Category Archives: Doctoring Data

Cleaning the Augean stables (Part I)

24th November 2022

Peer-review: Time to get rid of it

‘There seems to be no study too fragmented, no hypothesis too trivial, no literature citation too biased or too egotistical, no design too warped, no methodology too bungled, no presentation of results too inaccurate, too obscure, and too contradictory, no analysis too self-serving, no argument too circular, no conclusions too trifling or too unjustified, and no grammar and syntax too offensive for a paper to end up in print.’ Drummond Rennie.

Somewhat damning?

It supports my considered opinion that medical research died decades ago. It is now populated by the undead to become, what could best be called, ‘Zombie science’. Or, possibly, the walking dead.

I would not be the first to think this. In truth, I nicked the term. Here is the abstract of a paper by Bruce Charlton in the Journal ‘Medical Hypotheses.’ It was written in 2008:

Zombie science: a sinister consequence of evaluating scientific theories purely on the basis of enlightened self-interest.’

‘Although the classical ideal is that scientific theories are evaluated by a careful teasing-out of their internal logic and external implications, and checking whether these deductions and predictions are in-line-with old and new observations; the fact that so many vague, dumb or incoherent scientific theories are apparently believed by so many scientists for so many years is suggestive that this ideal does not necessarily reflect real world practice.

In the real world it looks more like most scientists are quite willing to pursue wrong ideas for so long as they are rewarded with a better chance of achieving more grants, publications and status. The classic account has it that bogus theories should readily be demolished by sceptical (or jealous) competitor scientists.

However, in practice even the most conclusive ‘hatchet jobs’ may fail to kill, or even weaken, phoney hypotheses when they are backed-up with sufficient economic muscle in the form of lavish and sustained funding. And when a branch of science based on phoney theories serves a useful but non-scientific purpose, it may be kept-going indefinitely by continuous transfusions of cash from those whose interests it serves.

If this happens, real science expires and a ‘zombie science’ evolves. Zombie science is science that is dead but will not lie down. It keeps twitching and lumbering around so that (from a distance, and with your eyes half-closed) zombie science looks much like the real thing.

But in fact the zombie has no life of its own; it is animated and moved only by the incessant pumping of funds. If zombie science is not scientifically-useable–what is its function? In a nutshell, zombie science is supported because it is useful propaganda to be deployed in arenas such as political rhetoric, public administration, management, public relations, marketing and the mass media generally. It persuades, it constructs taboos, it buttresses some kind of rhetorical attempt to shape mass opinion.

Indeed, zombie science often comes across in the mass media as being more plausible than real science; and it is precisely the superficial face-plausibility which is the sole and sufficient purpose of zombie science.’ 1

Unfortunately, I can only provide you with a reference to the abstract. Because, in what I consider a majestic, universe spanning irony, the full article sits behind a paywall. Nowadays most medical papers are kept safe from the public, or the amateur researchers, or anyone else who is not a millionaire. They can only be viewed by those who have access via their university – usually. I call it ‘censorship by inability to pay.’

You cannot even read medical research that will have been funded by your taxes, or someone else’s taxes in another country. Instead, it sits in a virtual room, secured behind the locked-doors of ‘pay per view.’ Which represents another twitching limb of zombie science. It senses money and reaches out blindly to grab it, with dead, bony fingers. ‘My precious.

Going back a couple of steps. Who is this Bruce Charlton of whom you speak? Well, he used to edit the journal Medical Hypotheses. But he made the error of publishing an article highly critical of the mainstream narrative on HIV. The article in question contained this statement. ‘There is as yet no proof that HIV causes AIDS.’ Inevitably, a major outcry took place. Glasses of Dom Perignon slipped from chubby, quivering fingers. Foie gras was left uneaten, that and the guinea fowl.

Many will strongly believe, that this statement, and the entire article, must be wrong, and should never have been published. But I would contend that this is absolutely not the point. The point is that anyone who believes articles should not be published because they are ‘clearly wrong’ needs to be gently led away from the world of science. Then booted out of the door and told, in no uncertain terms, to get out and stay out. Until they learn the error of their ways.

‘In science, the primary duty of ideas is to be useful and interesting even more than to be true.’ Wilfred Trotter.

What happened next was depressingly predictable. Elsevier, the publishers of Medical Hypotheses, did exactly what you would expect of the walking dead. They did not defend the right of the editor – of a journal titled ‘Medical Hypotheses’ – to publish contentious articles. They panicked, then piled the blame on Bruce Charlton.

After receiving a raft of complaints, Elsevier had the article peer reviewed under the oversight of editors from The Lancet. Following the peer review, the article, and another by Marco Ruggiero of the University of Florence in Italy, was withdrawn and a reform of the journal was mooted.

“They were withdrawn because of concerns expressed by the scientific community about the quality of the articles, and our concern that the papers could potentially be damaging to global public health,” the publisher said in a statement.’ 2

 My favourite comment is below:

‘This journal has published ‘hypotheses’ that are regrettable… “I do not think that the medical community will lose anything if the journal does not continue in its current form.’

And if you want to find a more Stalinist, Big Brother(ist), and frankly sinister comment than the final one, you will need to travel far. ‘Regrettable’ … a word most commonly used by the evil baddie in a James Bond movie. Just before feeding his underling to the sharks waiting below.

Evil bad guy:           ‘Your actions, I am afraid, are regrettable.’ Presses button.

Underling:                ‘Aaaarrrgggh….’ Chomp, thrashing, blood.

And lo it came to pass that Bruce Charlton was fired. Then, in an even more majestic, metaverse spanning irony, Elsevier decreed that the journal Medical Hypotheses must become peer-reviewed. Bruce Charlton had vehemently disagreed to this – another reason why he was fired.

Yes, a journal dedicated to publishing new scientific thinking was to be peer-reviewed. But who could they choose to carry out such a task? All those ‘peers’ who just happened to have previously published the exact same new hypotheses – never published before. A clever trick you may think.

Of course, they do not mean that. What they mean is that established figures within the field should be chosen to do the hatchet job … sorry, peer-review. The very people who would suffer the greatest reputational (and financial) damage, if their established views were to be successfully overturned. Now let me think about the likely outcome of any such review … for approximately one picosecond.

The simple fact is that peer-review has become a slaughtering field for new ideas, and new hypotheses. It is the perfect place to send a timid new-born hypothesis blinking into the sunlight. I visualise a David Attenborough documentary. The bit where a baby wildebeest plops to the ground, under the baleful watching gaze of a pack of hyenas. You know what happens next. It ain’t pretty.

Do you think my view of peer-review is a bit over the top, a wild conspiracy theory of some kind? Well, here is what Richard Horton, long-time editor of the Lancet, has to say of peer-review.

‘The mistake, of course, is to have thought that peer review was any more than a crude means of discovering the acceptability — not the validity — of a new finding. Editors and scientists alike insist on the pivotal importance of peer review. We portray peer review to the public as a quasi-sacred process that helps to make science our most objective truth teller. But we know that the system of peer review is biased, unjust, unaccountable, incomplete, easily fixed, often insulting, usually ignorant, occasionally foolish, and frequently wrong.’

Or this quote from Richard Smith, discussing Drummond Rennie:

‘If peer review was a drug it would never be allowed onto the market,’ says Drummond Rennie, deputy editor of the Journal Of the American Medical Association and intellectual father of the international congresses of peer review that have been held every four years since 1989. Peer review would not get onto the market because we have no convincing evidence of its benefits but a lot of evidence of its flaws. 3  

Listen guys, sorry to disillusion you, but peer-review was never meant to push forward the boundaries of scientific research. It was primarily designed to keep the top guys at the top, and squash anyone with dissenting views. You think not? You think it has been proven to be effective?

‘Multiple studies have shown how if several authors are asked to review a paper, their agreement on whether it should be published is little higher than would be expected by chance. A study in Brain evaluated reviews sent to two neuroscience journals and to two neuroscience meetings. The journals each used two reviewers, but one of the meetings used 16 reviewers while the other used 14. With one of the journals the agreement among the journals was no better than chance while with the other it was slightly higher. For the meetings the variance in the decision to publish was 80 to 90% accounted for by the difference in opinions of the reviewers and only 10 to 20% by the content of the abstract submitted.’4

And yes, since you ask, I have been asked to peer-review papers. I sent one off recently. Hypocrite? Well, hypocrisy makes the world go around. In my defence I believe it’s a good idea for me to recommend that a ‘contentious’ paper on LDL gets published. Otherwise, my sworn enemies get to clamp it within their pitiless jaws and crush it to death. Why do you suppose I get sent papers from time to time? Because the editor knows exactly what I think, and wants the paper published. Hypocrisy! Why, yes.

In reality, peer-review is about as much use as a chocolate teapot. All journal editors know it’s bollocks, most reviewers know it’s bollocks. But it suits everyone to pretend that the ‘all hallowed’ peer-review cleaves the sword of truth in a mighty fist, protecting us all from bad science.

Does it? Just to give you one recent example where you can replace the words ‘peer-review’, with the words ‘chocolate teapot’ I refer you back to the world of COVID19. Where one, now infamous paper, passed straight through the editorial team, peer-review, and every other check and balance, to find itself published in the Lancet, no less. Even though it rested on completely made-up data:

‘The Lancet will alter its peer review process following the retraction of a paper that cited suspect data linking the controversial drug hydroxychloroquine to increased COVID-19 deaths.

In the future, both peer reviewers and authors will need to provide statements giving assurances on the integrity of data and methods in the paper, the journal’s editor Richard Horton told POLITICO.

“We’re going to ask our reviewers more directly, whether they think there are any issues of research integrity in the paper,” he said. This stipulation will apply to every paper submitted to the journal.

“If the answer to that question is yes, that’s the moment where we trigger some kind of data review,” he added.

These changes to the eminent U.K. journal’s peer review policies are a direct result of a paper that used data from the U.S.-based firm Surgisphere, purporting to be from around 700 hospitals in six continents. But as questions emerged over the study, Surgisphere refused to allow a review of its dataset.

It wasn’t just the Lancet paper that had used data from Surgisphere. The New England Journal of Medicine had used the data for a paper.

The paper was retracted at the request of three of its four authors. They claimed that they couldn’t see the raw data because the fourth author — Sapan Desai, the CEO of Surgisphere — refused to hand it over. But the fact that the co-authors hadn’t seen the raw data pre-publication also raised questions for many readers.’ 5

Yes, indeed, the great and mighty Lancet published a paper based on completely fabricated research. Do you think Horton’s sticking plaster solution is going to have the slightest effect? “We’re going to ask our reviewers more directly, whether they think there are any issues of research integrity in the paper.

Yup, that’ll sort everything out, no doubt about it. No … doubt … about … it. Ask a few peer-reviewers to accuse their peers of potential research fraud. I can see no problem with doing that, at all. I can just imagine the frosty silence that will ensue the next time the author and peer-reviewer meet up.

Peer-reviewer:        ‘You’re a liar.’

Researcher:             ‘No, you’re a bloody liar.’

Hands up those who think that Richard Horton was simply attempting to deflect criticism away from himself, towards the peer-reviewers. ‘It’s not my fault, it was the peer-reviewers. They made me do it.’ Boo hoo. Poor little you.

Some may believe (as would I dear reader) that this utterly fraudulent load of crap sailed through editorial control, and the peer-review process, because it was attacking the use of hydroxychloroquine in COVID19. Claiming that it killed people. Of course, this was very much the party line at the time. Still is. [Not getting into that debate here].

However, I know, and you know, and everybody knows – although those at the top of this particular game would deny it vehemently – that if the authors had claimed the opposite well then. Well then… well then, their research paper would have been scrutinised to within an inch of its life, then rejected. On whatever grounds could possibly be found. A semi;colon in the wrong place. ‘Off with their heads.’

Peer-review. Yes, peer-review… a crude means of discovering the acceptability — not the validity — of a new finding.

