Category: Medical Science Research

The health experts are united in proclaiming the importance of preventative health in general, and regular colonoscopies in particular. Get one so you can avoid dying of colon cancer! As is sadly all-too-usual, the colon cancer early detection campaign is propaganda to cajole people into putting lots of money into the pockets of doctors and health systems — with no provable benefit to the patients who do their best to patiently put up with the pointless nonsense.

Do people who get colonoscopies avoid getting colon cancer? Yes, the vast majority of tested people avoid it; but then the vast majority of untested people also avoid getting it. Does getting colonoscopies as recommended help you live longer? All the authorities say it does, but the recently published RCT (random controlled trial) with over 80,000 subjects — the ONLY such gold-standard trial EVER conducted — shows that colonoscopies do NOT help the people who get them live longer.

It's no wonder that the medical-industrial complex has united to discredit this trial that threatens their revenue stream. Experts are speaking out, waving their arms wildly and pronouncing with deep-voiced authority that the trial is misleading. I guess all the people and organizations drinking from the fire hose of tens of billions of dollars a year in testing fees have been too busy to conduct a trial of their own to demonstrate that what they do actually helps people.

Colon cancer is a big deal

There is no doubt that colon cancer is something to be avoided, if at all possible. It's the fourth leading cause of cancer deaths, behind breast, prostate and lung cancer. Lots of people are diagnosed with it and die from it, according to the National Cancer Institute:

Getting colon cancer isn't a death sentence — look at the survival rate above — but we would all like to avoid getting it.

An ever-increasing number of people are screened for this terrible disease. According to the National Cancer Institute:

This adds up to over 16 million colonoscopies in 2019! The cost? Good numbers are hard to find, but it's probably in the range of $30 to $60 Billion dollars a year for screening.

The Voice of the Experts

Here is the summary recommendation of the U.S. Preventative Services Task Force:

The Grade A is primarily because the screening has "substantial net benefit." (Bold in the original.)

This organization has plenty of prestigious company in making this recommendation. For example, they say:

There is a general consensus that average-risk adults aged 50 to 75 years should be screened. The American Academy of Family Physicians (AAFP),⁴² American College of Physicians (ACP),⁴³ American Cancer Society (ACS),⁴⁴ and the US Multi-Society Task Force (which includes the American College of Gastroenterology, American Gastroenterological Association, and American Society for Gastrointestinal Endoscopy)³¹ all recommend routine colorectal cancer screening in this age group, although specific recommended tests and frequency of screening may vary.

It's not just the big organizations. Doctors and health systems on the front lines pitch the same message. Mount Sinai hospital in New York City recently put up a strong pitch on the subject. They lead their long article with this:

Colonoscopy is one of those important, routine medical procedures that most people would rather avoid. But experts say the test is a highly effective tool for both preventing colorectal cancer and diagnosing it at an early stage.

Along with the American Cancer Society, they recommend that screening start at age 45.

The trouble is, when you read all this carefully, particularly the extensive review that led to the USPST report above, you find a complete lack of RCT's for the effectiveness of colonoscopies. Nothing but modeling and authoritative-sounding guessing.

Experts attack the skeptics

Every once in a while, someone pops up who says that colonoscopies don't do any good. Fortunately for concerned patients, the experts tend to jump on such baseless assertions and tear them apart with facts and sound reasoning. Most of the Mount Sinai article just mentioned is devoted to this. It says:

Those looking for an excuse to put off a colonoscopy might now point to a large study conducted in Europe and published in September 2022 in The New England Journal of Medicine (NEJM) that appeared to question the benefits of colonoscopies.

For some reason, the Mt Sinai article fails to give a link to the study in question, which is here. I guess they feel that readers don't need to waste their time, since Dr. Greenwald's  take-down is authoritative. It continues with this:

In this Q&A, Dr. Greenwald, Immediate Past-President of the American College of Gastroenterology, and Co-Chair of New York’s Citywide Colorectal Cancer Control Coalition (C5), discusses the recent study and why the value of colonoscopies remains unchanged.

