Ornish Diet Worsens Heart Disease Risk: Part I

Dr. Dean Ornish has come under a lot of criticism lately for his misleading statements about diet and heart disease.
See, for example:
Critique of Dean Ornish Op-ed, by Nina Teicholz, and
Why Almost Everything Dean Ornish Says about Nutrition Is Wrong, from Scientific American.
Ornish made his name with a study that claimed to actually reverse heart disease [1].
There are at least three problems with the study.
First, it included several confounders to the dietary regimen.
For example, the intervention groups spent an hour a day on stress management techniques, such as meditation, and three hours a week exercising.
Second, although it was touted as the first study to look at “actual” heart disease results, it made no measurements of cardiac events!
Instead, it was based on measuring stenosis — the degree of narrowing of coronary arteries.
Considering that stenosis is only a predictor of cardiac events,
it seems disingenuous to call it a direct measure of heart disease.
Stenosis is used to predict heart disease (though it is often not the previously found blockages that are ultimate culprits [2]).
However, the measurement has a lot of variability.
Because of this, differences in measurements over time need to be quite large to be showing a true progression or regression, and not just error.
We found three studies attempting to pinpoint the minimum difference in measurements to make such a claim.
They respectively recommended 15%, 9.3%, and 7.8% as a basis for this judgment [3], [4], [5].
So how much reduction of stenosis was there in Ornish’s study?

“The average percentage diameter stenosis decreased from 40.0 (SD 16.9)% to 37.8 (16.5)% in the experimental group yet progressed from 42.7 (15.5)% to 46.11 (18.5)% in the control group (p = 0.001, two-tailed).”

That’s the extent of the success in a year: a -2.2% change for the claim of “regression” vs. a 3.4% change for the claim of “progression”.
It does not reach a level of significance given the measurement tool.
Fortunately, there were other measurements taken that are also predictors of cardiac events: blood lipids.
Even the AHA, an association that changes its mind slowly in response to evidence,
considers triglycerides above 100 to be higher than optimal [6].
Low HDL is a strong marker of heart disease, with HDL below 40 considered by the AHA a “major heart disease risk factor” [7].
The intervention group went from an average triglyceride level of 211 to 258, and their HDL from 39 to 38.
This shows that the intervention actually worsened the participants’ risk factors!
Moreover, although not acknowledged by the AHA, we know that the ratio of triglycerides to HDL is a very strong predictor of heart disease; among the best [8].
A triglyceride-to-HDL level of less than 2 is considered ideal.
Over 4 is considered risky.
Over 6 is considered very high risk.
The intervention group’s average triglycerides-to-HDL ratio leapt from 5.4 to 6.8!
It went from bad to worse.
Thus, the third problem with the study is that it actually showed a worsening of heart disease by other important measures.
The bottom line is that Ornish’s study never showed what it claimed to show.
After a year of intervention, even with other lifestyle changes incorporated, the subjects on his diet had a higher risk of heart disease than before they started.

References

[1] Ornish, Dean, et al. “Can lifestyle changes reverse coronary heart disease?: The Lifestyle Heart Trial.” The Lancet 336.8708 (1990): 129-133.
[2] Evidence type: experiment

Little WC, Constantinescu M, Applegate RJ, Kutcher MA, Burrows MT, Kahl FR, Santamore WP.
Circulation. 1988 Nov;78(5 Pt 1):1157-66.

Abstract
To help determine if coronary angiography can predict the site of a future coronary occlusion that will produce a myocardial infarction, the coronary angiograms of 42 consecutive patients who had undergone coronary angiography both before and up to a month after suffering an acute myocardial infarction were evaluated. Twenty-nine patients had a newly occluded coronary artery. Twenty-five of these 29 patients had at least one artery with a greater than 50% stenosis on the initial angiogram. However, in 19 of 29 (66%) patients, the artery that subsequently occluded had less than a 50% stenosis on the first angiogram, and in 28 of 29 (97%), the stenosis was less than 70%. In every patient, at least some irregularity of the coronary wall was present on the first angiogram at the site of the subsequent coronary obstruction. In only 10 of the 29 (34%) did the infarction occur due to occlusion of the artery that previously contained the most severe stenosis. Furthermore, no correlation existed between the severity of the initial coronary stenosis and the time from the first catheterization until the infarction (r2 = 0.0005, p = NS). These data suggest that assessment of the angiographic severity of coronary stenosis may be inadequate to accurately predict the time or location of a subsequent coronary occlusion that will produce a myocardial infarction.

[3] Evidence type: experiment

Abstract
BACKGROUND:
Clinical trials with angiographic end points have been used to assess whether interventions influence the evolution of coronary atherosclerosis because sample size requirements are much smaller than for trials with hard clinical end points. Further studies of the variability of the computer-assisted quantitative measurement techniques used in such studies would be useful to establish better standardized criteria for defining significant change.
METHODS AND RESULTS:
In 21 patients who had two arteriograms 3-189 days apart, we assessed the reproducibility of repeat quantitative measurements of 54 target lesions under four conditions: 1) same film, same frame; 2) same film, different frame; 3) same view from films obtained within 1 month; and 4) same view from films 1-6 months apart. Quantitative measurements of 2,544 stenoses were also compared with an experienced radiologist’s interpretation. The standard deviation of repeat measurements of minimum diameter from the same frame was very low (0.088 mm) but increased to 0.141 mm for measurements from different frames. It did not increase further for films within 1 month but increased to 0.197 mm for films 1-6 months apart. Diameter stenosis measurements were somewhat more variable. Measurement variability for minimum diameter was independent of vessel size and stenosis severity. Experienced radiologists did not systematically overestimate or underestimate lesion severity except for mild overestimation (mean 3.3%) for stenoses > or = 70%. However, the variability between visual and quantitative measurements was two to three times higher than the variability of paired quantitative measurements from the same frame.
CONCLUSIONS:
Changes of 0.4 mm or more for minimum diameter and 15% or more for stenosis diameter (e.g., 30-45%), measured quantitatively, are recommended as criteria to define progression and regression. Approaches to data analysis for coronary arteriographic trials are discussed.

[4] Evidence type: experiment

Brown BG1, Hillger LA, Lewis C, Zhao XQ, Sacco D, Bisson B, Fisher L.
Circulation. 1993 Mar;87(3 Suppl):II66-73.

