This is a third talk in a series that began with Relationship Based Medicine , continued with Beware of Doctors Bearing Gifts and concludes with this talk, which could called History of a Medical Psychosis, Medical Neoliberalism, Evident versus Evidence Based Medicine, A Lutheran Moment, or Does Objectivity Come from using Chance to Control Bias or Bias to Control Chance?

It is the most important talk I have ever given.

The first lecture was delivered to clinicians in New York with a Q and A afterwards.

The second was delivered to the public in Lethbridge Alberta, thanks to Jennifer Williams and Dan Johnson but owing to tech difficulties at the venue (See In Memory of Dexter Johnson), it was difficult to record the Q and A with the public. Suffice to say though between the technical difficuties, the lecture and the Q and A, we were all there for the better part of 3 hours and the discussion was great.

This third lecture was delivered to Aaron Kesselheim’s PORTAL group – Program on Regulation, Therapeutics and Law. There are two versions. The History of a Medical Psychosis was recorded by Bill James the day before in case of glitches – same day as Putin and Biden gave speeches. The second was recorded by Aaron – Faulty Evidence and Moral Hazard.

There are slight differences between them. The text and slides below add some detail to both talks but the tone of voice and gestures in the talks likely convey things not in the text.

Slide 1: Faulty Evidence and Moral Hazard

Welcome to a very conservative talk – based on a belief in the medical model and in evaluating the drugs we use thoroughly.

Slide 2: These quotes are a precis of key points in the deposition of Ian Hudson, Chief Safety Officer of GlaxoSmithKline (GSK) in 2000 in the Tobin v SmithKline trial.

Forty-Eight hours after starting Paxil Don Schell shot his wife, daughter and granddaughter and then himself. Hudson is being asked – Can SSRIs cause Suicide?

The jury dismissed Hudson’s Evidence Based Medicine view in favor of Evident Based Medicine and in this Civil trial found GSK guilty of negligence that resulted in the death of this family.

Hudson’s view, however, remains ensconced at the top of Britain’s drugs regulator, of which he was later the CEO – as well as FDA, EMA, TGA, Health Canada, WHO, and Boston institutions like Harvard, MRCT, and Vivli. Joe Biden and the Pope’s advisers will also endorse and tell their bosses to say – Yes RCTs are the Way the Truth and the Light.

Slide 3: Hudson’s views originate 70 years earlier in the work of a strange man – Ronnie Fisher.

Here you see Fisher smoking a pipe. He dismissed the later link between smoking and lung cancer, saying personality types predisposed to both cancer and smoking. Evidence was not Fisher’s strong point.

He had nothing to do with medicine and never ran an RCT. Controlled trials and randomization were there before Fisher and were no big deal but for no clear reason his book the Design of Experiments transformed what came next.

Fisher ran a thought experiment to characterize expert knowledge. He mentioned randomization as a means to control for any trivial unknown unknowns. Randomization later became semi-mystical.

Fisher’s expert knew parachutes worked so if we set up two groups, one with parachutes and the other not, we might randomize in case there was someone with webbed feet who might behave differently when falling. Otherwise, we would expect those wearing parachutes to live and those not to die – unless a chance strong wind lands a person in snow covered trees.

If randomization eliminated webbing as a factor, the only thing that could get in the way of an expert being right was chance and this could be assigned a statistically significant value. If 1 in 20 of those without parachutes lived we wouldn’t say the expert didn’t know what he was talking about. Fisher was characterizing expertise rather than characterizing an exploration of the unknown.

Randomization can’t control for ignorance.

Slide 4: Fisher’s expert is a Robin Hood who 19 times out of 20 can split a prior arrow lodged in the Bull.

Slide 5: But the trials done to license drugs especially antidepressants look more like this. A mismatch on this scale indicates medical RCTs are nothing like what Fisher had in mind.

Slide 6: The first RCT in medicine was a trial of streptomycin for tuberculosis. Tony Hill used randomization as a method of fair allocation – he was not managing mystical confounders. Hill helped put the effects of smoking on the map. He had no time for Fisher. He also knew doctors were not experts. His trial was not a demonstration of expertise.

Hill’s RCT found out less about streptomycin than a prior non-randomized trial in the Mayo Clinic, which showed it can cause deafness and tolerance develops rapidly.

Slide 7: Twenty years later, here is Tony Hill taking stock of controlled trials. In this 1965 lecture, he mentions that it is interesting that the people who are most heavily now promoting controlled trials are pharmaceutical companies.

Hill didn’t think trials had to be randomized. He thought double-blinds could get in the way of doctors evaluating a drug. He was a believer in Evident Based rather than Evidence Based Medicine.

Hill said we needed RCTs around 1950 to work out if anything worked. By 1960 he figured we had lots of things that worked – none of which had been brought on the market through an RCT – and he thought the need was to find out which drug worked best. This is not something RCTs can do – there is no such thing as a best drug. RCTs have instead become a way for companies to get weaker drugs on the market.

He said that RCTs produce average effects which are not much good in telling a doctor what to do for the patient in front of them.

All drugs do 3000 + things – one of which might be useful for treatment purposes. In focusing on one element, by default, Hill is saying RCTs are not a good way to evaluate a drug. All RCTs generate ignorance. But we can bring good out of this harm if we remain on top of what we are doing. Hill never saw RCTs replacing clinical judgement.

Slide 8: This 1960 RCT run by Louis Lasagna makes Hill’s point well. Thalidomide has therapeutic efficacy as a sleeping pill but the trial missed the SSRI-like sexual dysfunction, suicidality, agitation, nausea and peripheral neuropathy it causes.

Two years later, Lasagna was responsible for incorporating RCTs in the 1962 Food and Drugs Act Amendments – in order to minimise the chance of another thalidomide. By doing this, more than anyone else, Lasagna was the man who got us using RCTs

This trial would have licensed thalidomide today. The 1938 Act had no requirement for RCTs.

Slide 9: Many claim RCTs demonstrate cause and effect in a way no other study design can.

The 1950s was a golden age of new drugs that gave us the best antihypertensives, hypoglycemics, antibiotics and psychotropic drugs we have ever had without RCT input into any discoveries.

Imipramine was the first antidepressant. It and other antidepressants beat SSRIs in later RCTs. It can treat melancholia – SSRIs can’t. Melancholia comes with a high risk of suicide.

Imipramine was launched in 1958. At a meeting in 1959, European experts made clear that while it was a wonderful treatment imipramine made some people suicidal. Stop the drug and it clears. Re-introduce and it comes back. This was Evident Based Medicine showing this drug can cause suicide.

Like Fisher, let’s do a thought RCT of imipramine versus placebo in melancholia. The red dots here are suicides or suicide attempts.

Even though it can cause suicide, we would expect it to reduce the number of suicides because it treats this high risk condition. If you didn’t know better, this RCT would look like evidence antidepressants do not cause suicide.

Slide 10: Here is the data on the trials in mild depression that brought the SSRIs to market – mild depression because SSRIs are no use in melancholia. You see an increase of suicidal events compared to placebo in people at little or no risk of suicide.

Slide 11: This is what the data for imipramine look like in the same mild depressions. This is not a thought experiment – it was used as a comparator in SSRI trials. Now it too causes suicides.

RCTs can give us diametrically opposite answers. This is because these are not Drug Trials. They are Treatment Trials and if the condition and treatment produce superficially similar effects, randomized trials cause confounding rather than solve it. This is true for most medical conditions and their treatments.

People evaluating drugs in traditional clinical trials, before RCTs, knew this. When a patient becomes suicidal in a trial you have to use your judgement to work out what is happening but in RCTs clinicians are not supposed to use their judgment. RCTs are more objective than our judgments – supposedly.

Slide 12: Here is what a Drug Trial looks like. In healthy volunteer studies in the 1980s, companies found SSRIs cause volunteers to become suicidal, dependent and sexually dysfunctional. We heard nothing about these problems when the drugs launched in part because Drug Trials enabled companies to engineer Treatment Trials to hide these problems.

Slide 13: If you break a limb and get recruited to an RCT randomly applying casts to one limb – not necessarily the broken one – the trial will show random application beats placebo. Practicing Evidence Based Medicine rather than Evident based Medicine here would clearly be crazy.

Slide 14: Here is a James Webb telescope image. James Webb is marvellously bringing out the infinite individuality of stars.

In addition to randomization, Fisher put a premium on Statistical Significance. By 1980 every leading medical statistician was saying we need to get rid of statistical significance in favor of Confidence Intervals.

Confidence Intervals had been introduced by Gauss around 1810. Because of measurement error, the telescopes in use often failed to establish whether there was one or two stars in a location. Measurement errors should distribute nornally and so constructing confidence intervals could help us distinguish individual stars.

We have moved a long way forward in this respect with the James Webb telescope you see here.

