Dangerous nonsense about vaping

If you thought you already had a good contender for “most dangerous, irresponsible, and ill-informed piece of health journalism of 2015”, then I’m sorry to tell you that it has been beaten into second place at the last minute.

With less than 36 hours left of 2015, I am confident that this article by Sarah Knapton in the Telegraph will win the title.

The article is titled “E-cigarettes are no safer than smoking tobacco, scientists warn”. The first paragraph is

“Vaping is no safer that [sic] smoking, scientists have warned after finding that e-cigarette vapour damages DNA in ways that could lead to cancer.”

There are such crushing levels of stupid in this article it’s hard to know where to start. But perhaps I’ll start by pointing out that a detailed review of the evidence on vaping by Public Health England, published earlier this year, concluded that e-cigarettes are about 95% less harmful than smoking.

If you dig into the detail of that review, you find that most of the residual 5% is the harm of nicotine addiction. It’s debatable whether that can really be called a harm, given that most people who vape are already addicted to nicotine as a result of years of smoking cigarettes.

But either way, the evidence shows that vaping, while it may not be 100% safe (though let’s remember that nothing is 100% safe: even teddy bears kill people), is considerably safer than smoking. This should not be a surprise. We have a pretty good understanding of what the toxic components of cigarette smoke are that cause all the damage, and most of those are either absent from e-cigarette vapour or present at much lower concentrations.

So the question of whether vaping is 100% safe is not the most relevant thing here. The question is whether it is safer than smoking. Nicotine addiction is hard to beat, and if a smoker finds it impossible to stop using nicotine, but can switch from smoking to vaping, then that is a good thing for that person’s health.

Now, nothing is ever set in stone in science. If new evidence comes along, we should always be prepared to revise our beliefs.

But obviously to go from a conclusion that vaping is 95% safer than smoking to concluding they are both equally harmful would require some pretty robust evidence, wouldn’t it?

So let’s look at the evidence Knapton uses as proof that all the previous estimates were wrong and vaping is in fact as harmful as smoking.

The paper it was based on is this one, published in the journal Oral Oncology.  (Many thanks to @CaeruleanSea for finding the link for me, which had defeated me after Knapton gave the wrong journal name in her article.)

The first thing to notice about this is that it is all lab based, using cell cultures, and so tells us little about what might actually happen in real humans. But the real kicker is that if we are going to compare vaping and smoking and conclude that they are as harmful as each other, then the cell cultures should have been exposed to equivalent amounts of e-cigarette vapour and cigarette smoke.

The paper describes how solutions were made by drawing either the vapour or smoke through cell media. We are then told that the cells were treated with the vaping medium every 3 days for up to 8 weeks. So presumably the cigarette medium was also applied every 3 days, right?

Well, no. Not exactly. This is what the paper says:

“Because of the high toxicity of cigarette smoke extract, cigarette-treated samples of each cell line could only be treated for 24 h.”

Yes, that’s right. The cigarette smoke was applied at a much lower intensity, because otherwise it killed the cells altogether. So how can you possibly conclude that vaping is no worse than smoking, when smoking is so harmful it kills the cells altogether and makes it impossible to do the experiment?

And yet despite that, the cigarettes still had a larger effect than the vaping. It is also odd that the results for cigarettes are not presented at all for some of the assays. I wonder if that’s because it had killed the cells and made the assays impossible? As primarily a clinical researcher, I’m not an expert in lab science, but not showing the results of your positive control seems odd to me.

But the paper still shows that the e-cigarette extract was harming cells, so that’s still a worry, right?

Well, there is the question of dose. It’s hard for me to know from the paper how realistic the doses were, as this is not my area of expertise, but the press release accompanying this paper (which may well be the only thing that Knapton actually read before writing her article) tells us the following:

“In this particular study, it was similar to someone smoking continuously for hours on end, so it’s a higher amount than would normally be delivered,”

Well, most things probably damage cells in culture if used at a high enough dose, so I don’t think this study really tells us much. All it tells us is that cigarettes do far more damage to cell cultures than e-cigarette vapour does. Because, and I can’t emphasise this point enough, THEY COULDN’T DO THE STUDY WITH EQUIVALENT DOSES OF CIGARETTE SMOKE BECAUSE IT KILLED ALL THE CELLS.

