Hi, everybody. For those I know some of you, but for those of you, I don't know.
My name is Carl Hennigan. I am professor of evidence based medicine and director of the Centre for Evidence based Medicine.
And welcome to many of you to the MFC course.
The title of this talk is What is evidence based medicine done for Health Care?
Well, let's talk through this. It's a sort of illustration.
We often forget about some of the historical perspective of evidence based medicine and how the evidence evolved and what that means.
And so I'm going to particularly just focus on the idea of heart attack.
And you've had a busy day today. Question formulation.
What an abstract thinking about some of the issue searching. And then tomorrow are you going to look at some treatment effects?
So some of this will be really relevant to that. Just to move on to a couple of things.
If you go to the CBM site, I want to do talks now and we're all going to do this.
If you go that there's a blog site and on the blog site here, you can see there's a particular one there.
What has been done for health care? And if you go to that site,
I've actually posted this talk with a summary of the talk and a downloadable PDF of the talk so you
can pull it all off and afterwards and think when you've got nothing to do later on this evening,
you can have a bit of bed night reading and think, Wow, that's fantastic.
Not only that, if you go to the blog at the end of the blog, I you can leave a response or comment.
So at the end of this, we're going to talk about some of the issues, maybe 20 minutes.
We're going to think about just some of the issues. So this talk, basically, I'm going to just take you through this is a timeline from about 1960,
1970, but actually some bits of it go back hundreds of years.
And when you start to think about something just as simple as a heart attack, there are loads of really interesting points in there.
This is the first report in The Lancet. The thrombotic properties of aspirin was published in 6774 with the first ever aspirin trial.
You can move forward here. Editorial by Richard Peto.
I'm going to talk about that. In the 1980s, the in-hospital mortality of a heart attack with about 13% and there's been a whole raft of publication,
31 randomised trials of aspirin there in 1988,
six years later, 145 trials and then moving through,
there's been a raft of evidence carrying on again that brings you right up to date where you can come through.
And I'm going to touch on all of these ACE inhibitors or little bit of beta blockers and some really interesting stuff that's happening right now,
like the use of oxygen in heart attack and the use of adrenaline in clinical a clinical trial that's going on now.
So this actually gives a whole structure when people say to me for many new treatments, what should the evidence base for?
A heart attack is actually almost a seminal understanding of ebben.
So let's move on. First ever trial aspirin, 1974.
It's not that long ago, is it? Only 40 years ago, indeed.
And this is by Peter Ellwood here, published in the British Medical Journal,
a randomised trial of acetyl salicylic acid in the secondary prevention of mortality from me.
But interestingly when you do look at the timeline of aspirin that the first trial of aspirin 1996 FDA approves aspirin for use in suspected I.
That is not that long ago is it. But if you do go back well what was happening if you go right back in time to about 1758,
you get this chap called Reverend Edmund Stone, who was a fellow down here at Wadham.
He found out about the bark of a willow tree in his report in 1763 of the many youthful discoveries
and down here I have found by experience to be a powerful astringent and very efficacious,
incurring anguish and intermittent disorders that fever, I think, you know, language.
But all of that basic sciences for 200 plus years were set on this discovery, and it took till 1974 to move forward to clinical trials.
And when you look at it, it's actually about here.
This is in Mississippi in about 1950s, the first reports of observational studies that were starting to say,
actually, we've got people on aspirin, they don't seem to have a heart attack.
And then beyond that, about 1967 started to see reports about the platelet aggregation effect.
And particularly some of these effects were not aggregated.
Normally, when this is put here, the bleeding tendency after aspirin ingestion that the drug may have anti drop from both properties.
So we're in the sixties now people going we're doing the basic science 200 years after the drug
discovery and then other said we moved to this trial and this was very profound at its time.
And interestingly, if you look at this trial, it's an interesting one.
If you move just a few years later, this is the first trial here, MRC one trial, 1974,
randomised 1239 patients and many of you tomorrow will have heard of the Cochrane Library.
And here's a slide that Peter Elwood and Archie Cochrane you.
The take round, didn't have Internet in them days, didn't have Twitter, didn't have all the TV.
So this was their slide for the dissemination at meetings about the effects of aspirin
when they have a whole bunch of doctors trying to disseminate clinical trial planning.
And what you can see that is they're proposing the thick first trial, all six trials had 10,859 patients.
And the weighted overall effect of aspirin with a 23% reduction in all cause mortality and the P values 0.001.
So that was their way of saying and if you think about it, this is really before Cochrane Cochrane came about six,
15 years later, in effect in thinking this is the start of why we need meta analysis, why we need six systematic reviews.
