Posts filed under Medical news (285)

March 25, 2015

Translating from Scientist to English

Stories were coming out recently about new cancer research led by Bryony Telford in Parry Guilford’s lab at Otago, and I’d thought I’d use it for an example of translation from Scientist to English. It’s a good example for news because it really is pretty impressive, because it involved a New Zealand family with familial cancer, and because the abstract of the research paper is well written — it’s just not written in ordinary English. Combining the abstract with the press release and a bit of Google makes a translation possible.

This will be long. (more…)

March 19, 2015

Model organisms

The flame retardant chemicals in your phone made zebra fish “chubby”, says the caption on this photo at news.com.au. Zebra fish, as it explains, are a common model organism for medical research, so this could be relevant to people

591917-2a8735a0-cced-11e4-a716-dcac481e1bbe

On the other hand, as @LewSOS points out on Twitter, it doesn’t seem to be having the same effect on the model organisms in the photo.

What’s notable about the story is how much better it is than the press release, which starts out

Could your electronics be making you fat? According to University of Houston researchers, a common flame retardant used to keep electronics from overheating may be to blame.

The news.com.au story carefully avoids repeating this unsupported claim.  Also, the press release doesn’t link to the research paper, or even say where it was published (or even that it was published). That’s irritating in the media but unforgivable in a university press release.   When you read the paper it turns out the main research finding was that looking at fat accumulation in embryonic zebrafish (which is easy because they are transparent, one of their other advantages over mice) was a good indication of weight gain later in life, and might be a useful first step in deciding which chemicals were worth testing in mice.

So, given all that, does your phone or computer actually expose you to any meaningful amount of this stuff?

The compounds in question, Tetrabromobisphoneol A (TBBPA) and tetrachlorobisphenol A (TCBPA) can leach out of the devices and often end up settling on dust particles in the air we breathe, the study found.

That’s one of the few mistakes in the story: this isn’t what the study found, it’s part of the background information. In any case, the question is how much leaches out. Is it enough to matter?

The European Union doesn’t think so

The highest inhalation exposures to TBBP-A were found in the production (loading and mixing) of plastics, with 8-hour time-weighted-averages (TWAs) up to 12,216 μg/m3 . At the other end of the range, offices containing computers showed TBBP-A air concentrations of less than 0.001 μg/m3 . TBBP-A exposures at sites where computers were shredded, or where laminates were manufactured ranged from 0.1 to 75 μg/m3 .

You might worry about the exposures from plastics production, and about long-term environmental accumulations, but it looks like TBBP-A from being around a phone isn’t going to be a big contributor to obesity. That’s also what the international comparisons would suggest — South Korea and Singapore have quite a lot more smartphone ownership than Australia, and Norway and Sweden are comparable, all with much less obesity.

March 18, 2015

Men sell not such in any town

Q: Did you see diet soda isn’t healthier than the stuff with sugar?

A: What now?

Q: In Stuff: “If you thought diet soft drink was a healthy alternative to the regular, sugar-laden stuff, it might be time to reconsider.”

A: They didn’t compare diet soft drink to ‘the regular, sugar-laden stuff’.

Q: Oh. What did they do?

A: They compared people who drank a lot of diet soft drink to people who drank little or none, and found the people who drank a lot of it gained more weight.

Q: What did the other people drink?

A: The story doesn’t say. Nor does the research paper, except that it wasn’t ‘regular, sugar-laden’ soft drink, because that wasn’t consumed much in their study.

Q: So this is just looking at correlations. Could there have been other differences, on average, between the diet soft drink drinkers and the others?

A: Sure. For a start, there was a gender difference and an ethnicity difference. And BMI differences at the start of the study.

Q: Isn’t that a problem?

A: Up to a point. They tried to adjust these specific differences away, which will work at least to some extent. It’s other potential differences, eg in diet, that might be a problem.

Q: So the headline “What diet drinks do to your waistline” is a bit over the top?

