In the abstract, we are told that their literature search identified 830 basic science experiments (ie experiments in labs, rather than clinical trials) of high potency homeopathic dilutions. For those not familiar with the terminology, homeopaths use the term “high potency” to mean “highly diluted”, to the point where it is extremely unlikely that a single molecule of the original substance remains.

Of those 830 studies, the abstract tells us that at least one positive result was reported in 90% of them.

Sounds impressive, doesn’t it?

Well yes, I have to admit that it does sound impressive. But to see whether it actually is impressive, you have to read the full paper.

The first thing I’d want to know is what exactly do they mean by a “positive result”. Do they mean a statistically significant result on the pre-specified primary outcome variable? Or perhaps they mean any statistically significant result on any of the (potentially many) variables investigated, which would be less impressive. Or maybe they even mean any result of any size in a hypothesised direction, whether or not it’s statistically significant, which would actually be completely meaningless.

Which of those definitions did they use? Well, I don’t know, because they don’t say. However, I’m prepared to bet the price of a year’s supply of 30C arnica that it wasn’t the first of those definitions.

So, we know that 90% of the studies found at least 1 positive result, but now we know that “positive result” was not defined, which already makes it pretty much meaningless.

But it gets worse.

We are also told that they did not collect the information on whether the “positive results” were actually obtained from the “high potency” dilutions. Many of the experiments (we are not told how many) also used low potency dilutions, ie substances which have not been diluted so much, so that they may well have a pharmacologically active substance in them. So even if studies did have positive results, we do not know whether they came from the high potency or the low potency dilutions. So as a way of assessing the effects of high potency dilutions, this paper is about as useful as a bacon sandwich at a Bar Mitzvah.

What we are told, however, is that 4 studies found that high potencies caused significant effects in the opposite direction to low potencies, which is what we might expect if the “like cures like” principle of homeopathy were true.

That’s 4 studies. Out of 830.

All of these details would be unavailable to someone who had just read the abstract. Anyone who read only the abstract would just read the headline conclusion that 90% of the experiments were positive, and not be aware of all the crushing limitations of that figure.

So the moral of the story is clear: never attempt to draw conclusions from a published paper based on the abstract alone.

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They were discussing student tuition fees, and some new estimates that students starting university next year will graduate with about £50,000 worth of debts. UK readers will doubtless be familiar with the background to this, but for those of you from further afield, this results from a decision to increase student tuition fees from their current £3000 per year to £9000 per year, in what represents one of the most dramatic broken promises from some members of the government for quite a while. And as we’re talking broken promises from politicians here, that’s saying something. Astute readers will notice that that still amounts to only £27,000 for a 3-year degree course, but the figure also includes the amount students need to borrow for their cost of living.

One of the contributors to the discussion was Professor Michael Arthur, chair of the Russell Group of universities. He attempted to put the figure into perspective by pointing out that people who go to university enjoy higher earnings than those who don’t, and gave a figure of £130,000 over a lifetime for this.

There is only one possible response to this: this one. (Any non-UK readers confused by that reference will find the explanation here).

I’ve blogged about pretty much exactly the same thing before when Vince Cable made the same point, although it’s intriguing that the figure seems to have risen from £100,000 when Cable quoted it a year ago.

OK, here’s the big problem: correlation does not equal causation.

Let me explain. I dare say that, on average, graduates earn more than non-graduates over their lifetime. Precisely what the figure is is open to dispute (and I raised some concerns about it before when I blogged about Cable’s use of the figure), but I’m happy to accept that it’s a large number, and may very well be greater than the £50,000 cost of going to university.

But it’s not as simple as that. The argument seems to go like this “going to university will cost me £50,000, but on the other hand it will also give me a better job which will make me £130,000 richer, so the net effect is that I’ll be better off”. But that argument makes the assumption that going to university makes you richer, ie that the relationship between university education and earnings is causal.