Here's the man himself. He is a seriously authoritative-looking guy:

The NordiCC Study and the response of the Experts

The NordiCC study is the one described in the recent New England Journal of Medicine article that Dr. Greenwald tore apart in the Mt. Sinai article promoting colonoscopies. The study followed over 84,000 "presumptively healthy men and women 55 to 64 years of age drawn from population registries in Poland, Norway, Sweden, and the Netherlands between 2009 and 2014."

The article seems to support performing colonoscopies. Here's the conclusion of the Abstract at the beginning of the paper:

In this randomized trial, the risk of colorectal cancer at 10 years was lower among participants who were invited to undergo screening colonoscopy than among those who were assigned to no screening.

I guess Dr. Greenwald and others were concerned about the fact that the numbers weren't strong. The Mt. Sinai article said the study "appeared to question the value of colonoscopies." Dr. Greenwald is quoted by Mt Sinai as saying

This study, along with prior studies, shows that colonoscopy decreases your chances of getting and dying from colorectal cancer. Getting sick and dying from colorectal cancer—especially due to delayed screening—is real. Screening with colonoscopy saves lives.

Done!

The NordiCC Study

Why would multiple European national governments go the trouble and expense of such a massive trial if the value of colonoscopies had been conclusively proven? Hmmm. The answer is simple: colonoscopies are expensive and highly unpleasant, and there have been NO RCT's that show a causal relationship between getting them and avoiding getting and dying from colon cancer. So before taking on all the cost and trouble, those groups figured they'd better get some real evidence on the subject.

First, let's see what the expert from Mt Sinai drew from the study:

Most importantly, in the section of the study that analyzed people who actually had a colonoscopy, the risk of developing colorectal cancer decreased by 31 percent and the risk of dying from colorectal cancer decreased by 50 percent, which is huge.

Wow. Why would anyone be worried about the NordiCC study scaring people from getting a colonoscopy, when it has such a huge benefit — and the doctor claims that in the US it is performed better, yielding even stronger preventative results!

When you read the NordiCC study itself, aided by understanding of the statistical tricks that are used to distort the results, a whole different message emerges. This is why the medical-industrial complex goes to great lengths to hide the truth.

In this case, the core trickery is a biased sub-group created from the group invited  to have a colonoscopy that they call an "adjusted per-protocol analysis." The other main tricks are widely used: reporting "efficacy" (relative risk); ignoring NNT (absolute risk); and endpoint selection (dying of cancer vs. dying of any cause).

Here is a brief summary of the real results of the trial by Dr's John Mandrola and Vinay Prasad. I have verified that this summary accurately reflects data in the NEJM paper (see Table 2 of the paper):

• Over 10 years of follow-up, an invitation to screening colonoscopy modestly reduced the risk of being diagnosed with colorectal cancer, but it did not significantly reduce the risk of dying from colorectal cancer. Survival from cancer was nearly identical in both groups.  And all-cause mortality was the same.

The specific numbers of the primary outcome:

• The chance of getting (diagnosed with) colorectal cancer in the invited group was 0.98% vs 1.2% in the usual care group. This represents an 18% reduction in relative terms, and an absolute risk reduction of 0.22% or 22 per 10,000.

• The chance of dying from colorectal cancer in the invited group was 0.28% vs 0.31% in the usual care group. This 10% reduction in relative terms amounted to a difference in 3 in 10,000 and did not reach statistical significance.

• In the invited group, 11.03% of patients died; in the usual care group, 11.04% of patients died.

Here is a key chart from the paper, showing the risk of dying from colon cancer. Note that the real data is a barely noticeable squiggle along the X axis at the bottom; most of the chart is a big blow-up of the bottom 1% of the Y axis.

The tiny difference (3 in 10,000) in dying of colon cancer was not statistically significant. And the most-important-of-all measure, all-cause death, was identical.

Those are the indisputable facts from the study itself.

The authors of the study did their best to fiddle with the results — they declared themselves to be "disappointed" in the study results. They put their fiddling in the paper.

The most significant game they played involved the fact that 42% of the subjects who were invited to have a colonoscopy actually had one. They recalculated the results for just the people in the invited group who actually had the procedure, trying to get better results; in the study, they call this a "per-protocol analysis." This shows the desperation of the authors, since doing this violates all the randomness and invites a host of what statisticians call "confounding factors," exactly the thing that a RCT avoids by being random. Naturally, this improved the results. By a small amount.