And moving on, I'm just going to put this up because at the time, Richard Peto,
who's here in Oxford, published an editorial in the month in The Lancet.
And Jeff nodding there, because Jeff has probably read The Lancet in 1980, but most people in this room did not read The Lancet.
I was still at school from a book, but actually he put this and said, Oh, this is a really important stuff.
Large trial. Putting them together gives you a systematic effect, how you look at treatment effect.
And importantly, if you take Richard Pinto's work, what he did is eight years later,
then publish the overview of 51 trials in patients with a history of a stroke, unstable angina or prior asthma.
And this is antiplatelet trials collaboration.
He still exists today in Oxford and still work out the clinical trial for this unit.
Really interesting and so published in the BMJ.
And when you look at this, it's really interesting. If you take these articles, these old articles, boy, can you learn a lot.
And if you look in the first point, two main purposes overview.
They include far large number of patients and individual trials do and hence your results
that are far less subject to randomised error compared to the single trial alone.
Now that's an incredibly important issue when you think about some of the trials today that come out with one single trial,
maybe manufactured, funded, maybe very small in nature.
And what are you saying that if you do that you get a lot of random error around that result?
That might become a bit more obviously tomorrow, but over a lifetime of evidence based medicine,
this random error is really important when we sit there and go, Oh, this could be false with positive finding.
The second issue is No, actually, well, I'll read this out.
They are about the substantial systematic bias that may be engendered when dozens of related trials
have been conducted and just a few become well known for trials may tend to become well known,
partly because their results are unusually promising or unusually unpromising.
And that issue is quite interesting. We would call this today if you take away the public, it's like publication bias in effect.
But I consider this is in the olden days before the Internet area, there was a real marketing and bias towards positive results.
So not quite publication both, but had the same effect with publication both.
And that's a really interesting issue that we still suffer with today is about half of all trials go unpublished.
There was not as many trials as it was then in about the seventies.
It was probably a couple of thousand trials each year. Now we're talking about 40,000 trials each year.
So if you take them results, you'll see tomorrow you'll learn about this is a forest plot and here down are all the single trials.
These were the bigger arms of a wider confidence interval, the smaller trials, and these are the bigger trial with a smaller confidence.
And if you follow this down, you start to get this 25% across all trials in all cause mortality.
And that's the forest plot. That's the purpose of systematic reviews, allows you to give rise to a precise estimate.
And moving on from that, I mean, it's really interesting.
There was obviously an explosion in trials of aspirin because in a six year window, we went from 51 trials to 145 trials.
That's a huge amount of trials. Now, if you think about it now, when we looked at drug treatment, we often seen I mean,
we did some work in Tamiflu, which you'll all be aware of is a really important issue.
And it's been a thick seven years in my life. But actually the number of trials in Tamiflu is actually incredibly small.
It's about 14 treatment trials, four or five prophylaxis trials, and in in children's about four clinical trials.
But here you see for a large effect, 545 12 I think there were about three learning points.
And maybe the more one is it was easier to do trials then than it is now.
We've made it much harder to do trials. The regulatory pathway means it's really difficult to get people in clinical trials and it.
Cost a lot of money. So in the old days you would probably think 30 year old days.
It sounds like you've done it 30 years ago. You're probably four.
I'm not quite sure about the effect of this treatment. Maybe I'll set up a trial and do my own trial in my own hospital.
You could probably get ethical approval by the end of the week, set up a simple randomisation system and probably run a trial within a couple of week.
Fair enough. Just a little bit extra, maybe a few a month.
But around the globe, you would be able to do it really simple.
And you would just do a simple test, like flip a coin, maybe a to accept flipping a coin in the order.
I think that's that's one to is the element of replication makes you less uncertain.
In fact, if there's a bias in one or two trials, you will find that out with all the different trials that occur.
And I think that's an important because if you did one large trial with 100,000 people and you had an inherent bias in the design of that trial,
it would systematically affect all of that trial. Whereas if you do a number of independent trials, it's highly unlikely.
For instance, they have one issue within the randomisation.
And then I think my third point is to say having 145 trials and we'll see later allows you
to do lots more interesting subgroup analysis if you can get the individual data to them.
I three point a moving on. So aspirin still remained a really interesting topic I think throughout its lifecycle.
In 2005, an editorial in the BMJ said that everybody over the age of 50.
Not quite there yet but will be soon will have to take an aspirin.
And that's a good idea. Indeed. You know,
and it's interesting and I put this point that whatever comes about is the continual need
to look at some of the issues about what we do and question what we do all the time.