That assumption is almost certainly not true. People who go to university are probably different from people who don’t go to university in many ways. It’s probably reasonable to assume that they are, on average, more intelligent and harder working people in the first place. It’s probably also reasonable to assume that more intelligent and harder working people earn more over their lifetime than their less intelligent or lazier peers. So we should not be surprised that people who go to university earn more than those who don’t, but it does not mean that a university education is the cause of their higher earnings.

Of course, there are many reasons to go to university other than a purely financial decision. Learning is a fantastic thing in its own right, irrespective of whether it leads to better job prospects. As someone currently studying for his 4th degree, I am very well aware of this.

However, the assumption that choosing to go to university will make you better off financially seems very hard to justify.

I was fortunate to go to university in the 1980s when tuition was still funded entirely by the government, so it was a complete no-brainer for me to do so. If I were 18 again now, I would be facing an extremely difficult decision: go to university, probably end up with a more interesting job, and learn things that would be generally improving, or go straight from school into the labour market, avoid being saddled with huge debts, and probably be better off financially in the long run.

I genuinely don’t know what I would do if I were in that position. I feel terribly sorry for all those who have to make that decision now.

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I got to see some of this first hand. I happened to be in Colliers Wood yesterday evening. One shop had been set on fire, and other shops had had windows smashed and were being looted. The police were present, but were not able to intervene in the looting. I saw police in riot gear guarding a petrol station. They had presumably taken the (no doubt very wise) decision that preventing a petrol station being set on fire was the most important use of their limited resources.

As a scientist, I want to be able to explain things. Here, I have to accept that my tools as a statistician are largely useless for doing so. Medical statistics is mostly about trying to draw generalisable conclusions from individual events. I’m pretty sure there are no generalisable conclusions that can be drawn from last night’s events. To explain last night’s events, we need the tools of social sciences.

I am by no means an expert in social sciences, although it is a subject that interests me, and I am currently studying part-time towards a “social sciences with economics” degree with the Open University. One thing I have learned already is that theories in social sciences are usually context-specific. In trying to understand what happened last night, it’s likely to be unwise to try to generalise. Last night’s violence was a collection of different pockets of violence, and even trying to explain what happened in Croydon in the same terms as explaining what happened in Ealing may well be over-generalising.

I don’t pretend to understand why such horrific violence erupted in London last night. Anybody who claims to be able to explain it at this stage is probably massively over-simplifying. But here are the sort of questions I hope social scientists will be able to answer when they have had a chance to reflect properly and gather some data:

• Clearly much of the criminal activity was based purely on personal greed, but were there other reasons as well? How common were those other reasons, and what were they?
• How many of those looting were habitual criminals who saw an opportunity, and how many were previously law-abiding people, drawn into criminality by the psychology of the mob?
• How does mob psychology manage to exert such a powerful influence in such situations?
• What factors in the way society is organised contribute to so many people turning to criminality?
• Were the reasons for the riots broadly similar in all areas of London, or were there important differences between the different areas where violence occurred?
• And most importantly, what societal measures could be taken to reduce the risk of this happening in the future?

This is a worrying time for London. My thoughts are with all the police officers who will have to put themselves in harm’s way this evening. I hope they remain safe.

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Why?

Well, if you are going to write a scientific paper criticising someone for introducing bias into the scientific literature, would it be too much to ask that you should do it in an unbiased way? What makes me grumpy is when people write papers about how evil and biased the pharmaceutical industry is (and this is certainly not the first such paper), but then themselves distort the facts to make a point.

Now, I’m not saying that the pharmaceutical industry is populated entirely by saints. It is true that some of the things that some people in the industry have done have indeed distorted the scientific literature. That is undeniably a bad thing. However, I do think it’s important to stick to the facts, and not to embellish them to make things sound worse than they are. If a paper misrepresents some facts, how can I trust anything else in the same paper? There may be some important points to be made, but by mixing them up with distortions and untruths, the whole message is weakened.

