard you with numerous examples.

Analyzing Statin Studies and Efficacy

My favorite reference is Calculated Risks by Gerd Gigerenzer.  This is such a powerful book.  Simply stated and elegantly presented examples of the misuse of risk analysis, and other statistical games.  Let me quote briefly from his analysis on use of Pravastatin — a commonly used statin for “prevention of cardiovascular disease.”

 “Absolute risk reduction: the absolute risk reduction is the proportion of patients who die without treatment (placebo) minus those who die with treatment.  Pravastatin reduces the number of people who died from 41 to 32 in 1000.  That is the absolute risk reduction is 9 and 1000, which is 0.9%.

Relative risk reduction: the relative risk reduction is the absolute risk reduction divided by the proportion of patients who die without treatment.  For the present data, the relative risk reduction is 9÷41, which is 22%.  Thus, Pravastatin reduces the risk of dying by 22%

The relative risk reduction looks more impressive than absolute risk reduction.  Relative risks are larger numbers than absolute risk and therefore suggest higher benefits than really exist.  Absolute risks are a mind tool that makes the actual benefits more understandable.  – Gerd Gigerenzer

This really drives the point home.  Exactly as I had previously written.

Low Dose Aspirin and Intra-Cranial Hemorrhage

Now let’s look at the recent JAMA Neurology 2019 article.

I will quote the results showing relative risk ratios (RR).  Hazard ratio (HR) is nearly the same measure often quoted.  A RR or HR value of 1.5 = 50% increased risk.  Either of these are the most commonly cited  statistics in all the medical studies.

Here is an abstract of the results of the study.  And so frequently that is all you will see and believe.  Because most people, including even most physicians, will not read or analyze the paper.  We are too busy.

RESULTS: The search identified 13 randomized clinical trials of low-dose aspirin use for primary prevention, enrolling 134,446 patients.

Pooling the results from the random-effects model showed that low-dose aspirin, compared with control, was associated with an increased risk of any intracranial bleeding (8 trials; relative risk, 1.37; 95%CI, 1.13-1.66; 2 additional intracranial hemorrhages in 1000 people), with potentially the greatest relative risk increase for subdural or extradural hemorrhage (4 trials; relative risk, 1.53; 95%CI, 1.08-2.18) and less for intracerebral hemorrhage and subarachnoid hemorrhage.

CONCLUSIONS AND RELEVANCE Among people without symptomatic cardiovascular disease, use of low-dose aspirin was associated with an overall increased risk of intracranial hemorrhage, and heightened risk of intracerebral hemorrhage for those of Asian race/ethnicity or people with a low body mass index.   — Meng Lee et al

The key phrase here is overall increased risk.

So let me excerpt just one portion of data from the study to show you why the conclusion is inaccurate and essentially bogus.  The true incidence was tiny.  So relative comparisons are nearly meaningless.

Pay attention to the extreme right hand column, highlighted in yellow, which shows my added absolute risk.  This column is absent from all medical papers.

Low dose aspirin and intra-cranial hemorrhage risk Relative vs Absolute Risk Graphic

Now let me illustrate even more graphically.  It is all dependent on the sample size and true incidence.  What is the difference between relative and absolute risk or statistics with a sample size of 10, 100, or 1,000?  It is the entire story.  This first graphic shows a relative risk reduction of 50% across 3 sample sizes.   The large yellow arrow shows an equal risk reduction across these sample sizes.

Relative risk statistics inflate and conflate results

This is how they fool you.  The relative risk reduction is independent of the sample size.

Now let’s look at the absolute risk reduction across these 3 sample sizes.

Absolute risk statistics are more meaningful

It should become much clearer.  The absolute risk reduction (large yellow arrow) becomes almost invisible as the sample size increases.  That is the take-home message today.  Absolute risk reduction is entirely dependent on the sample size and incidence.  It is also, incidentally, what is necessary to determine the “numbers needed to treat (NNT).”  How large a sample size is necessary in order to arrive at meaningful results?   To find at least one event.