A: Yes. Especially as this is a study only in people over 65, and there weren’t big differences in waistline at the start of the study, so it really doesn’t provide much information for younger people.

Q: Still, there’s some evidence diet soft drink is less healthy than, perhaps, water?

A: Some.

Q: Has anyone even claimed diet soft drink is healthier than water?

A: Yes — what’s more, based on a randomised trial. I think it’s fair to say there’s a degree of skepticism.

Q: Are there any randomised trials of diet vs sugary soft drinks, since that’s what the story claimed to be about?

A: Not quite. There was one trial in teenagers who drank a lot of sugar-based soft drinks. The treatment group got free diet drinks and intensive nagging for a year; the control group were left in peace.

Q: Did it work?

A: A bit. After one year the treatment group  had lower weight gain, by nearly 2kg on average, but the effect wore off after the free drinks + nagging ended. After two years, the two groups were basically the same.

Q: Aren’t dietary randomised trials depressing?

A: Sure are.

 

March 13, 2015

Clinical trial reporting still not happening

According to a paper in the New England Journal of Medicine, about 20% of industry-funded clinical trials registered in the United States failed to report their summary results with no legally acceptable reason for delay. That’s obviously not good enough, and this sort of thing is why people don’t like drug companies.

As the paper says

On the basis of this review, we estimated that during the 5-year period, approximately 79 to 80% of industry-funded trials reported summary results or had a legally acceptable reason for delay. In contrast, only 49 to 50% of NIH-funded trials and 42 to 45% of those funded by other government or academic institutions reported results or had legally acceptable reasons for delay.

Um. Yes. <coughs nervously> <shuffles feet>

via Derek Lowe

Feel-good gene?

From Stuff

Suffering anxiety, is not a mark of character, but at least in part to do with the genetic lottery, he says.

“About 20 per cent of adult Americans have this mutation,” Professor Friedman says of those who produce more anandamide, whose name is taken from the Sanskrit word for bliss.

There’s good biological research behind this story, on how the gene works in both mice and people, but the impact is being oversold. The human data on anxiety in the paper look like

feelgood

Combining this small difference with the claim that 20% of people  in the US carry the variant, it would explain about 1% of the population variation in the anxiety questionnaire score. Probably less of the variation in having/not having clinically diagnosable anxiety.

The story continues

“Those who do [have this mutation] may also be less likely to become addicted to marijuana and, possibly, other drugs – presumably because they don’t need the calming effects that marijuana provides.”

The New York Times version mentioned a study of marijuana dependence, which found people with the low-anxiety mutation were less likely to be dependent. However, for other drugs the opposite has been found:

Here, we report a naturally occurring single nucleotide polymorphism in the human FAAH gene, 385A, that is strongly associated with street drug use and problem drug/alcohol use.

People with the mutant, A, version of the gene, the low-anxiety variant, were more likely to have drug problems.  In fact, even the study that found (weak) evidence for lower rates of marijuana dependence found much stronger evidence of higher rates of sedative dependence.

Simple, binary, genetic explanations for complex human conditions are always tempting, but usually wrong.

March 12, 2015

Variation and mean

A lot of statistical reporting focuses on means, or other summaries of where a distribution lies. Often, though, variation is important.  Vox.com has a story about variation in costs of lab tests at California hospitals, based on a paper in BMJ OpenVox says

The charge for a lipid panel ranged from $10 to $10,169. Hospital prices for a basic metabolic panel (which doctors use to measure the body’s metabolism) were $35 at one facility — and $7,303 at another

These are basically standard lab tests, so there’s no sane reason for this sort of huge variation. You’d expect some variation with volume of tests and with location, but nothing like what is seen.

What’s not clear is how much this is really just variation in how costs are attributed. A hospital needs a blood lab, which has a lot of fixed costs. Somehow these costs have to be spread over individual tests, but there’s no unique way to do this.  It would be interesting to know if the labs with high charges for one test tend to have high charges for others, but the research paper doesn’t look at relationships between costs.