And that’s a shame, because the integrity of the medical literature is important.

So, which paper am I talking about, and why do I think it’s distorted? The paper, by Joel Lexchin, is entitled “Those who have the gold make the evidence: how the pharmaceutical industry biases the outcomes of clinical trials of medications”. Not that that’s an emotive title or anything.

I haven’t extensively fact-checked the paper, but it did cite a couple of pieces of evidence with which I was already familiar, and I couldn’t help but notice that those pieces of evidence had been badly misrepresented.

One of the things we are told in the paper is that industry-sponsored papers have a discordance between their results and conclusions, and that results are “spun” to yield favourable conclusions. The evidence cited to support this is a paper published in the BMJ in 2007 by Yank et al. That is what Yank et al concluded, but sadly their methods were deeply flawed, as I pointed out at the time. They assessed spin with a single reviewer, who was aware of the study hypothesis, and was not blinded to whether papers were sponsored by industry or not. The potential for bias in a study like that is huge, but Lexchin made no attempt to acknowledge the limitations of Yank et al’s study, presumably because it supported his argument.

In fact there is some other evidence, not cited in Lexchin’s paper, that argues against the idea that industry papers “spin” the results in their conclusions (at least not any more so than anyone else). A far more careful study by Boutron et al did not find any difference between industry-sponsored studies and independent studies in the amount of spin in their conclusions (this wasn’t reported in the paper, for some strange reason, but was clarified in subsequent letters.

Interestingly, one of the ways in which it’s possible to spin results is to write a paper that pretends that a favourable secondary outcome was the primary outcome all along. Why did Lexchin not mention that? Could it be that a recent paper by Bourgeois et al found that a mismatch between pre-specified and reported outcomes was significantly less likely in industry-sponsored studies? That’s a highly relevant piece of information if you’re trying to answer the question of whether the industry are any worse than anyone else at spinning results, and yet it was entirely left out of Lexchin’s paper. Ignoring evidence that doesn’t fit with your preconceived notion of what the results should be is itself a pretty serious form of spin.

The paper also talks about ghostwriting. As regular readers of this blog will know, that’s something of a specialist subject of mine. What really annoys me is when people write about ghostwriting and don’t make the distinction between ghostwriting and legitimate, transparent assistance from professional medical writers. Guess what? Lexchin doesn’t once mention the latter. Much of the discussion about ghostwriting is therefore rather confused.

But one bit struck me as a particularly heinous crime against accuracy: a claim that “evidence points to [ghostwriting] being widespread and systematic”. The “evidence” (and trust me, I use that term loosely) cited in support of that claim was a paper by Ross et al published in JAMA in 2008.

So, how widespread exactly did Ross et al find that ghostwriting was? Well, I don’t know, because Ross et al did not present any quantitative data whatsoever on the prevalence of ghostwriting. They found, using a very broad definition of ghostwriting (which again, confuses ghostwriting with legitimate and transparent writing assistance) that “some” papers were ghostwritten. Now, perhaps as I statistician I have greater expectations than most people that data should come with numbers, but I don’t see how anyone can conclude that something is “widespread” just because it happens “sometimes”. Oh, and Ross et al’s paper looked only at publications on a single drug sponsored by a single company, so even if it did present quantitative data, it would be pretty bizarre to try to extrapolate its results to the entire pharmaceutical industry.

When Lexchin cites such mind-crushingly weak evidence to make his points, it’s clear that either he has made no attempt whatsoever to critically evaluate the literature he cites, or he is deliberately misrepresenting it just to fit his agenda. I honestly don’t know which would be worse. Either way, it makes it very hard to believe anything I read in the rest of the paper.

I could go on about this paper for much longer, but I imagine you’re getting slightly bored of reading this by now, so I think I’ll stop there.

