This edition of talk evidence was recorded before the big increase in covid-19 infections in the UK, and then delayed by some self isolation. We'll be back with more evidence on the pandemic very soon. As always Duncan Jarvies is joined by Helen Macdonald (resting GP and editor at The BMJ) and Carl Heneghan (active GP, director of Oxford University’s CEBM and editor of BMJ Evidence). in this episode (1.01) Helen talks about variation in prescription of opioids - do 1% of clinician really prescribe the vast majority of the drug? (8.45) Carl tells us that its time papers (in this case a lung screening one) really present absolute numbers. (17.30) Carl explains how a spoonfull (less) of salt helps the blood pressure go down (21.25) Helen puts test results under a microscope, and finds out that they may vary. (33.20) What do conflicts of interest in tanning papers mean for wider science? (48.05) Carl has a "super-rant" about smartphone apps for skin cancer - and a sensitivity of 0. Reading list: Opioid prescribing patterns among medical providers in the United States, 2003-17: retrospective, observational study https://www.bmj.com/content/368/bmj.l6968 Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial https://www.nejm.org/doi/full/10.1056/NEJMoa1911793 Effect of dose and duration of reduction in dietary sodium on blood pressure levels https://www.bmj.com/content/368/bmj.m315 Your results may vary: the imprecision of medical measurements https://www.bmj.com/content/368/bmj.m149 Association between financial links to indoor tanning industry and conclusions of published studies on indoor tanning: systematic review https://www.bmj.com/content/368/bmj.m7 Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies https://www.bmj.com/content/368/bmj.m127
Chapter 1: What are the patterns of opioid prescribing among clinicians?
Welcome back to Talk Evidence, your monthly look at the world of EBM. I'm Duncan Jarvis, multimedia editor here at the BMJ. As always, I'm joined by Helen and Carl, who've both made it into the studio today. Carl, can I get you to introduce yourself?
Yes, hi, I am Carl Hennigan. I'm editor-in-chief of BMJ Evidence-Based Medicine and professor of EBM at the University of Oxford and a general practitioner.
And Helen.
I'm Helen MacDonald.
Chapter 2: How can absolute numbers improve the presentation of lung screening data?
I'm the UK research editor for the BMDA and arresting GP.
I like how you've stuck with that.
Yeah, I have. I think it suits me well.
I think, though, with the coronavirus, you may have to... I might be called up.
They might be desperate enough that they'll call me back immediately.
This week we are going to be doing some starting and some stopping. Helen, shall we start with you?
Yes, I wanted to talk about an interesting paper which was published in the BMJ back at the end of January, actually.
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Chapter 3: What is the impact of dietary sodium reduction on blood pressure?
And I think this is a start, maybe to start looking at your opioid prescribing in chronic pain. And the background is that prescription opioids are a big problem. They cause iatrogenic harm in some cases. And in the US, this is an even bigger problem than in some other parts of the world.
Chapter 4: Why do test results vary and how should they be interpreted?
And the authors of this particular research paper say that in order to educate and support prescribers, we really need to understand who's prescribing and what their patterns of prescribing are. So they did this retrospective study in a big US healthcare insurance system between 2003 and 2017, looking at the volume and patterns of prescriptions by provider.
By provider, I think they mean a single person, but I could be wrong. And what they find is that things are very skewed. And what seemed astounding to me was that they said the top 1% of prescribers accounted for essentially half of all of the opioid doses and about 27% of all of the opioid prescriptions. And they felt quite confident in these findings because it's a big study. It's national.
It was over a long time period. They did lots of clever adjustments accounting for the prescription length and the number of people people see and the number of prescriptions they do. And over time, these high prescribers seemed like a stable group of people in this kind of countrywide phenomenon.
So there's that whole like atlas of variation thing that said that, you know, you get these pockets of the way people do medicine. So, you know, whatever it is, sending people for MRI can be quite a localised thing.
Chapter 5: What do conflicts of interest in tanning research mean for public health?
Was there any data about who these people were? Yeah. Were they clustered?
They did. They said, and it's hard to infer. to interpret in some ways, but more than half of that top centile of prescribers were in family medicine, so about 24%, or in physical or pain medicine and rehabilitation. That was about 14% of them. Anesthesiology and internal medicine.
So in some ways you think, well, that's kind of justified because those people are probably the people that are dealing with chronic pain. But at the same time, they sort of make a suggestion that not all of that prescribing can be So they say that those top prescribers are consistently prescribing well above the CDC recommended opioid doses and durations for the management of chronic pain.
So they think that there's something unusual about that group of people. And it's quite interesting because I like the way that they try to apply this to then what should happen in the real world. And their suggestion is that with this top centile, there's clearly a group of people that have sustained high prescribing over time and their patients are perhaps at the highest risk of harm.
So they suggest that those are the target clinicians or maybe they're not clinicians, they're healthcare services, whatever provider means in this paper.
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Chapter 6: What issues arise from smartphone apps for skin cancer diagnosis?