The authors and all the establishment defenders of colonoscopies do the classic thing that people who want to promote a drug or procedure do to mislead patients: they focus on relative risk instead of absolute risk. Relative risk, often called "efficacy," makes you think that the procedure is terrifically effective. What do you think when you read that your risk of death is "decreased by 50 percent?" It's huge, right? See this post on vaccine efficacy for a detailed explanation. What most people care about is absolute risk, which is how likely it is that the feared thing will happen to you. This is sometimes called NNT (Number Needed to Treat), which is the number of people who have to undergo the procedure in order for just one of them to benefit.

The per-protocol analysis (the best case) showed the risk of dying from colon cancer to be 0.15% in the invited group and 0.30% in the control group. This is a 50% improvement in relative terms which sounds great!  But in real-life absolute terms, it's a different of 0.15%, which is 15 for each 10,000 people And again, the difference of dying from any cause between these two groups was effectively zero. Here is a detailed discussion of per-protocol fiddling and the results of a statistically sound approach, which reduces the statistical significance of the colonoscopy benefit to zero … as shown in a table of the supplement of the NEJM study.

And then there are the harms. What can go wrong with a colonoscopy? The USPST, the government group quoted above that recently recommended that colonoscopies start earlier than before, at age 45, discusses them deep in the supporting material. They report: "Harms from screening colonoscopy have been reported in 67 observational studies (n = 27,746,669)." You have to read carefully, Here's what they report:

14.6 major bleeding events per 10,000 colonoscopies (95% CI, 9.4-19.9; 20 studies; n = 5,172,508) and 3.1 perforations per 10,000 colonoscopies (95% CI, 2.3-4.0; 26 studies; n = 5,272,600)

That is a high confidence result of harm based on millions of patients, vs. the nearly identical low-confidence results of benefit from the NordiCC study.

Conclusion

The authors of the NordiCC study wanted to find that colonoscopies are effective — they say so! They did their best to slant the results and obscure the real results. Experts reporting on the study in the US cherry pick and criticize the slanted results and confidently proclaim that colonoscopies are essential to health and longevity, when the clear numbers in the published study of over 80,000 subjects show no such thing. This is yet another example of self-serving advice from a medical establishment that depends on trusting, gullible patients to keep the money rolling in. For more, read these posts about flu, diet, saturated fat, cholesterol and blood pressure.

Why do insurance companies jack up premiums to shell out big bucks for drugs and procedures that don't help?

 

The drumbeat happens every year, echoing far and wide: It's flu season! Protect yourself and others — get a flu shot right away! Roughly half of the population heeds the message and gets the shot.

The reality of the flu and flu vaccines can be found, but it's elusive. Once you find out what's really going on, you can't help but wonder why public authorities and provider groups keep pounding everyone to take these shots.

What we're told about the flu and flu shots

I got an email from my primary care provider. Here was the attention-grabber:

And here was the lead paragraph:

They go on to give lots of detail in an FAQ.

It's pretty clear: get a flu shot and you won't get the flu. It's not just my medical group; they all seem to say it, along with major pharmacies like CVS. The FDA is equally clear: "A flu vaccine can be given to anyone who wants to avoid the flu (persons over 6 months of age."  The CDC pushes it hard:

The message is similar to "shovel the snow off your snowy walk, and you won't slip and fall." 

The flu is awful!

The CDC makes repeated strong claims about how awful flu is and how flu shots protect you from getting the flu. Surely those claims are backed by solid data, gathered by some of the more than 10,000 employees of that organization.

First, the CDC collects and presents highly detailed data about what they call the "burden" of flu, by which they mean the number of people made ill, hospitalized or killed by it. While the numbers vary from year to year, the totals are massive:

For example, for the last flu season entirely unaffected by Covid, here are the annual numbers from the CDC:

The overall burden of influenza (flu) for the 2018-2019 season was an estimated 29 million flu illnesses, 13 million flu-related medical visits, 380,000 flu-related hospitalizations, and 28,000 flu deaths (Table 1)

Huge, right? It makes sense that everyone should be protected against these consequences of the terrible disease of flu.

Let's dig a little deeper into those catastrophically bad outcomes. Again, we'll use the CDC's own data.