Slide 15: Confidence intervals rushed into medicine in the mid-1980s. All the authorities on the right – many linked to Boston – argued they were much more appropriate than significance testing. They are appropriate for measurement error but are they any more a cure for ignorance than statistical significance?

Slide 16: Confidence intervals we are told allow us to estimate the size of an effect and the precision with which it is known. We have much more precise details on the likelihood of the Red Drug here killing you than we have for the Yellow Drug. The best estimate of the lethal effect for the Yellow Drug however is greater. The standard view is that if we increase the size of the Yellow Drug Trial we will have greater precision and know better what the risks are. As we shall see, this is wrong.

As things stand, if you are asked to take one of these drugs, should you be guided by precision or effect size? Ian Hudson, FDA and WHO say the only dangerous drug here is the Red One. This is because more than 95% of the data, more than 19 out of 20 lie to the right of the line through 1.0 – confidence intervals have defaulted into statistical significance.

I would take the Red rather than the Yellow one. This is not measurement error and we don’t know what confidence intervals represent when they are not representing measurement error.

Slide 17: Faced with claims Prozac causes suicide, Lilly analysed their clinical trials and claimed there is no evidence their drug causes suicide. Confidence Intervals are being spun here as indicating we don’t know Prozac causes suicide as nothing is statistical significant. This is Ian Hudson thinking – at odds with all statistical expertise. It’s wrong. The consistency across young and old, depression and eating disorders strongly suggests in real life there is an excess of suicidal events.

Slide 18: There is an intriguing mystery behind these figures. Here you see a representation of suicidal events that happened in the trials that brought Prozac, Paxil and Zoloft to market around 1990. You’ll note there are events under the word screening here. There is a 2 week washout period before a trial starts where people are whipped off their prior drugs before being put on the new treatment or placebo. This is a highly dangerous phase where people are in withdrawal and very likely to go on to a suicide attempt.

Slide 19: And here you see the moves companies made to avoid having a confidence interval excess of suicidal events on treatment. Companies only moved the events – not the people.

These moves were justified on the basis that people in the run in phase were not on active treatment – which is equivalent to being on placebo – but they often were withdrawing from active treatment which is highly dangerous. Some who stopped treatment at the end of the active phase of the trial committed suicide and were designated placebo too. Some on placebo, put on active treatment in the follow up period, committed suicide and were designated as placebo suicides on an intention to treat basis.

There are two articles from 2006 that bring out this point Did Regulators Fail and The Antidepressant Tale: Figures Signifying Nothing. The Antidepressant Tale gives other examples of confidence interval abuse.

After all these maneuvers, there was still an excess of suicidal events on these SSRIs but the confidence interval was no longer entirely to the right of 1.0. Confidence intervals have degenerated into statistical significance tests because regulators need a Stop-Go mechanism and statistical significance provides this. But doctors don’t need an external Stop-Go mechanism to replace their clinical judgement, so why do they go along with this?

Slide 20: Nobody noticed these maneuvers around 1990, but fourteen years in a crisis about children becoming suicidal on antidepressants, questions began to be asked. GSK and Pfizer responded:.

‘GSK did not intentionally submit any erroneous or misleading information to FDA. The suicide data submitted to FDA explicitly identified when events occurred during the placebo run-in period. FDA had all this information right from the beginning.’

“Pfizer’s 1990 report to FDA plainly shows … that 3 placebo attempts as having occurred during single blind placebo phases… FDA has neither criticized these data or the report as inappropriate, nor required additional analyses”.

These maneuvers breach FDA regulations and FDA staff noted this in memo’s at the time. But not only did FDA ignore these breaches of regulations senior figures, like Tom Laughren, put their name to articles that embraced these breaches of regulation – in one case in the cause of showing it was not unethical to have placebo controls in RCTs, as those on placebo were not at any greater risk than those on treatment.

There was much back and forth between FDA and companies in 1990. Was it criminal? Perhaps. I prefer the idea of strategic ignorance.

What I think we are seeing are events circling around a major crisis in knowledge production. This is not something you can expect FDA to take a lead on – they are not political actors, they are bureaucrats. Companies create knowledge or were creating the appearances of knowledge at this point, but doctors are surely primarily responsible for the creation of medical knowledge and doctors were missing in action around 1991– other than as spokespeople for companies.

Slide 21: The Sacred Mantra is that randomization controls for all possible confounders in all possible universes. The reality is randomization introduces confounders into clinical trials.

The images for the next 3 slides come from a GSK paper prepared in 2006 for submission to FDA. The small print is hard to read – the bold at the bottom gives you the key details.

The data for suicidal events on Paxil in Major Depressive Disorder trials in this first slide show it causes suicidal events. Even Ian Hudson would have to agree and these data were available at the time of the Tobin trials. But randomization is about to come to GSK’s rescue.

Slide 22: Faced with a problem like this, had GSK consulted me I’d have said do a trial in Intermittent Brief Depressive Disorders (IBDD). They might have said but there are trials of SSRIs in IBDD and they don’t work. I’d have said do one. They did and it had to be terminated early, Paxil did so poorly. I’d have said do another. Why – the figures for Paxil still look bad in this group?

Slide 23: But when you add the IBDD data to the MDD data, all of a sudden the figures say Paxil protects against suicidal events.

This scenario can happen every time a condition we are treating is heterogenous – that is dementia, diabetes, parkinson’s disease, breast cancer, back pain, hypertension – pretty well everything in medicine. In these cases randomization will act to hide effects good and bad and leave us able to use a problem a drug causes to hide a problem a drug causes.

Slide 24: Graphically this is what it looks like. The Red Drug here is the MDD curve alone – more than 95% of the data are to the right of the 1.0 line. The traditional wisdom is that adding some more events to the Red Drug above should give us a more precise version of the same estimate

In fact when you add a few more people, about 3%, we have shifted the curve to the opposite side of the 1.0 line. Its far a more precise confidence interval but this is a precision that speaks to our ignorance rather than to better knowledge. No medical statistics book ever hints at this possibility.

We could add 40 suicidal events to the paroxetine IBDD arm before Ian Hudson would have to admit paroxetine causes a problem – on the basis that the results are now statistically significant.

IBDD patients could be admitted to MDD trials – we have no way to distinguish them. Some patients become IBDD by virtue of a poor response to an SSRI.

Randomization in heterogenous conditions will hide effects drugs cause. It allows us to use an adverse effect a drug causes to hide the same adverse effect that drug causes. Confidence intervals do not help us work out what is going on in these cases.

Nor do they help in heterogenous drug responses. Lets take 20 Aarons who are all sedated by a Red Drug and 20 Davids all stimulated by it. The best estimate in the confidence interval in this case will lie on the 1.0 line, showing the drug has no effect. A method to distinguish between one and two stars should not produce an answer that there are no stars here. Algorithmic judgements cannot substitute for a human judgement.

Slide 25: Here is another problem with Confidence Intervals. Young men take Finasteride to restore a thick head of hair. We could count hairs and build confidence intervals around before and after hair follicle numbers.

Finasteride also causes suicide and permanent sexual dysfunction and like most drugs has 3,500 other effects. Confidence intervals for hair numbers before and after is one thing, but applying them to suicidality or sexual function, which were not measured in the trial, and for Merck to then claim on this basis that the science does not support a link between finasteride and suicide on the basis that not all the data lie to the right of the 1.0 line isn’t managing measurement error. It’s a confidence trick – that happens all the time.

Slide 26: There are more dead bodies on antidepressants in trials than on placebo, yet the RCTs as Ian Hudson told you show the drugs work. This is because most RCTs have a surrogate outcome. For antidepressants its the Hamilton Rating Scale for Depression.

Fifteen years after its creation, Max Hamilton commented on his scale:

It may be that we are witnessing a change as revolutionary as was the introduction of standardization and mass production in manufacture. Both have their positive and negative sides

Hamilton saw this scale as a checklist of things to ask about in an interview – a mixed blessing.

Slide 27: Checklists are now viewed as more scientific than David Healy in a clinic asking you about your family. They will produce standardized but possibly disastrous interviews.

For instance, on this scale, there is a suicide item. Suicidality can stem from the illness or the drug. This needs a judgement call. If caused by the drug you should rate a Zero. If caused by the illness you might rate 3 or 4. If you just check yes for suicidality, the default is to the illness. Ditto for sex, and for sleep.

In the case of sleep, the illness can produce too much sleep or not enough sleep and each of the medicines can inhibit sleep or heavily sedate. There are 3 sleep questions. A scientific interview has a multitude of options requiring judgement calls.

In the 1980s, we brought problems to doctors needing help to get on with the lives we wanted to live. Since then, for drug companies, rating scales, sometimes left in the waiting room, ensure you do an interview that produces figures for which a company drug might seem an answer. Your interview will help you to help your patient to live the life Pfizer want him to live. Do that and you are no longer practicing medicine.

