STARD WARS

I’m working on my MSc dissertation (Sensitivity and specificity of molecular methods for detecting markers of antimalarial resistance in clinical samples of Plasmodium falciparum: a systematic review) and I’ve been trying to track down eligible studies.

All the studies should be easily found in bibliographic databases, and all the data I need should be in the published papers, right?

Of the 35 potentially eligible studies:

  • 17 report too little data for me to be able to extract the results I need.

What would the results of my review be if I could include this data? Maybe leaving out nearly 50% of eligible studies which report data from over 50% of participants isn’t ideal and might affect the validity of my results?

I thought trial registries might be useful for finding out more.

Of 35 potentially eligible studies:

  • None were registered, either prospectively or retrospectively.

(One study had an associated study of adherence to rapid diagnostic tests registered – results not provided).

So I have no idea if study protocols were changed, had missing outcomes, new outcomes…

Trial registries were not helpful for checking details of studies I know exist. How many studies are there that I don’t know exist?

Are my systematic review results going to be bollocks due to all the different biases introduced by crappy study designs and ad hoc changes, unpublished studies, outcome switching, and missing data from published studies?

And how can I find out, if I can’t ever know how much data I’m missing or how biased the data I have is?

It should be so simple..

REGISTER AND REPORT – diagnostic test accuracy studies can be registered at any of the registries listed in Table 1 of this great paper, and should be registered somewhere prospectively. They should be reported according to STARD.

Even using the resources I have free and easy access to – the Bodleian, the British Library, and kind friends at plenty of other institutions with awesome libraries, I still couldn’t get all the papers I might have wanted. So what is everyone else supposed to do?

OPEN ACCESS – often funded by public money, often work done by public employees, time and samples and personal data always donated by members of the public – make OUR data available to us, the people you’re doing it for/with.

Fair disclosure, we didn’t register the one study on which I’m a co-author. Or report it following STARD. I am going to register it retrospectively. And we did report enough data in the published paper for inclusion in my systematic review.

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Bugs AND bollocks

Stemming from one research paper is a google* of total wank.

*now a collective noun

 

Headlines.png

Minus points to The Sun for worst pun-biggest misleading stat combination


 

 

So who has covered themselves in glory? From the top hits, pretty much everyone. NPR, WebMD, The Sacramento Bee (?), CBS, Time, the BBC, the Huffington Post, The Sun

Many of these pieces contained small sections discussing the limitations of the research paper, and clarifying the difference between correlation and causation. BUT. They spent WAY MORE space speculating about possible mechanisms that would explain a causal link. The overwhelming feeling reading each of these articles is that there is little doubt that pubic hair removal causes an increased risk of STIs.

 

I found one well-written article at Lifehacker which made it clear through that this was an association and…

lifehacker

…(excited squeak) ACTUALLY LINKED TO THE RESEARCH PAPER! Full points.

 


 

I’m not a fan of the research paper itself.

paper

Observational studies are important. Observational studies that are well designed to investigate their question of interest are much more important. Obviously. This is not one of those.

In a study of a possible association with, or cause of, STIs, would you:

  1. Want to know about safer sex and condom use? These researchers didn’t.
  2. Assume that people are open and honest about sex and STIs? These researchers did.
  3. Assume that people can accurately remember their lifetime history of STIs and pubic hair removal? These researchers did.

 

 

Confounders

Younger people might remove more hair, more often than older people. They might be having sex more often with more people, more recently. They are doing this in an era with higher prevalence and transmission of STIs.

People who are lucky enough to be having lots of sex or sex with lots of people might be more inclined to remove more pubic hair more often. Ask any woman about hair removal. EVERYONE KNOWS you don’t make a real effort unless someone is going to notice. Shave your legs in the winter in the absence of a new(ish) naked friend? NO WAY. Bikini line unless you’re going to the beach? NEVER.

 

Science = having sex means a higher risk of STDs.

Common sense = having sex means higher chance of removing body hair.

 

For the benefit of the Huffington Post:

huff

People removing pubic hair are having more sex with more people, and the more sex with more people is giving them more STIs. That’s why.

 

Probably. I’m going to need a really interesting RCT to be sure.


Some unconnected and enjoyable advice…

 

Magic Bacteria I

I try to be logical about which health charities I support (those that make the greatest difference to the most people) and which research excites me (useful, high quality) but my brain snags on Alzheimer’s.