Abstract
BACKGROUND:
Imaging trials using arteriography have been shown to be effective alternatives to clinical end point studies of atherosclerotic vascular disease progression and the effect of therapy on it. However, lack of consensus on what end point measures constitute meaningful change presents a problem for quantitative coronary arteriographic (QCA) approaches. Furthermore, standardized approaches to QCA studies have yet to be established. To address these issues, two different arteriographic approaches were compared in a clinical trial, and the degree of concordance between disease change measured by these two approaches and clinical outcomes was assessed.
METHODS AND RESULTS:
In the Familial Atherosclerosis Treatment Study (FATS) of three different lipid-lowering strategies in 120 patients, disease progression/regression was assessed by two arteriographic approaches: QCA and a semiquantitative visual approach (SQ-VIS). Lesions classified with SQ-VIS as “not,” “possibly,” or “definitely” changed were measured by QCA to change by 10% stenosis in 0.3%, 11%, and 81% of cases, respectively. The “best” measured value for distinguishing definite from no change was identified as 9.3% stenosis by logistic regression analysis. The primary outcome analysis of the FATS trial, using a continuous variable estimate of percent stenosis change, gave almost the same favorable result whether by QCA or SQ-VIS.
CONCLUSIONS:
The excellent agreement between these two fundamentally different methods of disease change assessment and the concordance between disease change and clinical outcomes greatly strengthens confidence both in these measurement techniques and in the overall findings of the study. These observations have important implications for the design of clinical trials with arteriographic end points.

[5] Evidence type: experiment

Gibson CM1, Sandor T, Stone PH, Pasternak RC, Rosner B, Sacks FM.
Am J Cardiol. 1992 May 15;69(16):1286-90.

Abstract
The purpose of this study was (1) to determine a threshold for categorizing individual coronary lesions as either significantly progressing or regressing, (2) to determine whether multiple lesions within individual patients progress at independent rates, and (3) to calculate sample sizes for atherosclerosis regression trials. Seventeen patients with 46 significant lesions (2.7 lesions/patient) underwent repeat coronary arteriography 3.0 years apart. With use of the standard error of the mean change in diameter from initial to repeat catheterization across 5 pairs of consecutive end-diastolic frames, individual lesions were categorized as either significantly (p less than 0.01) progressing or regressing if there was a 0.27 mm change in minimum diameter or a 7.8 percent point change in percent stenosis. The mean diameter change of a sample of lesions can also be analyzed as a continuous variable using either the lesions or the patient as the primary unit of analysis. A lesion-specific analysis can be accomplished using a multiple regression model that accounts for the intraclass correlation (rho) in the degree of change among multiple lesions within individual patients. The intraclass correlations in percent stenosis (rho = 0.01) and minimum diameter (rho = -0.24) were low, indicating that disease progression in different lesions within individual patients is nearly independent. With use of this model, 50 patients per treatment group would permit the detection of a 5.5% difference between treatment group means in the change in minimum diameter and a 2.7% percentage point (not percent) difference in the change in percent stenosis.(ABSTRACT TRUNCATED AT 250 WORDS)

[6] From The American Heart Association’s “Scientific Statement”
“New clinical recommendations include reducing the optimal triglyceride level from <150 mg/dL to <100 mg/dL, and performing non-fasting triglyceride testing as an initial screen.”
[7] From Levels of Cholesterol

Less than 40 mg/dL for men; less than 50 mg/dL for women: Major heart disease risk factor
60 mg/dL or higher Gives some protection against heart disease

[8] Evidence type: observational

Gaziano JM1, Hennekens CH, O’Donnell CJ, Breslow JL, Buring JE.
Circulation. 1997 Oct 21;96(8):2520-5.

Abstract
BACKGROUND:
Recent data suggest that triglyceride-rich lipoproteins may play a role in atherogenesis. However, whether triglycerides, as a marker for these lipoproteins, represent an independent risk factor for coronary heart disease remains unclear, despite extensive research. Several methodological issues have limited the interpretability of the existing data.
METHODS AND RESULTS:
We examined the interrelationships of fasting triglycerides, other lipid parameters, and nonlipid risk factors with risk of myocardial infarction among 340 cases and an equal number of age-, sex-, and community-matched control subjects. Cases were men or women of <76 years of age with no prior history of coronary disease who were discharged from one of six Boston area hospitals with the diagnosis of a confirmed myocardial infarction. In crude analyses, we observed a significant association of elevated fasting triglycerides with risk of myocardial infarction (relative risk [RR] in the highest compared with the lowest quartile=6.8; 95% confidence interval [CI]=3.8 to 12.1; P for trend <.001). Results were not materially altered after control for nonlipid coronary risk factors. As expected, the relationship was attenuated after adjustment for HDL but remained statistically significant (RR in the highest quartile=2.7; 95% confidence interval [CI]=1.4 to 5.5; P for trend=.016). Furthermore, the ratio of triglycerides to HDL was a strong predictor of myocardial infarction (RR in the highest compared with the lowest quartile=16.0; 95% CI=7.7 to 33.1; P for trend <.001).
CONCLUSIONS:
Our data indicate that fasting triglycerides, as a marker for triglyceride-rich lipoproteins, may provide valuable information about the atherogenic potential of the lipoprotein profile, particularly when considered in context of HDL levels.

The Ketogenic Diet Reverses Indicators of Heart Disease

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The Ketogenic Diet Reverses Indicators of Heart Disease

Cardiovascular disease (CVD) is the leading cause of death worldwide
1.
Because of its prevalence and life-threatening nature, and because it appears that a keto diet is likely to reverse it, we consider it one of the most important conditions to discuss here.

In our last post, we argued that CVD, being a disease strongly associated with metabolic syndrome, is likely to be best treated with a ketogenic diet.
In this post we will present more evidence that ketogenic diets do improve heart disease risk factors.

Unfortunately, there is much confusion and misinformation about the impact of nutrition on CVD among scientists and non-scientists alike.
Not only does a high fat, keto diet not worsen heart disease risk — as would commonly be assumed — it actually improves it.
This confusion about dietary fat is probably the reason that we do not yet have clinical trials directly testing the effects of ketogenic diets on CVD outcomes.

However, we already have many trials of ketogenic diets that measured known CVD risk factors, especially cholesterol profiles.
It turns out that these trials show a powerful heart disease risk reduction in those following a ketogenic diet.
It is powerful both in absolute terms, and in comparison with low-fat diets, which tend to improve some weakly predictive factors while worsening stronger predictors.

As such, a high-fat ketogenic diet is currently the best known non-drug intervention for heart disease, as defined by mainstream measures of risk. It is arguably better than drug interventions, too.