Slide 28: Many think RCTs are fine if only they were done by angels.

Study 329 was conducted in the very best university centres in North America. It has an authorship line to die for, starting with Marty Keller and including a Canadian Liberal Party Senator – Stan Kutcher. It was published in the Journal with the highest impact factor in child psychiatry. The article claims Paxil works wonderfully well and is safe for depressed teens.

What I am about to tell you applies to all industry trials across medicine.

Slide 29: Three years earlier, in 1998, GSK concluded Paxil didn’t work in Study 329 and was not safe. That could not be published so they were going to pick out the good bits of the data and publish them. The good bits formed the Keller et al 2001 paper.

This 1998 internal SKB document led New York’s Attorney General to file a fraud action against GSK. As part of the resolution of this, GSK agreed to make their Paxil trial data public. A decade later, GSK resolved a Dept of Justice action, which also involved Study 329, for $3 Billion dollars.

Slide 30: These actions gave a team of us an incentive to Restore Study 329 and we now had more raw data from this study than FDA or other regulators had seen for this or any company study.

Slide 31: In contrast to Keller, we found the 8-week acute phase showed no difference between Paxil or placebo. We found the same for the never published 6 month continuation phase – never published till we published it 18 years after the trial ended.

Slide 32: Keller noted 6 emotionally labile events in the trial, some of which might have been suicidality, 4 on paroxetine. But in our hands a fifth of the children on Paxil had a behavioral event mostly suicidality – 18 out of 93 children.

Suicide is not what I want to focus on. It’s the ability of company studies to hide adverse events. Our paper lists 10 ways to hide things. Coding – as in calling suicidality emotional lability, is top of this list – this is the first act of authorship but no reviewer or journal pays any heed to it.

Slide 33: In a Pfizer trial, at the same time, a man on active drug got agitated, poured gasoline/petrol on himself and set fire to it intending to kill himself but he only died from his burns 5 days later. Pfizer coded him as death by burns. Once the coding is done, the paper is all but written.

There is some chance FDA found out about this man because if you have to go to hospital or you die companies had to file a report outlining what happened and did so for this man.

Slide 34: But in Study 329, FDA know nothing about a 15 year old boy, 2 weeks after being put on Paxil, who was out on the street waving a gun, threatening to kill people. He was brought to hospital by the police. There was no report to tell FDA what happened. Thirty years ago companies found a way to legally avoid filing these reports. Companies are still using this trick in trials published this year in all major journals and regulators either don’t spot or are not bothered to close a very obvious loophole. In Study 329, 4 children vanished through this loophole.

Slide 35: The sentences on the right are the 3 sentences with which this article ends – the message is companies have created an impression that RCT articles are like tablets of stone brought down from the mountain top, commanding doctors to prescribe and us to take. But when we have access to RCT data, this raises questions – as science should – rather than issues commands.

In addition to Coding, Grouping is also an act of authorship. If you have 500 events in 93 children on Paxil, rather than list them all, cardiac events are usually grouped in a Cardiac group etc. Behavioral events are usually grouped in a Psychiatric group. GSK grouped all behavioral events under Neurological. This groups emotional lability with headaches and dizziness, which are very common. Grouped this way the behavior problems disappear. Grouped as Psychiatric, the problem is immediately clear.

The Restoring Study 329 article took over a year to get it published. What was fascinating was the BMJ did not contest the data but they were very exercised by the act of interpretation. They appeared to assume that the data had spoken and GSK faithfully transmitted what they had heard. They found it heard to grasp that GSK used a coding dictionary that even FDA had never heard of.

Any scientific analysis inevitably involves an act of authorship or interpretation. But BMJ found it hard to let us author the behavioral events out of the neurological group into a Psychiatry group. There is no such thing as data without an interpretation. Ideally the interpretation should command consensus but for BMJ this appeared to mean that we should adopt what GSK had done without question.

Slide 36: Everyone knows Prozac was approved for children who are depressed but not that Paxil was too. A year after the Keller paper came out, this is part of an FDA approvable letter for Paxil.

It says GSK have told FDA Study 329 is negative. FDA agree its negative – in fact all 3 trials are negative – but FDA will still approve Paxil for kids. FDA also agree with GSK’s suggestion not to mention the negative trials in the label of the drug. Why would FDA agree to this?

Before answering that, let me note FDA also viewed the Prozac trials in teens as negative.

Slide 37: This slide from Erick Turner’s 2008 article shows published adult ‘trials’ on various antidepressants, almost all indicating the drugs work well and are safe. Look at the sertraline column – 3 from the right. It shows two studies – the minimum needed for approval.

Slide 38: Another slide shows the trials as FDA viewed them. 46% of these trials are negative. Many published as positive were negative to add to the unpublished negative trials. Look at the sertraline column – only one positive study.

Why do FDA say nothing about this? Well if FDA said trials are negative – the companies might get sued for fraud or fined – as happened for Study 329.

Slide 39: Here you see the PTSD page of a 30 page document listing Zoloft articles in progress. These papers aim at capturing markets not at informing us on how to use Zoloft safely.

Pfizer did 4 Zoloft PTSD trials. All negative. FDA approved it on the basis of 2 trials with a minimal benefit for women. These good bits plucked out are what’s being published. You see under Status on the right two articles are complete and will be sent to the very best journals. On the left you see TBD – to be determined – when Pfizer decide which names would sell most Zoloft.

You saw a 24 person authorship line for Study 329 but the real author is not there. Across medicine studies of on-patent drugs are ghostwritten.

In the case of children’s antidepressant trials the entire literature was written by ghosts and there is a complete mismatch between the published claims and the data – the greatest mismatch in all of science. On the basis of published claims the use of these drugs is escalating rapidly in teenagers with predictably bad results.

Slide 40: Fifty years ago, Britain joined the EU and ran into trouble. Cadbury’s chocolate, their favorite chocolate, they were told, could not be called chocolate. It didn’t have the right quota of cocoa solids. British consternation over chocolate led to Brexit some decades later.

What FDA do is in their name – they regulate Food and Drugs. Faced with butter or chocolate or drugs, companies must meet an assay standard – so much cocoa solids, animal fats, or so many points on a Depression rating scale in 2 trials. Meet that and FDA let you use the words chocolate, butter, or antidepressant. It’s not FDA’s job to decide if this is good butter, or if chocolate is good for you, or to police the medical literature.

Sllide 41: Since 1990, however, regulators increasingly say they approve drugs on the back of a supposed positive Benefit-Risk ratio. This is Ian Hudson thinking. If there are no proven adverse effects and just a benefit then of course there is a positive Benefit-Risk ratio.

The medical act of bringing good out of the use of a poison is incompatible with all this.

We would all agree there is a positive benefit-risk ratio for parachute approval in terms of lives saved versus lives lost – even though some men might have difficulties making love in the weeks afterwards, owing to harness effects. If things aren’t clear enough for us all to endorse, regulators are de facto getting us to live the lives companies want us to live when they make Benefit-Risk claims.

Unlike parachutes, SSRI RCTs have more dead bodies on SSRIs than placebo. In addition. the commonest effect of an SSRI is to cause genital numbness in close to everyone who takes one within 30 minutes of a first tablet. Almost everyone will have the way they make love changed while on an SSRI and they may later find themselves unable to make love ever again, either because they can’t stop or because the drugs can wipe out sexual function for ever. This may be far more important to a person than any mood benefit.

But the focus on the mood effect, means the sexual effect was missed entirely in the trials regulators scrutinized both because that’s how trials work but also with a little extra gaming from companies.

Some years ago treating a man with OCD, I tried an SSRI – the first line treatment and then more heavy duty drugs when the SSRI didn’t work. All made him worse. One day he came in much better – he had stopped all his drugs but he was cured by going back smoking. He had also googled nicotine and OCD and found studies showing nicotine and related drugs can help OCD.

When I say the Art of Medicine lies in Bringing Good out of the Use of a Poison, people hiss at me but everyone would likely agree this man was bringing good out of the use of a poison. SSRIs however are prescription-only because we expect them to be more dangerous than over the counter alcohol and nicotine.

The important thing is that this man (perhaps with input from me) is the only person in a position to make a meaningful Benefit Risk call. I can’t see what role FDA could have in this. Benefit-Risk calls are an individual matter. Making the claims FDA now make puts them in a role of getting people to live the life Pfizer want them to live.

Am I making all claims on the basis of Citizen Research more than Expert input? No – among the articles this man found about nicotine and OCD was one whose significance passed him by. One of the authors was Arvid Carlsson, who created SSRIs and won a Nobel Prize for Medicine.

But when you have Skin in the Game, Motivation can be worth just as much as Expertise.

Slide 42: As a result of Ian Hudson’s views, as I wrote 25 years ago, everyone who participates in a company trial today puts all the rest of us in a state of Legal Jeopardy. We should boycott trials, until this changes. See Clinical Trials and Legal Jeopardy.