They're the places to target for education and support for clinicians on prescribing. And that might be a better approach if you want to minimise inappropriate prescribing than just targeting blanket education initiatives at everybody. Because it actually seems to be a much smaller proportion of prescribers who are doing that work.
prescribing yeah i found this quite an interesting issue but i think it's a nice start but there's a lot of bits of information missing in the paper because it just gives us a headline figure one percent of prescribers are responsible for all the problems but we know that's not the case because there can be clear reasons why you're in that high level and we looked at this in sometimes in terms of deaths
And people start saying deaths cluster in 1% of GPs or 1% of family docs, but they're all the ones that have palliative care and nursing homes under their wing. Interestingly here as well, it picks out one of the indications as back problems. But I think it's interesting when you see back problems, often people have tried a lot of intervention.
So they've tried the paracetamol, they've tried the non-steroidal. And they want to get moving and it's debilitated. So you're at that crux where you are at. We're going to go to the codeine now because we want to get you moving. So I think there's a lot more to be drawn out in this paper to help us understand what we should and shouldn't do.
My position is to say if I'm going to prescribe them in these indications, it's only to give a short duration of use so that you don't get beyond the three to five days and you're still on them and actually have got better, but the problem is you don't want people to get addicted.
Yes, I think that's what they're saying when they're looking at the prescriptions above and beyond the CDC recommendations because that's very similar to what they lay out in the paper, that short-term defined duration.
But I think there's an interesting point. One of the big things in America is the...
opiate sort of a crisis is the number of deaths being caused by opioid prescriptions but there's a real interesting caveat as you solve one problem then another problem emerges and in the back of the discussion they say that actually there's been a recent increase in deaths from illicit opioids as an unintended consequence of reducing the availability of medical prescribed opioids more people are going on to substitutes are going on to heroin and actually they're far more
serious and far more potent and are giving rise to more deaths. So it's not quite as straightforward as this. If you reduce this, you'll solve all the problems here.
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Chapter 7: How can clinicians better understand the variability in test results?
So you've created that anxiety. You'll also get six cases of lung cancer will be over-diagnosis. That's the people who will have a lung cancer detected, and it will never go on to cause any problems. So one of the things here is what I'm really interested in is the decision to screen or not will be a value judgment, whether you think it's a good or bad thing to do.
Our job is to educate and inform the policymakers and the public. And these journal papers certainly don't do that as they currently stand. And I think we need a real change in terms of these papers to say, here's the absolute numbers.
And now you can make a value judgment on whether you think this is an important thing to do based on all of the data and all of the important issues that you want to know about.
Interestingly, I was just looking up while you were talking, I was looking at the consort statement which is the reporting guideline for trials to give researchers guidance on what information to include in their journal publication and in the results section on the outcomes and estimation item 17b it says for the outcomes you need to present both the absolute and the relative effect sizes
So that's interesting, isn't it? Because you're being asked for that, but maybe those items are not getting enough prominence in that section or in the abstract. So I guess you can always go in the tables and dig this out, but I think you just need a lot of expertise to piece those numbers together.
I think what's important is that people doing the research have to understand the emotiveness around the decision to screen or not. And in understanding that, they should be adhering to this concept of producing the absolute effects. But what's clear is that is not happening. You have to go in the back of the paper. You have to do quite a bit of maths to get to that sort of natural frequencies.
And it did take me quite a considerable time. And I consider myself quite numerous. I'm sure there's many statisticians out there who disagree. But actually, it is difficult. And what's interesting is so few people do this. So you're left with this confusing picture of, oh, well, there's a reduction in lung cancer mortality. What's the problem? We should screen everybody.
And often that's enough for people to then go, yeah, let's go and screen. But actually, you've got to consider all of the evidence, and particularly what you said about the absolute effects, incredibly important.
So you've snuck in what we should do is put absolute numbers there in guise of a lung cancer screening approach.
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Chapter 8: What should be done to address financial conflicts in medical research?
And I'm sure somebody will be writing and telling me I'm all over the show, but I've rounded it up. So five grams of salt is about 2,000 milligrams of sodium. 100 millimoles of sodium is roughly about equal to that 2,000 milligrams of sodium. And that is equivalent to about one teaspoon of salt. Okay. 100 millimoles of sodium gets me about 4 millimetres of mercury.
That 100 millimoles is about equivalent to 2,000 milligrams of sodium, which is equal to 5 grams of salt, which is around about a teaspoon.
So if you eat a teaspoon less... Yeah. your systolic blood pressure would go down by about four millimetres of mercury in the short term.
Isn't that so? Isn't that much more useful information that could have been imparted in the paper?
It's like you're interviewing for another job, Carl, to join the research team.
I am joining the research, but I want to know when you get your statistics, is you can do all the statistics right. Now, please, please podcast, email in, write in and tell me I'm wrong. But what I'm trying to do is say, can I find some usable advice for clinicians and patients based on these results?
And I do think that's the sort of thing as a little infographic could have said, here's what you can do with this paper. And I think we need more of that to make this more usable research. And I will say to people about a teaspoon of salt is a useful thing to do.
I mean, reducing it by that much, that seems like an awful lot of salt you must be eating in the first place. Well, just have that as a baseline.
Well, just remember.
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