Playing the odds

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Published October 4, 2010 Health Topics 2 Comments

Much of what we do today in medicine isn’t treating diseases, but manipulating risk of disease.

Two people with the same elevated cholesterol value may be treated differently because their other risk factors for heart disease are different. A 65-year-old smoker with diabetes and high blood pressure is statistically more likely to benefit from cholesterol lowering medication than a younger, healthier person. Both these people can lower their heart attack risk by 50%, but, in the case of the younger, healthier person with an already low risk of heart disease, 50% of nothing is nothing. One of the findings of the recent JUPITER study was that lower risk patients could also reduce their heart attack risk by lowering their cholesterol. The question is whether they should be treated, since their risk is already low.

The way I explain this to patients is with lottery tickets and rebate coupons.

“If I buy a megabucks ticket and you buy two, you will have twice the chance of winning that I have, but you probably shouldn’t start spending your money yet” usually gets a nod or a smile.

That example illustrates relative risk. Just like in the example with one or two lottery tickets, relative risk isn’t enough to make a treatment decision. You need to know the absolute risk. For example, who would wear an insulated rubber suit just because it reduces your risk of getting hit by lightning while walking your dog by 60%? Most of us would probably say, “No thank you, I’ll take my chances”.

The Framingham Heart Study provides a simple risk calculator for heart disease. With it, I can show patients their relative and absolute risk of disease in the next ten years. I can then show them the impact of reducing that risk by lowering blood pressure, quitting smoking or treating cholesterol.

Our middle aged diabetic, hypertensive smoker may be facing more than 20% risk of getting a stroke, heart attack or a symptomatic blockage of a coronary artery, while the younger, healthier person may have only a 2% risk of disease in the next ten years.

Which one of these patients to treat for their high cholesterol might be illustrated with a question of when you would rather use a “50% off” coupon – buying a cup of coffee or buying a new car?

Let’s look at the wisdom of treating both the low risk and the high risk person for their high cholesterol in order to reduce their heart attack risk by 50%:

If we treat 100 patients with a 25% 10-year heart attack risk for ten years, only 12 would have a heart attack instead of 25. Treating 100 patients for ten years would prevent 12 heart attacks. You would therefore have to treat 8 patients to prevent one heart attack. We call this the Number Needed to Treat (NNT). An NNT of 8 is a pretty good deal.

For patients with a 2% heart attack risk, we would have to treat 100 of them for ten years in order to avoid one heart attack. An NNT of 100 is clearly very different from an NNT of 8, so “50% risk reduction” really doesn’t tell us much if we don’t know the absolute risk.

Here are some more or less surprising examples of the number needed to treat:

Shingles vaccine doses given in order to avoid one case of shingles: 59.
Ear infections treated with Amoxicillin to avoid one ruptured eardrum: 20.
65-69-year old women treated for osteoporosis to avoid one hip fracture: 88.
Cortisone shots to relieve one sore shoulder: 3.
Aspirin prescriptions to prevent one heart attack: 200.
Prostate cancers treated in order to prevent one death: 18-48 (most men with prostate cancer don’t die from their disease)
Adenomatous colon polyps removed to prevent one colon cancer: 50 (only 2% of “precancerous polyps” actually turn into cancer)

The Number Needed To Treat is not popular with the makers of many of today’s blockbuster drugs. In the case of symptomatic treatment, like heartburn, bladder spasms or pneumonia, patients can more easily judge whether a medication works or not. With risk reduction, we’ll never know ourselves whether we wasted our time and money or not.

As physicians we should not accept claims of relative risk reduction without knowing the absolute risk and the Number Needed To Treat.

I remember people in Sweden talking about a book in the sixties, titled “Hur man ljuger med statistik”. The author, it turns out, was American. Darrell Huff’s “How to lie with statistics”, first published in 1954, is still in print. No wonder; statistics are still being used to trick people, including doctors and patients.

We Use Too Many Medications: Be Very Afraid of Interactions

Published October 17, 2021 Progress Notes 5 Comments

I happened to read about the pharmacodynamics of parenteral versus oral furosemide when I came across a unique interaction between this commonest of diuretics and risperidone: Elderly dementia patients on risperidone have twice their expected mortality if also given furosemide. I knew that all atypical antipsychotics can double mortality in elderly dementia patients, but was unaware of the additional risperidone-furosemide risk. Epocrates only has a nonspecific warning to monitor blood pressure when prescribing both drugs.

This is only today’s example of an interaction I didn’t have at my fingertips. I very often check Epocrates on my iPhone for interactions before prescribing, because – quite frankly – my EMR always gives me an entire screen of fine print idiotic kindergarten warnings nobody ever has time to read in a real clinical situation. (In my case provided by the otherwise decent makers of UpToDate.)