First, let's look at the flu disease burden by age. The CDC, quite sensibly, presents these next numbers as a rate per 100,000, so that you can get how likely the outcome is to actually affect you.

For little kids, age 4 and under, the rate of catching the flu is a whopping 15,238 per 100,000 — about 15% of little kids got the flu! For people aged 5 to 64, it was in the range 7- 12,000 for most older kids and adults; less for those 65 and older. Lots of people get the flu, around 10%.

With so many people catching the flu, it makes sense that the flu shot is pushed by health authorities. It's not rare, it's widespread! The numbers back it up.

What about all those hospitalizations and deaths?

While getting the flu, going to the doctor and even getting hospitalized aren't great, the thing you really want to avoid is death.

So what happens after you get the flu? For the vast, vast majority, not much. For young kids and older adults, only 0.1% end up in the hospital, and for most it's less than half of that. Death? The death rate for adults 18 to 49 is 1.2 per 100,000. That's a rate of 0.001%. The rate for younger people is even lower.

How the the flu rank among the other causes of death? The CDC has the numbers.

Flu ranks number nine out of the top ten, about the same as kidney disease. Things like accidents, strokes and the ever-present heart disease and cancer are way more dangerous. And the chart says "flu and pneumonia," without getting specific. Chances are it's mostly pneumonia. From another CDC data table, I find that the rate of death due to suicide in 2019 was 14.5 per 100,000. So the chances of dying from the flu or pneumonia were about the same as killing yourself!

But wait! Something's wrong! The deaths per 100,000 are listed as about 13, while we learned from the CDC (table 2 above) that the flu deaths for kids and adults per 100,000 were only about 1 — truly tiny!

Putting the death rate for kids and most adults into the chart above, the rate of dying of the flu is less than one tenth that of the least likely of the top ten, way under 1% of dying from one of the top two causes. For kids and most adults, dying of the flu is not even close to being a leading cause of death.

Old people and the flu

Let's read the stats about flu burden by age (table 2 above) more carefully. Go down to the bottom and look at the numbers for older people, 65 and over. Only 4% of older people get the flu (way less than other ages), but for those who do, the rates of hospitalization and death are dramatically higher. Roughly 10% of those who get the flu end up in the hospital and 10% of the hospitalizations result in death! That's a mortality rate of 40 per 100,000. So it's the old people dying of flu (and pneumonia) that puts flu into the top ten causes of death! Without the old people, not only would the flu death rate not make the top ten causes of death, it would be less than 10% of the bottom cause, kidney disease! And way lower than other things such as accidents and suicide.

Let's understand the death rate for old people. Yes, it's forty times larger than the rate for most younger people. Scary, right? But running out the numbers, 0.4% of old people are hospitalized due to flu, and 0.04% of old people die of the flu. That's according to the CDC. Here's a chart from the CDC's annual report (a PDF file) of the leading causes of death for older people:

See flu and pneumonia there on the left? Pretty low on the list of things for older people to be worried about.

The charts for younger people are also interesting. For ages 10 to 24, accidents, suicide and homicide cause more than two thirds of deaths, while flu is less than a percent. For adults aged 25 to 44, flu is one percent, while for ages 45 to 64, flu doesn't even make the chart.

What about the flu shots?

The CDC and the rest of the health establishment may flash warning lights with loud warning sounds about the flu and how we need protection from it, but we now know that the numbers aren't compelling. But getting a flu shot isn't a big deal. shouldn't we get it anyway so that we're protected against the flu?

Flu shots: the CDC

First, let's look at the CDC's own numbers. They went to the trouble of assembling patient panels so they could get good numbers. The numbers have increased over the years; the recent 2018-19 panels are over 10,000 people. Here is the chart from the 2018-19 panel for effectiveness of flu shot against by age:

This is tough to make sense of at a glance. First, look at the top line, for all ages. 2763 people got the flu — and almost half of them (48%) were vaxed! Meanwhile, 7249 people were flu-free, with a bit over half (56%) vaxed. Clearly, the vax didn't make much difference.

The numbers for older people are interesting. As we saw above, people 65 and older are the least likely to get the flu but the most likely to be hospitalized or die from it. The table shows that the older were far more likely than the rest to be vaxed, over 80%. But the number vaxed was nearly identical in the groups with and without the flu. Let's dig in.