Slide 43: That article was 25 years ago, this is 25 days ago and argues everyone entering a trial now are deceived by consent forms that promise coverage for injuries, unaware that there are no injuries on modern treatment, or no injuries that can be admitted. See The Coverage of Medical Injuries in Compary Trial Informed Consent Forms.

Slide 44: However, since 2010, the US Supreme Court in the Matrixx case made it clear that Ian Hudson’s views do not apply to investors wanting to make up their mind about the Benefits and Risks of investing. We who are investing our lives in these treatments still do not have such rights.

Slide 45: The beating Tell Tale Heart of this talk came with the publication of this article 33 years ago this month, in which 3 Boston clinicians claimed fluoxetine caused 6 people to become suicidal. Analyzing the cases closely and following traditional clinical approaches for determining causality, this article nailed beyond doubt that fluoxetine could cause some people to become suicidal.

Lots of other groups reported similar findings. I published 2 cases of men, who were challenged, dechallenged and rechallenged with an SSRI. There was no other way to explain what happened them except that fluoxetine had caused it. This was Evident Based Medicine .

Slide 46: Almost the same week as my article came out, BMJ published an article in which Lilly claimed an analysis of their clinical trials showed no evidence fluoxetine made people suicidal. The cases being reported, therefore, were sad but anecdotal – and the plural of anecdote is not data. Depression was the problem not fluoxetine. Clinical trials are the science of cause and effect. Doctors, the public, media, and politicians were being asked – are you going to believe the science or the anecdotes?

This was a knowledge creation moment that likely had input from all companies and perhaps FDA. This article created Evidence Based Medicine and just as with RCTs 30 years earlier, the people most commonly exhorting doctors to practice EBM today are Pharma companies.

In fact, the original phrase is the plural of anecdotes is data – otherwise Google wouldn’t work.

The idea the disease is responsible for suicide attempts and suicides in healthy volunteers is hard to believe but companies can wheel out experts to say just that.

My key point is that the Teicher paper is the science – the Lilly data is an artefact. My challenge to you is which are you going to believe the Science or the Artefact?

The Science of Medicine lies in making hard judgement calls. The made by algorithm approach, combined with inappropriate statistics, creates artefacts not science.

You’ve seen earlier how Lilly cooked the books. When you get the trial data, the Evident Based Medicine and Evidence Based Medicine approaches here can be reconciled – as you might expect with real science.

But even there was an incompatability there isn’t a problem. Resolving discrepancies is how we do science.

This points to a deep problems with Lilly’s argument. They are not in the business of being scientific – resolving discrepant observations. Lilly’s argument is a religious one – a dogmatic one – they forbid us to believe the evidence of our own senses.

This is papal infallibility riding again.

Peter Drucker, the doyen of marketing gave us a secular update – the goal of marketing is not to increase the sales of Prozac, its to own the market. This was the moment Pharma took ownership of the market.

This ownership allows companies to dictate what the risks, the benefits and the trade-offs of drugs are. Allows them to force us to live the lives they want us to live rather than engage with the risky and unprofitable business of producing products that will help us to live the lives we want to live. Following this Artefact is profoundly alienating.

Slide 47: This faces us with a what is science question? The usual histories start with the foundation of The Royal Society in 1660, which established the ground rules for Science. Science would deal with matters that could be Settled by Data. Participants could be Xtian, Hindu, Jew, Muslim, or Atheist, but participants were called on to leave these badges at the door and make a consensus based judgement call about the best way to explain the experimental outcome in front of them.

The histories of science emphasize the word Data. Settled is the more important word. Statistics played no part in this science. The experiments were events and didn’t need the descriptions statistics can provide. Science was emphatically not about replacing judgment calls with a statistical artefact. It only became so 33 years ago.

Slide 48: This account of our history overlooks an earlier event. In 1618, Walter Raleigh was executed – for being too close to those pesky Europeans. Raleigh was convicted on the basis of things said about him by people who did not come into court to be cross-examined.

Legal systems worldwide recognized the injustice of this and introduced Rules of Evidence. Hearsay could not be used as evidence. Jurors – a group of 12 people, Xtians, Hindus, Muslims, Atheists and Jews, can only base a verdict on material put in front of them that can be examined and cross-examined. The process of forcing 12 people with very different biases to come to a Verdict about what is in front of them is the essence of science.

Verdicts and diagnoses are provisional – the view that best fits the current facts. This might appear to contrast with the objectivity of science, but scientific views are similarly provisional. Scientists attempt to overturn verdicts with new data.

Let’s say I gave Aaron fluoxetine 33 years ago and he became suicidal. I could examine and cross-examine him, run labs and scans, raise the dose, stop the drug, add an antidote, check with colleagues has anyone else seen anything like this or can they explain it in any other way. Aaron is the data – all of the data. He is the apparatus in which the experiment is taking place.

If Aaron and I conclude fluoxetine made him suicidal and report this to FDA, the first thing FDA does is to remove his name. No-one can now examine or cross-examine him and come to a scientific view about whether there is a link or not. His injury has been made Hearsay – indeed misinformation.

If you are later injured in the same way and see tens of thousands of reports of suicidality on SSRIs on FDA’s adverse event reporting system, you cannot bring this into court because no-one can be brought into court. It’s Hearsay not Evidence.

Company RCTs are equally hearsay and should not be let into Court as evidence. Accessing the data in this case means accessing people – like Aaron or me – and we cannot do that with the people in company trials, who often don’t exist. Except rarely, the authors on the articles have seen none of these people and cannot speak to what happened either.

In contrast, if Aaron and I report his case in he New England Journal or the American Journal of Psychiatry as a Case Report, with our names on it, we can both be brought into Court.

Slide 49: By 1983 the view was emerging that RCTs offered the scientific and sophisticated way to establish if a drug had adverse effects as this quote by Rossi et al indicates:

Spontaneous reporting is “the least sophisticated and scientifically rigorous . . . method of detecting new adverse drug reactions.

A mid-career Lasagna, the man who more than anyone introduced RCTs, responded:

This may be true in the dictionary sense of sophisticated meaning ‘adulterated’ . . . but I submit spontaneous reporting is more ‘worldly-wise, knowing, subtle and intellectually appealing’ than grandiose, expensive RCTs.

Slide 50: Here you have an older Louis Lasagna saying:

In contrast to my role in the 1950s which was trying to convince people to do controlled trials, now I find myself telling people that it’s not the only way to truth.

Evidence Based Medicine has become synonymous with RCTs even though such trials invariably fail to tell the physician what he or she wants to know which is, which drug is best for Mr Jones or Ms Smith – not what happens to a non-existent average person.

Slide 51: Here is James Webb again to remind you that confidence intervals were a step on the way to revealing the individuality of stars. In medicine, statistical approaches operate against individuality.

Using Chance to control Bias does not foster clinical science, especially when we allow a mindless algorithm to replace clinical judgement. Clinical medicine, like law, and the first 300 years of science uses Bias to Control Chance and both medicine and law need to assert the validity of this approach.

Slide 52: Using Bias to control Chance rather than some algorithmic method of controlling Chance is critical when numbers enter the frame. This is our only defense against medical neo-liberalism.

Around 1980 Pharma began treating healthy people. They discovered that numbers for our peak flow rates, bone densities, blood pressure, lipids, or sugar provided opportunities to sell drugs. Up to 1980, we brought our problems to healthcare – seeking help to live the lives we wanted to live. After that health services began to give us problems and the amount of medicines consumed rose dramatically. We began treating numbers rather than people.

Remaining on top of data like this is difficult. Just after weighing scales for people were introduced in the 1860s, we got the first descriptions of anorexia nervosa. In the 1920s, weighing scales in drug stores came with norms for our ideal weight given our height and sex and eating disorders mushroomed. When scales migrated into our homes in the 1960s eating disorders became epidemic – in the countries that had weighing scales. Measurements can make both us and our doctors neurotic.

Slide 53: There is an extra element to the equation. The service industries emerged in the 1950s. Through to 1980, no-one viewed health as a service industry – doctors were professionals who exercised judgement the way a Judge might. But service industries have managers and health got managers. With this the exercise of clinical discretion, the jewel in the crown of Health Care became a problem for those who manage services.

The idea of bringing good out of the use of a poison does not compute for managers, insurers, politicians or increasingly the public.

Before 1980, clinicians mobilized the resources of the organization they worked to handle the risks your condition posed to you. Now instead you can palpably feel the clinicians you meet are managing the risks you pose to the organization we work for.

Slide 54: Managers manage what they can measure. For them figures have a sheen of scientific gold. We are re-running the King Midas story – this gold coating is incompatible with Human Care and Life.