In brief:

  • Total cholesterol and LDL cholesterol are only weak predictors of CVD.
  • Triglycerides, HDL, LDL particle size, and the HDL-to-triglyceride ratio are much stronger predictors of CVD.
  • Keto diets improve triglyceride levels, HDL, and LDL particle size — precisely those measures that strongly indicate risk.

Total cholesterol and LDL cholesterol are only weakly associated with CVD

The connection between blood cholesterol levels and the development of heart disease began to be explored in the last century.
Over the last several decades, our understanding of the predictive power of various blood lipids has gone through many refinements as our ability to measure finer and finer detail has advanced.

In the early years, it appeared that high levels of total cholesterol carried some risk of heart disease in many cases.
However, it is now well established that total cholesterol by itself is a weak predictor
2,
3,
4.

The reason is quite simple.
The different subtypes of cholesterol work together in an intricately balanced system.
There is a wide range of total cholesterol levels that are perfectly healthy, so long as the proportions of the subtypes are healthy ones.
By the same token, a given level of total cholesterol, even if it is perfectly normal, could be pathological when examined by subtype.
Strong evidence from recent decades suggests that the best known blood lipid measures for predicting future risk of CVD are HDL, triglycerides, and related ratios (see below).

Similarly, while LDL cholesterol is probably important, it appears that it does not have good predictive power when looking at its magnitude alone
5,
6,
7,
8.

One reason for this is that like total cholesterol, LDL is not uniform.
Just as we distinguish between HDL and LDL, the so-called “good” and “bad” cholesterol, LDL itself is now known to have two important subtypes with opposite risk
implications.
Having more large, light LDL particles (also called Pattern A), does not indicate high CVD risk, but having more small, dense particles (Pattern B) does
9,
10,
11,
12,
13.
Therefore high LDL by itself is not necessarily indicative of CVD.

Low HDL cholesterol is strongly associated with CVD

Having high blood levels of HDL is now widely recognized as predicting lower levels of heart disease.
The proportion of total cholesterol that is HDL cholesterol is a particularly strong predictor.
In 2007, a meta-analysis was published in the Lancet that examined information from 61 prospective observational studies, consisting of almost 900,000 adults.
Information about HDL was available for about 150,000 of them, among whom there were 5000 vascular deaths. According to the authors, “the ratio of total to HDL cholesterol is a substantially more informative predictor of IHD mortality than are total cholesterol, HDL
cholesterol, or non-HDL cholesterol.”
14

This is consistent with many other studies, for example this very recent analysis from the COURAGE trial
15.

High triglycerides are strongly associated with CVD

There has been drawn out controversy in the medical community as to the relationship of triglyceride levels to CVD.
There are two parts to the controversy: whether or not triglycerides are an independent predictor of CVD, and whether or not triglycerides play a causative role in CVD.

In both cases, however, it doesn’t matter in which way the controversy is resolved!
Whether or not triglycerides independently predict CVD
(and there is at least some evidence that they do),
and whether or not they cause CVD, there is no controversy about whether they predict CVD.
The association between triglyceride levels and CVD still holds and is strongly predictive
16,
17,
18.
In fact it is so predictive that those who argue that triglyceride levels are not an independent risk factor, call it instead a “biomarker” for CVD
19.
In other words, seeing high triglycerides is tantamount to seeing the progression of heart disease.

HDL-to-Triglycerides Ratio: compounding evidence

Triglycerides and HDL levels statistically interact.
That means it is a mistake to treat one as redundant with respect to the other.
If you do, you will miss the fact that the effect of one on your outcome of interest changes depending on the value of the other.
Despite the fact that most heart disease researchers who study risk factors have not used methods tuned to find interactions between triglycerides and HDL, many studies have at least measured both.
This has allowed others to do the appropriate analysis.
When triglycerides and HDL have been examined with respect to each other, that is, when the effect of triglycerides is measured under the condition of low HDL, or when the effect of HDL is measured under the condition of high triglycerides, this combination of factors turns out to be even more indicative of CVD
20,
21,
22,
23.

One of the most interesting aspects of this finding from our perspective, is that the ratio of triglyceride levels to HDL is considered to be a surrogate marker of insulin resistance
(See The Ketogenic Diet as a Treatment for Metabolic Syndrome.)
In other words, the best lipid predictors of CVD are also those that indicate insulin resistance.

Ketogenic Diets improve risk factors for CVD

There is now ample evidence that a low carbohydrate, ketogenic diet improves lipid profiles, particularly with respect to the risk factors outlined above: triglycerides, HDL, and their ratio
24,
25,
26,
27,
28,
29,
30,
31.

Although a ketogenic diet typically raises LDL levels, which has been traditionally seen as a risk factor, it has also been shown to improve LDL particle size.
In other words, although the absolute amount of LDL goes
up, it is the “good” LDL that goes up, whereas the “bad” LDL goes down
31,
32.
This is hardly surprising, since LDL particle size is also strongly predicted by triglycerides
33,
34,
35.

Although there have not yet been intervention studies testing the effect of a ketogenic diet on the rate of actual CVD incidents (e.g. heart attacks), the evidence about lipid profiles is strong enough to make ketogenic diets more likely to reduce heart disease than any other known intervention.

Summary:

  • Current medical practice uses blood lipid measurements to assess the risk of heart disease.
  • Despite the continuing tradition of measuring total cholesterol and LDL, we have known for decades that triglycerides, HDL, and the ratio of the two, are much better predictors of heart disease.
    LDL particle size is also considered strongly predictive.
  • A ketogenic diet has a very favourable impact on these risk factors, and thus should be considered the diet of choice for those at risk of CVD.

In their 2011 paper, “Low-carbohydrate diet review: shifting the paradigm”, Hite et al. display the following graph (VLCKD stands for Very Low Carbohydrate Ketogenic Diet, and LFD for Low Fat Diet)
36 based on data from 31:

It makes an excellent visualization of the factors at stake, and how powerful a ketogenic diet is.
It also shows quite clearly that not only is restricting carbohydrate more effective for this purpose than a low fat diet, but that a low fat diet is detrimental for some important risk factors — apolipoprotein ratios, LDL particle size, and HDL — but a low carb diet is not.
The ketogenic diet resulted in a significant improvement in every measure.

References:

1 Evidence type: observational


World Health Organization Fact sheet N°317: Cardiovascular diseases (CVDs) September 2011

  • CVDs are the number one cause of death globally: more people die annually from CVDs than from any other cause.
  • An estimated 17.3 million people died from CVDs in 2008, representing 30% of all global deaths. Of these deaths, an estimated 7.3 million were due to coronary heart disease and 6.2 million were due to stroke.
  • Low- and middle-income countries are disproportionally affected: over 80% of CVD deaths take place in low- and middle-income countries and occur almost equally in men and women.
  • By 2030, almost 23.6 million people will die from CVDs, mainly from heart disease and stroke. These are projected to remain the single leading causes of death.

