The FDA assures Americans that its review process guarantees that “drugs are safe and effective.” But anyone who watches television knows from the drug commercials that the agency approves medications that can cause heart attacks, kidney damage, cancer or death. Safe? Not really. What about effective? Most people assume if a doctor writes a prescription the medicine works. Ditto for OTC remedies. You are about to learn that your definition of effective is dramatically different from the FDA’s definition!
How Do Smart Consumers Shop?
How do you decide which mattress, smart phone or toaster to buy? Some people just look for the best price. Others depend upon advertising. Smart consumers check ratings and reviews, preferably from an unbiased source such as Consumer Reports (CR).
This nonprofit consumer organization tests products independently and does not accept advertising. Their analysts review cars, TVs, laptops, headphones and a wide range of other consumer goods in a scientific and objective fashion.
The results are reported in an easy-to-understand graphic format. There is often a rating number that allows you to compare one car against another.
For example, CR rates the most reliable midsized sedan the Toyota Camry Hybrid 2023 a 90, whereas the Hyundai Sonata 2023 comes in at 80.
How about sports utility vehicles (SUVs)? They are extremely popular these days, but which scores highest? The 2024 Suburu Forester tops the list of compact SUVs at 87. On the other hand, CR rates the Mitsubishi Eclipse Cross at 56.
In the market for a vacuum cleaner? The Miele Complete C3 Marin at $999 scores an 84 rating at CR. Lower is the Dyson Big Ball Multi Floor, scoring 56 at $309.98.
How Would You Know How Well Your Medicine Works?
We wish doctors, pharmacists and patients had access to a similar system for evaluating medications. Most health professionals have no clue about the actual effectiveness of the drugs they prescribe or dispense. They also may not have a good way of evaluating the potential for harm.
People are exposed to way too much pharmaceutical information in the form of television commercials. Drug companies present their medicines in the best possible light. Actors portray individuals having a wonderful time at parties, climbing mountains or frolicking on the beach. Children and dogs are prominent in these ads.
An announcer often recites a long list of side effects at top speed while people on the screen are having fun. It’s a highly effective distraction technique. Such commercials rarely provide data that would help a patient decide whether a particular medicine would be helpful or hurtful.
Beware Relative Risk Reduction (RRR)!
Drug companies have figured out a way to confuse both health professionals and patients. It’s sneaky!
The trick is to use something called “relative risk reduction” or RRR. A former FDA commissioner, Dr. Stephen Hahn, fell into this trap.
He described the benefits of convalescent plasma against COVID-19. He announced that 35 patients out of 100 could be saved if they got blood plasma transfusions from someone who had recovered from a very bad COVID infection.
Many people were impressed and might have considered such treatment. It was totally misleading, however. The RRR always make it seem something is far better than it really is.
Dr. Eric Topol is a renowned cardiologist. He is the founder and director of the Scripps Research Translational Institute, Gary and Mary West Endowed Chair of Innovative Medicine, professor of Molecular Medicine and Executive Vice President of Scripps Research. Dr. Topol has published more than 1,200 peer-reviewed articles. He told NPR this about FDA Commissioner Hahn’s goof up regarding his description of convalescent blood plasma transfusions against COVID:
“I can’t remember a mistake by FDA or the commissioner as serious as this one. Serious mistakes undermine your credibility.”
Dr. Hahn later amended his RRR statement to say:
“What I should have said better is that the data show a relative risk reduction not an absolute risk reduction.”
In our article about this deception we wrote:
“It turns out that the message that 35 lives would be saved out of every 100 patients treated was totally deceiving. The study Dr. Hahn was referring to did not have a placebo arm. Everyone in the study with COVID-19 received convalescent plasma.
“One group of patients got the plasma within three days of being hospitalized. The other group received their intravenous plasma later. Mortality was assessed after a week and again after 30 days. The death rate for the early plasma recipients was 9% after seven days compared to 12% in the delayed plasma group. At one month, 22% of the early plasma recipients had died compared to 27% in the delayed group.
“The absolute risk reduction (ARR) of death was somewhere between 3 and 5 percent. That doesn’t sound nearly as impressive as the 35% Dr. Hahn originally cited.”
Most of the headlines you read in newspapers about drug “advances” report RRR instead of ARR. That makes it seem as if the medication is hugely effective. Do not fall into the trap that the Commissioner of the FDA fell into, however. Always seek information about the absolute risk reduction!