This governance by numbers is the essence of the neoliberalism that began in Chile and Britain – treat the money supply numbers or inflation numbers regardless of what is happening a country. Medicine is the best place to see this and its deleterious effects in action – aggravated by the fact that bowing down before a golden algorithmic idol inhibits anyone from leading us out of this desert in which we now wander.

Slide 55: When the pilot here reports problems, safety systems pay heed because they know she won’t fly if they don’t because of the consequences for her.

Jane Frazer is the CEO of Citibank. Since the financial crisis, bankers have an Early Warning System. Who knows if it helps? The financial crisis was linked to a moral hazard. Bankers were outsourcing risk, knowing that if things crashed you and I would suffer but they would continue to collect their bonuses. This made it hard for them to do the right or brave thing.

If the doctor on the left reports a problem, no-one pays any heed. She too outsources risk putting pills that like mortgages look too good to be true in our mouths. This is morally hazardous. Like a mortgage, if a drug looks too good to be true it probably is. If we blow up, she continues to be well paid. There is no incentive for her to do the right thing.

Slide 56: This moral hazard is leading to a pharmaceutical crisis that maps onto the financial crisis of 15 years ago. Here is a recent New York Times image of Life Expectancy in the US. You’ll see it began dropping in 1980, when we began treating numbers rather than people and converted health into a service industry. This Fall cannot be attribued to COVID. My view is that it is most likely linked to polypharmacy. The UK has similar falling Life Expectancy data – again pre-COVID.

Slide 57: Drugs like guns are techniques – amoral. The morality of their use lies in us. If we stop thinking about what we are doing when we use them, we are highly likely to be diminished.

Like Guns, Drugs create an arms race. The country with the best Medical Techniques and Guns wins wars and both armament and medical developments have been driven forward by military needs – to keep men able to fight in the case of drugs.

There is difference between Guns and Drugs. The chemicals in drugs are always risky. The information that transforms those chemicals into medicines has become increasingly dangerous. At the moment, the Drugs Race is not a better Chemical Race – it’s about creating more effective propaganda. The best propaganda is invisible – in this case it masquerades as science. The greatest concentration of fake literature on earth now centers on the reports of RCTs on the Drugs our doctors give us.

With both Guns and Drugs there is a limit to effectiveness. In the case of the Atom Bomb it is so effective that it cannot be used. It is the same with Drugs, if you are on more than 3, the effectiveness of each falls off as you add more meds into the mix.

To get the most effectiveness you need to be on 3 or less. As of 2016, over 40% of over 45s in the United States were on 3 or more drugs every day of the year – this figure includes the people who never come to see doctors. Over 40% of over 65s are on 5 or more drugs every day of the week. Knowing what is happening teenagers, this can only increase.

We know that reducing medication burdens can increase life expectancy, reduce hospitalizations, and improve quality of life.

Slide 58: Reducing a medication burden is not easy – as this image from the movie The Hurt Locker illustrates. Many of these drugs explode on attempting to withdraw them. This is the primary medical task of our age and there will never be any RCTs to help us out. The best evidence will likely lie in clinical experience of tackling similar situations. Great if I have a walkie-talkie to clinical colleagues but my key partner in this is you – you bring cues from missing doses of some of these drugs, and your sense of what they are doing that I can only access through you. And of course you ultimately dictate which risks we take.

In the 1940s and 1950s, RCTs had a role when we didn’t know if things worked. From the 1960s we had so many good drugs that worked – brought on the market without an RCT in sight – a new role beckoned for RCTs – to work out what worked best. RCTs cannot do this and besides it did not suit company interests. Companies instead created Randomized Controlled Assays which among other things allow weaker and weaker drugs on the market.

The pressing medical need now is to get people off the meds they are on and RCTs and what is called EBM have little or no role to play in helping us with this.

Slide 59: If a doctor tries to modestly reduce medication burdens or recognize that in some cases a treatment might have become a problem, current public health systems will not accommodate her. In the US, it is current culture that will mobilize against this. The doctor will be told this would be a good private practice offer that people can choose, but the public health system expectation is that people want and should get more diagnoses and drugs.

This is because getting treatment to save our lives was once a privilege and wealth and public health systems want everyone to be able to access treatment. They cannot now see that these good intentions are killing people. Now we have to be wealthy to get off medicines to save our lives.

Canada now leads the world in MAiD – Medical Assistance in Dying. In places like Belgium and Holland young women are getting MAiD because they have drug induced treatment resistant depression. While there must be concerns when young women in their 20s get MAID for treatment resistant depression – an antidepressant induced illness – I’m not quibbling about the morality of MAiD – any good doctor will almost certainly have cases where MAiD is the caring thing to do.

What I am quibbling about is the morality of a system that encourages us to have any service we want, including MAiD, but denies us the option of having less services. Denies us a Greener, more sustainable HealthCare. At the moment, not even Green parties have got a handle on this.

Slide 60: This lady comes from an Arthurian Legend. Arthur has been out-fought by a Black Knight who spares his life if he can answer a riddle – What do Women Most Desire. He has a year to find the answer. He and his court hunt desperately for it. The day he is due to die, Arthur and his troop meet this woman who tells him that she has the answer to the riddle but one of his knights must become her husband. Gawain jumps down and offers himself up. Arthur answers the riddle, and a furious Black Knight lets him go.

Slide 61: Gawain gets married. Everyone at the Court is unhappy for him.

Slide 62: In the bedchamber Gawain can’t bear to look at her. She takes control and asks him – do you want me to look like this by night with you and the way I was by day in court or like this by day in court. He has no idea and says – whatever you want. This is the right answer.

The answer to both riddles is she, like us, wants to control her own life. There may be a disease that needs treating – but she doesn’t want us to tell her how to live life, or want her negative emotions eliminated with a pill. She may be doing better at living life than you or I.

The evidence based medicine we now practice creates a False We – a non-existent average person – a fairy tale.

Rather than paying heed to the non-existent average person who comes out of clinical trials, when we relearn that we can learn much more from the person right in front of us, she and others who come to see us will seem more interesting and as they sense that we will be more attractive to them – easier to work with.

A relationship based medicine is the only validly scientific form of clinical practice. If you can’t build up a relationship with people because you and they see a different doctor every time, a relationship in which you are looking closely at and listening attentively to them – perhaps even detecting if there is a change in their smell, you are not doing science. The person in front of you is the apparatus in which the experiment is taking place. The computer screen is not.

Both science and morality depend on collaboration. Collaboration creates a virtuous circle – an Us – that leaves us all better placed to live the life we want to live. It creates Social Capital.

Redesignate Company Trials as Assays

Government of the People by the People has been replaced by governance.
If it is not to perish entirely from the earth…
We need to do…

Footnotes

This may be the most important lecture I have ever given – it’s the longest at least. It has been heavily shaped by Dee Mangin, Peter and Julie Wood and everyone linked to RxISK – Bill James, Johanna Ryan, Peter Selley, Sarah Tilley, Mary Hennessey, Annemarie Kelly and many others who have worked behind the scenes but don’t want to be named and others whose comments on posts are often more illuminating than the posts themselves.

It has been shaped over a 25 year period by Andy Vickery, Cindy Hall, Skip Murgatroyd and Michael Baum who in the legal cases they involved me in brought me face to face with the many issues covered here.

It has been shaped by Jon Jureidini, Melissa Raven, Joanna Le Noury, and Elia Abi-Jaoude, who along with Mickey Nardo and Catalin Tufanaru, both now dead, were the team behind the Restoration of Study 329 – see the final article at Restoring Study 329.

It would not be possible to leave Peter Goetzsche out of the frame and an intense struggle to restore the Prozac trials in adolescents – along with the bravery of Ralph Edwards in publishing this paper. See Flat as Kansas.

Finally to complete a set of Peters, Peter Doshi has been one of the most remarkable people working on all these issues extraordinarily effectively.

There have been any number of fabulous media people like Shelley Jofre and Andy Bell who brought key issues to light, along with Ariane Denoyel and others who have grappled with the issues outlined here.

More recently, Dan Johnson, along with Yoko Motohama and Vincent Schmitt who have lost teenage sons to the drugs mentioned here, triggered the series of lectures noted above of which this is the third in the series. Jon Thompson and his colleagues in the math department in the University of New Brunswick, along with Peter Selley and colleagues in the Devon and Exeter Medical Society allowed me to dress rehearse and improve the talk.

I have stolen ideas from lots of people such as Steve Lanes – too many to acknowledge. As Steve’s example shows, some of the best help has come from people working in industry.

The Q and A after this talk in Boston reveals a tendency we all have to say things would be fine if industry just weren’t involved in trials. This is not my view. Industry don’t help but they are primarily exploiting medical failures to get to grips with the faultlines in RCTs – and a medical willingness to accept a simplistic solution to the problem of objectivity rather than engage with others in establishing what is objective or at least the best provisional version of objectivity.