2 Evidence type: observational


Role of lipid and lipoprotein profiles in risk assessment and therapy.
Ballantyne CM, Hoogeveen RC.
Am Heart J. 2003 Aug;146(2):227-33.

Despite a strong and consistent association within populations, elevated TC [(total cholesterol)] alone is not a useful test to discriminate between individuals who will have CHD [(coronary heart disease)] events and those who will not.

3 Evidence type: observational


Relation of serum lipoprotein cholesterol levels to presence and severity of angiographic coronary artery disease.
Philip A. Romm, MD, Curtis E. Green, MD, Kathleen Reagan, MD, Charles E. Rackley, MD.
The American Journal of Cardiology Volume 67, Issue 6, 1 March 1991, Pages 479–483

Most CAD [(coronary artery disease)] occurs in persons who have only mild or moderate elevations in cholesterol levels. Total cholesterol level alone is a poor predictor of CAD, particularly in older patients in whom the major lipid risk factor is the HDL cholesterol level.

4 Evidence type: observational


Lipids, risk factors and ischaemic heart disease.
Atherosclerosis. 1996 Jul;124 Suppl:S1-9.
Castelli WP.

Those individuals who had TC [(total cholesterol)] levels of 150-300 mg/dl (3.9-7.8 mmol/1) fell into the overlapping area (Fig. 1), demonstrating that 90% of the TC levels measured were useless (by themselves) for predicting risk of CHD [(coronary heart disease)] in a general population. Indeed, twice as many individuals who had a lifetime TC level of less than 200 mg/dl (5.2 mmol/1) had CHD compared with those who had a TC level greater than 300 mg/dl (7.8 mmol/l) (Fig. 1).

5 Evidence type: observational


Range of Serum Cholesterol Values in the Population Developing Coronary Artery Disease.
William B. Kannel, MD, MPH.
The American Journal of Cardiology, Volume 76, Issue 9, Supplement 1, 28 September 1995, Pages 69C–77C

The ranges of serum cholesterol and LDL cholesterol levels varied widely both in the general population and in patients who had already manifested CAD (Figures 1 and 2). Because of the extensive overlap between levels, it was impossible to differentiate the patients with CAD from the control subjects.

6 Evidence type: observational


Lipoprotein cholesterol, apolipoprotein A-I and B and lipoprotein (a) abnormalities in men with premature coronary artery disease.
Jacques Genest Jr., MD,FACC, Judith R. McNamara, MT, Jose M. Ordovas, PhD, Jennifer L. Jenner, BSc, Steven R. Silberman, PhD, Keaven M. Anderson, PhD, Peter W.F. Wilson, MD, Deeb N. Salem, MD, FACC, Ernst J. Schaefer, MD.
Journal of the American College of Cardiology Volume 19, Issue 4, 15 March 1992, Pages 792–802.

Our data suggest that total and LDL cholesterol may not be the best discriminants for the presence of coronary artery disease despite the strong association between elevated cholesterol and the development of coronary artery disease in cross-sectional population studies and prospective epidemiologic studies.

7 Evidence type: observational


Apolipoprotein B and apolipoprotein A-I: risk indicators of coronary heart disease and targets for lipid-modifying therapy.
Walldius, G. and Jungner, I. (2004),
Journal of Internal Medicine, 255: 188–205. doi: 10.1046/j.1365-2796.2003.01276.x

(Emphasis ours.)

For over three decades it has been recognized that a high level of total blood cholesterol, particularly in the form of LDL cholesterol (LDL-C), is a major risk factor for developing coronary heart disease (CHD) [1–4]. However, as more recent research has expanded our understanding of lipoprotein function and metabolism, it has become apparent that LDL-C is not the only lipoprotein species involved in atherogenesis. A considerable proportion of patients with atherosclerotic disease have levels of LDL-C and total cholesterol (TC) within the recommended range [5, 6], and some patients who achieve significant LDL-C reduction with lipid-lowering therapy still develop CHD [7].

Other lipid parameters are also associated with elevated cardiovascular risk, and it has been suggested that LDL-C and TC may not be the best discriminants for the presence of coronary artery disease (CAD) [5].

8 Evidence type: observational


Plasma Lipoprotein Levels as Predictors of Cardiovascular Death in Women.
Katherine Miller Bass, MD, MHS; Craig J. Newschaffer, MS; Michael J. Klag, MD, MPH; Trudy L. Bush, PhD, MHS.
Arch Intern Med. 1993;153(19):2209-2216.

Using a sample of 1405 women aged 50 to 69 years from the Lipid Research Clinics’ Follow-up Study, age-adjusted CVD death rates and summary relative risk (RR) estimates by categories of lipid and lipoprotein levels were calculated. Multivariate analysis was performed to provide RR estimates adjusted for other CVD risk factors.

RESULTS: Average follow-up was 14 years. High-density lipoprotein and triglyceride levels were strong predictors of CVD death in age-adjusted and multivariate analyses. Low-density lipoprotein and total cholesterol levels were poorer predictors of CVD mortality. After adjustment for other CVD risk factors, HDL levels less than 1.30 mmol/L (50 mg/dL) were strongly associated with cardiovascular mortality (RR = 1.74; 95% confidence interval [CI], 1.10 to 2.75). Triglyceride levels were associated with increased CVD mortality at levels of 2.25 to 4.49 mmol/L (200 to 399 mg/dL) (RR = 1.65; 95% CI, 0.99 to 2.77) and 4.50 mmol/L (400 mg/dL) or greater (RR = 3.44; 95% CI, 1.65 to 7.20). At total cholesterol levels of 5.20 mmol/L (200 mg/dL) or greater and at all levels of LDL and triglycerides, women with HDL levels of less than 1.30 mmol/L (< 50 mg/dL) had CVD death rates that were higher than those of women with HDL levels of 1.30 mmol/L (50 mg/dL) or greater.

9 Evidence type: plausible mechanism and observational review


Particle size: the key to the atherogenic lipoprotein?
Rajman I, Maxwell S, Cramb R, Kendall M.
QJM. 1994 Dec;87(12):709-20.