The Number Needed to Treat Helps Evaluate How Well Medicine Works:
There is, however, an approach that could be highly useful if more health professionals and patients utilized it. Calculating the number need to treat (NNT) or the number needed to harm (NNH) can be extremely helpful.
There are some websites that provide this kind of information for many medications. One is theNNT.com.
Here is how NNT works. The analysis depends upon data from randomized controlled trials. This number allows someone to tell how likely a drug is to help an individual patient. Conversely, the NNH describes the statistical risk that a medicine will be harmful.
Antibiotics vs. Sinusitis:
One example of how medicine works would be antibiotics for sinusitis. One person out of 17 was cured within one to two weeks. That yielded an NNT of 17.
On the other hand, one in eight individuals were harmed due to antibiotic side effects. This is actually a fairly good result, even though more people were harmed than benefitted.
The same data in percentages:
“6% were helped (cure at 7-14 days)
12.5% were harmed (adverse medication effects)”
Aspirin vs. Heart Attacks:
Another example is aspirin taken to prevent an initial heart attack. The analysis shows that 333 people had to take aspirin for one person to avoid a nonfatal heart attack (NNT=333). On the other hand, one person out of 250 experienced serious bleeding (NNH=250).
The same data in percentages:
“0.3% lower risk of heart attack
0.4% higher risk of major bleeding”
Blood Pressure Medicines vs Heart Attacks, etc:
This will come as a shock to both physicians and patients. Most people believe that BP meds will protect them from bad outcomes. The NNT website reports the following stats for:
“Blood Pressure Medicines for Five Years to Prevent Death, Heart Attacks, and Strokes”
“Benefits in NNT:
“1 in 125 were helped (prevented death)
1 in 67 were helped (prevented stroke)
1 in 100 were helped (prevented heart attack: fatal and non-fatal myocardial infarction and sudden or rapid cardiac death)”
“Harms in NNT:
“1 in 10 were harmed (medication side effects, stopping the drug)”
The same data in percentages:
“97% saw no benefit
0.8% were helped by preventing death
1.5% were helped by preventing stroke
1.0% were helped by preventing heart attack”
“10% were harmed by medication side effects, stopping the drug”
Of course this does not mean that someone with hypertension should stop taking medicine. Controlling high blood pressure is very important! But it is also important for physicians to be precise when telling their patients how well a medicine works at preventing a problem.
You can read more about “The Pros and Cons of Treating Mild Hypertension” at this link.
Making Sense of Drug Effectiveness and Risks:
The NNT calculations can help a patient better determine their odds of getting benefit compared to experiencing harm. Patients should ask their health care providers about the NNT for any proposed prescription. Doctors and pharmacists can calculate these numbers by going to ClinCalc.com/stats/NNT.aspx. It requires data from well-controlled trials, however.
In his book, Sickening: How Big Pharma Broke American Health Care,” Dr. John Abramson tells his readers how to calculate the NNT for themselves:
“NNT is easily calculated by dividing 100 by the absolute risk reduction.”
Dr. Abramson goes on to calculate the NNT for statins:
“Similarly, the absolute risk reduction of death among people treated with a statin who already have cardiovascular disease is 1.25 percent over five years, so to prevent a single death with five years of statin therapy the NNT is eighty (NNT = 100/1.25). Again, statin therapy will not protect the other seventy-nine from death.”
If consumers can use independent ratings to make well-informed decisions about cars, computers or coffee makers, why shouldn’t they have access to objective information about the risks and benefits of the medicines their doctors have prescribed?
Ask How Well Your Medicine Works!
When your health care provider offers you a prescription, why not ask some questions:
• What are the chances I will get benefit from this medication? Please provide numbers!
• Can you share with me the absolute risk reduction for my health problem?
• Can you tell me the number needed to treat (NNT) for this medication?
• What is the number needed to harm (NNH)? What are the most common side effects and the most serious adverse reactions?
• Are there symptoms that I should be on the lookout for?
• What symptoms would require emergency action?
• If something goes horribly wrong, how can I contact you promptly? Could you give me your cell phone # so I can text you if I need emergency care?
Please share your own medication experience in the comment section below. Would you like to know the likelihood that your medicine works or could cause harm? If you think a friend or family member might benefit from this article please scroll to the top of the page and send it by clicking on the icon for email. Thank you for supporting our work.