Max Plank was the man who published Albert Einstein’s special theory of relativity. Much against forceful dismissals by his peers it must be said. Einstein’s theory was, at the time, very much unacceptable to most physicists. Plank held out against them, which was perhaps to be expected. He was a bit of a free-thinker. As he once famously said:

‘A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.’

Science can never be about acceptability – which is, too often, the purpose of peer-review. It is about the truth. Or reality, or whatever term is the best description to use. Science is about rocking the boat, and upsetting the established views, and informing ‘experts’ that they are talking rubbish.

As Richard Feynman said. ‘Science is the belief in the ignorance of experts.’

Peer-review achieves the exact opposite of what we should want from science. It cements the power of experts. It acts as a brake on progress. It rewards those who maintain the status-quo. It helps to ensure that acceptable papers are published, and unacceptable papers are not.

Yes, I am fully aware that the vast majority of people use the term ‘peer-reviewed’ as a term of praise. A stamp of scientific veracity. It has the exact opposite effect on me. It grates horribly. Just publish the damned paper and let me decide if it is a load of rubbish, or not, thank you very much. I do NOT need a board of censors to decide what I can and cannot see. Lest my poor little unformed and childish mind becomes corrupted.

I also know, I really do know that we would all love to believe in peer-review. Surely it is better than doing nothing. We cannot just let any old crap get published, can we? To be perfectly frank, the idea that we have to do something, simply because we believe something must be done, is an insatiable human drive that is another of my pet hates.

A.N. Idiot:                  ‘Something must be done.’

A.N. Other Idiot:       ‘Here’s something, let’s do that.’

Me:                             Sigh. ‘With or without any evidence that it works?’

Further Idiot:             ‘Evidence, we don’t need evidence. It is obvious that this will be effective.

All idiots together:    ‘Well, that’s good enough for me.’

Here is the contrary standpoint. If doing nothing is just as effective as doing something, then I always recommend we take the ‘doing nothing’ option. Apart from anything else it frees up time to do other things that are clearly more beneficial. Such as getting in a bit of whisky tasting or picking your teeth.

In fact, doing nothing is part of my broader ‘don’t just do something, stand there’ initiative. Unfortunately, almost everyone else seems to favour the ‘Work, work, busy, busy, chop, chop, bang, bang.’ philosophy. ‘Looks how busy I am. I must be doing good.’ To quote Bing Crosby:

We’re busy doin’ nothin’

Workin’ the whole day through

Tryin’ to find lots of things not to do

We’re busy goin’ nowhere

Isn’t it just a crime

We’d like to be unhappy, but

We never do have the time

I have to watch the river

To see that it doesn’t stop

And stick around the rosebuds

So they’ll know when to pop

And keep the crickets cheerful

They’re really a solemn bunch

Hustle, bustle

And only an hour for lunch.’

I love that song.

Having said this, I also do believe we should try to ensure that research papers are not complete rubbish, based on fraudulent research (see under the Surgisphere paper on hydroxychloroquine – published in the Lancet). For science to work, we should be able trust what we read. As far as this is possible.

But the peer-review system, as it currently exists, does not achieve this. It allows utter made-up rubbish to be published. Worse, much worse, it stops a great deal of potentially valuable research dead in its tracks.

‘If mankind is to profit freely from the small and sporadic crop of the heroically gifted it produces, it will have to cultivate the delicate art of handling ideas.’ Wilfred Trotter.

Therefore, gentle reader, I have a suggestion. Journal editors should make their own decisions about what should and should not be published, based on how interesting and valuable it seems, then publish. Do not hide behind shadowy peer-reviewers, who have their own agendas to pursue.

At which point you use the Internet for what it is good at. Get a bloody good discussion going. Make the article free to view, for anyone, for the first two or three months – or longer. Invite a broad scientific audience to get involved.

Make it easy for people to attack it or praise it. Hit the upvote button. There are very many, very smart people out there. If they can’t find a problem with a paper, fine. If they can, get the authors to argue their case. Publish the best responses. Expose the discussion to the world. Pull the paper, if needed. Slap various addendums on it, such as ‘readers should note that this paper is a steaming pile of…’

Would this work. Well, it was certainly not the Lancet editorial team, or the peer-reviewers, or even the authors of the paper, who recognised that the hydroxychloroquine paper was fraudulent. It was other researchers from around the world who pointed out that the data were made-up.6

So, in my view, we need to allow the entire world to be reviewers and get rid of peer-review. Other than use it to provide helpful suggestions as to how to make the paper better. Just to add that the helpful elf who edits my blog ramblings, had this to say about this blog:

‘Like it – what you’re suggesting is a TripAdvisor like free scientific paper web site that can be commented on by anyone … ‘ Which is a bloody good summary.

I lay this suggestion before you with all great humility. Next, I hope to discuss the FDA, and the other regulatory bodies around the world. Let me see. What comes after hyenas? Vultures, great white sharks, vampires, leeches … let me think.

1: https://pubmed.ncbi.nlm.nih.gov/18603380/

2: https://www.nature.com/articles/news.2010.132

3: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3005733/

4: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3005733/

5: https://www.politico.eu/article/lancet-review-process-following-covid-19-saga-coronavirus/

6: https://www.the-scientist.com/features/the-surgisphere-scandal-what-went-wrong–67955

How the world now works – or doesn’t

30th October 2022

[How fewer doctors means more doctors – it’s official]

This blog has nothing to do with heart disease, or vaccines, or anything directly about medical practice at all.

However, it does have a great deal to do with data manipulation, which is something very close to my heart. It also illustrates how a ‘fact’ can be anything but.

I am also hoping to help highlight an increasingly worrying trend that now scours the planet. Namely that we are living in a world distorted to fit whatever narrative those in power are trying to stuff down our throats. Although, I continue to marvel at how anyone can spout utter, utter, nonsense, and not simply curl-up and die of acute embarrassment.

Anyway, gentle reader, let me set the scene for your delectation.

In the UK, more specifically England, doctors and nurses have been leaving the profession in droves. In particular GPs. This has caused a degree of faux concern by politicians, who always wish to claim they are the great protectors of the NHS. The NHS is inevitably a big issue at every election.

Years ago, Jeremy Hunt, the then health secretary – and slippery eel made flesh – promised he would ensure there would be five thousand more GPs within about five years(ish). The actual number of years it was going to take kept moving around as the target receded into the distance. ‘Did I say three, I meant five… or was it ten.

Commentary on this was not complementary:

“Delivering 5,000 extra GPs in five years, when training a GP takes 10 years, was a practical impossibility that was never going to be achieved,” said Dr Chaand Nagpaul, chair of the BMA’s GPs committee.

“It was a pledge that also ignored the fact that one third of GPs are planning to retire by 2020, and the current medical graduates do not want to join an overworked, underfunded service, with more than 400 GP trainee posts left unfilled last year.”

Andrew Gwynne, the shadow health minister, said Hunt was backtracking on the pledge, and that “the Tories’ election promises are unravelling one by one”.1  

Seven years, or so, have now passed since Hunt’s promise, and the number of GPs has fallen. As predicted by anyone who knew why GPs were leaving. Basically, they were all burnt out, and pissed off, and nothing was being done to make their lives easier, especially, especially not by Jeremy Hunt – who did nothing but make the job considerably more difficult. I should know, I am one. Both burnt out, and pissed off, but clinging on – for increasingly unfathomable reasons. Money, mainly.

Now, however, the UK has a new Prime Minister, a new cabinet, a new health minister and a new Chancellor of the Exchequer (one Jeremy Hunt, no less). Lo and behold, we find that the number of doctors and nurses has actually, mysteriously, who’d have thunk it … increased. Even GP numbers have increased!

‘Latest data published by NHS Digital shows that, compared to August 2021, there are also over 3,700 more doctors and over 9,100 more nurses working in the NHS.

Secretary of State for Health and Social Care Steve Barclay* said:

More healthcare staff means better care for patients, which is why it’s fantastic to see a record number of over 1.2 million staff working hard in the NHS.

With over 3,700 more doctors and 9,100 more nurses, we are really putting patients first and NHS England is developing a long-term workforce plan so we can continue to recruit and retain more NHS staff.

Thanks to all our doctors, nurses and NHS healthcare staff who work tirelessly to look after us and our loved ones and continue to inspire future generations to join this rewarding career.

The government continues to deliver on its commitment to recruit 50,000 more nurses by 2024, with 29,000 more nurses since September 2019.’ 2

[*this is a new, new, health secretary. The previous new one, began this sorry saga]

Phew, all is well. Sorted. What a remarkable thing. How has this been achieved … virtually overnight? Did they manage to compress the average training time for a fully qualified doctor from at least ten years to one month? Did they find a locked room full of 3,700 doctors and 9,100 nurses that no-one had noticed before? ‘You are now free to leave and start working. Go, go now, and tend to the sick.’

No, to understand where these figures come from, let us go back in time. Twenty-nine days from the date I wrote this blog – to be exact. We shall visit a website known as doctors.net. A place where doctors post about various things – but nothing critical of vaccines obviously. Here, twenty-nine days ago, we find this, possibly, strange post:

‘I’ve just had an email from the GMC saying the secretary of state has asked for my emergency registration to run until 2024.  I doubt she had me in mind specifically.  I wonder what has been foretold?’

And this one:

Oh. My wife tells me she has also been re-registered.’

And this one, amongst many others:

‘I’ve had the email too. They’ve also apparently restored emergency registration for the nurses, too; just after some of the ones I was working with at the vaccination centre paid to continue their registration. They are somewhat pissed off.’

What is this emergency registration of which they speak? Well, during the COVID19 panic, sorry pandemic, a number of doctors and nurses who had recently retired, (and who had handed back their registration) were unceremoniously dragged back onto the register. Thus, allowing them to keep on practicing medicine. Whether they wanted to or not … most didn’t.

These doctors and nurses didn’t need to do anything themselves, not even ask to be re-instated. It was just done. This policy was designed to help plug holes in staffing. It was known as emergency registration. As stated here, with regard to nurses:

‘The Coronavirus Act 2020 gives the Registrar a new emergency power to temporarily register a person or group of persons as registered nurses, midwives or nursing associates if the Secretary of State advises that an emergency has occurred, is occurring or is about to occur.’ 3

Then as the panic, sorry pandemic, fell away, emergency registrations began to be withdrawn.

‘Many temporary Coronavirus Act provisions remain in force. However, by default they will expire on 25 March 2022. The Government has said it will allow almost all these provisions to expire.

The following policy areas have temporary changes which are set to expire in England or (where relevant) on a UK-wide basis:


temporary registration of health and social care professionals’ 4

Of course, getting rid of emergency registration would have the effect of (appearing to) sharply reduce the number of doctors and nurses. Even if the vast majority of those who had been plonked on the register never did an extra day’s work and remained happily retired. Yes, this was always a ‘pretend’ workforce. ‘Look at all these additional doctors and nurses we have created… who we haven’t spoken to, and we have no idea if they will ever work again …’

Anyway, the Government was dispensing with emergency registration. Then, out of the blue, it was back again. With retired doctors and nurses placed back on the ‘pretend’ doctors and nurse’s lists once more – until 2024. Which just happens to be the year of the next general election.

What is the explanation for this? Well, according to the General Medical Council in September 2022:

‘The UK government asked us to give temporary emergency registration to suitable people, as part of the response to the coronavirus (COVID-19) pandemic.’ 5

[The General Medical Council (GMC) controls medical registration].

What…? We had a new COVID-19 pandemic last month? I thought it started in 2020. Did you know it was back with a vengeance? Did you? Did you hear anything about it? No, you didn’t, because it never happened. This statement is simply … not true. I would never dream of calling it a damned lie. Other’s may feel differently.

Anyway, let me take you through this from a slightly different angle.