The Vox story also illustrates a point about reporting, with this graph

 F1.large-1

If you look carefully, there’s something strange about the graph. The brown box second from the right is ‘lipid panel’, and it goes up to a bit short of $600, not to $10169. Similarly, the ‘metabolic panel’, the right-most box, goes up to $1000 on the graph and $7303 in the story.

The graph is taken from the research paper. In the research paper it had a caption explaining that the ‘whiskers’ in the box plot go to the 5th and 95th percentiles (a non-standard but reasonable choice). This caption fell off on the way to Vox.com, and no-one seems to have noticed.

February 25, 2015

Measuring what you care about

If cannabis is safer than thought (as the Washington Post says), that might explain why the reporting is careful to stay away from thought.

thought

 

The problem with this new research is that it’s looking at the acute toxicity of drugs — how does the dose people usually take compare to the dose needed to kill you right away.  It’s hard to overstate how unimportant this is in debates over regulation of alcohol, tobacco, and cannabis.  There’s some concern about alcohol poisoning (in kids, mostly), but as far as I can remember I have literally never seen anti-tobacco campaigns mentioning acute nicotine poisoning as a risk, and even the looniest drug warriors don’t push fatal THC overdoses as the rationale for banning marijuana.

Alcohol is dangerous not primarily because of acute poisoning, but because of car crashes, violence, cancer, liver failure, and heart damage. Tobacco is dangerous not primarily because of acute poisoning, but because of lung cancer, COPD, heart disease, stroke, and other chronic diseases.

It’s hard to tell how dangerous marijuana is. It certainly causes dependence in some users, and there are reasons to think it might have psychological and neurological effects. If smoked, it probably damages the lungs. In all these cases, though, the data on frequency and severity of long-term effects are limited.  We really don’t know, and the researchers didn’t even try to estimate.

The conclusions of the researchers — that cannabis is over-regulated and over-panicked-about relative to other drugs — are reasonable, but the data provide very little support for them.  If the researchers had used the same methodology on caffeine, it would have looked much more dangerous than cannabis, and probably more dangerous than methamphetamine. That would have been a bit harder to sell, even with a pretty graph.

 

[story now in Herald, too]

February 21, 2015

If it seems too good to be true

The Herald (from the Daily Telegraph) has a story about a new high-antioxidant chocolate

Its makers claim it can change the underlying skin of a 50 to 60-year-old into that of someone in their 20s or 30s.

Actually, in an uncontrolled short-term trial in 400 people they say

“We used people in their 50s and 60s and in terms of skin biomarkers we found it had brought skin back to the levels of a 20 or 30-year-old

The target market is

“elegant, educated and affluent” city-dwelling women in their 30s and businessmen “to support their appearance in a stressful environment and on their business travels”.

or, in other words, people who would be willing to bore on about how young and beautiful their skin biomarkers are, in case you can’t tell by looking.

To be fair, there is independent expert comment (which is not entirely convinced). If you read right to the last sentence you get the real highlight:

Nutrition experts at UCL also warned that previous trials showed that astaxanthin worked better when applied directly to the face rather than ingested.

 

Updated to add: the story was also on Prime News, where they made explicit the point that this really has nothing to do with the chocolate. They could have put the astaxanthin in a pill, but they thought it would be more attractive if they put it in chocolate. A spoonful of sugar makes the medicine go down, etc,

February 20, 2015

Why we have controlled trials

 

joc80747f2

The graph is from a study — a randomised, placebo-controlled trial published in a top medical journal — of a plant-based weight loss treatment, an extract from Garcinia cambogia, as seen on Dr Oz. People taking the real Garcinia cambogia lost weight, an average of 3kg over 12 weeks. That would be at least a little impressive, except that people getting pretend Garcinia cambogia lost an average of more than 4kg over the same time period.  It’s a larger-than-usual placebo response, but it does happen. If just being in a study where there’s 50:50 chance of getting a herbal treatment can lead to 4kg weight loss, being in a study where you know you’re getting it could produce even greater ‘placebo’ benefits.