And that's what happened. The aspirin trial is collaboration have now changed their name to Antithrombotic trial.
A collaboration of a mouthful looked at this in the primary and secondary prevention 2009 now.
So this is only a few years ago and asked this question about some of these effects.
And so if you look at the effects in primary and secondary prevention, what happens is if you take, say, for instance,
males over the age of age, 52 and 59, in secondary prevention, you get this vascular death quite a big difference.
But if you look at primary prevention, the difference is only about 0.5 percent.
The absolute the difference. You could still do a relative effect and you still see that's great in the 10%.
So relative looks okay but is offset by this increase in GI bleed.
So any small reduction is offset by the increase in gastrointestinal bleeds and that's exactly the outcome.
So we do not recommend aspirin in primary prevention.
Ten years ago we were going to give it everyone. But because of this difference between primary and secondary effect, absolute effect, not relative.
It's a really important issue to understand. When you look at absolute and at the baseline, risk comes lower.
You often get this problem.
We could turn and say, that's exactly the same issue we're now looking at with cholesterol lowering advice that we've had in the UK.
What we want to do with lower the risk which will give treatment.
And people are probably thinking, well, haven't we been there before to aspirin?
The really interesting. Okay, I'm going to move on now. Aspirin is a quick tool.
Here's another one. And I want you to think of as I'm talking.
Imagine if we didn't have any evidence based medicine and we just decided we were going to do treatment based on our own observations,
our own experiential learning, because that's what we did feel about the seventies, in effect, because with no clinical trial,
you come in with your heart attack and I might make a decision probably up until about 1982.
I'm just going to treat you as I think my peers would treat you.
So think, although I wonder what it would look like the world if we didn't have an IBM approach.
So this is a book by Thomas Moore Why tens of Thousands of Heart Patients Died in America's Worst Drug Disaster.
Very good book.
You can buy it for a few pounds, about £7 on Amazon, although every time I recommend it, the price goes up for a few weeks and then it comes down.
You will have heard of the case trial,
the really interesting trial in effect because of what it revealed in terms of excess mortality for these drugs.
Antiarrhythmic And if you look at it, it's really profound.
You could argue that this trial started the whole of the evidence based medicine ideology,
because observation said that clinicians use this drug because it stopped the arrhythmias in the heart,
the electrical conduction problems that come after heart attack because they've killed a bit heart, they can be seen an EKG.
These are you stop them. They leave me. But unfortunately, some people literally drop dead.
And when you look at it, at least a decade before the initiation of KAUST,
it was recognised that these had an increased risk of subsequent arrhythmic death as compared with patients without these arrhythmias.
But that recognition was based on observational data and we continue I continue to get this in.
There's a real mantra around now that we should use big data and observational data to inform treatment effect.
And that's a big, interesting issue actually. But actually this should warn you off immediately if you go this is a bit of a bad news.
So for about ten years, people use these treatments widespread until the trial was published.
And this is a preliminary report in 89 in the New England Journal of Medicine, which clearly shows whether the therapy is you should not use.
We conclude that neither Encalade nor Fleck and I should be using the treatment for patients
with asymptomatic or minimally symptomatic ventricular arrhythmia after myocardial infarction.
Even though these drugs may be effective initially in suppressing ventricular arrhythmia.
Ten years. Lots of death. More death. On that treatment then I killed in the whole of the Vietnam War.
And that's what the book, Thomas Moore's book. So I think that's a profound.
Interesting issue about the use of randomised trial evidence versus the use of observation.
And I'll come back to that point. And sometimes statistics is not very difficult.
You don't need the numbers there and this green line is a survival and that's the people on placebo.
And boy, do you wish you were in the placebo group, because you can see it's a dramatic difference.
Very rapid. Okay. Accumulating the evidence.
Here's another one from Blythe. If that's the treatment we've used in in heart attack and we continue to use and
this is a really interesting paper by chaps called Antman and Lao in JAMA in 1992.
You probably see this in the course. Somebody will probably use it at some point, but it's a really interesting piece.
What happened is you had these initial early trials and you can look at the recommendations in textbook reviews.
His 21 not mentioned or not recommended experimental.
And so here but here's the small trials and when you look at them small trials,
what it was basically saying by the 1980s there were 20 very small trials and bleeding could be a side effect.
There were too small to answer the question Does Thrombolysis save lives in patients with heart attack?
And they thought about suggested that the benefit might be about 25 per thousand patients treated.
So actually quite a big benefit, but nobody's using it. Doctors are not convinced.
Nobody use the treatment.