The UK Government is desperately trying to claim they are doing everything they can to support the NHS, which is currently falling to bits, and will damage their prospects at the next election. One of the key things they wish to claim is that they are increasing the work force – especially doctors and nurses (not managers for some strange reason).  However, …

‘More than 40,000 nurses have left the NHS in England in the past year, an analysis by the Nuffield Trust has revealed.

The analysis, conducted by the think tank for the BBC, said that this is the highest number and proportion of nurses leaving the NHS since trend data began.

It found that many of these nurses were often highly skilled and knowledgeable with many more years of work left.’ 6

In addition:

‘Over the last year, the NHS has lost 339 individual (headcount) GP partners and 305 salaried, locum and retainer GPs. This has created a net loss of 644 individual GPs since September 2021… There are now just 0.44 fully qualified GPs per 1,000 patients in England – down from 0.52 in 2015.’ 7

Yet, despite all these people heading for the exit, the Government now informs us that the workforce is not falling, it is going up, up, up, baby. I find this apparent conundrum to be spookily similar to my findings when studying research papers. How can various results be reconciled, when they seem directly contradictory? Heart attacks fell, but deaths from heart disease increased. In the same trial? Oh no, I must read the methodology section – usually impenetrable.

In the same way, we find the number of ‘registered’ doctors is going up, whilst the number of doctors is falling. This leaves us with two seemingly contradictory facts. Which of them is true? Or can they both be true?

In my simple little world, the true ‘fact’ is that the number of doctors is falling, rapidly. However, the Government have solved this issue by creating an equal and opposite fact. Which is that the number of doctors is going up.

They achieved this remarkable feat by bringing back the emergency re-registration of retired doctors, sharply increasing ‘pretend’ doctor’s numbers. In this weird, distorted, manipulated way we have another’ fact’ on our hands. Which is that there are more doctors on the register a.k.a. ‘more doctors.’

Which of these facts is true? Yes, in the hands of politicians, facts can become slippery little swine.

To quote John Martyn: ‘Half the lies I tell you are not true.’

In truth, once you cut through the utter steaming bullshit, I know, and you now know, what is going on – as did many doctors at the time. Here are a few more posts, from twenty-nine days ago, commenting on the re-introduction of emergency registration:

‘After a few hours to consider, I have now emailed the GMC to ask that my temporary registration be removed. FWIW (for what it is worth) I think it highly likely that this is an attempt by the government to inflate the apparent numbers of doctors available.’

Or this one:

‘It has been foretold that for purposes of political spin, they need to say that they have more doctors on the register.’

Another doctor was even more acute in their observation – twenty-nine days ago:

‘The weird thing about this is the clear and direct nature of cheating.

If – as is highly likely – this process relates to absolutely nothing at all apart from manipulating stats to misrepresent reality for political ambitions, then there would be people with job time allocated to it, meetings, emails, conclusions, notes, presentations etc.

“Are you going to the meeting about cheating the doctor numbers tomorrow?”

“Yes, I should make that meeting where we deliberately lie about how many doctors there are”

“Great, see you there. Hopefully we can cheat those figures really efficiently and get away on time!”

And lo, the game played out, exactly as predicted. One month ago, the Government very deliberately inflated figures on doctor’s numbers (and nurse’s numbers). Now they are crowing, in public, about this magnificent increase. ‘Look how brilliant we are. ‘

Crikey, how did you manage this totes amazeballs thing?’

Well, wouldn’t like to boast about it, really. Hard work, dedication … I would like to thank my team. Golly, is that the time, must dash.’

Do they think we are all completely stupid? Don’t answer that, they clearly do. Do they think no-one noticed? People were tweeting about it at the time:

‘Why has Secretary of State for Health and Social Care @theresecoffey asked the GMC @gmcuk to extend temporary registrations until 2024? Is this to prevent a sudden drop in the number of doctors on the register, causing embarrassing stats in the press?’ 8

Today, we are swimming in a sea of misinformation, and deliberately manipulated statistics. Yet, people seem to shrug their shoulders. ‘Don’t get worked up about it. Everyone is up to it, who cares. Same old, same old. The other lot are just as bad.

It is time, I believe, for pitchforks and burning torches, and people taking to the streets in protest about the way that this world is going. So very badly wrong.

In a time of deceit telling the truth is a revolutionary act.’ George Orwell.

1: https://www.theguardian.com/society/2015/jun/24/doubt-lingers-over-jeremy-hunts-pledge-5000-new-gps

2: https://www.gov.uk/government/news/record-numbers-of-staff-working-in-the-nhs

3: ‘https://www.nmc.org.uk/globalassets/sitedocuments/registration/covid-19-temporary-emergency-registration-policy.pdf

4: https://commonslibrary.parliament.uk/expiry-of-the-coronavirus-acts-temporary-provisions/

5: https://www.gmc-uk.org/registration-and-licensing/guide-for-doctors-granted-temporary-registration

6: https://www.nursingtimes.net/news/workforce/record-number-of-nurses-leaving-the-nhs-in-england-30-09-2022/

7: https://www.bma.org.uk/advice-and-support/nhs-delivery-and-workforce/pressures/pressures-in-general-practice-data-analysis#:~:text=%2D-,Number%20of%20NHS%20GPs%20by,FTE)%20%2D%20fully%20qualified%20GPs%20only&text=Over%20the%20last%20year%2C%20the,individual%20GPs%20since%20September%202021.

8: https://twitter.com/TheSmartGP/status/1575832771821727746

Evidence Based Medicine – it was a good idea

25th April 2022

[Until it died]

Once upon a time I was a member of the General Practitioners Committee. A sub-committee of the British Medical Association that represents GPs. This was during a time when the Quality and Outcomes Framework (QOF) system was being rolled out. There is hardly anyone working in the NHS, including almost all hospital doctors, who has any idea what QOF is. But GPs [Family physicians] sure as hell do.

I donned my armour and battled against it, in a purely Don Quixote style. I was aware that I was tilting at windmills, but I felt the need to do something, however unlikely I was to succeed. This stance did offer the advantage that I could then say two things that really irritate other people. First ‘It wasn’t my fault.’ Even worse ‘I told you so.’

Ah yes, what on earth is he talking about this time? What is this QOF thingy, you ask? And what has it to do with evidence-based medicine? Well, you could say that QOF represents the inevitable end-point of evidence-based medicine. The crowning glory of a system designed to remove uncertainty from clinical practice. Replace it with carefully crafted treatment algorithms, based on the best possible evidence.

To explain in a little more detail. QOF itself is a system whereby GPs can earn points for reaching various targets. They are then paid money for each point gained. How much money? You can skip the next bit, but it makes me laugh. It is but the tip of a mighty iceberg of complexity. A system that makes filling in a tax return look like light-hearted fun.

‘To work out your actual QOF value for your practice, you need to divide your population by 8,479 to derive a factor and multiply this to the QOF point value to derive the actual QOF value for your practice.

For example, if your practice has 4000 patients.

4000/8479 = 0.4717537

0.4717537 x £187.74 = £88.57 per QOF point.’

At present it is possible to achieve a maximum of 567 points (last time I looked). This equates to an income of roughly fifty thousand pounds, for a practice of four thousand patients. If, that is, you achieve all the points on offer. Which is tricky.

What sort of activity earns points? Well, take diabetes as an example. You start by establishing, and maintaining, a register of all patients, aged seventeen or over, with diabetes. The register must also specify the type of diabetes – where a diagnosis has been confirmed.

You may think this all sounds perfectly reasonable, but then ask yourself why does it need to be done? In the UK, all GPs use computer systems. If someone has diabetes, this will be known. It will be on screen. It’s not as if the GP is going to be taken by surprise to learn that the patient has diabetes when they carry out an audit.

In short, an up-to-date list makes no difference to their management. Nor are you going to suddenly stumble across more patients with diabetes simply by the magical act of creating a list.

No, the reason why a list must be created is that you can gain points for such things as lowering the blood pressure to a ‘target’ level in the approved percentage of patients. Or driving the cholesterol level down below the ‘target level’, or getting the blood sugar (HbA1c) level below the ‘target’ level in the approved percentage of patients.

In short, for QOF to work, the GP needs to create database after database of different diseases. Then carry out audit … after audit. What a great use of clinical time it all is. Appointment after appointment filled with patients called in to have their annual blood pressure check, which just sneaks in just below target level – every single time.

For the pharmaceutical companies this is manna from heaven. Every patient with diabetes logged and audited. Every one driven to reach a ‘target’. A target that will inevitably require medication. Medication that the pharmaceutical company just, ahem, happens to have developed. Medication where they just, ahem, happen to have done all the clinical trials.

In addition to QOF, you also need to link everything into NICE guidelines. NICE stands for ‘The National Institute for Health and Care Excellence’. They produce magnificent ‘evidence based’ medical guidelines on such matters as the management of low back pain, or treatment of high blood pressure. Amongst a multitude of other things.

Some of these guideline documents are, literally, hundreds of pages long. But if you do not follow them then you are in trouble. You could find yourself struck off the medical register.

If you add NICE to QOF, what do you get?

What you get are extraordinarily rigid pathways, and algorithms, for treating patients. Soviet style central planning at its finest. Everything commanded from on high, everything measured, everything inspected. All five-year plans in place …comrade.

At this point you may well ask, why the need for highly trained clinicians? Disease X requires treatment Y, at dose Z, to achieve the desired outcome. Anyone sitting in front of a computer can do this. It requires no knowledge of why you are doing any of it.

Equally, it requires zero understanding of the complex relationship between various physiological systems, or the specific medical needs of a patient either. What if the patient has three different diseases, where you must balance one system against another? What if no-one has ever studied the use, benefit, or harms, of four different drugs given at the same time? How do you balance one set of guidelines against another?

Leaving such issues to one side, depending on your philosophy of life, you may believe this is all a fantastic idea. Repeatable and reliable treatment protocols replacing potentially flawed clinical judgement. Factory worker vs. skilled artisan. Ford vs Rolls Royce.  In general, we know who usually wins this one. Command and control vs. individual decision making. No contest.

However, if the medical authorities decide, as they have done, to go down the bureaucratic ‘command and control’ model – based on the best evidence available – then there is a critical thing. It is the absolute requirement to be certain that the evidence you use is of the highest quality. Untouched by bias … if not, your house of algorithms simply collapses.

So, how reliable is the evidence base? Here is what Richard Horton (editor of The Lancet) stated a few years ago in an article ‘Has science “taken a turn towards darkness”?

“The case against science,” wrote Richard Horton, editor of the medical journal the Lancet, “is straightforward: much of the scientific literature, perhaps half, may simply be untrue.”1

A while back I wrote a book called Doctoring Data, in which I tried to help people understand the many, many, ways in which the data from major clinical trials are manipulated and biased. How they are carefully designed to obtain only the desired results. I also attempted to clarify the endless data manipulations used to report the results themselves.

If I had to sum up the overall message of the book, it is that we are all, essentially, bunny rabbits caught in the headlights of an onrushing car. The onrushing car, in this case, being pharmaceutical company profits.

More recently the BMJ published an article entitled ‘The illusion of evidence-based medicine.’ 2

It begins, thus:

‘The advent of evidence-based medicine was a paradigm shift intended to provide a solid scientific foundation for medicine. The validity of this new paradigm, however, depends on reliable data from clinical trials, most of which are conducted by the pharmaceutical industry and reported in the names of senior academics. The release into the public domain of previously confidential pharmaceutical industry documents has given the medical community valuable insight into the degree to which industry sponsored clinical trials are misrepresented. Until this problem is corrected, evidence-based medicine will remain an illusion.’

It goes on to say:

‘Regulators receive funding from industry and use industry funded and performed trials to approve drugs, without in most cases seeing the raw data. What confidence do we have in a system in which drug companies are permitted to “mark their own homework” rather than having their products tested by independent experts as part of a public regulatory system? Unconcerned governments and captured regulators are unlikely to initiate necessary change to remove research from industry altogether and clean up publishing models that depend on reprint revenue, advertising, and sponsorship revenue.’