Using different analytical methods, up to 12 low-density lipoprotein (LDL) subfractions can be separated. LDL particle size decreases with increasing density. Smaller, denser LDL particles seem more atherogenic than the larger, lighter particles, based on the experimental findings that smaller LDL particles are more susceptible for oxidation in vitro, have lower binding affinity for the LDL receptors and lower catabolic rate, have a higher concentration of polyunsaturated fatty acids, and potentially interact more easily with proteoglycans of the arterial wall. Clinical studies have shown that a smaller LDL subfraction profile is associated with an increased risk of heart disease, even when total cholesterol level is only slightly raised. There is a strong inverse association between LDL particle size and triglyceride concentrations. Although LDL particle size is genetically determined, its phenotypic expression may also be affected by environmental factors such as drugs, diet, obesity, exercise or disease. Factors that shift the LDL subfractions profile towards larger particles may reduce the risk of heart disease.

10 Evidence type: nested case-control study


Association of Small Low-Density Lipoprotein Particles With the Incidence of Coronary Artery Disease in Men and Women.
Christopher D. Gardner, PhD; Stephen P. Fortmann, MD; Ronald M. Krauss, MD
JAMA. 1996;276(11):875-881. doi:10.1001/jama.1996.03540110029028.

Incident CAD cases were identified through FCP surveillance between 1979 and 1992. Controls were matched by sex, 5-year age groups, survey time point, ethnicity, and FCP treatment condition. The sample included 124 matched pairs: 90 pairs of men and 34 pairs of women.

LDL size was smaller among CAD cases than controls (mean ±SD) (26.17±1.00nm vs 26.68±0.90nm;P

The Ketogenic Diet as a Treatment for Metabolic Syndrome

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The Ketogenic Diet for Metabolic Syndrome

Metabolic Syndrome (MetS) can be viewed as a set of symptoms of insulin resistance.
Taken together, those symptoms signify a threat of heart disease, diabetes, cancer, and other diseases that appear to be different manifestations of a common cause.
That common cause is likely to be insulin resistance.

This hypothesis is supported by evidence that ketogenic diets not only normalize insulin sensitivity and the symptoms of MetS, but they treat (or have promise in treating) many MetS-associated diseases.

In light of this, it seems plausible that adopting a ketogenic diet will significantly improve your chances of avoiding these diseases in the first place.

* * *

In brief

  • Metabolic Syndrome is a cluster of symptoms, not a disease.
    Those symptoms are useful to class together, because their association with a variety of different diseases strongly suggests a common cause.
    In other words, it has provided us with a compelling hypothesis.
  • If there were a common cause, then a therapy that treats that cause should help them all.
    Moreover, it should reduce the symptoms of Metabolic Syndrome itself.
    Further, treatments that work for one but not the others should be considered inferior, “band-aid” treatments.
  • A ketogenic diet improves Metabolic Syndrome.
    Also, for every disease associated with MetS that we have investigated, a keto diet has either been shown to help, has shown preliminary evidence in its favour, or has not been sufficiently tested to rule out.
  • This supports the hypothesis that those diseases have a common cause, and that a ketogenic diet addresses it.

* * *

What is Metabolic Syndrome?

Metabolic Syndrome is a cluster of symptoms that commonly occur together and indicate increased risk of cardiovascular disease (CVD), type 2 diabetes (T2D), cancer, and other diseases.
Clinically, to be diagnosed with MetS, you have to score above (or in the case of HDL, below) a healthy threshold in at least 3 of the following 5 measurements: waist size, fasting blood glucose, blood pressure, triglycerides, and HDL.
All of these are associated with insulin resistance, although some are more predictive than others
1,
2,
3
, and so metabolic syndrome might be more accurately described as insulin resistance syndrome (and it sometimes is)
4,
5.

Just as with any such measure, it can be misleading to draw a threshold at such a particular point.
The cost of ignoring warning signs because they fall below a threshold may be worse than the benefit of giving a special diagnosis to those who have multiple symptoms, each of which could be recognized as warranting treatment on its own
6.

Nonetheless, it is useful to have a name for a set of associations for two reasons.

  1. It allows us to recognize the commonalities in symptoms of a variety of disease states which is suggestive of common mechanisms.
  2. It promotes the insight that any treatment that is purported to improve risk of CVD or T2D ought to have a beneficial impact on all of the associated symptoms.
    If it doesn’t, there is a risk that it is a band-aid solution that temporarily hides the problem rather than fixing it.

Because these symptoms so often occur together, and because they are all risk factors for a group of diseases which in turn are risk factors for each other, it is the contention of many scientists that they have a common cause.
Some argue that this common cause is obesity itself.
A separate cause is postulated for obesity, which then is supposed to cause the other risk factors.
However, other researchers, ourselves among them, believe that obesity and the other symptoms have a common cause related to insulin signalling.
For this reason, we have grouped together several diseases which appear to have insulin signalling at their root, and which have elevated risk in the presence of Metabolic Syndrome symptoms.
These diseases include (but are not limited to) cardiovascular disease
7,
type 2 diabetes
8,
polycystic ovarian syndrome
9,
Alzheimer’s disease
10, and cancer.
11.


In other words, we believe that Metabolic Syndrome is not itself a disease, but is a class of warning signs associated with the progression of several other diseases. If this is true, then when you treat the underlying cause of these symptoms, they will all normalize together, and the risk of all associated diseases will simultaneously be reduced.

* * *

Ketogenic diets treat insulin resistance and therefore are expected to treat all diseases that have Metabolic Syndrome as a symptom.

The following is just a sample of evidence showing that not only does a keto diet address the symptoms of MetS itself, but also those conditions associated with it.
This is not meant to be comprehensive — there are many more supporting experiments in each category!

  • Carbohydrate restriction has a more favorable impact on the metabolic syndrome than a low fat diet12.
  • A ketogenic diet favorably affects serum biomarkers for cardiovascular disease in normal-weight men
    13.
  • In addition to decreasing body weight and improving glycemia, a ketogenic diet can be effective in decreasing antidiabetic medication dosage
    14 .
  • In a pilot study, a ketogenic diet led to significant improvement in weight, percent free testosterone, LH/FSH ratio, and fasting insulin in women with obesity and PCOS over a 24 week period
    15
    .
  • An oral ketogenic compound, AC-1202, was tested in subjects with probable Alzheimer’s disease, and resulted in a significant improvement to cognitive scores
    16.
  • It seems a reasonable possibility that a very-low-carbohydrate diet could help to reduce the progression of some types of cancer, although at present the evidence is preliminary
    17.