Poor Medical Reporting

I had previously quoted work by the highly respected Douglas Altman, D.Sc., in a short editorial in JAMA 2002.  Where he writes:

there is considerable evidence that many published reports of randomized controlled trials (RCTs) are poor or even wrong.  Despite their clear importance.  The results of several reviews of published trials briefly summarized in table 1.  Poor methodology and reporting are widespread.  — Douglas Altman, D.Sc.

He was such a tireless advocate of improving medical reporting, improving peer review and exposing the inadequacy of most published papers.

Two months months later in the Aug 2002 Scientific American, Benjamin Stix quoted this erudite statistician with his own comments on poor medical reporting.  Essentially lambasting (or exhorting) the entire medical literature community

Only the Best

Advertising campaigns routinely hype the most flattering claims to sell their products. Evidently so do papers in medical journals. Researchers at the University of California at Davis School of Medicine found too much emphasis given to favorable statistics in five of the top medical journals: the New England Journal of Medicine, the Journal of the American Medical Association, the Lancet, the Annals of Internal Medicine and the BMJ. The study, which looked at 359 papers on randomized trials, found that most researchers furnish a statistic only for “relative risk reduction”–the percentage difference between the effect of the treatment and a placebo. Just 18 included the more straightforward absolute risk reduction. If a treatment reduced the absolute risk from, say, 4 to 1 percent, it appears more impressive to present only the relative reduction of 75 percent. Researchers also failed to show other statistics that provide a more nuanced picture of the results of clinical trials. The article is in the June 5 Journal of the American Medical Association.(full pdf) —Benjamin Stix   [emphasis added for clarity – ed.]


Those of you who are followers of Dr. Peter Attia have also been treated to this same discussion of risk management, risk analysis, and poor statistical methodology.

So next time you read a headline — drug reduces risk 43%, a vitamin increases risk 14%, this car now accelerates 30% faster, or whatever, you will have a better appreciation of risk and performance.

“We won’t get fooled again” — The Who

Philip Lee Miller, MD

Carmel CA 93923

Is Cholesterol the Culprit?

Is Cholesterol the Culprit?

 Probably as long as you can remember, cholesterol is “known” to be the cause of cardiovascular (heart and blood vessel) disease.  Does dietary cholesterol cause heart disease?  What about familial super high cholesterol?  Does that cause heart disease?  The short answer is – probably not.  Let’s expand.  I have written extensively on the subject in the past.

Cholesterol has been studied since the early 1900s.  Initially in fits and starts. John Goffman studied cholesterol in the 1950s at Donner labs in Berkeley.  There was no interest.  So he turned to other pursuits.  The cumulative effects of low level radiation.  Lipid research picked up in the  1970′ and 80’s.

Remember, the admonition to limit your egg consumption consumption?  Or fats?  You should reduce fats to reduce your weight.  We have now found it didn’t work.  My good friend Dr. Ron Rothenberg  famously quips, “cholesterol: found at the scene of the crime – not guilty.”  How do we prove this assertion?

cholesterol: found at the scene of the crime – not guilty.  — Dr. Ron Rothenberg

Rudolph Virchow in the 19th century postulated that most human disease is a result of inflammation.  Most especially cancer, but probably vascular disease as well.  Later Sir Thomas Sydenham postulated, “a man is as old as his arteries.” So we have historical precedents for the cause of cardiovascular disease– inflammation.

“a man is as old as his arteries.” — Sir Thomas Syndenham

When I was young medical student, we looked at total cholesterol.  Over time the entire picture has evolved with more and more refinements and “precision.”  So we now look at LDL, HDL, and VLDL.  These are actually lipoprotein carriers of cholesterol and not cholesterol itself. LDL cholesterol is transported to the heart initially for repair.  HDL is the reverse cholesterol transport system carrying cholesterol away from the heart.  This has come under more intensive scrutiny in the last few years.

Further refinements have followed, including Lp(a), LpPLA2, myeloperoxidase, hs-crp, homocysteine, uric acid, and now particle counts.  Let me return to this in a minute.