So what happened from there is basically in the next the next few years, what we saw is a massive increase in very large scale trials of this to GC.
And these trials came on board and clearly answered the questions.
And here what you can say is this is a cumulative meta analysis and as you go down the confidence intervals getting smaller by tomorrow,
you should all know this today you might be like, where what we aren't about.
But by here you can see a very narrow confidence interval, 48,000 people in the randomised trial, huge amount of people randomised.
Importantly the textbooks still some not mentioned, some experimental.
It takes quite a long time for textbooks to appear. You can see routine in textbooks and actually that's really interesting.
It's reflected in the evidence base because if you look at the evidence,
both this is in Lancet shows in the Trent region, the uptake of Thrombolysis and there's the GC trial,
the large trial, those are these two still no take takes about another six months to a year and
then we see a dramatic uptake over the next three years of the evidence comes in.
There is a lag. But you know what? One thing of all with being convinced by is that actually clinicians are really good.
When the evidence base is good, they don't need guidelines when the evidence is strong.
Often what we get is guidelines when the evidence is poor, quality, uncertain, and people tell you what to do and we all argue and moan about it.
But actually what we really want is guidelines that say here's really important evidence and actually what we should do.
If you want to get the most benefits out of health care,
we should be doing the things that are evidence based in 100% of the patients all the time optimising treatments that are known to be effective.
And we often don't do that. We discard that. And a good example of that is this paper.
Then moving on is what's called the golden hour. And if you look at the golden hour,
if looking at the Thrombolysis papers and taking that evidence and looking at
the relationship of the time to onset of treatment to that effect on mortality.
And when you do that, you end up with this,
which is called a meta regression and you see the red line absolute benefits per thousand treated start up here about eight.
And if you get down here in a window of treatment delayed by hours, you can see it goes down to less than ten.
That means if you delay treatment by one hour from 0 to 1 to 1 to 2 hours, that will cost you around about 30 lives lost.
The best place to have your heart attack in the whole of the UK is in reading right now and they we still publish a 90 minute target.
We don't publish 60 minute targets.
I don't know why, but if you wanted to save a lot of lives, this is the one intervention that would be amazing to optimise within an hour.
But nobody ever talks about optimising them. And if you did that, you'd have to buy in everybody.
You have to buy in patient because they can't sit around going to got bit of chest pain.
Half an hour later, maybe I'll ring the doctor. You have to buy everybody in the sequence.
Don't you operationalise that and do that really well.
We never talk about doing the things that are on the periphery, but we certainly could push this line back in here in a one hour window.
Okay. We've had primary angioplasty.
I won't touch on that.
But that's sort of in the same issue has replaced the concept of Thrombolysis and the evidence for that has strong 23 randomised trials.
So lots of evidence there. So moving on. Loading lots of evidence again in cholesterol lowering.
When you look at cholesterol, there's a lot of research, actually a very huge amount of evidence here.
The fourth trial, one of the early that's in chronic coronary heart disease.
His Wolfcamp stone in Scotland in primary prevention. And then we've had these yellow ones.
Have we changed the definition? We had to go, oh, my gosh, we've got to start again and do it in acute coronary syndrome.
But a huge amount of trials have been gone, have occurred.
These are the large scale trials. There are many small if you take all the small trials, it's about 135 trials.
Again, these are the ones with over a thousand patients in them.
And here's the fourth trial. That's a 30% relative risk reduction from 11 and a half to 8.2%.
So take that out of 111 and a half to about eight people's lives saved.
And the interesting bit about that is the risk reduction is sustained over the long term,
six years of follow up since randomisation and then not moving on to evidence and
people have not stood still because in the nineties when this evidence come out,
you had to have an elevated cholesterol to be treated after a heart attack.
And Hfpef, which was done here in Oxford, coordinated in Oxford, looked at a different that,
looked at 20,000 people and randomised them to statin or placebo,
but then looked at the baseline cholesterol levels, LDL and looked at the effect across them LDL.
And basically what it showed is irrespective of where you start,
the benefit is consistent and that again change practice radically going from achieve had a heart
fat will measure your cholesterol we know you've had a heart attack actually this is 2002.
We're going to treat you with a cholesterol lowering agent because on average you'll get this 25% reduction in mortality.
So again, evidence radically change practice in the way we thought about it.
And it's interesting nowadays when I teach medical students, we just take this as granted.
This is the way we do these things, don't we? But actually, when you think about it,
what's interesting about this whole talk is actually every single decision is based on really sound evidence and you can move on.
We looked at cholesterol and this is part of the issue now.