The last column, CI (confidence interval) will be mysterious to most people. The CDC has an explanation in its section on vaccine effectiveness  It's standard statistics. They give the effectiveness number based on a tiny fraction of the number of people who could get the flu. How likely is it to be the true value? The CI is the range of values it would be, with 95% statistical confidence. See the negative numbers in the far right for teens and adults age 50 and older? According to the CDC (and statistics in general) that means:

…if a confidence interval crosses zero, for example, (-20% to 60%), then the point value estimate of VE provided is considered “not statistically significant.”

Not only was the VE tiny, the number is effectively meaningless — the flu vax could increase your chances of getting it, or decrease your chances. The CDC's main flu vax effectiveness ongoing study can't tell the difference! Which means … getting the flu shot has no impact on whether you get the flu.

Flu shots: published controlled trials

There have been dozens of published controlled trials of flu vaccines in multiple countries. Reviews of the many trials have been conducted and published. This is an updated version published in 2018 of the prior review.

We included 52 clinical trials of over 80,000 people assessing the safety and effectiveness of influenza vaccines.

The effectiveness they found:

Inactivated influenza vaccines probably reduce influenza in healthy adults from 2.3% without vacination to 0.9% (risk ratio (RR) 0.41

"Risk ratio" is what is called the "efficacy" of the vaccine, normally reported as a percent; in this case it would be 41%. Most people when they read a number like that think it means they've reduced their chances of getting the flu by about 40%. Not so. Read the quote again: "2.3% of the unvaccinated got the flu, while 0.9% did get it." This means that most people didn't get the flu, whether vaxed or not. The study translates this into NNV (number to treat NNT, which is NNV for vaccines — see this for an explanation)

71 healthy adults need to be vaccinated to prevent one of them experiencing influenza,

What about other consequences?

Vaccination may lead to a small reduction in the risk of hospitalization in healthy adults, from 14.7% to 14.1%

What do they conclude?

Healthy adults who receive inactivated parenteral influenza vaccine rather than no vaccine probably experience less influenza, from just over 2% to just under 1% (moderate-certainty evidence). They also probably experience less ILI following vaccination, but the degree of benefit when expressed in absolute terms varied across different settings. Variation in protection against ILI may be due in part to inconsistent symptom classification. Certainty of evidence for the small reductions in hospitalizations and time off work is low. Protection against influenza and ILI in mothers and newborns was smaller than the effects seen in other populations considered in this review. Vaccines increase the risk of a number of adverse events, including a small increase in fever, but rates of nausea and vomiting are uncertain. The protective effect of vaccination in pregnant women and newborns is also very modest. We did not find any evidence of an association between influenza vaccination and serious adverse events in the comparative studies considered in this review. 

Makes you want to run right out and get the shot, doesn't it?

Flu shots: Huge UK study on older people

There was a massive study in the UK on the extent to which getting flu shots helps older people. This is the background they give:

Observational studies using traditional research designs suggest that influenza vaccination reduces hospitalizations and mortality among elderly persons. Accordingly, health authorities in some countries prioritize vaccination of this population. Nevertheless, questions remain about this policy's effectiveness given the potential for bias and confounding in observational data.

They studied adults aged 55 to 75 in England and Wales during 2000 to 2014. Here is what they found:

The data included 170 million episodes of care and 7.6 million deaths. Turning 65 was associated with a statistically and clinically significant increase in rate of seasonal influenza vaccination. However, no evidence indicated that vaccination reduced hospitalizations or mortality among elderly persons. The estimates were precise enough to rule out results from many previous studies.

Flu shots: are they harmless?

The data says clearly that flu shots don't do much good. But it's no big deal to get one, it might help, so why not? It turns out there are good reasons to avoid getting the flu vaccine, based on how vaccines work and supported by data. The CDC even explains some it, buried away.