I have been saying this, or something pretty much like this, for years. As have many other voices … howling in the wilderness. Has anything changed? Well, yes, it has changed. It has all got considerably worse.

For example, much of the recent research done during the COVID19 pandemic was almost laughably biased and dreadful. Anything that could make a pharmaceutical company money was promoted ruthlessly – did someone say remdesivir. Anything where no little money could be made was slammed though the floor. Did someone say hydroxychloroquine?

As for the vaccine trials themselves. Let us draw a discrete veil over those …vague approximations to science.

What we currently have is a crisis in evidence-based medicine. The evidence that we use is, at best flawed and incomplete. At worst, just plain wrong. Yet, this is this evidence used to create the NICE guidelines and drive the QOF targets.

Any wonder so many GPs are completely fed up. It is not the only reason, but it is a major reason. ‘You trained me for ten years, now I cannot even make a bloody clinical decision. What is the point?’ A GP colleague calls it ‘monkey medicine.’ In that a well-trained monkey could do it.

When QOF was first being heavily promoted as the glorious future of primary care, I made a prediction. I predicted that life expectancy of the elderly (where most of the QOF points aggregate) would gently start to fall. This would happen because everyone was going to be monitored and measured. Then treated with drug after flawed ‘evidence-based ‘drug.

Two problems. First, this would inevitably drive polypharmacy [many different drugs prescribed simultaneously], and the evidence for this is overwhelming, and clear. Here is a short section from a paper examining the increasing use of multiple medications. ‘Medication usage change in older people (65+) in England over 20 years: findings from CFAS I and CFAS II.’

‘The number of people taking five or more items quadrupled from 12 to 49%, while the proportion of people who did not take any medication has decreased from around 1 in 5 to 1 in 13.’3

Polypharmacy is, in of itself, potentially dangerous, in that all the different drugs can start interacting with each other in unexpected and, often, damaging ways. Many studies have demonstrated this unequivocally. 4

These inherent problems with polypharmacy are, of course, made far worse by being driven by biased evidence. It does not take a genius to add two and two in order to predict that, in this situation, life expectancy may well go down, rather than up.

Biased evidence base + polypharmacy = increased morbidity and mortality

In support of this, here is an analysis from Imperial College London entitled ‘Life expectancy declining in many English communities even before pandemic.’

‘A substantial number of English communities experienced a decline in life expectancy from 2010-2019, Imperial College London researchers have found … For such declines to be seen in ‘normal times’ before the pandemic is alarming.’’ 5

Cause and effect? This cannot be said for certain – rather too many variables flying about. I know what I think.

However, one thing you can certainly argue is the following. If the evidence we now use to audit and treat everyone, using QOF, was of unbiased high quality, then you should expect to see some improvement in life expectancy.

But that is not what happened. What happened, was a fall. Not a huge, oh my God fall, but a fall, nonetheless. Has anyone pointed to QOF, and NICE, and the endless proliferation of guidelines as potential factors? You already know the answer to that one. Not a chance.

Whilst other countries do not have QOF, or NICE, the relentless march of evidence-based guidelines, and the subsequent clinical algorithms that they are based on, has become a world-wide phenomenon. The US, too, is seeing a fall in life expectancy.

At one time, long ago, I was a great believer in evidence-based medicine. It seemed like a good idea at the time. I now recognise that I was hopelessly naïve. First, as a student of history, I should have known that centralised command and control systems always end in disaster.

This happens, no matter how well intentioned it may have been to start with, and QOF was well intentioned. A crushing and inflexible bureaucracy will inexorably grow, and suffocate, and drain enthusiasm and energy from the workplace. The guidelines themselves would also, inevitably, end up as a Procrustean bed, upon which no patient can ever fit. So, you have to chop bits off, or stretch, as required.

Procrustes “the stretcher [who hammers out the metal]”, was a rogue smith and bandit from Attica who attacked people by stretching them or cutting off their legs, so as to force them to fit the size of an iron bed. [The process was always fatal].

In this case, the Procrustean bed has been further distorted by the fact that the evidence base itself rests of quicksand. It is a horribly biased mess. So, yes, evidence-based medicine was a good idea (sort of). It died long ago. R.I.P.

As an end-note, the impact of QOF was reviewed a few years ago. In 2017, to be precise. Nothing since that I am aware of. As the study concluded:

‘The lack of effect of the QOF on mortality is surprising, given that the indicators are based on high-quality evidence of effectiveness of interventions. Why this is the case is not clear… ‘6

Not clear… There are none so blind as those who have not eyes to see.

1: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(15)60696-1/fulltext

2: https://www.bmj.com/content/376/bmj.o702

3: https://academic.oup.com/ageing/article/47/2/220/4237359

4: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-021-02192-1#:~:text=Background,among%20older%20adults%20with%20polypharmacy.

5: https://www.imperial.ac.uk/news/231119/life-expectancy-declining-many-english-communities/

6: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5647921/

Covid19 – the final nail in coffin of medical research

28th June 2021

“The lamps are going out all over Europe, we shall not see them lit again in our life-time.” Edward Grey

Several years ago, I wrote a book called Doctoring Data. It was my attempt to help people navigate their way through medical headlines and medical data.

One of the main reasons I was stimulated to write it, is because I had become deeply concerned that science, especially medical science, had been almost fully taken over by commercial interests. With the end result that much of the data we were getting bombarded with was enormously biased, and thus corrupted. I wanted to show how some of this bias gets built in.

I was not alone in my concerns. As far back as 2005, John Ioannidis wrote the very highly cited paper ‘Why most Published Research Findings are False’. It has been downloaded and read by many, many, thousands of researchers over the years, so they can’t say they don’t know:

‘Moreover for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias.’1

Marcia Angell, who edited the New England Journal of Medicine for twenty years, wrote the following. It is a quote I have used many times, in many different talks:

‘It is simply no longer possible to believe much of the clinical research that is published, or to rely on the judgement of trusted physicians or authoritative medical guidelines. I take no pleasure in this conclusion, which I reached slowly and reluctantly over my two decades as an editor of the New England Journal of Medicine.’

Peter Gotzsche, who set up the Nordic Cochrane Collaboration, and who was booted out of said Cochrane collaboration for questioning the HPV vaccine (used to prevent cervical cancer) wrote the book. ‘Deadly Medicine and Organised Crime. [How big pharma has corrupted healthcare]’.

The book cover states… ‘The main reason we take so many drugs is that drug companies don’t sell drugs, they sell lies about drugs… virtually everything we know about drugs is what the companies have chosen to tell us and our doctors… if you don’t believe the system is out of control, please e-mail me and explain why drugs are the third leading cause of death.’

Richard Smith edited the British Medical Journal (BMJ) for many years. He now writes a blog, amongst other things. A few years ago, he commented:

‘Twenty years ago this week, the statistician Doug Altman published an editorial in the BMJ arguing that much medical research was of poor quality and misleading. In his editorial entitled ‘The scandal of Poor Medical Research.’ Altman wrote that much research was seriously flawed through the use of inappropriate designs, unrepresentative sample, small sample, incorrect methods of analysis and faulty interpretation… Twenty years later, I feel that things are not better, but worse…

In 2002 I spent eight marvellous weeks in a 15th palazzo in Venice writing a book on medical journals, the major outlets for medical research, and the dismal conclusion that things were badly wrong with journals and the research they published. My confidence that ‘things can only get better’ has largely drained away.’

Essentially, medical research has inexorably turned into an industry. A very lucrative industry. Many medical journals now charge authors thousands of dollars to publish their research. This ensures that it is very difficult for any researcher, not supported by a university, or a pharmaceutical company, to afford to publish anything, unless they are independently wealthy.

The journals then have the cheek to claim copyright, and charge money to anyone who actually wants to read, or download the full paper. Fifty dollars for a few on-line pages! They then bill for reprints, they charge for advertising. Those who had the temerity to write the article get nothing – and nor do the peer reviewers.

It is all very profitable. Last time I looked the Return on Investment (profit) was thirty-five per-cent for the big publishing houses. It was Robert Maxwell who first saw this opportunity for money making.

Driven by financial imperative, the research itself has also, inevitably, become biased. He who pays the paper calls the tune. Pharmaceutical companies, food manufacturers and suchlike. They can certainly afford the publication fees.

In addition to all the financial and peer-review pressure, if you dare swim against the approved mainstream views you will, very often, be ruthlessly attacked. As many people know, I am a critic of the cholesterol hypothesis, along with my band of brothers…we few, we happy few. In the 1970s, Kilmer McCully, who plays double bass in our band, was looking into a cause of cardiovascular disease that went against the mainstream view. This is what happened to him:

‘Thomas N. James, a cardiologist and president of the University of Texas Medical Branch who was also the president of the American Heart Association in 1979 and ’80, is even harsher [regarding the treatment of McCully]. ”It was worse than that – you couldn’t get ideas funded that went in other directions than cholesterol,” he says. ”You were intentionally discouraged from pursuing alternative questions. I’ve never dealt with a subject in my life that elicited such an immediate hostile response.

It took two years for McCully to find a new research job. His children were reaching college age; he and his wife refinanced their house and borrowed from her parents. McCully says that his job search developed a pattern: he would hear of an opening, go for interviews and then the process would grind to a stop. Finally, he heard rumors of what he calls ”poison phone calls” from Harvard. ”It smelled to high heaven,” he says.’

McCully says that when he was interviewed on Canadian television after he left Harvard, he received a call from the public-affairs director of Mass. General. ”He told me to shut up,” McCully recalls. ”He said he didn’t want the names of Harvard and Mass. General associated with my theories.’ 2

More recently, I was sent a link to an article outlining the attacks made on another researcher who published a paper which found that being overweight meant having a (slightly) lower risk of death than being of ‘normal weight. This, would never do:

‘A naïve researcher published a scientific article in a respectable journal. She thought her article was straightforward and defensible. It used only publicly available data, and her findings were consistent with much of the literature on the topic. Her coauthors included two distinguished statisticians.

To her surprise her publication was met with unusual attacks from some unexpected sources within the research community. These attacks were by and large not pursued through normal channels of scientific discussion. Her research became the target of an aggressive campaign that included insults, errors, misinformation, social media posts, behind-the-scenes gossip and maneuvers, and complaints to her employer.

The goal appeared to be to undermine and discredit her work. The controversy was something deliberately manufactured, and the attacks primarily consisted of repeated assertions of preconceived opinions. She learned first-hand the antagonism that could be provoked by inconvenient scientific findings. Guidelines and recommendations should be based on objective and unbiased data. Development of public health policy and clinical recommendations is complex and needs to be evidence-based rather than belief-based. This can be challenging when a hot-button topic is involved.’ 3

Those who lead the attacks on her were my very favourite researchers, Walter Willet and Frank Hu. Two eminent researchers from Harvard who I nickname Tweedledum and Tweedledummer. Harvard itself has become an institution, which, along with Oxford University, comes up a lot in tales of bullying and intimidation. Willet and Hu are internationally known for promoting vegetarian and vegan diets. Willet is a key figure in the EAT-Lancet initiative.

Where is science in all this? I feel the need to state, at this point, that I don’t mind attacks on ideas. I like robust debate. Science can only progress through a process of new hypotheses being proposed, being attacked, being refined and strengthened – or obliterated. But what we see now is not science. It is the obliteration of science itself:

‘Anyone who has been a scientist for more than 20 years will realize that there has been a progressive decline in the honesty of communications between scientists, between scientists and their institutions and the outside world.