I keep coming back in my thoughts to, and blogging about, drug interactions. And every time I run into one that surprised me or caused harm, I think of the inherent, exponential risks of polypharmacy and the virtues of oligopharmacy.

One conclusion I have come to is that too often the benefit of our prescribed medication is actually too small to justify the drug. The way drugs are approved today is pretty much that they have to bring a 20% or so advantage over placebo for a certain outcome. Other than the drug versus placebo, all other factors are ignored or “controlled for”, which is easier said than done.

But this whole premise seems wrong to me: If pill A is 20% better than placebo at lowering blood pressure, but salt restriction, weight loss, exercise and stress reduction are twice as powerful as pill A, why are we so stuck on prescribing pill A? If a Mediterranean diet lowers cardiovascular risk as much as atorvastatin, why isn’t that a blockbuster/no-brainer intervention?

The health of our nation is not great, in spite of all the pills at our disposal. And the more pills we prescribe, the more we risk interactions: antidepressants and cholesterol pills with blood thinners, gout medicines with cholesterol pills, mood stabilizers with cardiac medications and on and on and on.

May we all take a step back and look at the big picture of what we are doing and where we are heading.

Donald W Light from the Harvard Center of Ethics wrote in 2014:

Few people know that new prescription drugs have a 1 in 5 chance of causing serious reactions after they have been approved. That is why expert physicians recommend not taking new drugs for at least five years unless patients have first tried better-established options, and have the need to do so.

Few know that systematic reviews of hospital charts found that even properly prescribed drugs (aside from misprescribing, overdosing, or self-prescribing) cause about 1.9 million hospitalizations a year. Another 840,000 hospitalized patients are given drugs that cause serious adverse reactions for a total of 2.74 million serious adverse drug reactions. About 128,000 people die from drugs prescribed to them. This makes prescription drugs a major health risk, ranking 4th with stroke as a leading cause of death. The European Commission estimates that adverse reactions from prescription drugs cause 200,000 deaths; so together, about 328,000 patients in the U.S. and Europe die from prescription drugs each year. The FDA does not acknowledge these facts and instead gathers a small fraction of the cases.

There are obviously more recent statistics out there, but this piece struck me because it was published in a forum about ethics. Think about that for a moment: We are subjecting our patients to known and unknown risks of harm with every prescription we issue.

Cave: Ignoring the NNT

Published October 23, 2017 Cave! 3 Comments

How would you like to double your chances of winning the lottery? Just buy two tickets!

Statistically, this is true, but is that a reason to spend more money on something that most likely offers no return on investment?

Yet, in medical research, study after study shows impressive improvement in relative risk for this, that and the other intervention but a small or even negligible effect on absolute risk.

For example, I just read a study in the New England Journal of Medicine comparing giving a new osteoporosis drug to women with osteoporosis and a prior history of an osteoporotic fracture for one year, followed by an older drug for one year to just giving the older drug for two years. The two drug regimen lowered an osteoporotic woman’s risk of hip fracture by 38%.

The number of hip fractures in the combination treatment group was 41 out of 2046 patients, and in the single drug group it was 66 out of 2047 patients.

In absolute numbers, treating 2046 patients reduced the hip fracture risk by 25 cases. The number of women one would need to treat to avoid one hip fracture, the “NNT”, is 2046 divided by 25, or 81.

That NNT isn’t terribly impressive, especially in light of the fact that 12 more patients in the new drug group had a cardiovascular event in the first year than in the old drug group.

The editorial accompanying this article does say “In sum, ARCH revealed that romosozumab has great potential as a short-term anabolic treatment for osteoporosis. However, until the cardiovascular and endocrine effects of this antibody are clarified, romosozumab will remain more a part of our expectations than our armamentarium.” But if the drug company starts promoting the relative risk reduction of this treatment, doctors could be misled and patients could come to harm.

Here are some more examples of he Number Needed to Treat for some common health interventions, published in a post I wrote 7 years ago:

1) Shingles vaccine doses given in order to avoid one case of shingles: 59.

2) Ear infections treated with Amoxicillin to avoid one ruptured eardrum: 20.

3) Cortisone shots to relieve one sore shoulder: 3.

4) Aspirin prescriptions to prevent one heart attack: 200.

5) Prostate cancers treated in order to prevent one death: 18-48 (most men with prostate cancer don’t die from their disease).

6) Adenomatous colon polyps removed to prevent one colon cancer: 50 (only 2% of “precancerous polyps” actually turn into cancer).

May I never forget to consider the NNT…