Let's start with a little-discussed fact: vaccines do not in themselves prevent anything. Everyone has an immune system. Immune systems are amazing things. They fight against a huge variety of invaders to the body, defeating the vast majority of them most of the time. What vaccines do is "trick" the immune system into strengthening its defenses against a particular invader by sending things that look like the real attackers, except they've been neutered. Here's the issue: immune systems don't have endless defensive "weapons," so increasing defenses against one thing means decreasing them for others. Also the defenders aren't endlessly energetic. If they've been mobilized against an attack that doesn't occur, they don't have as much energy for the next mobilization.

This means that if you trick the immune system into shifting weapons for a threat and a different one occurs, the defense against the real attackers isn't as strong. This happens every year with flu vaccines as the variants change and particularly older peoples' immune strength fades. It also happens with covid.

Here is a summary of the most important studies.

The CDC has claimed that influenza vaccines do confer this benefit to older people. However, to support that claim, the CDC relies on observational studies that have been discredited by the scientific community.

In fact, as observed in a 2005 study in Archives of Internal Medicine (which is now JAMA Internal Medicine), despite a considerable increase in vaccination coverage among the elderly between 1980 and 2001, pneumonia and influenza mortality rates actually rose substantially. A 2008 review in Virology Journal similarly observed that “influenza mortality and hospitalization rates for older Americans significantly increased in the 80’s and 90’s, during the same time that influenza vaccination rates for elderly Americans dramatically increased.”

The effect of influenza vaccines on influenza mortality—much less their effect on all-cause mortality—was never studied in clinical trials, and later studies showed that the studies relied upon by the CDC to support its claim were fatally flawed due to a selection bias known as “healthy user bias”. In short, it wasn’t that elderly people who got a flu shot were less likely to die that flu season but that elderly people who were so frail that they were likely to soon die were less likely to get a flu shot. As a 2006 article in the International Journal of Epidemiology observed, the magnitude of this demonstrated selection bias “was sufficient to account entirely for the associations observed”.

In other words, there is no good evidence to support the claim of a mortality benefit of influenza vaccination for elderly people.

Unlike some vaccines, flu vaccines don't seem to do much active harm to those who get them. However, they do little to no good, and getting them repeatedly weakens your immune system, making you more likely to get the disease you are supposedly protected from. The fact that as more elderly people get the flu shot the more of them die of the flu is unsettling, to say the least. Doesn't sound like a boat I'd like to jump on to.

Conclusion

Why does the entire health establishment keep banging away at promoting flu shots? What is it exactly that causes the medical establishment to heavily promote treatments that not only don't help but can seriously hurt you? Things like diet, cholesterol, blood pressure and flu? If your goal is to promote trust in government and medical health advice, this is the last thing you should be doing.

The Moderna and Pfizer Covid vaccines have 90-95% efficacy, but the studies submitted for their approval showed they helped only about 1% of the people who took them. This is news to most people. How can this be?

We are constantly told that vaccines are safe and highly effective, for example by the CDC. Numbers like 90% efficacy are thrown around, which most people understand to mean that getting vaccinated means there's only a 1 chance in 10 that you'll get sick. You're really protected!

What the CDC and major authorities fail to disclose is that standard statistical methods applied to the vax vendors' own data shows that only about one in a hundred people who get the jab would be protected from getting covid! The tests did indeed show 90% or better "efficacy" (relative risk improvement), but what's more relevant is "absolute risk" (AR), which their own data showed was around 1%.

Read on to understand these industry-standard measures that are mostly ignored; if widely understood and acted on, they would transform not just vaccines, but pharma and public health in general.

Winter Coats and Vaccines

Winter coats are a standard solution to protect people from getting cold when the weather outside is cold. Kind of like when the air is suffused with invisible vaccine particles, you want to help your body defend itself.

There are a wide variety of coats available to protect against the cold. What would happen to a new coat vendor that promoted its coats as being highly effective against the cold, protecting most people who wear them, but it turned out that the maker and seller knew that 99% of the people who wear them on a cold winter day wouldn't be helped by them — word would get out quickly and the coat maker's reputation would be in the cellar.

What would happen if major authorities had subsidized the coat making, regulated their testing, and then promoted them as "safe and effective?" And then what would happen if all the authorities demanded that you buy and wear the coats, to the point refusing to let you enter a football stadium on a cold day unless you were wearing one of the approved coats? There would be mass revolt. Which is what would have happened with covid if people knew the facts that were so carefully concealed from them.