Yet, real science must be an area where truth is the rule; or else the activity simply stops being scient and becomes something else: Zombie science. Zombie science is a science that is dead, but is artificially keep moving by a continual infusion of funding. From a distance Zombie science looks like the real thing, the surface features of a science are in place – white coats, laboratories, computer programming, PhDs, papers, conferences, prizes etc. But the Zombie is not interested in the pursuit of truth – its citations are externally-controlled and directed at non-scientific goals, and inside the Zombie everything is rotten…

Scientists are usually too careful and clever to risk telling outright lies, but instead they push the envelope of exaggeration, selectivity and distortion as far as possible. And tolerance for this kind of untruthfulness has greatly increased over recent years. So, it is now routine for scientists deliberately to ‘hype’ the significance of their status and performance and ‘spin’ the importance of their research.’ Bruce Charlton: Professor of Theoretical Medicine.

I was already pretty depressed with the direction that medical science was taking. Then COVID19 came along, the distortion and hype became so outrageous that I almost gave up trying to establish what was true, and was just made up nonsense.

For example, I stated, right at the start of the COVID19 pandemic, that vitamin D could be important in protecting against the virus. For having the audacity to say this, I was attacked by the fact checkers. Indeed, anyone promoting vitamin D to reduce the risk of COVID19 infection, was ruthlessly hounded.

 Guess what. Here from 17th June:

‘Hospitalized COVID-19 patients are far more likely to die or to end up in severe or critical condition if they are vitamin D-deficient, Israeli researchers have found.

In a study conducted in a Galilee hospital, 26 percent of vitamin D-deficient coronavirus patients died, while among other patients the figure was at 3%.

“This is a very, very significant discrepancy, which represents a big clue that starting the disease with very low vitamin D leads to increased mortality and more severity,” Dr. Amir Bashkin, endocrinologist and part of the research team, told The Times of Israel.’ 4

I also recommended vitamin C for those already in hospital. Again, I was attacked, as has everyone who has dared to mention COVID19 and vitamin C in the same sentence. Yet, we know that vitamin C is essential for the health and wellbeing of blood vessels, and the endothelial cells that line them. In severe infection the body burns through vitamin C, and people can become ‘scrobutic’ (the name given to severe lack of vitamin C).

Vitamin C is also known to have powerful anti-viral activity. It has been known for years. Here, from an article in 1996:

‘Over the years, it has become well recognized that ascorbate can bolster the natural defense mechanisms of the host and provide protection not only against infectious disease, but also against cancer and other chronic degenerative diseases. The functions involved in ascorbate’s enhancement of host resistance to disease include its biosynthetic (hy-droxylating), antioxidant, and immunostimulatory activities. In addition, ascorbate exerts a direct antiviral action that may confer specific protection against viral disease. The vitamin has been found to inactivate a wide spectrum of viruses as well as suppress viral replication abd expression in infected cell.’ 5

I like quoting research on vitamins from way before COVID19 appeared, where people were simply looking at Vitamin C without the entire medico-industrial complex looking over their shoulder, ready to stamp out anything they don’t like. Despite a mass of evidence that Vitamin C has benefits against viral infection, it is a complete no-go area and no-one even dares to research it now. Facebook removes any content relating to Vitamin C and COVID19.

As of today, any criticism of the mainstream narrative is simply being removed. Those who dare to raise their heads above the parapet, have them chopped off:

‘Dr Francis Christian, practising surgeon and clinical professor of general surgery at the University of Saskatchewan, has been immediately suspended from all teaching and will be permanently removed from his role as of September.

Dr Christian has been a surgeon for more than 20 years and began working in Saskatoon in 2007. He was appointed Director of the Surgical Humanities Program and Director of Quality and Patient Safety in 2018 and co-founded the Surgical Humanities Program. Dr. Christian is also the Editor of the Journal of The Surgical Humanities.

On June 17th Dr Christian released a statement to over 200 of his colleagues, expressing concern over the lack of informed consent involved in Canada’s “Covid19 vaccination” program, especially regarding children.

To be clear, Dr Christian’s position is hardly an extreme one.

He believes the virus is real, he believes in vaccination as a general principle, he believes the elderly and vulnerable may benefit from the Covid “vaccine”… he simply doesn’t agree it should be used on children, and feels parents are not being given enough information for properly informed consent.6

When I wrote Doctoring Data, a few years ago, I included the following thoughts about the increasing censorship and punishment that was already very clearly out in the open:

…where does it end? Well, we know where it ends.

First, they came for the communists, and I didn’t speak out because I wasn’t a communist

Then they came for the socialists, and I didn’t speak out because I wasn’t a socialist

Then they came from the trade unionists, and I didn’t speak out because I wasn’t a trade unionist

Then they came for me, and there was no-one left to speak for me

Do you think this is a massive over-reaction? Do I really believe that we are heading for some form of totalitarian stated, where dissent against the medical ‘experts’ will be punishable by imprisonment? Well, yes, I do. We are already in a situation where doctors who fail to follow the dreaded ‘guidelines’ can be sued, or dragged in front the General Medical Council, and struck of. Thus losing their job and income…

Where next?

The lamps are not just going out all over Europe. They are going out, all over the world.

1: https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020124

2: https://www.nytimes.com/1997/08/10/magazine/the-fall-and-rise-of-kilmer-mccully.html

3: https://www.sciencedirect.com/science/article/pii/S0033062021000670

4: https://www.timesofisrael.com/1-in-4-hospitalized-covid-patients-who-lack-vitamin-d-die-israeli-study

5: https://www.researchgate.net/publication/14383321_Antiviral_and_Immunomodulatory_Activities_of_Ascorbic_Acid 6: https://off-guardian.org/2021/06/25/canadian-surgeon-fired-for-voicing-safety-concerns-over-covid-jabs-for-children/

COVID19, hidden figures and OODA

20th March 2021

What figures about COVID19 do you believe?

Indeed, what figures can you believe?

Do you simply take them all at face value, and work from there? That would certainly be nice, but it’s not really possible, and you would come to some pretty weird conclusions.

For example, I was running through the Worldometer site the other day. Yes, what an exciting life I now lead.  Sitting right on top to each-other, on ‘deaths per million’ of the population were: Singapore, New Zealand and China. They are way down towards the very bottom of the list.

Deaths per million

  • Singapore (188) = 5 deaths per million (total deaths 30)
  • New Zealand (189) = 5 deaths per million (total deaths 26)
  • China (190) = 3 deaths per million (total deaths 4,636)

Just to give you a quick comparison with countries rather closer to the top of that list, where the deaths per million are around four hundred times higher, on average:

Deaths per million

Czechia (3)                                        = 2,206 deaths per million

UK (6)                                                = 1,843 deaths per million

USA (12)                                            = 1,649 deaths per million

Returning to Singapore, New Zealand and China. What do they have in common? From a COVID19 perspective they all locked down pretty hard. At least they say they did. They are all pretty wealthy countries. Apart from that… not much.

On the surface, there is nothing much to get excited, or confused about, yet. However, when you start looking a little more closely, you begin to notice stranger things. For example, if we look at total ‘cases.’

Total COVID19 cases

  • Singapore = 60,121
  • New Zealand = 2,432
  • China = 90,062

So, China with a population of 1.4Bn (One billion, four hundred million) had ninety thousand cases. Singapore with population of just over five and a half million, had sixty thousand cases. Just in case you cannot do the mental arithmetic. Singapore’s population is two hundred and forty-six times smaller than China’s.

Which means that Singapore had two thirds the number of cases in China – resulting in almost the same rate of deaths per million but in a population two hundred and fifty times smaller.

Where does this then take us? It takes us to a place where the case fatality rates are widely different. Not just between China and Singapore, but in all three countries. In fact, these figures are not even in the same ballpark. Not even in the same city. By case fatality rate (CFR) I mean the percentage of people with a clear-cut infection, who then died [terms and conditions apply].

Here are the resultant case fatality rates from the three countries, in order.

Case fatality rates

China                                                 = 5%

New Zealand                                    = 1%

Singapore                                          = 0.05%

Which means that, using the figures provided, the case fatality rate from COVID19 is one hundred times higher in China than in Singapore. Or, to put it another way, you are one hundred times more likely to die if you get COVID19 in China than in Singapore.

On the other hand, you are only twenty times more likely to die in New Zealand than in Singapore. So, should we all rush to Singapore and find out what on earth they can be doing to cure so many people. Or….

Yes, you’re right. These figures simply do not add up. Not even remotely. Medical interventions, sadly, have made very little difference to mortality rates from COVID19. A few percentage points here or there. So that cannot even remotely explain such massive differences.

What is the other explanation? It is, and can only be, that we cannot possibly be comparing like with like. Which, in turn, means that the figures in one, or all of these countries, are so incomplete, biased or wrong, as to be utterly useless.

Are they missing cases, or not counting cases, or defining cases and deaths from COVID19 in completely different ways? Whichever of these is true it doesn’t really matter. The only thing that really matters is that at least two of these three countries are reporting figures that are of absolutely no use to man nor beast. Perhaps all three.

Equally, if you’re planning what do to next in this pandemic, you must have figures that you can trust, otherwise you are simply floundering about in a sea of confusion. What’s the other choice. Delete the statistics from the countries where you simply do not believe them. And where would you start with that?

There is a military strategy called OODA: Observe, Orientate, Decide Act. It was used in the Gulf War, and by Dominic Cummins to achieve victory in the Brexit referendum – so it is claimed. It sounds simple, but it actually becomes complex, quite quickly.

With COVID19 you can observe all you like, and I have done a lot of observing. However, if the data you are looking at are clearly nonsense, it becomes impossible to orientate. Then, in turn, it becomes impossible to decide how to act.

It is why, up to this point, I have mainly contented myself with pointing out that the data that we have been presented with thus far is almost perfectly meaningless. Let’s consider another example. Which is that the gold standard for diagnosis of COVID19 is to use a system known as PCR (polymerase chain reaction). We do not use symptoms, or clinical signs, as has been the case for all other diseases known to humanity over the ages.  A major problem in itself.

Another major problem is we know that if you run PCR test processing for forty-five amplification cycles, the results become entirely meaningless. No-one will officially provide the data on how many cycles are being done. But it does seem that, in the UK at least, many labs were using forty-five cycles.

Now, the numbers of cases are falling, they have reduced PCR processing to thirty cycles. But, who knows?  Perhaps it is because they have reduced PCR to thirty cycles, that the cases have gone down. Or maybe it is the fact that we are using millions of lateral flow tests which has led to the number of positive tests falling. Because you get far fewer positive results with lateral flow kits than PCR.

In addition to that area of confusion and conflict, recorded deaths from COVID19 in the UK are based on having a positive test within twenty-eight days of dying. Yet we know that COVID19 tests can remain positive for months after someone has recovered. So, you can have had a positive test in November, go into hospital in January – for whatever reason – where you will have another test, that has remained positive. You then die of something completely unrelated. You become a COVID19 death statistic. What nonsense.

Even if you truly have COVID19, then die, how do we know if the main cause of death was COVID19, or something else? I have seen terminally ill patients close to death from cancer, or suchlike, who have had a positive swab. They then died, and they became another ‘COVID19 death.’ Really? Is that what killed them?

We do know that at least ninety-five per-cent of people who are recorded as dying of COVID19 had other serious medical conditions. Claiming that COVID19 was the primary/recordable cause of death in all of these cases is just ridiculous. Beyond ridiculous.

Frankly, anyone who asks me to trust in any data about COVID19 is going to have a pretty tough sell. Right now, I feel that there is almost no statistic which has not been wildly bent out of shape to suit the narrative.

At this point, I shall change direction slightly, and point you at the most incomprehensible statistic of all.

It comes from the UK. In this data set, the UK has been split into four countries. England, Northern Ireland, Scotland and Wales. Here, we are looking at the figures on overall mortality – that is deaths from all causes – during the period January 1st, 2017 up until the present day. These data cover the age group of forty-five to sixty-four (I set the graphs to specifically show this age group).