All that remains is to say that the integrity of the medical literature is hugely important. It is literally a matter of life or death. We know that much of the medical literature is biased or otherwise imperfect, and that’s something that deserves to be taken extremely seriously. It’s certainly possible that the pharmaceutical industry may be responsible for biasing the literature, although as I’ve argued elsewhere, the evidence that the pharmaceutical industry does any worse than anyone else in this regard is pretty weak. It is important that we all—industry or otherwise—make an effort to improve standards in reporting of clinical trials, and highlighting any shortcomings in the way things are done at the moment is an important part of that.

But if we’re going to look at shortcomings, it is essential to do so in an unbiased and scientific manner. Distorting the evidence to fit a political agenda is not helpful. You would hope that people who write papers about other people distorting the evidence would know better.

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However, I’m not convinced.

The finding is based on a relatively small number of studies. Only 6 studies were used in the meta-analysis of the duration of symptoms. 4 of those studies were rather unimpressive, showing either non-significant reductions in the duration of symptoms, or a reduction of less than 1 day. The overall finding of a significant reduction in symptom duration was largely driven by 2 small studies (48 and 50 patients respectively), which found much larger reductions.

This is consistent with a pattern known as publication bias: small studies with significant positive results get published, small studies with negative results don’t get published. It’s possible that other small studies have been done, but not published, because their results were negative, and that inclusion of those studies would move the overall results to being negative.

Assessment of publication bias is an important part of a systematic review. Oddly, the methods section of the Cochrane review tells us that they looked for publication bias, but I can’t find anywhere in the results section a description of what they found.

I think that’s quite important here. Without knowing more about how likely publication bias is (and a quick glance at the results suggests it is quite likely), it’s hard to know whether to believe these results. I am not convinced that zinc supplementation is truly a useful treatment for the common cold. Further research, as they say, is needed.

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So what does the evidence show?

The short answer is: not much. A systematic review, last updated in 2006 (bizarrely described as a 2002 paper in Fewtrell et al’s paper) found conflicting evidence. A randomised trial from Honduras found some evidence that hinted in the direction that breastfeeding for 6 months might increase the risk of anaemia, but the evidence was weak. There was a statistically significant, but small reduction in haemoglobin levels, but no significant increase in the risk of haemoglobin levels below 110 g/L in infants exclusively breastfed for 6 months, compared with those weaned at 4 months.

In contrast, however, an Italian study found that exclusively breastfed infants had higher haemoglobin concentrations. So the evidence from that review that exclusive breastfeeding increases the risk of anaemia is very weak, particularly in developed countries. It is quite possible that the different nutritional statuses in developed and developing countries mean that trials in one setting are not generalisable to the other.

Anyway, back to Fewtrell et al’s paper. They discuss the risk of iron deficiency anaemia further, and and point to a study published since the systematic review (in 2007) by Chantry and colleagues. Fewtrell et al’s paper is not a systematic review, and so it’s possible that there are other relevant papers that have been published in recent years. I don’t know whether they have been or not. I couldn’t find any in a 5 minute literature search, but it’s quite possible that a more careful search would have revealed something.

Chantry et al’s study is described by Fewtrell et al as showing that “US infants exclusively breast fed for six months, versus four to five months, were more likely to develop anaemia and low serum ferritin”. They also point out that iron deficiency has “irreversible long term adverse effects on motor, mental, and social development”.

Let’s take the second point first. The evidence cited for the risk of adverse consequences resulting from iron deficiency was not specific to breastfed infants. To claim that 6 months exclusive breastfeeding causes iron deficiency and iron deficiency causes irreversible developmental problems and therefore that 6 months exclusive breastfeeding causes irreversible developmental problems is a rather weak argument. It would be much more convincing if it were shown that 6 months exclusive breastfeeding causes irreversible developmental problems, but that has not been shown. It is quite possible that infants with iron deficiency as a result of delayed weaning could be very different from infants with iron deficiency due to other causes.

But anyway, how sure are we that 6 months exclusive breastfeeding really does increase the risk of iron deficiency?