When locations like restaurants and performance halls opened, authorities in places like New York City declared that only people with proof of vaccination would be admitted. People were eager to eat out and be entertained, so this was another reason to get the jab. Vaccination cards were checked on entry so that everyone could be "safe."

While covid is the most current example of this grotesque propaganda/misinformation, it is all too common in healthcare and pharma, as I have shown for example here for saturated fat, here for cholesterol and here for hypertension. What's new in covid is the level of coercion involved.

Relative risk, absolute risk and Number Needed to Treat (NNT)

The widely used number for a vaccine called "efficacy" is technically "relative risk" (RR). In scientific papers, it's typically a number like .05, which means that compared to the number of people who got sick without the vax, just .05 of the vaxed got sick. This is translated to saying 95% of the vaxed avoided sickness compared to the unvaxed who got sick. While technically true, it is NOT about your chances of getting sick or staying well. It means relative risk, which is how much better the vax is compared to those who had no vax and got sick, independent of the number of people in the study.

Let's go back to winter coats. When people go out in the cold, they put something on to keep warm. Sometimes the coat doesn't keep some of them warm enough. Suppose the august health authorities got real worried about people dying of the cold without adequate protection. Huge amounts of time and money were spent developing what the developers thought was a great winter coat. Never mind that, for various reasons, the vast majority of people weren't getting cold. They went to a northern football stadium near the end of play-off season (winter). They got everyone entering at half the entrance gates to wear their wonderful coat and everyone who entered at the other half to wear a fake, ineffective version of the coat (the placebo) on top of whatever they were already wearing. At the end of the game, they briefly interviewed and temperature-measured everyone who left, noting which version of the coat they wore.

Let's suppose that 20,000 people went to the football game, with 10,000 getting fancy new coats and the other 10,000 getting fake coats. Suppose 10 people wearing the fancy new coat got cold, while 100 people in the fake coat group got cold.

First let's calculate the number everyone talks about, efficacy, technically known as Relative Risk (RR). RR in this case is 100 minus 10 divided by 100 = 90% efficacy. The wonderful coat did much better when added to what people were already wearing, about ten times better than the fake coat (placebo)! This is the number everyone thinks means that 90% of the people who take the vax won't get sick. Except it doesn't mean that. The key to understanding that is that RR has NOTHING to do with the size of the group, the number of people getting poked.

So let's calculate Absolute Risk (AR). In this case, of the 10,000 in the fake coat (placebo) group, 100 got cold, which is 1 in 100, for an AR of 1.0%. Your chances of avoiding getting cold without the fancy coat were excellent — 99 out of 100! For the 10,000 people in the fancy coat group, just 10 got cold, which is 1 in 1,000, an AR of 0.1%. The relative difference between the fake and real coats was truly big — ten times! But the absolute difference means that 10,000 people had to get the fancy coat in order to avoid just 90 of them getting cold. The reduction in absolute risk was 1.0% – 0.1% = 0.9%.

How many people have to get the fancy coat in order for one to benefit? Scientists have a name for this. It's NNT: Number Needed to Treat, sometimes called NNTV (Number Needed To Vaccinate) when a vax is involved. While "efficacy" focuses on "relative" risk, NNT turns the absolute risk (AR) into a more relevant number — of those getting the treatment, how many will benefit? In this case, all 10,000 football fans would have to wear the fancy coat so that about 100 wouldn't be cold, ignoring the 10 who got cold anyway. In other words, in order for one person to benefit, 100 people have to get the treatment, an NNT of 100. For the other 99, the fancy coat made no difference — they would have been warm without it.

Getting back to reality, this means that the coats most people choose to wear protect them from getting cold remarkably well. Anyone surprised? What's the normal reaction to being in the stands and getting cold? Doing something to warm up! Jump up and down. Wave your arms. Drink a cup of hot cocoa. Get hugged. Sit on someone's lap, get wrapped in their coat. If worse comes to worse, leave for someplace warm. There are "treatments" that work just fine.

Why would anyone bother accepting and wearing the authorized coat on top of what they already have? In the vast majority of cases, they'll be fine without it, and there are things they can do if they start to feel cold. Not to mention the risk of side effects of the fancy new thing. Here and here are more detailed explanations with examples.