If you had some other, new, potentially-wonderful natural plant extract that was going to help with weight loss, you might start off with a small safety study. Then you’d go to a short-term, perhaps uncontrolled, study in maybe 100 people over a few weeks to see if there was any sign of weight loss and to see what the common side effects were. Finally, you’d want to do a randomised controlled trial over at least six months to see if people really lost weight and kept it off.

If, after an uncontrolled eight-week study, you report results for only 52 of 100 people enrolled and announce you’ve found “an exciting answer to one of the world’s greatest and fastest growing problems” you perhaps shouldn’t undermine it by also saying “The world is clearly looking for weight-loss products which are proven to work.”

 

[Update: see comments]

February 16, 2015

Pot and psychosis

The Herald has a headline “Quarter of psychosis cases linked to ‘skunk’ cannabis”, saying

People who smoke super-strength cannabis are three times more likely to develop psychosis than people who have never tried the drug – and five times more likely if they smoke it every day.

The relative risks are surprisingly large, but could be true; the “quarter” attributable fraction needs to be qualified substantially. As the abstract of the research paper (PDF) says, in the convenient ‘Interpretation’ section

Interpretation The ready availability of high potency cannabis in south London might have resulted in a greater proportion of first onset psychosis cases being attributed to cannabis use than in previous studies

Let’s unpack that a little.  The basic theory is that some modern cannabis is very high in THC and low in cannabidiol, and that this is more dangerous than more traditional pot. That is, the ‘skunk’ cannabis has a less extreme version of the same problem as the synthetic imitations now banned in NZ. 

The study compared people admitted as inpatients in a particular area of London (analogous to our DHBs) to people recruited by internet and train advertisements, and leaflets (which, of course, didn’t mention that the study was about cannabis). The control people weren’t all that well matched to the psychosis cases, but it wasn’t too bad.  The psychosis cases were somewhat more likely to smoke cannabis, and much more likely to smoke the high-THC type. In fact, smoking of other cannabis wasn’t much different between cases and controls.

That’s where the relative risks of 3 and 5 come from.  It’s still possible that these are due at least in part to some other factor; you can’t tell from just this sort of data. The atttributable fraction (a quarter of cases) comes from combining the relative risk with the proportion of the population who are exposed.

Suppose ‘skunk-type’ cannabis triples your risk, and 20% of people in the population use it, as was seen for controls in the sample. General UK data (eg) suggest the rate in non-users might be 5 cases per 10,000 people per year. So, in 100,000 people, 80,000 would be non-users and you’d expect 40 cases per year. The other 20,000 would be users, and you’d expect a background rate of 10 cases plus 20 extra cases caused by the cannabis. So, in the 100,000 people, you’d get 70 cases per year, 50 of which would have happened anyway and 20 due to cannabis. That’s not exactly the calculation the researchers did — they used a trick where they don’t need the background rate as long as it’s low, and I rounded more — but it’s basically the same. I get 28%; they got 24%.

The figures illustrate two things. First, the absolute risk increase is roughly 20 cases per 100,000 20,000 people per year. Second, the ‘quarter’ estimate is very sensitive to the proportion exposed. If 5% of people used ‘skunk-type’ cannabis, you can run the numbers again and you get 5 cases due to cannabis out of 55 in 100,000 people: only 9% of cases due to exposure.

Now we’re at the ‘interpretation’ quote from the research paper.  In this South London area, 20% of people have used mostly the high-potency cannabis and 44% mostly have used other types, with 37% non-users. That’s a lot of pot.  Even if the relative risks are correct, the population attributable proportion will be much lower for the UK as a whole (or for NZ as a whole).

Still, the research does tend to support the idea of regulated legalisation, the sort of thing that Mark Kleiman advocates, where limits on THC and/or higher taxes for higher concentrations can be used to push cannabis supply to lower-risk varieties.