They've looked at 90,000 participants in 14 trials and started to look at people primary and secondary prevention.
They're looking at the IPD collaboration. And right now you can look at cholesterol.
The issue with the guidance is now I said let's lower the risk to 10% to give people cholesterol.
What's been the problem? The problem is the people who've done this work in Oxford never collected some of the adverse event data.
So they've got to go back to the drawing board and say, could we have your adverse event data for this individual data collaboration without problem.
If you've got we were looking at this just this afternoon, if you've got a 10% risk.
Well, actually, I looked at my own risk. My own risk in the next ten years came a 5%.
Not that I don't smoke, have not got diabetes to try and keep myself fit.
If I take a cholesterol lowering treatment, I can lower that from 5 to 4%.
But I've got to take the tablet every single day and it didn't quite have all the adverse effect data because my risk of diabetes,
about half a percent. And we can't quantify. The adverse effects in terms of muscle fatigue.
But there is studies out there suggest these equal. But some of this is not reported from these large trials.
It's not been reported. The question we had is at what point and I think this is an important one.
When would you what risk would we as clinicians forget patients, as clinicians or as health professionals?
What risk would you decide that it's important for me to take a treatment?
Because remember, the relative effect stays the same. The absolute effect gets greater and greater as you go up.
So when you get to about 20%, your risk can come down to about 14, 15% of a treatment of an absolute event.
So you get much greater absolute effect. But actually, we haven't even asked ourselves what we would tolerate.
And then we were expected to communicate this with patients. And I'm not sure what we use.
We like these programs and these diagrams, but our patients just want sometimes a simple communication for myself.
I think the field of evidence based communication is right up for grabs.
Now it's really interesting time because the Internet area has made our patients much more knowledgeable.
Okay, beta blockers, another one, really interesting.
We're nearly there now, just through the the bit. You're the beta blockers.
Again, loads of evidence about beta blockers. This is a two in 1999 BMJ paper by Nick Freemantle showing all the absolutely facts.
But what's interesting about beta blockers is actually the first ever paper trial was in 1965 before aspirin.
And this is the effect of propranolol in me in The Lancet.
So actually quite a long time ago. But one of the interesting things about beta blockers is this trial, the comment trial.
So we know beta blockers using this. What was helpful about the comment trial 40,000 people randomised is it clearly showed
that in people with cardiogenic shock or who have any hemodynamic instability,
you should withhold the beta blockers. And actually they're the people who do really badly and consider starting in hospital only when they die.
My condition after me is stabilised so that changed the way we treatment or other evidence also changed the way we think.
We used to not give people with COPD beta blockers, but actually in 1998, trial 201,000 patients with acute MRI.
This is the difference. Actually, they do tolerate beta blockers, so actually we shouldn't withhold and that of the treatment ACE inhibitors.
I was at medical school when we looked at the Hope trial. And if you think I'm a pro player,
an important difference in terms of the relative risk effect and the absolute effect in people with coronary heart disease.
Okay. And finally, clopidogrel. So these are all the treatments and capital is probably a lateral.
This is part of the comment trial. 40,000 people. Very small reduction.
Only a 1% absolute reduction.
So you need an awful lot of people to say with certainty a 9% relative risk is actually only a 100 patients will benefit from clopidogrel.
So you do need a lot of people to understand that size of effect.
Okay. And then this really does interest I mean,
these last two just finishing up this is a Cochrane review on the routine use of oxygen in patients with heart attack.
And when you look at that Cochrane review and this has been in the news, in fact,
actually it looks like if there is about a 25 to 30% more heart damage in patients, not given oxygen is three small trials.
So we're in the same position as you. When you have benefit or harm, you've got random error.
So what we need now is large trials and there are two trials I'm pretty sure going on at the moment.
I haven't checked on trials scope to answer this question, which I think again would profoundly change the way I think about mechanisms,
expert opinion, because when I was in training oxygen with the wonder drug and actually every the wonder drug, it looks like no oxygen.
And you can think about some of the mechanism. And then here's another one.
I got asked about this in the news. Oxford Ambulance Service is accused of playing God and putting life at risk in new drug trial.
Chairwoman of Oxford Health Group patient voice Jackie Pierce said What they are doing is basically playing God by enrolling people into this trial.
I think it's a very worrying trial. I'm highly suspicious when health care services don't publicise trials.
Director of the Oxford based Centre for Evidence based Medicine says there are areas of clinical
practice where the effects of what we do are uncertain and drugs like a generally may cause more death.
And here we're going to A.V in the eighties. I don't know about the case trial, but I did say Cath,
so I must say I heard about the cath and killed more Americans and the number of it died in the Vietnam War.