This key post in the Politics of Care series stems from an invite from Norman Fenton to give a lecture on December 6 to a group interested in the evidence swirling around vaccines. It is accompanied by The Handmaid’s Vaccine on RxISK, which gives a video of the talk, whose text and slides are below. The sound effects in the video are slightly mixed at one or two point and you might need the text to clarify the points made.

This talk is for all who are interested in evidence and how we generate it as well as for a group of people who are pro-vaccine, to the point of being volunteers in clinical trials, but who have ended up being harmed by them. They are the ones doing the science and demonstrating what science means – as I’ll explain – but their work is written off as misinformation.

The company handling of SSRI harms shows we came to classify real Evidence as misinformation. Many of the company tricks involved in this effort to persuade us the world is flat will be known to you but the brazenness with which they were deployed and the failure of physicians to spot what was going on may be new.

Slide 2

I have a doctorate in Serotonin Reuptake and was keen to try the SSRIs early on. Two men I put on Prozac became suicidal. Their problems cleared after stopping and re-emerged on starting another serotonin reuptake inhibitor and stopped again after stopping. See Creaney et al.

This is as clear a causal connection as you can get anywhere in science. I sent the cases to Lilly for comment and presented them in forums. No-one offered alternate explanations. Others reported similar cases during the year to publication of this article.

Slide 3

This rash of cases forced FDA to require Lilly to defend their drug. As my article came out, Lilly published this Beasley et al article in the BMJ. It came out on the same day the company presented their case at an FDA hearing – September 20, 1991 – stating:

• The plural of anecdote is not data
• It’s the disease not the drug
• Are you going to believe the misinformation or the science?
• It’s all the fault of the Church of Scientology (1991’s Anti-vaxxers).

The BMJ article shows more suicidal events on Prozac but the paper said these were not statistically significant and so there was no problem. FDA talked about heart-breaking cases reported to them but concluded the science didn’t link Prozac to the problem.

Slide 4

Here is Tony Hill, who created RCTs, saying 20 years later RCTs can help assess one of the 100 things a drug does – something we might be able to use for treatment purposes. This, by definition, means RCTs are not a good way to evaluate a drug. See Clinical Trials are not Safe.

Saying RCTs are not the way the truth and the light, these days, is like saying the Bible, the Koran or the US Constitution aren’t reliable.

Slide 5 Watch this.

Slide 6

In a depression trial, investigators focus intensely on one thing – does Prozac have an effect on mood. Pretty well everything else is ignored. The statistics we use don’t work unless there is an intense effort to collect everything we can about this one outcome.

And so, depression trials miss something that happens to almost everyone who takes an SSRI within 30 minutes of the first pill – your genitals go numb. You can search the RCTs on these drugs and all you will find is that perhaps 5% of people have sexual issues on these drugs.

Emotional numbing is another extremely common effect almost completely missed. This is how these drugs help. This is how these drugs might help someone diagnosed as depressed but the key point is that it is much more common than depression recovery.

Similarly in the vaccine trials, the common thing is a multiplicity of Spike protein effects – doing this we hope might help but if we are hypnotized by what is hoped for we will miss and have missed what these Spike proteins are actually doing.

If we just depend on RCTs, we end up knowing almost nothing about a drug.

The idea that an RCT shows there is a favourable Risk-Benefit ratio for a drug or vaccine can only hold true if the thing we are looking at is the commonest thing this vaccine does – like a parachute for instance. The commonest thing is a life saved and the Risk Benefit is favourable but we don’t need an RCT for parachutes.

If what we are hoping for is pretty rare – as in vaccine or SSRI trials – and in particular if we don’t know what we are missing, such as an obliteration of our ability to make love, perhaps for all time, then claiming a favourable Risk Benefit ratio is psychotic.

Slide 7

The first rating scale for behaviour was the Hamilton Rating Scale for Depression. An aid to make sure physicians checked on most of the things that might be abnormal in depression while they were interviewing a patient. An aid to help a doctor do an interview that would help the patient to live the life they wanted to live.

If you cleave to the checklist you will do very standardized but possibly disastrous interviews. For instance, on the Hamilton Scale, there is an item on suicide which could stem from the illness or from the drug – it needs a judgement call as to which of these is responsible. Ditto for sex, for sleep. Just checking yes for suicidality risks going badly wrong.

Checklists like these however became viewed as scientific instruments. They look better to hospital managers than DH asking about your daughter or partner. Without judgements, in medicine we call these diagnoses, rating scales are meaningless – other than to help a doctor to help you to live the life Pfizer want you to live.

Slide 8

The latest twist on this story are the rating scales for adverse events companies now run electronically which let people rate up to 12 things that happen after the vaccine – such as sore arm, headache, nausea etc. This ensures certain events become statistically significant – and are put forward as a result as the only things we know for sure happen on the vaccine. See Johanna Ryan’s work on Virtual Trials.

There is no area for people to contribute anything else – so reports of other adverse events end up coming from outside the trial and are viewed anecdotes – misinformation. Companies like Pfizer tally anecdotes. What else would you do with misinformation?

Slide 9

Here is Fluvoxamine, an SSRI supposedly good for Covid. There have been lots of dropouts in the trials done on this, enough to invalidate the trial.

Side effects though could be endorsed on pre-populated lists that included cough, fever, nausea etc but not suicidality, homicidality, sexual dysfunction or the other things this drug causes that were likely responsible for the huge dropout rate.

Many look to drugs like this as an alternate to vaccines. Some doctors advocate them as our Hi Tech versus Albert Bourla’s Hi Tech. There are lots of low tech things that might be more helpful like getting you off some of the Tech you’re on rather than throwing more Hi Tech at you.

As we throw Hi Tech at you, we miss the fact that RCTs convert poisons, from whose use we hope to bring some good, into sacraments – something that can only do good. Most believers figure having as many sacraments as you can daily is a good thing where its seems equally obvious to most of us that taking more than one poison at the same time is unlikely to be all that safe.

One more quirk is companies always want their Ugly Ducklings to have an I’m a Swan moment – thalidomide was the fourth most profitable drug in the US last year but will be pushed down to fifth by Albertine this year. Thalidomide is a drug that causes suicidality, sexual dysfunction and birth defects – just like the SSRIs including fluvoxamine.

Slide 10

For drug companies, rating scales ensure you do an interview that produces figures which are the most seductive way to get the patient on their drug. The interview helps you to help them to live the life Pfizer want them to live.

This is not just true for rating scales, it is true for any measure – peak flow rates, bone densities, blood pressure or lipids, or sugar. It may be important to do something about some figures, but the goal is to help people to live the life they want to live – not the life Pfizer want them to live.

A stopwatch can be a wonderful motivator to achieve a dream – it provides data from one fraction of our lives. If we remain on top of that fine – but what about weighing scales? Just after they were introduced we got the first descriptions of anorexia nervosa. In the 1920s, they had norms for ideal weight attached to them and eating disorders mushroomed. They migrated into our homes in the 1960s and eating disorders became epidemic.

It’s very difficult to ignore figures for weight. Without data from every other aspect of our lives at the same time, we risk being trapped by this one data source. We become neurotic.

Can we let bone densities remain thin, or lipid levels remain high? Yes, we can. You think of post-mortems as something that reveal what we died from – they more often reveal what we can live with.

Slide 11

Figures create risks and pharma makes money from treating risks rather than diseases. We are seduced into taking drugs when we are healthy.

The Covid dashboards are a great mechanism to generate perceptions of risk and fear. The vaccines of course treat risks – not disease.

The Meatloaf title Paradise by the Dashboard Light is what Pfizer sees but its Hell by the Dashboard Light for us – this now extends to the evaluation of lectures and ensures we pander to people rather than challenge them.

It’s extraordinary how little we have put into treating SARS-Cov, the disease in this case and its associated pneumonia. Curing diseases is not a good business model.

Slide 12 As Peter Drucker, the Guru of Marketing Science put it 50 years ago:

The goal of marketing is to make selling superfluous. The aim is to know and understand the customer so well that the product or service fits and sells itself.

Slide 13

Imipramine was the first antidepressant. It beats the later SSRIs in RCTs. It treats melancholia – they can’t. They are useless for severe depression. Melancholia comes with a high risk of suicide.

Imipramine was launched in 1958. A year later at a meeting in England, Danish psychiatrists made it clear that while it was a wonderful treatment it made some people suicidal.

Let’s do a thought RCT of imipramine versus placebo in melancholia. Even though it can cause suicide, we would expect it to reduce the number of suicides because it treats the condition. This RCT would be great evidence antidepressants do not cause suicide.

Slide 14

Here is the data on the trials in mild depression that brought the SSRIs to market – a doubling of suicidal events compared to placebo.

Slide 15

Imipramine looks the same in mild depressions. Now it too causes suicides. So RCTs tell us nothing about cause and effect – they can give us diametrically opposite answers. This is because these aren’t drug trials. They are Treatment Trials and in any clinical Trial, the condition confounds the effects of the drugs.