Well, after reading Chantry et al’s paper, I have to say the answer is “not sure at all”. Chantry et al looked at 2 separate cohorts of children, and measured iron deficiency by 3 different measures: low serum ferritin, low haemoglobin, and a history of anaemia. A major weakness of the study is that history of anaemia was based mainly on reports by the parents, with no medical verification. I’m not at all sure how reliable such self-reporting is.

If I were to be convinced that 6 months exclusive breastfeeding increases the risk of iron deficiency, then I would like to see some sort of consistency in the results. However, the results were highly inconsistent.  The risk of low haemoglobin was not significantly increased in either cohort after 6 months exclusive breastfeeding. The risk of low serum ferritin was increased in one cohort, and the risk of a history of anaemia was increased in the other cohort. Only 2 significant results out of a possible 6 results does not strike me as convincing. It’s also worth noting that although the risk of low haemoglobin was not significantly different between those exclusively breastfed for 6 months and those exclusively breastfed for 4-5 months, the risk of low haemoglobin was significantly higher in those exclusively breastfed for less than 4 months in one cohort.

To cite that paper as evidence that exclusive breastfeeding for 6 months increases the risk of iron deficiency anaemia therefore strikes me as misleading. Now of course it’s possible that there may be an increased risk of anaemia, as the evidence is inconclusive, and although we don’t have good evidence that there is an increased risk, we also don’t have enough evidence to say with certainty that there is no increased risk.

But, of course, there is much good evidence that 6 months exclusive breastfeeding is beneficial on other outcomes. It’s probably still wise to recommend breastfeeding for 6 months given that we know there are benefits, and the possibility of harm is at this stage unproven. As Chantry et al concluded in their paper “Full or exclusive breastfeeding for 6 months provides greater protection against both respiratory and gastrointestinal infections than does shorter durations, and should continue to be recommended.”

Not surprisingly, the paper has been poorly presented in the media. And if you are a regular reader of this blog, you will know by now that it’s important to read the research paper before making up your mind about any health stories reported in the media. But there is a further lesson here. Even the journal article may not give the full story. I found out how weak the evidence was here by going back a stage further and looking at the papers cited in the first paper. Just because something is cited in a journal article as being evidence of something doesn’t mean that it’s good evidence.

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OK, given that I’m quoting the Daily Mail, you’ve probably guessed by now that I’m not entirely happy with the way this story has been reported.

We are told that 584 women who used Implanon got pregnant, and this is presented as some sort of terrible scandal. Well, clearly it’s pretty rough on those women who thought they were using an effective contraceptive and got pregnant anyway, but the fact is that no method of contraception is 100% effective. Everyone knows that (or should know that).

So the question is whether 584 is more than the number of women using Implanon who might reasonably be expected to get pregnant.

None of the media sources gives us any information on that. And without that information, it’s impossible to judge whether there’s anything really wrong here, or whether this is just a small and probably unavoidable failure rate that can be expected with any form of contraception.

However, the Channel 4 story gives some numbers that have allowed me to do a quick back-of-an-envelope calculation.

We are told there that 16,000 women used contraceptive implants in 2005 and 82,000 did in 2010. If we assume that the rate of increase was uniform over that period, then that would be 294,000 implants in that 6-year period. We are not told the time period in which the 584 pregnancies were reported, but if it applies to the same 6-year period, then the failure rate is 0.2% per implant. Given that the implants are intended to be used for 3 years, that implies a failure rate of 0.07% per year.

Now, given that the failure rate of the oral contraceptive pill, when used perfectly, is 0.3%, and a whopping 8% in typical use (as not all women use it perfectly, for example they may miss doses), a 0.07% failure rate for Implanon doesn’t sound so bad. In fact it also seems to be within the confidence interval for the failure rate calculated from clinical trials of Implanon, which was from 0 to 0.09%.