Actually, just the cast because the team stands for trial.
Yeah. So it's cath trial? Yeah. And finally, though,
his the paramedic to trial is looking at whether a general adrenaline is helpful
or harmful in treatment of cardiac arrest that goes outside of hospital.
The key about this trial is they are randomising the ambulances to adrenaline or not.
So if you have a cardiac arrest at the roadside, you they will be blinded and they won't know what treatment you get so you don't get consented.
And that's a is in terms of like stroke or in certain situations when we've done the crash trials,
when people have had a head injury, that they're out of a completely ethical way to answer questions of uncertainty.
So and lastly, there's a big movement now, which I think this presents an interest in this with just out this year.
This is from the American College of Physicians.
And if you talk to me, the Americans 3 to 5 years ago were coming out with evidence based statements like this.
I would have thought maybe we'd lost the war or something had gone badly wrong.
But what they're saying is we've looked at the evidence and they have understood the principle of overdiagnosis and too much medicine.
And in looking at the evidence, they said there is no evidence that cardiac screening improves patient outcomes in asymptomatic, low risk adults.
The number of false positives is too high. You end up in a treatment cycle.
That's a disaster and it costs a lot of money for no benefits.
And that basically is overdiagnosis. And that's a really important issue that the Americans are grasping.
They do about twice as many diagnostic tests for, say, the UK for no added value, and the cost of that is crippling their health.
So finally, think about the discussion I want to have and we just have five or 10 minutes.
All you might want to think about it and comment. Consider the consequences of a health system without an evidence based approach.
What do you think it would look like if we stripped all of that evidence out?
And then what would the treatment of heart attack look like in an evidence void?
How do you think we would track practice in hospital or when people came out of hospital with all that evidence,
not in front of us and in in place to make treatment decisions.
Thank you for listening. Far off with with a question comment.
Can I hear more about the lipid lowering, your cholesterol lowering?
So you're saying that no matter what,
whenever you start the treatment effect of that with a statin drug is the same that that that it reduces your of the relatives.
Yeah. So the relative effect of a starting is about 30% reduction in mortality.
Relative effect. Right. And so if you start your baseline and that's what they've looked at,
vote for consistently across all the different baselines and said, so if you start at 20% absolute your risk.
And so if you're when I'm about 65 with the same blood pressure, if I don't smoke and if I'll have diabetes, I'll be a 20% baseline risk.
Right? If I then take the statin, I can reduce my risk from about 20 to 14%.
So that's an absolute effective fix for ten years of treatment with a small increase in diabetes and I might get some muscle pain.
The same issue now if I take that stuff in at 5%, a 30% is around about ground in oh four.
If I go to ten, that will come to about seven, maybe just a little bit more.
So that's what the argument is. So the key is for that relative effect.
At some point you say the absolute benefits are so great, I'm going to take the treatment.
Well, if you have a heart attack tomorrow, your risk of another heart that goes immediately beyond 30%.
Right. So you can see beyond 30%. The risk are significant because you come from 30.
That's ten lives, every hundred people treated. So we've gone from a secondary prevention to a primary prevention.
What we don't know, and this is in the discussion, I think if we start to treat a whole wave of population at low risk,
I think we should do the trials again because we don't understand what type of
behaviours they may adopt if they suddenly go well if they came on a statin,
I think I think I'll take up smoking again actually. What's the problem?
The doctor said, I'm going to live forever. I might eat more, I might get diabetic, I might stop exercising.
So we don't know.
You can't just say blinder we would like to say let's just blindly because actually the number of people in them trials were some time ago.
And actually we may be different as the population now in some way and behave differently.
So I think it is crucial that we should still consider doing the clinical trial.
The reason why you get the same percentage reduction no matter where you are is a consequence of the low dose response curve,
which is a basic pharmacological phenomenon. It applies to all drugs.
If you draw the relation between the effect of the compound and the concentration of drug producing and therefore the dose you get,
the thing that looks like that, it's a rectangular hyperbola and it plateaus.
So above a certain dose should get no more thing. If you transform the x axis to have a rhythmic axis, you get a sigmoid curve.
And between 20 and 80% of the maximum effect, that sigmoid curve is approximately linear.
And that tells you that for every unit change in the concentration of the drug, you get the same percentage change.
In effect, the same thing is happening with cholesterol.
To reduce your cholesterol by one, to remove 32,
you reduce your risk of a coronary event or stroke by 10% no matter where you are because it's a logarithmic.
So what you need to do is go and read it.