People evaluating drugs pre-RCTs knew this. When a patient becomes suicidal in a trial you have to use your judgement to work out what has happened but you are told not to.

Slide 16

This is true in every clinical situation where drugs and conditions cause superficially similar effects – diabetes and glitazones both cause heart failure, osteoporosis and bisphosphonates both cause fractures – and this makes it impossible for an algorithmic exercise as most RCTs are to establish what is happening.

Slide 17

Here is what a real drug trial looks like. Companies ran these studies in the 1980s and found that SSRIs make healthy volunteers suicidal, cause dependence and sexual dysfunction but we heard nothing about this when the drugs launched. These Trials enabled companies to game their Treatment Trials to hide these problems.

Vaccine trials are healthy volunteer trials.

Slide 18

This slide shows data straight from a 2006 GlaxoSmithKline paper. GSK’s SSRI paroxetine was in trouble – the RCTs data for Major Depressive Disorder seem to show paroxetine causes suicidal events. The real data are likely worse that GSK admit to here.

Slide 19

But never fear RCTs come to the rescue. GSK also did trials in people with Intermittent Brief Depressive Disorders – IBDD. These are borderline personality disorder to most people – patients who have suicidal events much more often than anyone else. But these patients can meet criteria for depression and could be entered into Depression RCTs.

Slide 20

Prozac in these patients didn’t work. Paroxetine didn’t either and had a 3-fold higher suicidal act rate than placebo. GSK then did another trial in a similar group of patients. Why?

The answer is here. Here are IBDD data from the two GSK trials. I have seen other data for these two trials which make paroxetine look worse but let’s stick with GSK’s story. We could even add 16 more events to the paroxetine arm and still get the same magical outcome

When you add the IBDD data to the MDD data – all of a sudden paroxetine doesn’t cause suicidal events it protects against them.

Something like this must happen in every treatment trial with heterogenous patients – back pain, breast cancer, diabetes, hypertension, osteoporosis, parkinson’s disease. We can use an effect a drug causes to hide an effect a drug causes.

RCTs are not a way to work out what is going on. Back pain trials will insist you use analgesics rather than antibiotics – which is wrong for the 10% of backpains caused by infections.

Slide 21

You’ve seen the son of this slide before. Here are the parents. In all AD RCTs there was a 2-week washout period during which patients were whipped off prior medicines. We now know this was a tricky thing to do – it gives lots of suicides – a bit like the two-week post vaccine period.

But companies argued as the patients were on nothing, all these events should be counted as placebo events – as the diagram here illustrates.

Slide 22

The Prozac 1991 paper had an increased number of suicidal events – but hey not statistically significant. Undo this maneuver –– and they are statistically significant.

Here are the paroxetine data presented to FDA. We’d prefer the figures for paroxetine to be better than placebo but what’s a fraction between friends.

Slide 23

Undo the washout maneuver and this is what the data looked like. FDA knew what was going on and that it breached regulations and did nothing. And these figures don’t look like a drug that should be approved without warnings.

Slide 24

When that was rumbled, companies changed the game. Patients terminated from their SSRI who went into withdrawal and became suicidal were viewed as placebo, while those who stopped placebo and were put on an SSRI and committed suicide were classified as a placebo suicide – on an intention to treat basis. Regulators didn’t ask questions.

Slide 25

Sylvia Plath committed suicide a week into an antidepressant – a common timeframe.

Slide 26

This advert is for the type of antidepressant she was given, an MAOI, featuring a space shuttle, aimed to giving doctors the impression this drug will get their patients into orbit faster.

Slide 27

Here is a space shuttle – the safest transport ever per million miles travelled – but not so safe if expressed in terms of exits from and entries back into earth’s atmosphere.

Rather than express suicidal events per patient exposed companies stuck to events per thousand patient years – having taken care to ensure some patients doing well remained in extended follow-up for months or years.

Slide 28

When the RCT data turned tricky and we got Black Box Warnings – companies turned to Real World Evidence – like national suicide rates. Here you see the claims for Norway which were typical of all Nordic countries – as SSRI use increased suicide rates fell – which is not compatible with the SSRI data.

If you look though suicide rates are going up with pre SSRI AD use until about 1988 – 3-4 years pre SSRI when they begin to fall.

Slide 29

Here is Norway again where you see suicide rates falling from 88 or so and what you see if them rising as autopsy rates rise and then falling in step – as ill-defined deaths fall and rise.

Slide 30 This is true for all the Nordic countries – See Reseland et al.

Slide 31

We routinely hear that SSRI use is escalating. It’s not – the same number of people go on them each year. The increase speaks to the growing numbers who are dependent on them.

Slide 32

This has implications for suicide rates – you are only likely to see an effect on an index like this during the first few years. In the case of vaccines, this years rate of myocarditis and thromboses will become the new normal – See Healy and Aldred 2005.

Slide 33

In 1999 I was asked to participate as a speaking at a company symposium in London – speakers would need to produce articles for a supplement. I said yes and soon after had an email with my article. It was a great Healy article saying the things Healy say in the way he says them with Healy references. No one who knew my stuff would pick it out as not mine.

I emailed back saying I figured on writing my own. There was surprise at the other end but they said okay. I sent it on to them and they said this is rather good but there are some important commercial messages in the other one – we’ll get Siegfried Kasper to put his name on it.

Here it is – only one word changed from the original paper – the name of author Kasper. Everybody in Vienna knows this but its done no harm to SK’s career. You can find materials saying you can trust doctors like Kasper because they have written a 1000 articles or more. Its still a great Healy article etc.

Slide 34

A year later I was in Pfizer’s archive where even the loo-paper was stamped confidential. I came across this working document – which was the articles on Pfizer’s SSRI Zoloft being managed by Current Medical Directions – a medical writing company.

Slide 35

Inside there are pages listing the articles published or in train on Zoloft for the anxious, the depressed, the young, the old etc – here you see the PTSD page.

You will see on the right – the articles were written for these essentially negative studies saying the drug worked wonderfully well. One would go to NEJM – the other to JAMA. And on the left – you see TBD – authors names are To Be Determined. Pfizer’s marketing department will work out who would be the best sales people for the drug.

This is not just a mental health issue. It holds for all treatments across medicine.

Slide 36

Here is the most famous RCT of all time. It has a distinguished authorship line and is in the journal with the highest impact factor in child psychiatry and says paroxetine works wonderfully well and is entirely safe for children who are depressed.

Slide 37

This internal GSK document from 1998 shows the company knew the trial had shown the drug didn’t work and proposed taking out the good bits of the data and publishing those which is the article you have seen. New York State took a fraud action against GSK on this basis who were also fined $3 billion which led to access to the trial data and what you are going to see next.

Slide 38 The full story is on Study329.org

Slide 39

Through this legal action we got access to company data no one ever sees. The efficacy data is pretty irrelevant, but it was still possible to show that no matter which way you cut the data paroxetine was not more efficacious than placebo.

Slide 40

The tricks used to hide the problems were the real interest in these data.

The original article had 10 pages. Regulators see an 800-page Clinical Study Report (CSR) plus nearly 5000 pages of appendices – these are notional they are there but no-one in MHRA or FDA will look at them. We saw these and a further 77,000 Clinical Record Form (CRF) pages.

Point 2 points to data that just didn’t get transcribed from the 77000 pages to the 5000 pages. Point 10 is patients on placebo got SSRIs – I can explain how. But I want to focus on the coding issues.

Slide 41

The psychiatric adverse events all got grouped in CNS or neurological events – into which the groupers also put headaches and dizziness. The dizziness was not neurological – it was cardiovascular because it this case the comparator drug lowers BP especially when used in double or triple the adult dose.

The effect of this was to drown out the signal from psychiatric adverse events. So there is an issue about grouping. We were sensitized to this by Elizabeth Loder, the BMJ editor handling out paper – which took over a year to publish with 7 review rounds and 7 reviewers – who objected to our every mention of headache. As it turned out was a headache-ologist, who was an opinion leader for GSK but above all was the wife of an attorney working in Ropes and Gray who had been the lawyers defending GSK against the $3 billion fine.

Slide 42

So here, leaving out headache and dizziness, in the lower bar you see the number of suicidal events in the Keller paper – once you decode them from emotional lability. In the middle bar, GSK revised this after being asked to do so by FDA when a fuss blew up. In the upper bar you see that we found more again – and there were more than we missed as I’m about to tell you.

Slide 43

How does this fit Co-Vaccines? Well, here you see Pfizer’s report of their adverse event data – a ton of them have disappeared into a higher order coding group called General Disorders. The crimson half of the bar shows you these are serious, potentially lethal. General Disorders is a meaningless group – it needs unpacking.