The goal of conventional cardiologists is reducing LDL numbers to less than 100 mg/dl or for “at risk” patients – as low as 60-80 mg/dl.  Does this make any difference? 

 Dr. Daniel Steinberg was one of the most notable researchers in lipidology while I was at UCSD School of Medicine.  He wrote The Cholesterol Wars.  A good read for its historical content.  At one point, he notes, “we almost lost the battle until statins arrived.”  Which implied that severe dietary restriction alone was insufficient to reduce cardiovascular morbidity and mortality.  Statins were much more potent.  We could lower LDL more aggressively.  But is reduction of LDL successful?  I contend not.  Statins are anti-inflammatory.  They do not work by simply lowering LDL levels as much as mitigating inflammation.

That is why statins may actually have the greatest effect and benefit surrounding the acute period of a myocardial infarction.

Berkeley Heart Lab (BHL) pioneered the concept of LDL particle sizing. This has drawn more recent attention and acclaim.  BHL developed the notion of pattern typing using an expensive and laborious gel electrophoresis process.  Which, in its day, superseded the expensive and neglected ultracentrifuges used by John Goffman.  He had access to the warehoused ultracentrifuges that were originally designed to refine uranium during the super secret Manhattan Project at Berkeley Lawrence Lab and Sandia Labs.

 Pattern A is characterized by low triglycerides, high HDL and large, fluffy LDL particles which are presumably less atherogenic.  That is, they cause less vascular disease.  A pattern B is characterized by high triglycerides, low HDL and small dense atherogenic LDL particles.

Pattern A vs Pattern B LDL risk

So we think particle sizing and LDL size may be a good marker of future pathology or disease. Again, large and fluffy LDL particles are less dangerous.  Small dense LDL particles are far more pathogenic and atherogenic.  This may be an impaired paradigm.

 Dr. Robert Superko, co-founder of BHL, has been lecturing and advocating since the early 1990s on the danger and pathogenicity of Pattern B.  He was aggressively trying to raise HDL and thereby lower heart disease with high dose Niacin.  Empirically, we do see patients who have high HDL’s are at less risk.  Unfortunately, therapeutic trials to increase HDL with niacin or experimental drugs (torcetrapib) have not been successful.  I have often asked why is that?   That may be the subject of a future blog.  Milano A1 and HDL2b.

 It is very likely we are missing or misinterpreting this picture.  The real risk is high triglycerides which are carbohydrate induced, increasing the risk of diabetes and glycation. A series of events leads to increasing hemoglobin A1c levels (glycation), arterial stiffening, hypertension, and increased cardiovascular disease.

 The most unfortunate, but glaring example was Tim Russert.  He was known to have normal cholesterol but very high triglycerides. He died at the age of 58.  Quite premature.  What is the lesson here?  Pattern B may be a biomarker for glycation because of its increase in triglycerides which are associated with higher carbohydrate intake.  We see this as increased hemoglobin A1c levels.

 Glycation is the end result of AGE products – Advanced Glycation End-Products. Which, by the way, was one of the postulates of my book the Life Extension Revolution: Growing Older without Aging.

 Now let’s add another seriously overlooked cause of cardiovascular disease.  Adhesion molecules.  VCAM-1 is the most notable.  Vascular Cell Adhesion Molecule. These adhesion molecules are highly active in cancer and in cardiovascular disease.  It initiates a cascade of inflammatory responses where white cells and macrophages are drawn (recruited) into an inflammatory process forming arterial plaque.  The end result of this inflammatory process is aggregated white blood cells and macrophages.  That is soft plaque.  This is, in essence, a pustular aggregation within the arterial wall.  Somewhat like acne on the face, but rather in the intimal-medial aspect of your arteries.

 Most unfortunately, Medicare and most insurance companies who follow suit, do not reimburse or recognize advanced cardiovascular risk factors.  Most of the medical community does not see cardiovascular disease as an inflammatory process. We are stuck in an old paradigm that overindulgence of fat and cholesterol causes heart disease.  There is no incentive economically or even medically to go beyond simple LDL measurements. Guideline derived, algorithmic medicine is short-circuiting our progress.