A charitable explanation of how Knapton could write such nonsense might be that she simply took the press release on trust (to be clear, the press release also makes the claim that vaping is as dangerous as smoking) and didn’t have time to check it. But leaving aside the question of whether a journalist on a major national newspaper should be regurgitating press releases without any kind of fact checking, I note that many people (myself included) have been pointing out to Knapton on Twitter that there are flaws in the article, and her response has been not to engage with such criticism, but to insist she is right and to block anyone who disagrees: the Twitter equivalent of the “la la la I’m not listening” argument.

It seems hard to come up with any explanation other than that Knapton likes to write a sensational headline and simply doesn’t care whether it’s true, or, more importantly, what harm the article may do.

And make no mistake: articles like this do have the potential to cause harm. It is perfectly clear that, whether or not vaping is completely safe, it is vastly safer than smoking. It would be a really bad outcome if smokers who were planning to switch to vaping read Knapton’s article and thought “oh, well if vaping is just as bad as smoking, maybe I won’t bother”. Maybe some of those smokers will then go on to die a horrible death of lung cancer, which could have been avoided had they switched to vaping.

Is Knapton really so ignorant that she doesn’t realise that is a possible consequence of her article, or does she not care?

And in case you doubt that anyone would really be foolish enough to believe such nonsense, I’m afraid there is evidence that people do believe it. According to a survey by Action on Smoking and Health (ASH), the proportion of people who believe that vaping is as harmful or more harmful than smoking increased from 14% in 2014 to 22% in 2015. And in the USA, the figures may be even worse: this study found 38% of respondents thought e-cigarettes were as harmful or more harmful than smoking. (Thanks again to @CaeruleanSea for finding the links to the surveys.)

I’ll leave the last word to Deborah Arnott, Chief Executive of ASH:

“The number of ex-smokers who are staying off tobacco by using electronic cigarettes is growing, showing just what value they can have. But the number of people who wrongly believe that vaping is as harmful as smoking is worrying. The growth of this false perception risks discouraging many smokers from using electronic cigarettes to quit and keep them smoking instead which would be bad for their health and the health of those around them.”

STAT investigation on failure to report research results

A news story by the American health news website STAT has appeared in my Twitter feed many times over the last few days.

The story claims to show that “prestigious medical research institutions have flagrantly violated a federal law requiring public reporting of study results, depriving patients and doctors of complete data to gauge the safety and benefits of treatments”. They looked at whether results of clinical trials that should have been posted on the clinicaltrials.gov website actually were posted, and found that many of them were not. It’s all scary stuff, and once again, shows that those evil scientists are hiding the results of their clinical trials.

Or are they?

To be honest, it’s hard to know what to make of this one. The problem is that the “research” on which the story is based has not been published in a peer reviewed journal. It seems that the only place the “research” has been reported is on the website itself. This is a significant problem, as the research is simply not reported in enough detail to know whether the methods it used were reliable enough to allow us to trust its conclusions. Maybe it was a fantastically thorough and entirely valid piece of research, or maybe it was dreadful. Without the sort of detail we would expect to see in a peer-reviewed research paper, it is impossible to know.

For example, the rather brief “methods section” of the article tells us that they filtered the data to exclude trials which were not required to report results, but they give no detail about how. So how do we know whether their dataset really contained only trials subject to mandatory reporting?

They also tell us that they excluded trials for which the deadline had not yet arrived, but again, they don’t tell us how. That’s actually quite important. If a trial has not yet reported results, then it’s hard to be sure when the trial finished. The clinicaltrials.gov website uses both actual and estimated dates of trial completion, and also has two different definitions of trial completion. We don’t know which definition was used, and if estimated dates were used, we don’t know if those estimates were accurate. In my experience, estimates of the end date of a clinical trial are frequently inaccurate.

Some really basic statistical details are missing. We are told that the results include “average” times by which results were late, but not whether they are mean or medians. With skewed data such as time to report something, the difference is important.

It appears that the researchers did not determine whether results had been published in peer-reviewed journals. So the claim that results are being hidden may be totally wrong. Even if a trial was not posted on clinicaltrials.gov, it’s hard to support a claim that the results are hidden if they’ve been published in a medical journal.

It is hardly surprising there are important details missing. Publishing “research” on a news website rather than in a peer reviewed journal is not how you do science. A wise man once said “If you have a serious new claim to make, it should go through scientific publication and peer review before you present it to the media“. Only a fool would describe the STAT story as “excellent“.