* * *

Summary

  • The ketogenic diet is a powerful therapy that exerts its healing effect in a wide variety of conditions that may seem superficially unrelated.
  • These conditions are linked by their connection to insulin resistance, and therefore their association with MetS.
  • This supports not only the hypothesis that a keto diet treats MetS, but also that insulin resistance is the underlying cause of many devastating diseases, and that the way a keto diet is treating those is
    by intercepting and correcting the underlying cause.

* * *

References:

1 Evidence type: observational analysis
Evidence type:


Insulin resistance in aging is related to abdominal obesity.
Kohrt WM, Kirwan JP, Staten MA, Bourey RE, King DS, Holloszy JO.
Diabetes. 1993 Feb;42(2):273-81.

(emphasis ours)

Abstract

Studies have shown that insulin resistance increases with age, independent of changes in total adiposity. However, there is growing evidence that the development of insulin resistance may be more closely related to abdominal adiposity. To evaluate the independent effects of aging and regional and total adiposity on insulin resistance, we performed hyperinsulinemic euglycemic clamps on 17 young (21-33 yr) and 67 older (60-72 yr) men and women. We assessed FFM and total and regional adiposity by hydrodensitometry and anthropometry. Insulin-stimulated GDRs at a plasma insulin concentration of approximately 450 pM averaged 45.6 +/- 3.3 mumol.kg FFM-1 x min-1 (mean +/- SE) in the young subjects, 45.6 +/- 10.0 mumol.kg FFM-1 x min-1 in 24 older subjects who were insulin sensitive, and 23.9 +/- 11.7 mumol.kg FFM-1 x min-1 in 43 older subjects who were insulin resistant. Few significant differences were apparent in skin-fold and circumference measurements between young and insulin-sensitive older subjects, but measurements at most central body sites were significantly larger in the insulin-resistant older subjects. Waist girth accounted for > 40% of the variance in insulin action, whereas age explained only 10-20% of the total variance and < 2% of the variance when the effects of waist circumference were statistically controlled. These results suggest that insulin resistance is more closely associated with abdominal adiposity than with age."]

2 Evidence type: retrospective observation


Use of waist circumference to predict insulin resistance: retrospective study.
Wahrenberg H, Hertel K, Leijonhufvud BM, Persson LG, Toft E, Arner P.
BMJ. 2005 Jun 11;330(7504):1363-4. Epub 2005 Apr 15.

In the multiple regression model, waist circumference was the strongest regressor of the five significant covariates (standardised partial regression coefficients: waist circumference β1 = 0.37; log-plasma triglycerides β2 = 0.23; systolic blood pressure β3 = 0.10, high density lipoprotein cholesterol β4 = -0.09; and body mass index β5 = 0.15 (P < 0.001)).

3 Evidence type: observational analysis


Biomarkers in Fasting Serum to Estimate Glucose Tolerance, Insulin Sensitivity, and Insulin Secretion
Allison B. Goldfine, Robert W. Gerwien, Janice A. Kolberg, Sheila O’Shea, Sarah Hamren, Glenn P. Hein, Xiaomei M. Xu, and Mary Elizabeth Patti
Clinical Chemistry 57:2 326–337 (2011)

A subset of 5 markers was associated with insulin sensitivity (assessed using the dynamic CISI measure): fasting glucose, insulin, Fas ligand, complement C3, and PAI-1. As shown in Fig. 3C, 91% of variance between predicted and observed CISI values was accounted for by these 5 markers alone (P 0.0001). In addition, a bootstrap R 2 value of 0.90 (IQR 0.83–0.94) indicates that the model could be expected to perform well on an independent data set. By comparison, HOMA-IR, a widely accepted estimate of insulin resistance based on fasting glucose and insulin, explained 88% of the variance of the dynamic measure of insulin sensitivity.

4 Evidence type: observation


A.D.A.M. Medical Encyclopedia.

Metabolic syndrome; Insulin resistance syndrome; Syndrome X

5 Evidence type: observation


Diabetes Health Center Insulin Resistance and Diabetes

If you have pre-diabetes or diabetes, chances are that you’ve heard of the medical term insulin resistance syndrome or metabolic syndrome. Insulin resistance or metabolic syndrome describes a combination of health problems that have a common link — an increased risk of diabetes and early heart disease.

6 Evidence type: observation


The metabolic syndrome: is this diagnosis necessary?
Gerald M Reaven.
Am J Clin Nutr June 2006 vol. 83 no. 6 1237-1247

The goal of diagnosing the metabolic syndrome is to identify persons at increased risk of CVD. Because each component that makes up the versions of the metabolic syndrome increases CVD risk (34, 36, 37, 62, 68, 69), it seems prudent to treat any of these abnormalities that are present. Furthermore, it would not be too surprising that the more abnormalities present in any given person, the greater would be his or her risk of CVD. The question can be raised, however, as to whether identifying a person as having metabolic syndrome necessarily indicates that he or she is at greater risk of CVD than is a person who may not qualify for that designation. This did not seem to be the case when the ATP III criteria were applied to the Framingham Study database (117); a recent report pointed out that persons meeting any 2 criteria were at no less risk than were those meeting 3 criteria. Indeed, it would be possible to describe a number of prototypic clinical situations in which a person with 1 or 2 abnormalities would be at greater risk of CVD than would a patient who met the metabolic syndrome diagnostic criteria.

7 Evidence type: retrospective observation


The Metabolic Syndrome and Total and Cardiovascular Disease Mortality in Middle-aged Men.
Hanna-Maaria Lakka, MD, PhD; David E. Laaksonen, MD, MPH; Timo A. Lakka, MD, PhD; Leo K. Niskanen, MD, PhD; Esko Kumpusalo, MD, PhD; Jaakko Tuomilehto, MD, PhD; Jukka T. Salonen, MD, PhD
JAMA. 2002;288(21):2709-2716. doi:10.1001/jama.288.21.2709.

The metabolic syndrome, a concurrence of disturbed glucose and insulin metabolism, overweight and abdominal fat distribution, mild dyslipidemia, and hypertension, is associated with subsequent development of type 2 diabetes mellitus and cardiovascular disease (CVD).