What you would expect to see, I think, is that all four countries that make up the UK should show almost exactly the same pattern of deaths. All four countries are virtually identical in their demographics, life expectancy, and suchlike. All four countries ‘locked down’ in almost exactly the same way, at almost exactly the same times.

Below, are the figures (z-scores/deviation from the mean) on overall mortality. https://www.euromomo.eu/graphs-and-maps#z-scores-by-country

We can see an enormous spike in England in the forty-five to sixty-four age group in Spring 2020, and Autumn/Winter 2021. We observe nothing, or virtually nothing, in the other three countries.

Just in case you are wondering. I do believe in these overall mortality data. If someone is dead, they are dead. It is difficult to misdiagnose or diagnose in any other way. So, these figures represent the real deal.

Observe, orientate, decide, act.

I observe that overall mortality rates went up sharply in England in the spring of 2020 and again in the autumn/winter of 2020/21 in the age group 45-64. I observe that the rates barely moved in Northern Ireland, Scotland or Wales.

Orientate

Something of great significance happened in England, that did not happen in the other three countries. I cannot orientate, because I have absolutely no idea what these figures are telling me.

Orientate

These data, unremarked open by anyone else – as far as I am aware – are trying to tell us something. Something that may well be of absolutely critical importance. These are the figures that we should be using to base our decisions and actions upon. If we could only understand what they were telling us.

There is one other country which has a pattern similar to England’s, and that is Spain.

Nowhere else looks remotely similar. For example, here is Sweden.

Orientate

What have England and Spain got in common? Or, at least, somewhat in common?

Decide

Do not decide anything until you are orientated. In turn, do not act until your decision is made on a good understanding of the environment you are operating in.

Do not decide what to do until you can explain why, for example, China has a case fatality rate that is one hundred times higher than in Singapore.

Equally, you cannot possibly claim to be orientated until you can explain why England, alone of all the countries in the UK, suffered such massive spikes in overall mortality in the forty-five to sixty-four year age groups.

In super-short summary, until you can rely on the figures that are provided from around the world, you cannot claim to be orientated.

Our glorious political leaders have decided that they are, indeed, oriented. Because of this false orientation, they have made decisions and acted. Based upon foundations of, precisely, nothing.

So, what are the odds that they acted in the right way?

Sunbathing is good for you

News announcer: ‘We interrupt the series of blogs on ‘what causes heart disease’ to bring you (slightly delayed), breaking news from Sweden… Sunbathing is good for you. Shock horror etc.’

Someone sent me this news story today, and I thought I should share it with you. For many, many, years I have been telling people that lying in the sun, getting a nice tan, is one of the healthiest things you can do. Despite the howls of anguish from all dermatologists telling us that one photon of sunlight is one photon too many. ‘You will cause people to die from skin cancer.’ Ho hum:

Why do sunbathers live longer than those who avoid the sun?

New research looks into the paradox that women who sunbathe are likely to live longer than those who avoid the sun, even though sunbathers are at an increased risk of developing skin cancer.

An analysis of information on 29,518 Swedish women who were followed for 20 years revealed that longer life expectancy among women with active sun exposure habits was related to a decrease in heart disease and noncancer/non-heart disease deaths, causing the relative contribution of death due to cancer to increase.

Whether the positive effect of sun exposure demonstrated in this observational study is mediated by vitamin D, another mechanism related to UV radiation, or by unmeasured bias cannot be determined. Therefore, additional research is warranted.

“We found smokers in the highest sun exposure group were at a similar risk as non-smokers avoiding sun exposure, indicating avoidance of sun exposure to be a risk factor of the same magnitude as smoking,” said Dr. Pelle Lindqvist, lead author of the Journal of Internal Medicine study. “Guidelines being too restrictive regarding sun exposure may do more harm than good for health.”1

There is a point here I think I should repeat… avoiding the sun is as risky for your overall health and life expectancy, as smoking. Which is pretty damned amazing? It has been estimated that smoking reduces life expectancy by six, on average. Thus, if you sunbathe regularly, it seems you can expect to live six years longer.

If I may indulge myself by quoting from my book ‘Doctoring Data’ on this very topic:

‘How about frightening people to stay out of the sun, or slap on factor 50 cream at the first suspicion that a deadly photon may sneak through 10 layers of protective clothing. Not necessarily a good idea, because without vitamin D synthesis in the skin, from exposure to the sun, there is significant danger that we can become vitamin D deficient, which can lead to all sort of other problems.

Here are just two stand-out facts from a major study in the Annals of Epidemiology entitled ‘Vitamin D for Cancer prevention.’

  • Women with higher solar UVB exposure had only half the incidence of breast cancer as those with lower solar exposure
  • Men with higher residential solar exposure had only half the incidence rate of fatal prostate cancer

To put that in simple English. If you spend longer in the sun, you may be far less likely to die of breast and prostate cancer. But what about the increased risk of dying of skin cancer! I have you cry. Well, what of it. Around 2,000 people a year die of malignant melanoma in the UK each year. It increased sun exposure were to double this figure we would have 2000 more cases.

On the other hand, breast cancer kills around 20,00 a year, as does prostate cancer. If we managed to halve the rate of breast and prostate cancer, we would reduce cancer deaths by 20,000 a year. Which is ten times as great as any potential increase in deaths from malignant melanoma.’

To what I wrote in Doctoring Data, I would further add that sun exposure is the best known way of increasing NO synthesis throughout the body. This protects the endothelium and, as you would expect, lowers blood pressure (the natural way). So, you are far less likely to die from CVD.

What this study highlights, once again (as with all advice on diet), what we are told to do by mainstream medical research, turns out to be actively damaging to health. Will advice on sun exposure now change? There is not the slightest, tiniest, possibility of this happening. Evidence has no impact on the pronouncements of the medical profession (at least not over the average human lifespan).

The only possible change I can see is that, whilst we will continue be hectored to stay out of the sun, at all possible costs, we will be advised to take vitamin D supplementation to make up for lack of sun exposure (even though there is little or no evidence that it actually does any good).

My advice is, and has always been. Sunshine is good for you. I have been saying this for twenty years. Ten years ago, whilst writing for Pulse Magazine in the UK I wrote an article called ‘Sunshine is good for you.’ I finished with the following:

Ponder this

I shall leave you to ponder the results of a study looking at people diagnosed with malignant melanomas, and then followed for five years.

‘Results: Sunburn, high intermittent sun exposure, skin awareness histories and solar elastosis were statistically significantly inversely associated with death from melanoma’

‘Conclusion: Sun exposure is associated with increased survival from melanoma.2

Did I say that sunshine is good for you? It even prevents malignant melanoma.

 

REFERENCES:

1: http://www.medicalnewstoday.com/releases/308202.php

The full study is: Avoidance of sun exposure as a risk factor for major causes of death: a competing risk analysis of the Melanoma in Southern Sweden cohort, P. G. Lindqvist, E. Epstein, K. Nielsen, M. Landin-Olsson, C. Ingvar and H. Olsson, Journal of Internal Medicine, doi: 10.1111/joim.12496, published online 16 March 2016.

2: Berwick M et al: Sun exposure and mortality from melanoma. J Natl Cancer Inst: 2005 Feb 2, 973(3):195-9

The Augean Stables – part II

It has become clear that much of medical research is flawed, and so inherently biased that much of it/most of it simply cannot be relied upon. One of the strongest critics of this current situation is a brilliant statistician, Professor John P Ionnadis. His seminal paper on the subject of medical research, which is nearly ten years old now, was entitled ‘Why Most Published Research Findings Are False ‘. I include the abstract here:

‘There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias1.’

Has his work been contradicted by anyone? The answer would be a resounding… no. In fact, all that has happened over the last ten years is more and more confirmation that medical research has become worse.

This is an incredibly worrying situation, yet very few people seem in the slightest bothered. The status quo remains in status. When new medical studies come out the press continue to regurgitate the findings as though they are unquestioned gospel. Experts have maintained their status as demi-gods, to be fawned upon as though their work is beyond any possible reproach.

Guidelines, the ones that instruct doctors on how to treat various conditions, are still published without any provisos. Guidelines which are based on evidence that… ‘may often be simply accurate measures of the prevailing bias.’ But woe betide any doctor that fails to follow said guidelines, for they may well be struck off the medical register. In the US, you could end up in jail.

All of these things are bad enough, and there are many other problems. However, in this blog, I want to focus on another issue. Namely, what about placebo controlled studies? Just to make it clear, for those who know a great deal about this area, I am not looking at the issue of ‘what the hell is in placebos anyway, cos it sure as hell ain’t inert substances.’ Whilst the fact that you cannot find out what manufacturers actually put in placebos, which should be inert ‘sugar pills’, but most certainly are not, is extremely important, that is an issue for another day.

Today’s issue is as follows. We have reached a situation in medical research where it may never be possible to find out if certain treatments actually work. Sub-header… ‘And in which case we are all doomed.

Here is the context. Once a treatment has been found to be superior to a placebo, it will be deemed unethical ever to carry out a placebo controlled study ever again. That may not mean much to many people, so I shall expand – using a concrete example (yes, statins again).

If placebo controlled studies have shown that statins reduce the risk of heart disease, and for the sake of argument let us accept that this is true, where does this leave us? It leaves us in the position whereby, if anyone wanted to set up a study to try and disprove that statins are no better than placebo, they will never be given permission to do so.

Why not? Well, before you are allowed to carry out a clinical study, you have to present it to an ethics committee. This committee will look at the proposal and decide if it is indeed ‘ethical.’ Exactly what this means is up for debate. However, if you decided to study the speed at which cars need to run into children, to result in a fifty per cent mortality rate, I imagine you would be turned down by the ethics committee.

More prosaically, if you have found that statins reduce the risk of dying of heart disease vs placebo, then you will no longer be allowed to do a placebo controlled statin trial ever again. The reason for this is that you have already ‘proved’ that statins are superior to placebo. So it will argued that any volunteer placed in the placebo arm of your study would be suffering avoidable harm. Bong! Ethics committee says no. We know statins work, so it is unethical not to give them.

The only studies the ethics committees will allow would be statins vs. statins and a new drug. Equally you would not be allowed to study a new drug vs. placebo, at least not for an indication where statins had shown a benefit. Because everyone ‘at risk’ should be on a statin already.

Now, I have some sympathy for pharmaceutical companies in this situation. If statins reduced the risk of heart disease by 50% (made up figure), then any new drug can only provide an incremental benefit over statins – there is only 50% possible benefit left. So you need to study more people, over a longer period, to demonstrate superiority over statins. A higher hurdle than statins had to get over to be approved.

In another way, obviously, I have less sympathy. Let us suggest that all of the statin trials were biased. Let us further suggest that statins do not have any benefit over placebo. Is there any evidence for this? Well, the only major non pharmaceutical funded study on statins vs placebo was ALLHAT-LLP. Which was run by the National Institutes for Health (NIH). It was reported thus:

‘Washington, DC – Surprising results of an unblinded but randomized comparison of pravastatin (Pravachol® – Bristol-Myers Squibb) vs “usual care” in patients with hypertension and moderate hypercholesterolemia enrolled in the Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial (ALLHAT-LLT) show that pravastatin did not significantly reduce either all-cause mortality or fatal or nonfatal coronary heart disease (CHD) in these patients.’

So, no benefit at all. This study was immediately attacked by all the ‘experts’ and dismissed as being useless, not enough LDL lowering, not enough difference from standard care blah, blah. Nothing to see here, move along.

However, I find it interesting that the only statin study which was not funded by the pharmaceutical industry was completely negative. You may even believe that this would give people pause for thought. If so, silly you.

Where does this leave us though? Well, as already stated, you can never, ever, do another statin vs placebo study. For it would be unethical to do so. You can never do a cholesterol lowering study on any other drug vs placebo either, for it would be unethical to do so. If the statin trials were all correct and unbiased and without the slightest doubt attached to them….fine. If, however, these trials were simply accurate measures of the prevailing bias then we are completely screwed.