Much of the media coverage makes the point that failures have generally occurred when doctors have inserted the devices incorrectly. No doubt that’s true. And maybe, just maybe, there is some cause for concern here. Clearly inserting the device is a procedure requiring some skill, and if some doctors who are inserting the device have not been adequately trained in its use, then something probably needs to be done about that.

However, doctors are humans, so its inevitable that some of them will sometimes insert the device incorrectly. It’s unrealistic to assume that it will be done perfectly every time. Statistics on the failure rate of the device need to take that into account.

It’s worth noting that clinical trials of the device may give a misleadingly favourable impression of the failure rate, as doctors participating in clinical trials were probably trained to a higher standard than your average local GP, so you would expect failure rates in real life to be higher than in clinical trials.

So, maybe there is a case for ensuring that doctors who use the device undergo more rigorous training than they currently do. But if my back-of-the-envelope failure rate of 0.07% per year is anything like the real figure, then it seems that Implanon is still a pretty effective form of contraception.

But hey, as they teach them at journalist school, why let the facts get in the way of a good story?

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Bob Ainsworth, a Labour MP and a former cabinet minister, has publicly declared his support for legalising all drugs. It’s certainly a radical solution. He imagines a future in which drug users can obtain heroin, cocaine, or whatever perfectly legally, either on prescription from their GP or perhaps bought from the local pharmacy (for such a radical policy, clearly there are a lot of details that would need to be worked out).

That would have 2 main advantages. First, the drugs themselves would be made to pharmaceutical standards, and so would be safer. But much more importantly, it would take the distribution of drugs out of the hands of gangs of organised criminals. At the moment, the supply of illegal drugs is a lucrative source of income for criminal gangs. Governments have tried and failed to tackle that problem through law enforcement measures.

Trying to eliminate illegal drug use through law enforcement doesn’t work. It never has, and it never will. The Americans should have learnt this lesson when they tried prohibition of alcohol in the 1920s. They had to abandon that policy because of the massive boost it gave to organised crime.

The situation is exactly the same today for illegal drugs. As long as the demand is there (and no matter how hard governments try to reduce demand, there is very little evidence that they have any chance of succeeding), criminal gangs will fill that demand. That is not good for society.

The government may claim that legalising drugs would simply mean more people using drugs, and thus creating greater harm. They have no evidence for that.  In fact the experience from Portugal suggests that legalising drugs may even reduce drug use.

Bob Ainsworth is so obviously correct in what he says. I fail to see how anyone can claim that the current policy on drugs is working. Drugs cause great misery, largely as a result of the criminal activity that accompanies them. Taking the supply of drugs out of the hands of criminals may not solve all drug-related problems overnight, but it is hard to imagine how it wouldn’t be a tremendous help.

It is also hard to imagine why government ministers can’t see this (or indeed why Ainsworth didn’t see this when he was the government minister responsible for drug policy, when he would have had far more influence than in his current role as an opposition back bencher). One could imagine conspiracy theories about government having reasons to want a society riddled with organised crime, but those theories strike me as rather far-fetched. The only plausible explanation I can think of is that governments judge that the policy would result in bad headlines in the tabloids. And for most government ministers, when it comes to doing the right thing versus headlines in the tabloids, the tabloids win every time.

So why “imperial war on drugs”? This has nothing to do with the war we are fighting in Afghanistan in a neo-imperialist way, although heroin production is indeed one of the main issues in that war. No, I write “imperial”, because I imagine the government’s War on Drugs being run by an emperor. The government sees this emperor as wearing particularly fine clothes. Bob Ainsworth has told them what the emperor is really wearing.

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Does it?

Well, it was certainly an excellent piece of research, which tells as a great deal about the effect of daily aspirin on the risk of cancer death. It seems pretty clear-cut in that respect: taking aspirin every day reduced the risk of dying of cancer (not all types of cancer, but enough types of cancer that the overall death rate from cancer was significantly reduced). It’s important to note that this was based on data from randomised controlled trials, and is therefore much more reliable than epidemiological studies. It was also based on multiple large trials, including over 25,000 patients, so the study was large enough to be statistically robust.