 “without deviation from the norm, progress is not possible” – Frank Zappa

 The real test of pathogenicity is imaging studies.  Carotid intimal medial thickness (CMIT) measures arterial wall thickness and developing plaque.  Superfast (EBT) CT scans (HeartScan) scores calcium load in your coronary (heart) arteries. Even a simple blood pressure measurement gives you valuable clues about arterial compliance and glycation.  This is directly visualizing actual disease. 

LDL and cholesterol is a bad predictor of eventual cardiovascular disease and events.

 Empirically, I have seen this most vividly in specific cases.  Extremely high familial LDL levels with entirely normal vascular studies. And extremely low LDLs associated with repeated coronary artery blockages requiring stents.

 Now, I want you to read my detailed review of the major cholesterol studies that I published here in June 2015.  This shows the results of all the major statin induced cholesterol lowering studies using absolute statistics and not relatives statistics.  There was virtually no survival advantage on a population basis from statins. On an individual basis, there may be lives saved.  But on a population wide basis there was no change.  Totally contrary to what you have heard.  What physicians believe or “know.”  But it is based on rigorous statistical analysis using absolute and not relative statistics.

Bottom line:  We need to change the paradigm. 

  We should be using new and more appropriate biomarkers for risk determination based on an inflammatory profile.

Triglycerides may be more pathogenic than cholesterol.

Low carbohydrate intake.  Carbs are killing us. Don’t overeat. 

Moderate exercise. 

Stress reduction.

Update and revise our entire therapeutic protocols.

Look at diabetic risk using HgA1c as a glycation biomarker.

High dose fish oils.

Appropriate anti-oxidants.

Prevent heart attacks and strokes with my natural anti-coagulant routine.

Let me know what you think.

Philip Lee Miller, MD

Carmel , CA

December 7, 2018

Statins: A Critical Appraisal

Statins: A Critical Appraisal

You can find a number of well written books with articulate statistical analyses over the years questioning the results of statin therapy.   What is the true value and efficacy of statins (HMG-CoA reductase inhibitors) in treating and preventing heart disease?   The statistics can be overwhelming.   What is the real risk benefit ratio?

Lipids and the Emergence of Statin Therapy

Lipid research actually started sometime in the early 1920’s.   It gained more momentum in the 1950’s with John Gofman at the Laurence Radiation Lab in Berkeley.  Then the interest waned, so the field languished for another few decades. John Gofman turned his energies to examining and warning us of the dangers of constant low level radiation therapy

In the 1950’s and 1960’s the cholesterol theory was gaining more adherents. Anyone over 50-60 remembers well the exhortation to eat less fat. No eggs. Skimmed milk. Substitute margarine for butter. It was much healthier.   Cholesterol was bad. Turns out margarine is literally the bottom of the barrel stuff. Highly hydrogenated oils. Much less healthy. Personally, I never believed the cholesterol theory even in Medical School and was labeled a heretic. “Dummy, everyone believes the cholesterol story.”

One of the most erudite and gentlemanly Professors at UCSD Medical School was Dr. Daniel Steinberg, a prominent lipid researcher. He wrote a wonderful book The Cholesterol Wars which is one of the best historical accounts of the lipid research over the past 80 years.   He even admits “we almost lost the cholesterol debate if it had not been for the emergence of Statins.”

The Framingham Study was a large study begun about 45 years ago in a small town outside of Boston where a majority of the population has been studied annually. It is the best cross sectional study we have.

Interestingly, even the Framingham study proved that cholesterol is a bad predictor of heart disease.   50% of those who suffered heart attacks had totally “normal” cholesterol levels.  By the way, the term “normal” is a moving target and subject to standards committee declarations.   There is no “normal” cholesterol, only declared “acceptable levels.”   A GP, an internist or a cardiologist will have different and increasingly aggressive definitions of “normal.”

Association vs causality is an ancient debate which is not well settled. Aristotle proposed four postulates for causality. Many centuries later, David Hume, the great Scottish Enlightenment philosopher expounded about this in detail.

Cholesterol does not cause heart disease.

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