This leaves us in a situation whereby if we test other drugs against statins, we are testing a drug against a drug that we cannot be certain has any benefits at all. So, what can we prove? Nothing. Which means that the very foundations of all future research in this area have been built on a bog.

So, what can we do? Carry on believing that all the research done is correct and above any suspicion of bias and manipulation. If so, fine, but you may have trouble sleeping at night. If not, you are going to have to tear apart all of the research that has been done, and do it again. I think that makes the task of Hercules look pretty easy.

1: http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020124

2: http://www.medscape.com/viewarticle/785851

Statins and cancer

(Ho hum, not again)

A number of people have written to me pointing out an outbreak of mass hysteria in the UK press about statins protecting against cancer. I suspect this hysteria has been repeated around the world. Here are the headlines from the eponymous Daily Mail

Statins slash risk of death by cancer: They slow tumour growth

by up to 50% reveal major studies

Experts say there is ‘overwhelming’ evidence that statins can treat cancer

Study showed they cut death rates for bone cancer patients by 55 per cent

GPs should make patients aware of pills’ new benefits, researchers say

I have been aware of claims that statins protect against cancer for many years. They pop up on a pretty regular basis. I have tended to ignore them on the basis that, anyone who is stupid enough to believe such research, deserves all the statins they can get.

However, such is the overblown hype this time, that I feel the need to rouse myself from my slumber, and explain why this is just complete rubbish. I don’t need to read the original studies to do this. I have read enough of these over the years. I hope this does not sound too arrogant, but I will happily apologise if any single thing I write here proves to be wrong.

Not randomised controlled studies

The studies quoted will not have been randomised and controlled. By which I mean they did not take, say, forty thousand people and split them into two, randomised, groups. One group to take statins the other to take a placebo. Then wait, say, five years to see what difference there was.

These studies will have been observational. By which I mean you look at people taking statins and see what happens to them vs. people who do not take statins. Such studies can show associations between two variables. But they cannot prove causality. (They cannot provide ‘overwhelming’ evidence of anything either). This is basic science, page one, paragraph one.

Just to provide one example of this. In 1987 a major observational study showed that women taking HRT had a more than forty per cent reduction in heart disease. At which point it was recommended that women took HRT to protect themselves against heart disease. This was, in fact, written into the guidelines of the American College of Physicians. To fail to prescribe HRT was considered medical malpractice in the USA.1

Some years later came the Women’s Health Initiative (WHI) study. The first randomised primary prevention trial to use HRT, and 17,000 women were involved.

‘Analysis of hazard ratios showed that after 5.2 years, there was a 29% increase in coronary heart disease risk, including an 18% risk of coronary heart disease mortality and a 32% increase risk of nonfatal myocardial infarction. There was a 20% increase in risk of fatal stroke and 50% increase in the risk of non fatal stroke in women assigned to HRT.2

So, a 42% reduction in heart disease turned into a 18% risk of dying of heart disease. In short, observational studies are hopelessly unreliable and often turn out to be complete nonsense. And there is a specific reason why I know these statins studies will be complete rubbish, which I will get to.

Relative not absolute risk

Once again, in these studies, we run into the distorting use of relative, not absolute risk. A fifty per cent reduction in risk can mean something, or nothing very much. It depends what the underlying risk was in the first place. In my book Doctoring Data I covered the use/misuse of relative risk in some depth.

Let us just say that if your underling risk of dying in the next five years is 50%, reducing that risk by 50% is a big deal. If the risk of dying in the next five years is 0.1%, then reducing that risk by 50% is five hundred times less of a big deal.

As for slowing tumour growth by 50%. Well, that could mean almost anything. Did you reduce tumour growth by 1%, 50% or some other number. And does reducing tumour growth actually reduce the risk of dying? Of course, you will always find some super rare cancer e.g. bone cancer, where death rates are cut by 55%.

I would imagine this meant about three deaths verses seven in bone cancer. Basically, however small the absolute figures can be to get to a relative risk reduction of 55%. I would guess there will be no statistical significance figure attached to this reduction. Many questions, almost none of them well be answered, you will find.

The elephant in the room (raised cholesterol protects against cancer)

Here, however, is the big issue. People with higher cholesterol levels are far less likely to die of cancer. Add this to the fact that people with higher cholesterol levels are far more likely be prescribed statins, and you start off with the most gigantic built in bias that it is possible to find.

In 1992 (before statins were being prescribed to more than a select few) a conference was held to look at low blood cholesterol and associations with mortality3. Going back this far in time is important. After this, statin prescribing makes it very difficult to disentangle those with naturally low, or high, cholesterol levels vs. those who were taking statins.

All the major studies of the time were reviewed, with nearly one million participants. As you can see from my little graph, reproduced from the figures in the paper, as cholesterol levels rise, the risk of cancer falls. For women, if your cholesterol level is below four, the risk of dying of cancer is 38% higher than if your cholesterol level is above 6.2mmol/l. In men we are looking at a 27% greater risk with low cholesterol levels. {See chart)

CL-vs-CR

Thus any observational study on lowering cholesterol with statins starts off with a massive inbuilt bias in the two populations. You are looking at one group of people who have a much lower risk of cancer to start with, then giving them statins, then declaring that statins protect against cancer….. just the most absolute unscientific codswallop.

As final warning. Be careful about lowering cholesterol too far. A very large Japanese study (that you will never have heard of, because it was not very supportive of statins) looked at prescribing statins to over forty seven thousand people over six years. As they found:

‘The patients with an exceptionally low TC (total cholesterol) concentration, the so-called ‘hyper-responders’ to simvastatin, had a higher relative risk of death from malignancy than in the other patient groups.’4

In fact, the rate of death from cancer in those whose cholesterol fell the most dramatically was increased by three hundred and thirty per cent (relative risk, apologies for doing this, but I do not know the absolute risk). The authors added this warning:

‘Further analysis is necessary to elucidate why the hyper-responders had an increased risk of death; their baseline characteristics will be described and discussed in detail in the future. Nevertheless, the health of patients who show a remarkable decrease in TC or LDL-C concentration with low-dose statin therapy should be monitored closely.’

Can I return to my slumbers on this issue now?

 

References

1: American College of Phyisicians. Guidelines for Counselling Post-Menopausal Women about Preventative Hormone Therapy. Ann Intern Med. 117:1038-41. (1992)

2: Writing group for the Women’s Health Initiative Investigators. ‘Risks and benefits of oestrogen plus progestin in healthy postmenopausal women. Principal results from the Women’s Health Initiative Randomized controlled Trials’ JAMA (2002)

3: Jabobs et al: Conference on Low Blood Cholesterol and Mortality: Circulation Vol 86, No 3 September 1992

4: Matsuzaki M et al: Large Scale Cohort Study of the Relationship Between Serum Cholesterol Concentration and Coronary Events With Low-Dose Simvastatin Therapy in Japanese Patients With Hypercholesterolemia Primary Prevention Cohort Study of the Japan Lipid Intervention Trial (J-LIT). Circ J 2002; 66: 1087 –1095

The dog that did not bark in the night

Some of you may have noticed this study, others may not. The amazing ‘wonderdrug’ trial proving that cholesterol lowering drugs have unparalleled benefits on preventing stroke. Here is just one headline from the Daily Express. A major newspaper in the UK.

Statins slash stroke risk by 30 per cent: Millions more should be given drug, say experts

New research has found that the wonderdrugs – which include statins and fibrates – can slash the risk of suffering a stroke by a third in the elderly. And experts now say there is clear evidence that even among the over-75s – a group not routinely prescribed statins – people can benefit from the life-saving drugs.

It is yet more evidence that the cholesterol-lowering drugs are lifesavers and that their benefits outweigh the potential side effects. Lead researcher Christophe Tzourio, Professor of Epidemiology at the University of Bordeaux and Inserm, said: “A one third reduction in stroke risk, if confirmed, could have an important effect on public health.”1

And so on and so forth.

Colleagues of mine love to wave articles like this at me with a triumphant smirk. ‘Seems you’re wrong about cholesterol lowering after all.’ What do you say to that? Eh..’ I usually ask them if they actually read the study. ‘Primary prevention with lipid lowering drugs and long term risk of vascular events in older people: population based cohort study.’2 I ask them this question, but I know that they’ve not. I find it rare to come across a doctor who would ever deign do such a thing as read a scientific paper.

However, when studies like this come out, I do feel the need to raise my enthusiasm to a sufficient level to have a peek at the paper. In this case it was rather easy. This paper was published in the British Medical Journal (BMJ), and I get it delivered to me every week by post. What a quaint thing, actual physical reading material.

My first problem, before I even started reading this study, is that I knew beforehand that a raised cholesterol level is not a risk factor for stroke. Never has been, not anywhere, not in any study I have read. Whilst you can find studies claiming that a raised cholesterol level (LDL) is a risk factor for heart disease [ and you can find others that show the opposite], I have yet to find any study demonstrating any association between raised cholesterol and stroke.

Here, for example, is a short extract from one massive study, the biggest, which looked at four hundred and fifty thousand people over seven million years of observation. It was published in the Lancet:

‘The associations of blood cholesterol and diastolic blood pressure with subsequent stroke rates were investigated by review of 45 prospective observational cohorts involving 450 000 individuals with 5-30 years of follow-up (mean 16 years, total 7·3 million person-years of observation), during which 13 397 participants were recorded as having had a stroke.

Most of these were fatal strokes in studies that recorded only mortality and not incidence, but about one-quarter were from studies that recorded both fatal and non-fatal strokes. After standardisation for age, there was no association between blood cholesterol and stroke except, perhaps, in those under 45 years of age when screened. This lack of association was not influenced by adjustment for sex, diastolic blood pressure, history of coronary heart disease, or ethnicity (Asian or non-Asian).3 [My bold].

Now, if you are unable to find an association between cholesterol levels and stroke in seven point three million years of observation then, you know what, it just ain’t there. In fact, I challenge anyone reading this blog to provide any evidence that cholesterol levels are associated with overall stroke risk. Gulp, that makes me hostage to fortune.

This is why stroke associations struggle when they talk about cholesterol and stroke. They seem desperate to say that raised cholesterol levels cause stroke, but just can’t. Here is how the National Stroke Association fudges the issue.

‘High cholesterol may raise your risk for stroke by increasing your risk for heart disease, a stroke risk factor.4

Whilst it is, of course, true that having heart disease does increase your risk of stroke, and vice-versa, the rest of this statement reveals a yawning gap in logic [For the sake of this argument, let us assume it is true that a raised cholesterol causes heart disease].

A (raised cholesterol) → B (heart disease) →C (Stroke)

A does not → C

Question. If A does not lead to C, how does A lead to B, then leading to C? I shall ask for this to become a question in the Oxford and Harvard entrance exams.

[BTW, if you can work this one out, then please feel free to let me know how it works. Exactly.]

Anyway. We find a study demonstrating that two cholesterol lowering drugs, in this case statins and fibrates, significantly reduce the risk of stroke. But a raised cholesterol level is not a risk factor for stroke. Which means that there can be no possibility that the benefit seen can have been due to cholesterol lowering? That, my friends, is simple logic. No need for Oxford and Harvard to get involved at all. This could be discussed on entrance to kindergarten.

Now, just to add to my short analysis this study I would like to draw your attention to something not remarked upon by the popular press at all. However, I thought that you may find it interesting. It was the following statement from the paper:

‘We found no association between lipid lowering drug use and coronary heart disease (hazard ratio 1.12, 0.90 to 1.40).’ [For those who hate figures/confidence intervals, sorry, I left them in for those who like them].

This was the dog that did not bark in the night.