ARR and NNT for Covid

I used round numbers above to make sure the concept was clear. But the whole point is the real world. There is a wonderful scientific website that provides NNT's for many treatments, based completely on scientific studies. For example, here is their article on cholesterol-reducing statins. which makes it clear that no one should be taking these widely used but destructive drugs.

Let's turn to the NNT for covid. What's amazing about this is that the information about NNT for covid is hidden in plain sight. Let's look at the FDA's announcement of their EUA (Emergency Use Authorization) for the Pfizer covid vaccination. The FDA states:

The FDA has determined that Pfizer-BioNTech COVID-19 Vaccine has met the statutory criteria for issuance of an EUA. The totality of the available data provides clear evidence that Pfizer-BioNTech COVID-19 Vaccine may be effective in preventing COVID-19. The data also support that the known and potential benefits outweigh the known and potential risks, supporting the vaccine’s use in millions of people 16 years of age and older, including healthy individuals.

Later in the same announcement, the FDA gives the details about how good the vaccine is. Here is the start of the key paragraph:

FDA Evaluation of Available Effectiveness Data 

The effectiveness data to support the EUA include an analysis of 36,523 participants in the ongoing randomized, placebo-controlled international study, the majority of whom are U.S. participants, who did not have evidence of SARS-CoV-2 infection through seven days after the second dose. Among these participants, 18,198 received the vaccine and 18,325 received placebo. The vaccine was 95% effective in preventing COVID-19 disease among these clinical trial participants …

This gives the key point of (relative) effectiveness: it's 95% effective! Hooray, we've got it! See what happens when you keep reading:

… with eight COVID-19 cases in the vaccine group and 162 in the placebo group. Of these 170 COVID-19 cases, one in the vaccine group and three in the placebo group were classified as severe. At this time, data are not available to make a determination about how long the vaccine will provide protection, nor is there evidence that the vaccine prevents transmission of SARS-CoV-2 from person to person. 

First, let's look at the chance of getting covid without getting vaccinated; it's 162/18,325 = 1 in 113. Fewer than 1% of the placebo group got covid! And of those 162 cases, just 3 were classified as severe, so just 1 in over 6100 unvaxed people got severe covid. The numbers to achieve the benefit of vaccination aren't much different. The NNT is over 1 in 110 — over 110 people had to take the vaccine for one person to avoid getting covid! Yes, the relative benefit is huge, but in absolute terms, less than 1% of people are actually helped by getting jabbed.

Note also that there was zero evidence that the vaccine prevents an infected person spreading the infection.

Is this the case only for Pfizer? A group of French scientists calculated ARR and NTT for the leading Covid drugs, based solely on the published studies of the trials of those drugs. Here is a summary and here is the study published in a scientific journal. It deserves much more attention than it seems to have gotten because of its focus on NNT.

Let's jump right to the key table.

The first drug, Pfizer, has a terrific efficacy (RR), listed there as 0.05, but normally reported as 95%. Everyone (including me, when I first saw it), thinks that means that taking the Pfizer vax means there's only a 5% chance of getting covid, right? It works great! Now look at the NNT, 141. That means that for each 141 people who are vaxed, just one benefits by not getting covid!! It makes common sense: there were 21,728 people in the control group (people who got shots that were placebos), and only 162 of them got covid,

You might think that relative and absolute risk are related, but the third drug, AstraZeneca, makes clear that they're not. AstraZeneca had efficacy (RR) of 0.30, normally reported as 70%, which is dramatically worse than Pfizer's — why would anyone choose it? But AstraZeneca has an NNT of 83, which means that your chances of the AstraZeneca vax helping prevent covid were much better than the Pfizer vax. But even with the better NNT, chances are extremely high that you wouldn't get covid, with or without the vax.

The issues I describe here are not radical or new. The paper above was notable only in that it covered all the major covid vaccines; other doctors and scientists have publicly pointed out the same facts. For example, here is a note by a doctor published in the BMJ shortly after the trial results were first published.

Conclusion

After learning about efficacy, absolute risk and NNT, your understanding of what it means for a treatment to be "effective" changes radically. Absolute risk and NNT are at least as important. Authorities should discuss all these number prominently.