Slide 44

In a Pfizer trial, one man poured petrol over himself and set a match to it, intending to kill himself. He died 5 days later from his burns. His death was coded as burns. But the company had to write a Serious Adverse Events narrative and if you got to see that you could work out that he should have been coded as suicide.

Slide 45

Companies have found a way to get around this, as found out after Study 329 finished. Here is a young man on a street waving a gun. Its Kyle Rittenhouse. In Study 329 a boy of 15 was picked up out on the street waving a gun around and threatening to kill people. He was hospitalized and should therefore have had an SAE narrative but the company coded him as intercurrent illness.

Four children dropped out of Study 329 coded as intercurrent illness – all were taking paroxetine. Add them into the picture you have just seen and things look a lot worse.

What is intercurrent illness? This was almost certainly an adverse event on paroxetine but invoking an intercurrent illness that means you really should not have been entered into this study means there is no need to write a narrative. This loophole has been there for 25 years and FDA have not moved to close it.

Slide 46

We know Astra-Zeneca broke the blind and got rid of serious adverse events like the ones that happened to Bri Dressen – see New England J of Misinformation. Here you see intercurrent illnesses turning up in this same Astra-Zeneca trial.

Slide 47

Here you have Maddie de Garay who has been tube fed and needs a wheelchair since a few days after the second dose of Pfizer’s vaccine in their trial for 12-15 year olds. But the company says no serious vaccine-related adverse events happened in this trial. They claim she has hysteria and of course that antedates the trial and so the vaccine can’t have caused it.

Slide 48

Few people know that FDA approved paroxetine for children – here is part of FDA’s 2002 letter of approval to GSK. The key bit is typed up so you can read it. The date is important – the Keller paper was 2001.

You can see here GSK told FDA that Study 329 was negative and you see that FDA agreed to approve the drug on the back of three negative studies and also agreed that there was no need to mention this in the labelling. Why would FDA do this?

Slide 49

Here are the published results of adult trials of antidepressants nearly a decade earlier. The picture looks pretty good.

Slide 50

But as Erick Turner has shown, this is how these studies looked to FDA. A different picture. Companies don’t leave negative studies unpublished, they know FDA are happy to let them publish negative studies as positive.

Why? Did GSK tell FDA – if you tell the world Study 329 was negative, we might get sued for fraud – which they did and fined for $3 billion. FDA don’t feel inclined to blow this whistle and MHRA and EMA have even less incentive.

Slide 51

So here is Study 329 again. The author is not listed. In the case of trials done in children, pretty well the entire literature was company written. The mismatch between what articles claim and the data when we see is the greatest known divide in medicine but likely not atypical. Study 329 was a good and ethical trial compared to some of the current vaccine trials.

There are now 45 negative trials for antidepressants in minors – out of 45 trials done. Yet antidepressants appear now to be the second most commonly taken drugs by teenage girls.

Slide 52

In this New England J of Misinformation article, the first thing to note is the author is not listed here. Twenty of the 29 apparent authors are company people. Few are clinicians and none are likely to have seen anyone harmed.

Second the trial was run by I Con rather than Pfizer who subcontracted to Palladium Research, who subcontracted to Ventavia and we know Ventavia ran a shit-show.

Anyone with experience of company trials knows that it is worth looking at the centres involved because for instance in a trial of aripiprazole where there might be 33 centres with 30 producing results for the drug that would not get approval, but perhaps 3 in places FDA won’t visit that found every patient put on the drug did fabulously and every on placebo was seriously injured or died a horrible death and adding both together produces a result that can squeak by FDA.

There is scope to wonder if something similar happened in this trial.

What we do know is that more people died on vaccine than placebo and lots more people disappeared on vaccine and FDA’s current leadership for whatever reason would prefer to be dead before anyone gets access to the data and their correspondence with Pfizer.

Slide 53

Is there a House in the Doctor? The medical drama House was watched and loved by many. Dr House was good at solving puzzling clinical cases by pulling on the thread of some minor detail which led to the answer.

Doctors today have close to lost the ability to say an evident X causes an evident Y – largely down to the mantra that only RCT evidence tells us what a treatment does and we can’t believe the evident anymore. Wife shoots husband point blank in chest – did she kill him? Who knows. In perhaps 1 case in 100 he had a heart attack just beforehand – we need to pass the 100 cases on to those experts in CDC, FDA, EMA etc and let them work it out.

As a result docs report maybe 1 in 10 or 1 in 100 serious side effects to regulators who file these away and do nothing with them.

This is unlike airline pilots who also report near misses and refuse to fly if these reports are not taken into account – after all if the customer dies the pilot does too. This is not true of doctors.

Slide 54

There is a profound misapprehension of the role of a regulator. They are not part of the health apparatus. Their job , perhaps easier to see in the case of food, is to decide if this yellow stuff is butter or lard colored to look like butter. If butter – it is not their job to decide if this is good butter or not or if butter is good for us or not. Ditto with drugs – the role is just to tick a box if certain criteria are met.

They have no abilities to or training in establishing if a drug or vaccine causes a problem.

Slide 55

Here is Walter Raleigh getting his head chopped off. After the fact legal systems recognized the injustice of convicting someone based on hearsay and said cases could only be decided on the basis of evidence in the room that can examined and cross-examined.

The first thing MHRA do with any reports is to remove the names of doctors and patients. This converts them into hearsay, anedcotes, misinformation. It means no-one can decide if there is a link.

MHRA will say till the crack of doom they are looking to find causal needles in the haystack of reports but faced with a needle-stack they can’t seem to spot a needle.

The key to determining cause and effect is an encounter between a doctor and patient. All the data is there. After a first run through there is a chance to follow up when oddities about the data come to mind. Remove the possibility for an ongoing two-way encounter like this and you remove the ability to establish cause and effect.

Slide 56

The one tool regulators have with anonymized drug reports is proportional reporting rates but as Matthew Crawford pointed out you can’t even use this for VAERS because you need lots of drugs in the mix for this to work properly. Besides proportional reporting rates are a cop-out. They might look more scientific than interviewing someone but they aren’t.

Slide 57

If someone commits suicide on an SSRI, their doctor will be advised by their insurer not to say the drug caused it or say anything that might lead to a further legal case. Insurance is supposed to be a business that supports us to take risks but is not doing this here.

If the doctor breaks ranks and blames the drug, a coroner, who can say a street drug caused a death, has no box to tick to implicate a prescription drug in a death.

Media guidance equally ensures journalists cannot say the obvious – the drug caused the suicide if the coroner hasn’t done so – and all this will apply to vaccines also.

If the coroner goes rogue and writes to the regulator and intimates that the evident cause of death was the drug or vaccine, the regulator will check on what the doctor has said and if the doctor didn’t finger the drug or vaccine – they won’t.

If the case is so Evident that both doctor and coroner go rogue, as in the Alana Cutland case, the regulator will respond, as MHRA did, that we only have a handful of reports like this – not enough to let us work out what might have gone on.

Slide 58

In the TV series House, the hero pays heed to tiny things that don’t fit the pattern and after twists and turns finds how it all hangs together.

When a wife shoots her husband in front of Dr House these days he seems unable to work out what’s gone on. Ok the guy may have had a heart attack at the same time and she shot him afterwards out of spite at being cheated out of a pleasant moment but 99 times out a 100 it’s pretty simple, she killed him. House though has lost this plot.

Some great doctors encourage their colleagues to report adverse events to regulators – which makes the problem worse. Regulators will file these reports away until the crack of doom. Unless doctors have the courage to say – look I know what I have seen and the vaccine or the drug killed my patient, they make things worse.

Dr House can’t get his head around the fact that with drugs and vaccines we hope to bring good out of the use of a poison, and sometimes people get poisoned. We and he prefer the idea he is giving sacraments – things that can only do good.

F Scott Fitzgerald once said that a sophisticated mind can hold two contradictory things in mind at the same time and still function – doctors could do this once but can’t now.

Science challenges Muslims and Jews, Xtians and Atheists to leave their biases at the door and come to a consensus about the data. But as in a jury trial, sticking with the data we still have to come to a verdict. A judgement. A diagnosis. It is not the role of a regulator to make diagnoses or deliver verdicts.

A verdict has effects in the real world just as much as shooting someone. There are evident effects from shooting on a husband who dies, and equally evident effects on the wife being tried.

This is important but more important for all of us just now are the effects on the doctor or failing to make any verdict, and just as much failing to make the diagnosis they know or suspect is the right one.

This failure transforms them into Model Doctors – a shrunken replica of the real thing.

When treating a patient, following the evidence can’t mean doing what ghostwritten fraudulent articles say. It has to mean following the person in front of me and coming to a consensus view just as a jury would.

If there is a mismatch between that and the so-called evidence – well all the books say that’s what moves science forward.

Slide 60

See The Handmaid’s Vaccine on RxISK – and its message about Albert and Ursula, the happy couple you see here.