One of the findings of the STAT story was that academic institutions were worse than pharmaceutical companies at reporting their trials. Although it’s hard to be sure if that result is trustworthy, for all the reasons I describe above, it is at least consistent with more than one other piece of research (and I’m not aware of any research that has found the opposite).

There is a popular narrative that says clinical trial results are hidden because of evil conspiracies. However, no-one ever has yet given a satisfactory explanation of how hiding their clinical trial results furthers academics’ evil plans for global domination.

A far more likely explanation is that posting results is a time consuming and faffy business, which may often be overlooked in the face of competing priorities. That doesn’t excuse it, of course, but it does help to understand why results posting on clinicaltrials.gov is not as good as it should be, particularly from academic researchers, who are usually less well resourced than their colleagues in the pharmaceutical industry.

If the claims of the STAT article are true and researchers are indeed falling below the standards we expect in terms of clinical trial disclosure, then I suggest that rather than getting indignant and seeking to apportion blame, the sensible approach would be to figure out how to fix things.

I and some colleagues published a paper about 3 years ago in which we suggest how to do exactly that. I hope that our suggestions may help to solve the problem of inadequate clinical trial disclosure.

Spinning good news as bad

It seems to have become a popular sport to try to exaggerate problems with disclosure of clinical trials, and to pretend that the problem of “secret hidden trials” is far worse than it really is. Perhaps the most prominent example of this is the All Trials campaign’s favourite statistic that “only half of all clinical trials have ever been published”, which I’ve debunked before. But a new paper was published last month which has given fresh material to the conspiracy theorists.

The paper in question was published in BMJ Open by Jennifer Miller and colleagues. They looked at 15 of the 48 drugs approved by the FDA in 2012. It’s not entirely clear to me why they focused on this particular subgroup: they state that they focused on large companies because they represented the majority of new drug applications. Now I’m no mathematician, but I have picked up some of the basics of maths in my career as a statistician, and I’m pretty sure that 15 out of 48 isn’t a majority. Remember that we are dealing with a subgroup analysis here: I think it might be important, and I’ll come back to it later.

Anyway, for each of those 15 drugs, Miller et al looked at the trials that had been used for the drug application, and then determined whether the trials had been registered and whether the results had been disclosed. They found that a median (per drug) of 65% of trials had been disclosed and 57% had been registered.

This study drew the kinds of responses you might expect from the usual suspects, describing the results as “inexcusable” and “appalling”.

SAS tweet

Goldacre tweet

(Note that both of those tweets imply that only 15 drugs were approved by the FDA in 2012, and don’t mention that it was a subgroup analysis from the 48 drugs that were really approved that year.)

The story was picked up in the media as well. “How pharma keeps a trove of drug trials out of public view” was how the Washington Post covered it. The Scientist obviously decided that even 65% disclosure wasn’t sensational enough, and reported “just one-third of the clinical trials that ought to have been reported by the trial sponsors were indeed published”.

But as you have probably guessed by now, when you start to look below the surface, some of these figures are not quite as they seem.

Let’s start with the figures for trial registration (the practice of making the design a trial publicly available before it starts, which makes it harder to hide negative results or pretend that secondary outcomes were really primary). Trial registration is a fairly recent phenomenon. It only really came into being in the early 2000s, and did not become mandatory until 2007. Bear in mind that drugs take many years to develop, so some of the early trials done for drugs that were licensed in 2012 would have been done many years earlier, perhaps before the investigators had even heard of trial registration, and certainly before it was mandatory. So it’s not surprising that such old studies had not been prospectively registered.

Happily, Miller et al reported a separate analysis of those trials that were subject to mandatory registration. In that analysis, the median percentage of registered trials increased from 57% to 100%.

So I think a reasonable conclusion might be that mandatory trial registration has been successful in ensuring that trials are now being registered. I wouldn’t call that “inexcusable” or “appalling”. I’d call that a splendid sign of progress in making research more transparent.

So what about the statistic that only 65% of the trials disclosed results? That’s still bad, right?

Again, it’s a bit more complicated than that.

First, it’s quite important to look at how the results break down by phase of trial. It is noteworthy that the vast majority of the unpublished studies were phase I studies. These are typically small scale trials in healthy volunteers which are done to determine whether it is worth developing the drug further in clinical trials in patients. While I do not dispute for a minute that phase I trials should be disclosed, they are actually of rather little relevance to prescribers. If we are going to make the argument that clinical trials should be disclosed so that prescribers can see the evidence on what those drugs do to patients, then the important thing is that trials in patients should be published. Trials in healthy volunteers, while they should also be published in an ideal world, are a lower priority.

