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Archive for Epidemiology

Statins – The Cochrane Review

A recent Cochrane review of the use of cholesterol-lowering statin drugs in primary prevention has sparked some controversy.  The controversy is not so much over what the data says, but in what conclusions to draw from the data.

Statin drugs have been surrounded by controversy for a number of reasons. On the one hand they demonstrably lower cholesterol, and the evidence has shown that they also reduce the incidence of heart attacks and strokes. The data on whether or not they reduce mortality has been less clear, although this latest data actually supports that claim. However, statins have also been blockbuster drugs for pharmaceutical companies and this has spawned concerns (some might say paranoia) that drug companies are pushing billions of dollars worth of marginally effective drugs onto the public.

So are statins a savior or a scam? Life does not always provide nice clean answers to such simple dichotomies. The evidence clearly shows that statins work and are safe. However, pharmaceutical companies do like to present their data in the best light possible, and they need to be watched closely for this. The recent review does call them on some practices that might tend to exaggerate the utility of statins. Finally, the real question comes down to – where should we draw the line in terms of cost-benefit of a preventive measure like statins.

Let’s look as this recent review of the data to see what it actually shows.

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Posted in: Epidemiology

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Obesity Denial

It seems that for every established science there is an ideological group who is motivated to deny it. Denialism is a thriving pseudoscience and affects any issue with the slightest political or social implications. Sometimes, even easily verifiable facts can be denied, as people seem willing to make up their own facts as needed.

Denialists have an easy job – to spread doubt and confusion. It is far easier to muddy the waters with subtle distortions and logical fallacies than it is to set the record straight. Even when every bit of misinformation is countered, the general public is often left with the sense that the topic is controversial or uncertain. If denial is in line with a group’s ideology, then even the suggestion of doubt may be enough to reject solid science.

We see this when it comes to the effectiveness of vaccines, the evolution of life on earth, and anthropogenic global warming. A recent Pew poll shows that the campaign of global warming denial has been fairly successful – while the science becomes more solid around the consensus that the earth is warming and humans are contributing to this, the public is becoming less convinced.

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Posted in: Epidemiology, Public Health

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A Disconnect between cell phone fears and science

Disconnect: The Truth About Cell Phone Radiation, What the Industry Has Done to Hide It, and How to Protect Your Family by Devra Davis, PhD is touted as a book about the issue of cell phones and health. It is instead a tract that conspiracy theorists will love that sheds no objective light on the often confusing scientific data in this area. The tag line on the jacket sets the tone: The TRUTH about cell phone RADIATION. What the INDUSTRY has done to hide it, and how to PROTECT your FAMILY. In the area of EMF and health, there are a certain number of studies that appear to find biological “effects”. This is perfect fodder for alarmists like Davis, who ignore the fact that virtually none of these “effects” have been reproduced in follow up studies. If you were expecting an objective review of the often confusing scientific data in this area, you should avoid this book.

Disconnect focuses almost exclusively on studies that support its alarmist conclusions while either ignoring or falsifying information about studies showing no harm. The quality of scientific studies varies greatly. Disconnect is highly selective and totally biased in discussing only studies that support its point of view, it rejects contrary studies accepted by the majority of mainstream scientists as the product of some vast conspiracy, and it completely misstates the findings of key studies that find no harm from cell phones. She interviewed only a relatively small group of dissident scientists who are outside of the mainstream. The book is completely lacking in objectivity.

Major Factual Misstatements

There are so many things wrong in Disconnect that it is difficult to know where to begin. We will start by reviewing a few of the most blatant examples of how it misrepresents key findings of some of the most important cell phone studies.
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Posted in: Book & movie reviews, Cancer, Epidemiology

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CAM Use by Brain Tumor Patients

A recent article in the journal Neurology reports the results of an observational study regarding the use of so-called complementary and alternative medicine (CAM) by patients with an incurable brain glioma. They found that 40% of patients sought some type of CAM treatment. These results are in line with prior surveys, but require closer inspection.

The study defined CAM as:

Complementary therapy was defined as methods or compounds not used in routine clinical practice and not scientifically evaluated.

This is a problematic definition, but reflects the fact that there is no universally accepted and clean definition of CAM. CAM is a hodge-podge of therapies and modalities that have only one thing in common – they have not met the science-based standard of care. It is not accurate to say that they are “not scientifically evaluated.” Some CAM therapies have not been evaluated, but many have, and have already been adequately found to lack efficacy. In the current study homeopathic remedies were the most commonly reported. Homeopathy has certainly been studied – and found to be indistinguishable from placebo.

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Posted in: Epidemiology

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Freeways, autism, and correlation versus causation

I have a love-hate relationship with epidemiology.

On the one hand, I love how epidemiology can look for correlations in huge sample sizes, sample sizes far larger than any that we could ever have access to in clinical trials, randomized or other. I love the ability of epidemiology to generate hypotheses that can be tested in the laboratory and then later in clinical trials. Also, let’s not forget that epidemiology is sometimes the only tool available to us that can answer some questions. Such questions generally involve hypotheses that can’t be tested in a randomized clinical trial because of either ethical concerns or others. A good example of this is the question of whether vaccines cause autism. For obvious ethical reasons, it’s not permissible to perform a randomized clinical trial in which one group of children is vaccinated and one is not, and then outcomes with respect to neurodevelopmental outcomes, such as autism and autism spectrum disorders, are tracked in the two groups. The ethical concern with such a study, of course, is the potential harm that would be likely to come to the unvaccinated control group, children who would be left unprotected against common and postentially deadly communicable diaseases.

On the other hand, epidemiology is one of the messiest of sciences, and epidemiological studies are among the most difficult in all of science to perform truly rigorously. The number of factors that can confound are truly amazing, and as a result, it’s very, very easy for an epidemiological study to detect apparent correlations that are either spurious or appear much stronger than the “true” correlation. There can be confounding factors beneath confounding factors wrapped in more confounding factors, the relationships among which are not always apparent. Not infrequently, a condition can appear to be correlated with, for instance, an environmental factor, but in reality that environmental factor and the condition both correlate with a third, unknown confounder. Worse, epidemiologists know that correlation does not necessarily equal causation, but the general public, for the most part, does not, which is why, when anti-vaccine activists, for instance, point out to a rising autism prevalence and then point out that autism prevalence started rising around the same time the vaccine schedule was expanded, to the average layperson the argument sounds compelling. As a result, the design of an epidemiological study is paramount in order to account for or minimize such factors. That’s why I always said I can’t be an epidemiologist. Even though I was very good at math in college, the statistics still made my brain hurt, and I don’t have the patience for the messiness of trying to account for all the possible confounding factors.

However, for all their strengths and flaws, epidemiological studies are an integral part of science-based medicine. They are used to identify predisposing factors to diseases and conditions, environmental contributors to disease, and adverse reactions to drugs, among many other useful pieces of data. That’s why, from time to time, I like to examine epidemiological studies, particularly if they’re epidemiological studies that are getting a lot of press.

The use and abuse of autism epidemiology studies

For instance, studies like this one described in a story in the Los Angeles Times on Friday entitled Proximity to freeways increases autism risk, study finds: More research is needed, but the report suggests air pollution could be a factor:
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Posted in: Epidemiology, Neuroscience/Mental Health, Public Health, Vaccines

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