In summary, here we have a study showing that cholesterol lowering reduced the risk of stroke, when a raised cholesterol level is not a risk factor for stroke. On the other hand, it failed to show any benefit on reducing the risk of heart disease. Some would consider that a study such as this raises more questions than answers. However, with wearisome inevitability, it has been twisted around to provide further proof that everyone should be taking statins. Sigh.

1:              http://www.express.co.uk/news/uk/578174/Statins-stroke-experts

2:              Alperovitch et al: BMJ 25 May 2015 pp12.

3:              Cholesterol, diastolic blood pressure, and stroke: 13 000 strokes in 450 000 people in 45 prospective cohorts The Lancet Volume 346, Issues 8991–8992, 30 December 1995, Pages 1647–1653

4:              http://www.stroke.org/stroke-resources/resource-library/cholesterol-and-stroke

Doctoring Data

I am pleased to announce that my book is finally written and edited and available to buy, on-line at http://doctoringdata.co.uk

The full, formal launch will not be until next year. But for those who cannot wait (hopefully several hundred million people), you can pre-order it now on a restricted print run. First come, first served as they say.

It has been a mighty effort to write, and I hope that people can both enjoy reading it, and feel that they have learned something by so doing. I am but your humble servant.

What is T?

Some questions puzzle me, and I search for the answer. For a number of years I am trying to establish. ‘What is T?’ My wife helpfully remarked that it is a drink with jam and bread. Ho, ho.

Moving swiftly on. My question relates to the concept of Number Needed to Treat (NNT). The NNT is a figure widely used in medicine as an outcome measure. It means how many people do you need to treat ‘T’ to achieve a benefit of some kind. The benefit can be many different things, for example: pain relief, curing a chest infection, improving pain and mobility following a hip replacement.

In these cases the ‘T’ is pretty clear cut. You have a medical problem and you intervene in some way to make it better, or cure it. But what is the ‘T’ when you are in the world of preventative medicine? If you are trying to stop something happening e.g. a heart attack, stroke, pulmonary embolism, or death, can you call preventing such things a form of ‘treatment?’

In reality, in preventative medicine, the ‘T’ turns into something else. It has become ‘P’, as in prevent. But treating and preventing are not the same thing, and you can’t use them interchangeably.

If you have a chest infection and I give you antibiotics then I have, in most cases, treated the infection. On the other hand, if you have a high blood pressure and I ‘treat’ it, all I have done is the lower the blood pressure. I have not immediately done anything else. A high blood pressure causes no symptoms, and there is nothing to be treated – other than future risk.

In fact, if lowering the blood pressure were a form of treatment, the NNT would be very nearly one, in that I will lower the blood pressure in almost every case where I prescribe a drug. But the NNT does not refer to the effect on blood pressure lowering; it refers to the number of people you need to treat to prevent, say, a stroke, by lowering the blood pressure.

As I hope is clear, in preventative medicine, the NNT should really be the NNP.

So what, you may think. Everyone working in this area knows that the NNT is really an NNP. You just need to know that when we use the term NNT, we are really talking about the number needed to treat to ‘prevent’ an event. Yes, this is true. However, the underlying problem with nomenclature does not disappear if we change NNT to NNP. The focus simply shifts to the word prevent itself. To prevent something means to stop it happening – forever.

Now, let us imagine death.

Can we prevent death? No, clearly we cannot. We do not make people immortal by lowering their blood pressure. All we can do, the very best we can possibly do, is to increase life expectancy – by some amount. Which means that prevention does not actually mean prevention. When we look at death as an outcome, prevention can only mean life extension. Or, turning this the other way round, the amount of time by which we delay something from happening.

At this point, I hope it has become clear that ‘T’ in preventative medicine has almost nothing to do with ‘treating.’ We treat nothing, we prevent nothing, we simply delay. At least that is all we can do with death. It is possible that we may prevent things such as non-fatal strokes, although we don’t really know, because we do not usually follow people up for long enough to be certain.

Why is this important? It is important for the following reason. When many clinical trials finish, and there is a difference in the number of deaths between the treatment and placebo arm, it is claimed that the difference represents lives that have ‘been saved.’ Which is another way of saying that death has been prevented which is, in turn, a different way of saying that death has been treated. NNT.

To give an example of how this work in real life I shall switch to statins and the Heart Protection Study (HPS)

Heart Protection Study
HPS1

This graph shows the ‘mortality’ curves for the statin and placebo arms. At the start of the trial everyone is alive, 100% in both groups. Five years later, the end of the study, 92.6% of those in the statin arm were still alive, and 90.8% of those in the placebo arm were still alive. A difference of 1.8%.

This was presented, in the HPS press-release, as follows:

‘In this trial, 10 thousand people were on a statin. If now, an extra 10 million high-risk people worldwide go onto statin treatment, this would save about 50,000 lives each year – that’s a thousand a week.’ http://www.ctsu.ox.ac.uk/~hps/pr.shtml
This is a very clear statement. Treat ten million people, and you will save 50,000 lives per week. But are these lives actually saved. No, of course not. Below, I have re-drawn the graph and extended both ‘survival’ lines by a year. We now have a year six.

HPS2

As I hope is clear, by year six, if we assume the lines continue along their previous trajectory, every single extra person who was alive in the statin arm, compared to the placebo arm, is now dead. Thus 1.8% of people did not have their lives ‘saved’. In fact, the average increase in survival time for these 1.8% was approximately six months. [Half of the 1.8% would have died after six months, which give you the mean/average].

So what is ‘T’ in this case. It is certainly not treatment, prevention, or number needed to treat to prevent death. Nor is it 1.8% of lives saved. It is a life extension of six months, for 1.8%.

Or, to put this another way. If you treat one hundred people at very high risk of heart disease (secondary prevention) with statins, what you are achieving is the following:

• 1.8 will live, on average, an extra 6 months.
• 98.2 will gain no benefit

What is ‘T?’ What indeed. Not perhaps what you first thought. T, at present, is taken to mean treatment. With preventative medicine treatment is taken to mean prevention, and prevention is taken to mean lives saved. But you cannot save a life, all you can do is extend life.

So, when someone says….

‘In this trial, 10 thousand people were on a statin. If now, an extra 10 million high-risk people worldwide go onto statin treatment, this would save about 50,000 lives each year – that’s a thousand a week.’

…they are talking nonsense.

In very short summary. NNT is a widely used treatment outcome, and it guides both clinical and economic decisions on what drugs should be used, or not used. It is a pity that in preventative medicine, NNT is meaningless, because ‘T’ has no value attached to it. Indeed, it might as well be a drink with jam and bread.

Can we believe any medical research – at all?

I have now finished my book, to be called ‘Doctoring Data.’ It has taken a long time to write, mainly because I had to bring together hundreds of different strands of thinking and research. Each strand seemed to get longer and longer as I attempted to pursue them to the end. In many cases I never really found the end.

Some ideas just keep stretching away forever and I had to give up, or else the book would have become a million pages long. And I was told three hundred and ten was to be my limit – or something like that. As if my genius could be contained to a mere hundred thousand words, or so.

Anyway, the main purpose of the book was to look at medical research and data, and try to make some sense of it for those who are interested in looking beyond a medical headline. The book was, at least in part, inspired by a paper written by John Ionnadis.

It was entitled ‘Why most published research findings are false.’ You can easily find it on the internet by searching the title. It is currently the most downloaded paper in recent medical scientific literature

The shortest summary of his paper is, as follows:

Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias.’ J Ionnadis.

How can it be, you may think, that most published research is false? Surely research is the one area of human endeavour where bias and dogma are ruthlessly hunted down and destroyed. A scientific finding is a scientific finding….is it not? Did Francis Bacon die in vain?

As Dogbert might say. Hahahahahahahahahahaha!

Or you might be best to pay attention to the quote from Friedrich Nietzsche. ‘There are no facts, only interpretations.’ Of course, he was a bit bonkers, but there is an awful lot of truth to what he said. Especially in medical research. Facts are the most tricky little blighters to get hold of. Interpretation, however, that is stated as fact all over the place

Surely, though, we have ways to ensure that research is pure and objective, such as peer-review. A system of using respected ‘experts’ to check and approve papers before publication. This will weed out papers that are flawed, will it not. Well, here is what Richard Horton (editor of the Lancet) has to say on peer-review:

The mistake, of course, is to have thought that peer review was any more than a crude means of discovering the acceptability — not the validity — of a new finding. Editors and scientists alike insist on the pivotal importance of peer review. We portray peer review to the public as a quasi-sacred process that helps to make science our most objective truth teller. But we know that the system of peer review is biased, unjust, unaccountable, incomplete, easily fixed, often insulting, usually ignorant, occasionally foolish, and frequently wrong.’

There we are, nice and reassuring to know that peer-review is such a fabulous system. As for the quality of published research itself, here is one of my favourite quotes by Drummond Rennie, at the time the Deputy Editor of the Journal of the American Medical Association.:

‘There seems to be no study too fragmented, no hypothesis too trivial, no literature citation too biased or too egotistical, no design too warped, no methodology too bungled, no presentation of results too inaccurate, too obscure, and too contradictory, no analysis too selfserving, no argument too circular, no conclusions too trifling or too unjustified, and no grammar and syntax too offensive for a paper to end up in print.’

A view supported from a slightly different angle by Dr Marcia Agnell, who was the editor of the New England Journal of Medicine for two decades. This was, and remains, the single most powerful and influential medical journal in the world. At least it is, when it comes to citations and impact factor:

“It is simply no longer possible to believe much of the clinical research that is published, or to rely on the judgment of trusted physicians or authoritative medical guidelines. I take no pleasure in this conclusion, which I reached slowly and reluctantly over my two decades as an editor of The New England Journal of Medicine.” Dr Marcia Agnell

Here is a further view on the issue by Richard Smith, editor of the BMJ for many years. He wrote this in his blog:

Twenty years ago this week the statistician Doug Altman published an editorial in the BMJ arguing that much medical research was of poor quality and misleading. In his editorial entitled, “The Scandal of Poor Medical Research,” Altman wrote that much research was “seriously flawed through the use of inappropriate designs, unrepresentative samples, small samples, incorrect methods of analysis, and faulty interpretation.” Twenty years later I fear that things are not better but worse…

…The poor quality of much medical research is widely acknowledged,” wrote Altman, “yet disturbingly the leaders of the medical profession seem only minimally concerned about the problem and make no apparent efforts to find a solution.”

Altman’s conclusion was: “We need less research, better research, and research done for the right reasons. Abandoning using the number of publications as a measure of ability would be a start.”

Sadly, the BMJ could publish this editorial almost unchanged again this week. Small changes might be that ethics committees are now better equipped to detect scientific weakness and more journals employ statisticians. These quality assurance methods don’t, however, seem to be working as much of what is published continues to be misleading and of low quality. Indeed, we now understand that the problem doesn’t arise from amateurs dabbling in research but rather from career researchers.’

So, Ionnadis states that most research findings may often be simply accurate measures of the prevailing bias. Current and past editors of the three most respected and powerful medical journals in the world confirm that medical research is warped, biased and flawed and, in many cases simply not believable.

Would this be very evidence used by NICE* to tell us which drugs to use – for example. Why, yes it would be. So be afraid, be very afraid. For an idiotic politician (sorry for the tautology) recently made this announcement1.

‘A Labour government could reduce variation in access to drugs and procedures by making it mandatory for commissioners to follow national clinical guidelines, Andy Burnham has revealed.’ Andy Burnham was, at one time Secretary of State for Health. His is now shadow secretary of state for health. So, if the UK votes for Labour, it will mandatory for all doctors to follow the guidelines based on the evidence that comes from clinical trials.

Oh Joy.

*NICE stands for the National Institute for Care and Health Excellence. It is supposed to review all evidence for various healthcare areas and decree what is best practice. What NICE says tends to get taken up in many, many, other countries as their views are widely respected and acted upon.

1: http://www.hsj.co.uk/news/exclusive-labour-could-make-nice-guidance-mandatory/5076286.article