So what about the phase III trials? Phase III trials are the important ones, usually randomised controlled trials in large numbers of patients, which tell you whether the drug works and what its side effects are like. Miller et al report that 20% of drugs had at least 1 undisclosed phase III trial. That’s an interesting way of framing it. Another way of putting is is that 80% of the drugs had every single one of their phase III trials in the public domain. I think that suggests that trial disclosure is working rather well, don’t you? Unfortunately, the way Miller et al present their data doesn’t allow the overall percentage disclosure of phase III trials to be determined, and my request to the authors to share their data has so far gone unheeded (of which more below), but it is clearly substantially higher than 80%. Obviously anything less than 100% still has room for improvement, but the scare stories about a third of trials being hidden clearly don’t stack up.

And talking of trials being “hidden”, that is rather emotive language to describe what may simply be small delays in publication. Miller et al applied a cutoff date of 1 February 2014 in their analysis, and if results were not disclosed by that date then they considered them to be not disclosed. Now of course results should be disclosed promptly, and if it takes a bit longer, then that is a problem, but it is really not the same thing as claiming that results are being “kept secret”. Just out of interest, I checked on one of the drugs that seemed to have a particularly low rate of disclosure. According to Miller et al, the application for Perjeta was based on 12 trials, and only 8% had results reported on clinicaltrials.gov. That means they considered only one of them to have been reported. According to the FDA’s medical review (see page 29), 17 trials were submitted, not 12, which makes you wonder how thorough Miller et al’s quality control was. Of those 17 trials, 14 had been disclosed on clinicaltrials.gov when I looked. So had Miller et al used a different cut-off date, they would have found 82% of trials with results posted, not 8%.

I would like to be able to tell you more about the lower disclosure rates for phase I trials. Phase I trials are done early in a drug’s development, and so the phase I trials included in this study would typically have been done many years ago. It is possible that the lower publication rate for phase I trials is because phase I trials are intrinsically less likely to be published than trials in patients, but it is also possible that it is simply a function of when they were done. We know that publication rates have been improving over recent years, and it is possible that the publication rate for phase I trials done a decade or more ago is not representative of the situation today.

Sadly, I can’t tell you more about that. To distinguish between those possibilities, I would need to see Miller et al’s raw data. I did email them to ask for their raw data, and they emailed back to say how much they support transparency and data sharing, but haven’t actually sent me their data. It’s not entirely clear to me whether that’s because they have simply been too busy to send it or whether they are only in favour of transparency if other people have to do it, but if they do send the data subsequently I’ll be sure to post an update.

The other problem here is that, as I mentioned earlier, we are looking at a subgroup analysis. I think this may be important, as another study that looked at disclosure of drugs approved in 2012 found very different results. Rawal and Deane looked at drugs approved by the EMA in 2012, and found that 92% of the relevant trials had been disclosed. Again, it’s less than 100%, and so not good enough, but it certainly shows that things are moving in the right direction. And it’s a lot higher than the 65% that Miller et al found.

Why might these studies have come to such different results? Well, they are not looking at the same drugs. Not all of the drugs approved by the FDA in 2012 were approved by the EMA the same year. 48 drugs were approved by the FDA, and 23 by the EMA. Only 11 drugs were common to both agencies, and only 3 of those 11 drugs were included in Miller et al’s analysis. Perhaps the 15 drugs selected by Miller et al were not a representative sample of all 48 drugs approved by the FDA. It would be interesting to repeat Miller et al’s analysis with all 48 of the drugs approved by the FDA to see if the findings were similar, although I doubt that anyone will ever do that.

But personally, I would probably consider a study that looked at all eligible trials more reliable than one that chose an arbitrary subset, so I suspect that 92% is a more accurate figure for trial disclosure for drugs approved in 2012 than 65%.

Are 100% of clinical trials being disclosed? No, and this study confirms that. But it also shows that we are getting pretty close, at least for the trials most relevant for prescribers. Until 100% of trials are disclosed, there is still work to do, but things are not nearly as bad as the doom-mongers would have you believe. Transparency of clinical trial reporting is vastly better than it used to be, and don’t let anyone tell you otherwise.

Update 23 January 2016:

I have still not received the raw data for this study, more than 2 months after I asked for it. I think it is safe to assume that I’m not going to get it now. That’s disappointing, especially from authors who write in support of transparency.