We have to put that up in the reading list, read the IPD paper because that's all in there,
that transformation, you know, and that's moving on to another level of understanding any of the fourth.
So what do you think? My question to everybody, what do you think would have been different if we would get rid of the beam?
But the evidence from the many of you might have thought about that.
I just don't come from your experience and from the other piece in this room.
What's the percentage of GP's who keep up to date with the latest outcomes from evidence based research?
Yeah. No, that's an interesting what we haven't worked how to keep people up to date in any sense.
I don't actually think you do need to keep up with so many things that we think.
I think there are actually a small number of treatments that we should just optimise and do really well.
And actually we have all these new treatments and new potential.
But actually I think we have to devise a self service that says, actually, we're not going to do this.
This is still uncertain. We're going to hold this back. Our job is to think about the bits of it.
So the problem is, and this is the problem we go into primary prevention is we still know there's about 20% of the
population walking out with a heart attack today who have not got their treatment optimised.
Our public health want to do anybody about that. We haven't got enough time to do anything about that.
And so we just say, let them walk around and do that. And that's what we should be optimising and telling other people until we've done that.
Sorry, we ain't going to your primary prevention and your lower we're going to get the maximum benefit here.
I think the favour the reason I like this story that the failure for many other interventions and treatments to do as much research as this.
But I think you can basically say when the research is sound, everybody would go, well, actually in an MRI.
We understand, based on the evidence, why we do these five things treatments really well, and we would put that to our patients.
But lots of other guideline stuff is based on much poorer quality evidence.
And I think our job is to start to reject treatments much more forcefully when the evidence is not good enough or insufficient.
And I think there are many areas we would be able to say, sorry, we're not going to treat this in this way.
The problem at the moment is we perceive any new piece of evidence is just as valid as of 145 trials of aspirin, isn't there?
So the next time you see a new intervention, as you said, for this question,
I wonder how it would stack up against aspirin in terms of an evidence base.
How would it fit?
What would it make me feel like compared to all then trial for all that work, I'd bet most interventions wouldn't even match up to our within.
Cochrane The regional dissemination of trial going here is a really important effect.
Yeah, difficult to quantify the effect of a new intervention when you already have therapy in the background that is taken,
whatever reduction that you were going to have in that you know what little you have left here.
So it is good that if it had been done earlier on other therapies.
So there are two important yet. So there are about three or four important points there.
The first is you've got much smaller benefit to work with.
So that tells you you need a bigger and bigger trial, more larger trials than you did originally.
So most trials now are underpowered quite considerably and you might think six 7000 people the about of error that's potentially still huge.
So most trials the new trials are underpowered. The second issue that if you do see this at the FDA a lot,
you think how is this drug got away with going to placebo when there are established treatments already?
And that's a real problem. And then the third issue is and we've looked at this, we Jeff, we ended up writing a piece for the MRC.
Here is comparative effectiveness. No drug companies want to do treatment against treatment, right?
So now you've seen an establishment of a new methodological approach called network meta analysis.
Really interesting, quite nice for the mathematicians in the room.
They really love it. It's a new way of doing something. They're all excited about it,
but basically they're putting in a load of rubbish into the machine and it creates huge issues
that really still want the randomised trial of treatment to the established treatment.
B So you're right, aspirin would probably have had to have been a bigger trial.
It might not be as effective now in secondary prevention if you've got the new agent.
Really important issue. But you said a couple of questions on for all treatments, however,
like this which is good for heart disease which is common and I would paediatric surgery
for small congenital diseases in order to get 400,000 patients talking about that.
Yeah. Yeah. How speciality how are we ever getting to evidence based.
Yeah, that shouldn't still I mean they've done it in cancer haven't they.
So what they've done in cancer in paediatric is create a whole network not only in the country but across the EU.
And I agree with you, it's difficult, but it's not impossible. And so you should be asking yourself the question.
What you're really looking for is dramatic effect. If you don't do surgery.
This is really important and it's not. So number one is you don't need randomised trials if you get dramatic effects and a dramatic effect
is you don't need a randomised trial to show you that if you jump out a plane you need a parachute.
Okay, that's the best one. But there are things like if you don't stop somebody's bleeding because it's all about confounders and bias.
If so, if you have children, if you don't operate a birth, they die and you do that live.
That's a dramatic effect. But actually, there'll be many things you might do in practice that you think, this is really interesting.
Can we do children get pulmonary embolism or are we going to reduce infection?
And you could just end up doing more and more work on the basis you haven't got the clinical trials to underpin what you're doing.
And this is an important area which is in orphan drug orphan drugs are about what, less than one in 1500 people.
