A little over 30 years ago, Henry Gadsden was the CEO of Merck Pharmaceuticals. And he was distressed that his products were limited to sick people. He wanted to expand the market. In fact, he wished Merck could become more like “Wrigley’s chewing gum.” He openly dreamed of making drugs for healthy people. That way, Merck could “sell to everyone.”
His feelings – revealed in Selling Sickness by Ray Moynihan – are representative of the true motivations of Big Pharma.
Today, the pharmaceutical giants fund aggressive marketing campaigns. They spend billions upon billions of dollars to widen the boundaries of illness. And they have largely achieved Henry Gadsden’s dream. Millions of otherwise healthy people have become lifelong customers of Big Pharma.
But the drug companies have not achieved this goal through scientific innovation alone. Nor is their success based on the proven safety and effectiveness of their drugs. In many cases, their products are not safe or effective.
Instead, much of their success comes from the manipulation of statistics. The drug companies know that numbers can be very persuasive. So they use those numbers to put their products in the most favorable light. But they don’t just manipulate statistics to magnify benefits… They also use them to sweep risks under the rug.
Mark Twain once said, “There are lies. There are damn lies. And there are statistics.”
Here are two ways that Big Pharma and Big Medicine have used statistical trickery and scientific sleight of hand to exaggerate the benefits (and hide the risks) of their drugs.
The Ruse of Relative Risk Reduction
We have pointed out before how Big Pharma is playing a numbers game with flu shots.1 One flu study came out of the University of Minnesota. It was headed by Dr. Michael Osterholm and published in The Lancet.
Dr. Osterholm and his team reviewed over 5,000 studies published over the last 45 years. They narrowed those studies down to 31 trials. They focused their research on about 32,000 people.
Their first discovery was that most flu shots are out of date. In fact, some are still using strains of the flu from the 1950s and 1960s. The flu virus has a very high mutation rate. In fact, some strains mutate from one host to the next. This fact alone makes most modern flu vaccines ineffective… So one made with a 50-year-old strain must be utterly worthless.
But there is a more important aspect of this study…
Dr. Osterholm’s study showed that flu shots prevent about 60 percent of flu cases. This is the number that was widely reported in the media. But if you dig into the actual results, you would find that they only prevent the flu about 1.5 percent of the time.
Here’s the thing: both statistics are correct. It all depends on how you interpret the results. And you can imagine the interpretation Big Pharma and their media minions would want.
Dr. Osterholm pooled the data for almost 32,000 people. He then compared the number of flu cases in those who got shots versus those who received a placebo. Out of those who received a placebo, 2.7 percent contracted the flu. Out of those who got the shot, 1.2 percent got the flu.
One honest way to report these results is to subtract the two percentages. This would give you the Absolute Risk Reduction. This is the number that reports the actual difference between the treated and untreated groups. In the case of this study, it means that the flu shot reduced cases of the flu by 1.5 percent compared to a placebo. Another way to put it is that the flu shot is 98.5 percent useless.
That’s not good if your goal is to paint the flu vaccine in a good light. So, instead the researchers focused on the Relative Risk Reduction. To get this number, you simply calculate the percentage reduction between 2.7 and 1.2. That gives you a relative risk reduction of 60 percent.
And that’s why the headlines about this particular study reported that the flu jab is effective at preventing the flu for 6 out of 10 people who receive it.
Highlighting the better statistics is pervasive in pharmaceutical research. For example, it has been used to sell billions (and billions) of dollars worth of cholesterol-lowering drugs.
The promoters of statin drugs insist that those with so-called “high cholesterol” can achieve a 36 percent reduction in the incidence heart attacks. That is the relative risk reduction. The same raw data yields an absolute risk reduction of a paltry 1 percent.
This is nothing less than advertising disguised as science. And it is a dangerous trend. It helps to promote drug use among healthy populations… Who then expose themselves to needless risk. The adverse side effects of statin drugs, for example, can include cancer, memory loss and even heart failure.
Dr. Nortin Hadler is a Professor of Medicine and Microbiology at the University of North Carolina. He joined the faculty almost 40 years ago, after getting his M.D at Harvard. He is also a member of the American Society of Clinical Investigation.
He knows how to interpret scientific studies. Dr. Hadler says, “The absolute reduction is what is meaningful. Never let anyone talk to you about relative risk reduction.”
He calls the focus on relative risk reduction “reprehensible.” It is a way of “torturing scientific data and massaging statistics” to protect or promote pharmaceutical drugs.
It’s easy to see why drug companies want scientists (and the media) to report on relative risk. It exaggerates benefits. But this is not the only way they contort statistics. They use another sleight of hand to hide risks.
NNT: Number Needed to Treat
Patients should be able to make informed decisions about whether a drug’s benefits are worth the costs. That’s true of medical procedures as well. But the medical establishment rarely makes it easy for you to do so.
One way that they hide the risks of drugs is with a statistic known as the Number Needed to Treat (NNT). This is the number of people you need to treat in order for one person to receive a benefit.
In some cases, doctors and drug companies will consider a particular drug effective even if the NNT is 20 or 30. That would mean 20 or 30 patients would have to be treated for just one to receive a benefit. But if that “benefit” is avoiding death, it might be worth it.
However, relying solely on NNT is superficial and dangerous. That’s because it only focuses on a single event – the positive one. It does not take into account the negative side effects of the drug. That would be the Number Needed to Harm (NNH). And this intentional oversight can have deadly consequences.
Consider the drug Vioxx. It was used to reduce pain and inflammation. Dangers associated with this drug first appeared in Merck studies around 1998. But the danger was buried under an avalanche of NNT statistics. The NNT for Vioxx was an exciting 2.2. In other words, 2.2 patients had to be treated for one person to receive pain-relief.
That sounded great. But the over-emphasis of this one statistic caused medical professionals and patients to overlook the dangers. Vioxx wreaked havoc for five years before it was finally withdrawn from the market. The FDA has estimated that this drug injured up to 139,000 Americans. According to one of the FDA’s own safety officers, Dr. David Graham, 40,000 of these people died as a result.
Would you take a “highly effective” pain reliever… if you knew there was a chance it could kill you?
Before you ever consider taking a drug, you should thoroughly investigate the risks. The same goes for medical procedures. The information is out there. But you can’t rely on the pharmaceutical companies or even your doctor to inform you.
It is YOUR body. Take responsibility for it.
And always remember that prescription drugs don’t heal. They mask. Drugs may help to relieve the symptoms of an illness. But they do nothing to address the cause.
If you truly want to remedy an illness you must address the source of the problem. Identify and eradicate the habits that may have led to the illness in the first place. Then seek the foods, natural supplements, sunlight and exercise that will enhance your body’s ability to heal itself.
And stay tuned to INH Health Watch. In a future issue of this newsletter, we will discuss another way that Big Medicine lies to you. It’s called Comparative Effectiveness Research. That’s when researchers compare two (or more) treatments or procedures against each another. But what they don’t tell you is that BOTH treatments are ineffective. So you get the comparison of one against the other… without the knowledge that neither one works![Ed. Note: If you want even more in-depth research into mainstream medical myths… Specific, science-backed treatments for everything from cancer to heart disease to Alzheimer’s and more… And real, useful information you can try yourself or take to your doctor… You’ll want to become a member of our monthly health advisory service, Natural Health Dossier. Click here to watch a short presentation and get all the details.]