However, I don’t think this is the the end of the story for aspirin. We already knew that aspirin reduces the risk of cardiovascular disease, and we now know that it reduces the risk of cancer. But aspirin also has harms, which need to be weighed against those benefits, the most important of which is an increased risk of gastrointestinal bleeding.

The balance of benefits and harms is likely to vary from one person to another. Someone with risk factors for cancer and heart disease but not for gastrointestinal bleeding is likely to benefit from aspirin, whereas someone with a history of gastrointestinal bleeds would be more likely to be harmed by aspirin. I don’t see anything in this new paper that gives an unambiguous answer to how we determine who would benefit from aspirin and who wouldn’t.

One important statistic in the paper was the effect on all-cause mortality, in other words not just deaths from cancer, but deaths from anything else as well. If all-cause mortality were reduced in the aspirin patients, then that would give a pretty good clue that the overall benefits outweigh the overall harms, at least in patients similar to the ones studied (although it’s still not a perfect measure, as it ignores any benefits or harms that don’t affect mortality, such as non-fatal gastrointestinal bleeding, which can seriously ruin your day even if it doesn’t kill you).

The results here were a little inconsistent. In-trial all-cause mortality (ie deaths among patients who were still taking part in the trials at the time of death) was slightly, but significantly reduced, from 11.1% to 10.2%., P = 0.047. Taking account of deaths occurring after the trials as well, mortality was significantly reduced after 15 years of follow-up (hazard ratio 0.92, 95% CI 0.86 to 0.99, P = 0.03), but not after 20 years of follow-up (hazard ratio 0.96, 0.90 to 1.02, P = 0.37). On the whole, it does appear that aspirin reduced all-cause mortality, but the results are suggestive, rather than compelling.

It’s also important to note that many of the patients in the trials had cardiovascular risk factors, and their all-cause mortality may have been more favourably affected than the general population, because of aspirin’s effect on cardiovascular mortality. So there is no guarantee that those figures for all-cause mortality would generalise to everyone.

I don’t think we are quite at the point where aspirin should be recommended for everyone over the age of 50 who doesn’t have any contra-indications (such as a history of gastrointestinal bleeding). We still need a better estimate of the effect of aspirin on all-cause mortality, particularly in different groups of patients with different combinations of risk factors, as well as a better assessment of exactly what the trade-off is between non-fatal benefits and risks. Maybe when further research has given us those answers it will become the default position for everyone to take aspirin, although I suspect it’s always going to remain a personal choice, based on an individual assessment of the importance of different outcomes.

As for me, I’m not going to start taking aspirin every day, but I will certainly keep watching the literature with interest. Another positive paper for aspirin might just convince me that I should start taking it.

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I have now had a further response, which frankly beggars belief. If anyone were in any doubt that the ASA (which, let’s remember, is funded by the advertising industry) is simply there to act on behalf of advertisers and let them get away with any ridiculous claims they like, no matter how far removed from the truth they are, then I think this response should remove any such doubt.

They are now stating that they do not believe the advert includes any specific claim to protect against disease. To quote from the letter:  ”The advertiser does not appear to make specific claims about the products [sic] efficacy against diseases and we do not consider viewers are likely to be detrimentally misled by the content of [sic] and claims made.”

What on earth do they think “Dettol protects” is claiming, if not claiming to protecting against disease? Do they think that the advert is claiming that Dettol protects against burglary? Perhaps we are supposed to think it protects against evil spirits? Or maybe a zombie apocalypse?

If anyone has any suggestion for what “Dettol protects” could reasonably mean if it doesn’t mean “Dettol protects against disease”, I would love to hear it.

When the ASA takes such a plainly ridiculous position as this to avoid having to investigate one of their mates in the advertising industry, the only conclusion we can reasonably draw is that anything we see in an advert in the UK has no guarantee of credibility whatsoever.

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