And there's a massive explosion in these drugs now because actually you get something.
If you get exclusivity, you get tax breaks, and you're the only person who is allowed to market that drug for that indication for ten years.
And so you get things like ibuprofen is remodelled and has an exclusive license for patent doctors.
Our theory health, if the price has gone up 8000 times on that basis because of one license.
But your your point is you will come to a point in surgery is coming to this point is it's a lot of areas are going we
need some evidence that what we do my thoughts are in a generation you will have changed the way the old system works.
There are people at the old end who are still going to end their careers like this. But you knew it will come in and go.
We have to question what we do. So it's only if only 40 years ago we were asking that about aspirin.
In the modern world, you might have these global networks where you all work together and go, Actually, we need a big trial.
We're going onto this. I think we will come to this understanding.
We can't afford not to. We can't afford you to be wasting a load of money and spending hundreds of thousands on some new way of doing surgery.
I'll give you a good example when we go as I go as to look at the data and published on the metal hips, I couldn't believe how bad the data was.
You know, you come from a 3% failure rate, a ten year to a 20% failure rate,
free for a change in somebody when we're going to just change the way we do this operation because people get back to work quicker.
And that was really interesting in that area. So I suspect there will be also mandatory registries for all surgical interventions, implants.
There will be mandatory registries and implants that are implanted in the body will have four clinical trials going forward.
We can't afford it otherwise. What about really well-designed observational studies?
Worrying about potential confounders and the like when you can't do drugs?
Yeah.
So, I mean, I guess the best observational study that we've ever seen was the one in Oxford done by Richard Doe and I think the number one priority.
So the smoking cessation, 50 years follow up, 99.8% of all doctors followed up this amazing study.
Most of what we do now is crap because we do retrospective studies on databases just cos they exist.
And that's big data, if you like. It's very dangerous.
However, when you do prospective studies, you can set them up really well.
You can start to important things called propensity scores.
You can talk about trying to understand the risk stratification of the individuals at the outset.
You then follow all the patients thought and create a reality to look out that data going forward.
And that's exactly how Thomas Charlie invented the hip in the first place.
He was a master evidence based medicine person. He followed everybody up and he refined the intervention.
So I think and then plug in some of the criteria from Bradford Hill.
And if you do that,
you'll have a potential to look at what you're doing without randomisation is still will be problematic one more will take one more.
We talked about I think when I guess was at the Centre for evidence based Medicine when a park was taking around,
a lot of a large percentage of decisions were changed. Was there any follow up data as far as outcomes like overall outcomes?
I'm sure it's a broad range. No, no.
And I think that was, again, an interesting issue.
Nobody's ever been shown that following an evidence based approach,
using evidence to inform your decision makes a difference to people population outcomes.
But I think to me, taking a side over busy rate,
it really worries me when I see people who don't practice in some evidence based way because the decisions they make
sometimes are really dangerous and often are stressed and overworked because they can't reel back from ideas and go,
Well, it's okay. We don't need to use that treatment evidence that we're okay.
And it's a really interesting way of working that I can't understand how anybody would adopt that because I would find
it incredibly stressful because I am making decisions here and I've no idea what I'm doing and why I'm doing it.
Apart from a colleague told me it was a good idea. And if that's what you're really saying, aren't we.
Now what David thing with the Commonwealth actually we were in the business of everything
actually about half of things we do we could change if we had some evidence to hand at the time.
Nobody still really should solve that issue because we still no better off in terms of the technology.
And there's a problem now. The amount of information is not getting more and.
Life and better from is getting bigger and bigger within it.
So every time you look at it, most people in this room and everybody outside of this room uses Google as their number one search engine.
And we've got a really smart I.T. chap working with a dphil who can show us that 97% of people will
only use the first page of the only ever resource for what they use to inform their decision making.
And that's how it generally works.
And so when you think of all that stuff going on and what we did, I think it's a very interesting time, but it's not got easier.
I think it's got actually a bit harder and nobody solved the point of care sourcing.
And I don't know if you have any thoughts about how you would practice in an evidence board for difficult issues and.
Okay. But you've got a long week ahead of you and this should set you up for some of the things tomorrow.
But have a think about when you're going through. What does it mean when you've got evidence to hand compared to not?
What would it look like the world if you didn't have any evidence in any area?
Think about the areas like you said in paediatrics where there's low evidence,
how you might use some of the levels of evidence is still low with evidence there.
There's no such thing.
I've never come across anywhere where there's no evidence because if if the best evidence is opinion, that's what you have to go with.
Have a good week. Thanks, everybody. That's coming.