The prevalence of the metabolic syndrome ranged from 8.8% to 14.3%, depending on the definition. There were 109 deaths during the approximately 11.4-year follow-up, of which 46 and 27 were due to CVD and CHD, respectively. Men with the metabolic syndrome as defined by the NCEP were 2.9 (95% confidence interval [CI], 1.2-7.2) to 4.2 (95% CI, 1.6-10.8) times more likely and, as defined by the WHO, 2.9 (95% CI, 1.2-6.8) to 3.3 (95% CI, 1.4-7.7) times more likely to die of CHD after adjustment for conventional cardiovascular risk factors. The metabolic syndrome as defined by the WHO was associated with 2.6 (95% CI, 1.4-5.1) to 3.0 (95% CI, 1.5-5.7) times higher CVD mortality and 1.9 (95% CI, 1.2-3.0) to 2.1 (95% CI, 1.3-3.3) times higher all-cause mortality. The NCEP definition less consistently predicted CVD and all-cause mortality. Factor analysis using 13 variables associated with metabolic or cardiovascular risk yielded a metabolic syndrome factor that explained 18% of total variance. Men with loadings on the metabolic factor in the highest quarter were 3.6 (95% CI, 1.7-7.9), 3.2 (95% CI, 1.7-5.8), and 2.3 (95% CI, 1.5-3.4) times more likely to die of CHD, CVD, and any cause, respectively.

Cardiovascular disease and all-cause mortality are increased in men with the metabolic syndrome, even in the absence of baseline CVD and diabetes.

8 Evidence type: retrospective observation


Risks for All-Cause Mortality, Cardiovascular Disease, and Diabetes Associated With the Metabolic Syndrome: A summary of the evidence.
Earl S. Ford, MD, MPH
Diabetes Care July 2005 vol. 28 no. 7 1769-1778

For studies that used the exact NCEP definition of the metabolic syndrome, random-effects estimates of combined relative risk were 1.27 (95% CI 0.90–1.78) for all-cause mortality, 1.65 (1.38–1.99) for cardiovascular disease, and 2.99 (1.96–4.57) for diabetes. For studies that used the most exact WHO definition of the metabolic syndrome, the fixed-effects estimates of relative risk were 1.37 (1.09–1.74) for all-cause mortality and 1.93 (1.39–2.67) for cardiovascular disease; the fixed-effects estimate was 2.60 (1.55–4.38) for coronary heart disease.

CONCLUSIONS—These estimates suggest that the population-attributable fraction for the metabolic syndrome, as it is currently conceived, is ∼6–7% for all-cause mortality, 12–17% for cardiovascular disease, and 30–52% for diabetes.

9 Evidence type: retrospective observation


Prevalence and Characteristics of the Metabolic Syndrome in Women with Polycystic Ovary Syndrome.
Teimuraz Apridonidze, Paulina A. Essah, Maria J. Iuorno and John E. Nestler.
The Journal of Clinical Endocrinology & Metabolism April 1, 2005 vol. 90 no. 4 1929-1935

The polycystic ovary syndrome (PCOS) is characterized by insulin resistance with compensatory hyperinsulinemia. Insulin resistance also plays a role in the metabolic syndrome (MBS). We hypothesized that the MBS is prevalent in PCOS and that women with both conditions would present with more hyperandrogenism and menstrual cycle irregularity than women with PCOS only.

We conducted a retrospective chart review of all women with PCOS seen over a 3-yr period at an endocrinology clinic. Of the 161 PCOS cases reviewed, 106 met the inclusion criteria. The women were divided into two groups: 1) women with PCOS and the MBS (n = 46); and 2) women with PCOS lacking the MBS (n = 60).

Prevalence of the MBS was 43%, nearly 2-fold higher than that reported for age-matched women in the general population. Women with PCOS had persistently higher prevalence rates of the MBS than women in the general population, regardless of matched age and body mass index ranges.

10 Evidence type: retrospective observation


Association of metabolic syndrome with Alzheimer disease: A population-based study.
M. Vanhanen, PhD, K. Koivisto, MD, PhD, L. Moilanen, MD, PhD, E. L. Helkala, PhD, T. Hänninen, PhD, H. Soininen, MD, PhD, K. Kervinen, MD, PhD, Y. A. Kesäniemi, MD, PhD, M. Laakso, MD, PhD and J. Kuusisto, MD, PhD
Neurology September 12, 2006 vol. 67 no. 5 843-847

Of the study subjects, 418 (43.6%) had MetS. Probable or possible AD was diagnosed in 45 subjects (4.7%). AD was more frequently detected in subjects with MetS than in subjects without MetS (7.2 vs 2.8%; p < 0.001). The prevalence of AD was higher in women with MetS vs women without the syndrome (8.3 vs 1.9%; p < 0.001), but in men with MetS, the prevalence of AD was not increased (3.8 vs 3.9%; p = 0.994). In univariate logistic regression analysis, MetS was significantly associated with AD (odds ratio [OR] 2.71; 95% CI 1.44 to 5.10). In multivariate logistic regression analysis including also apolipoprotein E4 phenotype, education, age, and total cholesterol, MetS was significantly associated with AD (OR 2.46; 95% CI 1.27 to 4.78). If only nondiabetic subjects were included in the multivariate analysis, MetS was still significantly associated with AD (OR 3.26; 95% CI 1.45 to 7.27).

11 Evidence type: review and meta-analysis


Metabolic syndrome and risk of cancer: a systematic review and meta-analysis.
Esposito K, Chiodini P, Colao A, Lenzi A, Giugliano D.
Diabetes Care. 2012 Nov;35(11):2402-11. doi: 10.2337/dc12-0336.

RESULTS: We analyzed 116 datasets from 43 articles, including 38,940 cases of cancer. In cohort studies in men, the presence of metabolic syndrome was associated with liver (relative risk 1.43, P < 0.0001), colorectal (1.25, P < 0.001), and bladder cancer (1.10, P = 0.013). In cohort studies in women, the presence of metabolic syndrome was associated with endometrial (1.61, P = 0.001), pancreatic (1.58, P < 0.0001), breast postmenopausal (1.56, P = 0.017), rectal (1.52, P = 0.005), and colorectal (1.34, P = 0.006) cancers. Associations with metabolic syndrome were stronger in women than in men for pancreatic (P = 0.01) and rectal (P = 0.01) cancers. Associations were different between ethnic groups: we recorded stronger associations in Asia populations for liver cancer (P = 0.002), in European populations for colorectal cancer in women (P = 0.004), and in U.S. populations (whites) for prostate cancer (P = 0.001). CONCLUSIONS: Metabolic syndrome is associated with increased risk of common cancers; for some cancers, the risk differs betweens sexes, populations, and definitions of metabolic syndrome.

12 Evidence type: controlled experiment


Carbohydrate restriction has a more favorable impact on the metabolic syndrome than a low fat diet.
Volek JS, Phinney SD, Forsythe CE, Quann EE, Wood RJ, Puglisi MJ, Kraemer WJ, Bibus DM, Fernandez ML, Feinman RD.
Lipids. 2009 Apr;44(4):297-309. doi: 10.1007/s11745-008-3274-2. Epub 2008 Dec 12.

Abstract

We recently proposed that the biological markers improved by carbohydrate restriction were precisely those that define the metabolic syndrome (MetS), and that the common thread was regulation of insulin as a control element. We specifically tested the idea with a 12-week study comparing two hypocaloric diets (approximately 1,500 kcal): a carbohydrate-restricted diet (CRD) (%carbohydrate:fat:protein = 12:59:28) and a low-fat diet (LFD) (56:24:20) in 40 subjects with atherogenic dyslipidemia. Both interventions led to improvements in several metabolic markers, but subjects following the CRD had consistently reduced glucose (-12%) and insulin (-50%) concentrations, insulin sensitivity (-55%), weight loss (-10%), decreased adiposity (-14%), and more favorable triacylglycerol (TAG) (-51%), HDL-C (13%) and total cholesterol/HDL-C ratio (-14%) responses. In addition to these markers for MetS, the CRD subjects showed more favorable responses to alternative indicators of cardiovascular risk: postprandial lipemia (-47%), the Apo B/Apo A-1 ratio (-16%), and LDL particle distribution. Despite a threefold higher intake of dietary saturated fat during the CRD, saturated fatty acids in TAG and cholesteryl ester were significantly decreased, as was palmitoleic acid (16:1n-7), an endogenous marker of lipogenesis, compared to subjects consuming the LFD. Serum retinol binding protein 4 has been linked to insulin-resistant states, and only the CRD decreased this marker (-20%). The findings provide support for unifying the disparate markers of MetS and for the proposed intimate connection with dietary carbohydrate. The results support the use of dietary carbohydrate restriction as an effective approach to improve features of MetS and cardiovascular risk.

13 Evidence type: non-randomized experiment


A Ketogenic Diet Favorably Affects Serum Biomarkers for Cardiovascular Disease in Normal-Weight Men.
Matthew J. Sharman, William J. Kraemer, Dawn M. Love, Neva G. Avery, Ana L. Gómez, Timothy P. Scheett, and Jeff S. Volek.
J. Nutr. July 1, 2002 vol. 132 no. 7 1879-1885

The primary objective of this study was to examine how healthy normolipidemic, normal-weight men respond to a ketogenic diet in terms of fasting and postprandial CVD biomarkers. Ketogenic diets have been criticized on the grounds they jeopardize health (8); however, very few studies have directly evaluated the effects of a ketogenic diet on fasting and postprandial risk factors for CVD. Subjects consumed a diet that consisted of 8% carbohydrate (27 kg/m2 and a clinical diagnosis of PCOS were recruited from the community. They were instructed to limit their carbohydrate intake to 20 grams or less per day for 24 weeks. Participants returned every two weeks to an outpatient research clinic for measurements and reinforcement of dietary instruction. In the 5 women who completed the study, there were significant reductions from baseline to 24 weeks in body weight (-12%), percent free testosterone (-22%), LH/FSH ratio (-36%), and fasting insulin (-54%). There were non-significant decreases in insulin, glucose, testosterone, HgbA1c, triglyceride, and perceived body hair. Two women became pregnant despite previous infertility problems.

16 Evidence type: randomized, double-blind, placebo-controlled, multicenter trial


Study of the ketogenic agent AC-1202 in mild to moderate Alzheimer’s disease: a randomized, double-blind, placebo-controlled, multicenter trial.
Samuel T Henderson, Janet L Vogel, Linda J Barr, Fiona Garvin, Julie J Jones and Lauren C Costantini.
Nutrition & Metabolism 2009, 6:31

AC-1202 significantly elevated a serum ketone body (β-hydroxybutyrate) 2 hours after administration when compared to Placebo. In each of the population groups, a significant difference was found between AC-1202 and Placebo in mean change from Baseline in ADAS-Cog score on Day 45: 1.9 point difference, p = 0.0235 in ITT; 2.53 point difference, p = 0.0324 in per protocol; 2.6 point difference, p = 0.0215 in dosage compliant. Among participants who did not carry the APOE4 allele (E4(-)), a significant difference was found between AC-1202 and Placebo in mean change from Baseline in ADAS-Cog score on Day 45 and Day 90. In the ITT population, E4(-) participants (N = 55) administered AC-1202 had a significant 4.77 point difference in mean change from Baseline in ADAS-Cog scores at Day 45 (p = 0.0005) and a 3.36 point difference at Day 90 (p = 0.0148) compared to Placebo. In the per protocol population, E4(-) participants receiving AC-1202 (N = 37) differed from placebo by 5.73 points at Day 45 (p = 0.0027) and by 4.39 points at Day 90 (p = 0.0143). In the dosage compliant population, E4(-) participants receiving AC-1202 differed from placebo by 6.26 points at Day 45 (p = 0.0011, N = 38) and 5.33 points at Day 90 (p = 0.0063, N = 35). Furthermore, a significant pharmacologic response was observed between serum β-hydroxybutyrate levels and change in ADAS-Cog scores in E4(-) subjects at Day 90 (p = 0.008).

17 Evidence type: review of experiments and case-studies


Beyond weight loss: a review of the therapeutic uses of very-low-carbohydrate (ketogenic) diets.
A Paoli, A Rubini, J S Volek and K A Grimaldi.
European Journal of Clinical Nutrition (2013) 67, 789–796; doi:10.1038/ejcn.2013.116; published online 26 June 2013

[I]t seems a reasonable possibility that a very-low-carbohydrate diet could help to reduce the progression of some types of cancer, although at present the evidence is preliminary. In the 1980s, seminal animal studies by Tisdale and colleagues demonstrated that a ketogenic diet was capable to reduce tumour size in mice, whereas more recent research has provided evidence that ketogenic diets may reduce tumour progression in humans, at least as far as gastric and brain cancers are concerned. Although no randomized controlled trials with VLCKD have yet been conducted on patients and the bulk of evidence in relation to the influence of VLCKD on patient survival is still anecdotal, a very recent paper by Fine et al. suggests that the insulin inhibition caused by a ketogenic diet could be a feasible adjunctive treatment for patients with cancer. In summary, perhaps through glucose ‘starvation’ of tumour cells and by reducing the effect of direct insulin-related actions on cell growth, ketogenic diets show promise as an aid in at least some kind of cancer therapy and is deserving of further and deeper investigation—certainly the evidence justifies setting up clinical trials.