Alzheimer’s is a big deal. Dementia (including Alzheimer’s) currently affects approximately 48 million people. It can affect “memory, thinking, orientation, comprehension, calculation, learning capacity, language, and judgement”, which is basically everything that makes you, you. There’s no cure, no treatment, and we don’t really know why some people get it and others don’t.

So a bit more clarity and the hope of any treatment would be a wonderful thing.

tele

sun

mail

The Mail gets in a little bit of fear-based selling on the side…

A quick look, and you might be considering taking probiotic supplements.

So why does this report make me grumpy? Not because I used critical appraisal tools http://www.cebm.net/critical-appraisal/ to carefully consider the paper. I got bored half-way through. Instead, here are some pet peeves.

A 12-week study is NOT LONG ENOUGH. People can have Alzheimer’s for over a decade. I need to know what happens to people who have Alzheimer’s for more than 12 weeks.

60 patients is NOT ENOUGH PARTICIPANTS, especially as 8 of them died before the study finished. The trialists managed to get some statistically significant stats – but having lost 13% of their participants, perhaps you would expect some variation between baseline and end of study results? How did they know 60 people was enough to detect the difference they hypothesised? How applicable are these results of these 60 people to the other 48 million?

15 different biomarkers, WHO CARES. Might be useful for mechanistic proof of concept. But are they outcomes relevant to patients? Or have they be stuck in post-hoc to ramp up the number of significant outcomes? Outcome switching.

Mini-mental state examination (MMSE) started at 8.47 (±1.10) and decreased to 8.00 (±1.08) in the control group. MMSE started at 8.67 (±1.44) and increased to 10.57 (±1.64) in the probiotic group. The numbers are statistically significantly different. But are the patient’s symptoms clinically significantly different? NHS Choices says probably not (they already thought of the things I wrote). So WHAT IS THE BENEFIT FOR PEOPLE WITH ALZHEIMER’S?

This trial does not show a benefit (or show lack of benefit) of probiotics in reducing symptoms of Alzheimer’s – because the trial hasn’t been well enough designed. And the reporting was crappy. THIS MAKES ME GRUMPY.

What’s the evidence: Do chickens prevent malaria and Zika infections?

It’s been four weeks since this paper was published, but I’ve been on holiday and received a lot of insect bites, so my interest in a chicken mosquito-deterrent hasn’t waned.

The Telegraph had the headline:

“Suspending a chicken over your bed could protect against Zika virus and malaria”.

They also had some fairly confident remarks from one of the authors about the size of the effect

“can cut populations by up to 95 per cent throughout an entire house, so it’s very efficient”

and possible utility of their tested compounds

“I think it should [prevent Zika]. We haven’t tested it on other mosquitoes but there are lots of varieties which won’t feed on chickens and so would be repelled.”

Malaria kills hundreds of thousands of people each year. Zika is disabling and afflicting thousands this year. Headlines and quotes like this generate a huge amount of hope. But is it false hope? What’s the evidence?

Rooster_portrait2.jpg

Photo by Muhammad Madhi Karim

This paper included many different useful and interesting pieces of work. The researchers:

  • collected data on the populations of human and domestic animal species in three villages
  • collected blood-fed mosquitoes from 10 houses and 5 pit shelters in three villages
  • identified mosquito species and source of last blood meal
  • collected headspace samples from 5 individuals from each species in 1 village
  • reared an Anopheles arabiensis colony
  • analysed chemicals present in the headspace of different species
  • measured electrophysiological response of antennae to samples and isolated compounds
  • counted mosquitoes captured in CDC suction traps baited with control solvent, synthetic compounds or a live chicken

 

This is a huge amount of work, so I’m going to focus on the question that seems to be of most interest:

 

Can chickens, or compounds extracted from chickens, reduce malaria or Zika infections in humans better than current mosquito repellents?

 

If this is the question of interest (although we may be more interested in whether we prevent deaths, or disability, rather than reducing the number of cases) then the key evidence is that generated in the final point. From the other aspects of this paper we can see that they started off well. They identified villages with mosquitoes. They identified the species of mosquito that would be present, and that these mosquitoes might be likely to bites humans indoors. They identified compounds that showed activity in a laboratory setting. Then they carried out a randomised controlled trial to see whether these compounds would reduce the number of mosquitoes captured in a trap near sleeping humans.

 

They found that compared to solvent only, the four identifiable chicken compounds, two host compounds, and a live chicken, significantly reduced the number of mosquitoes captured in a suction trap. This sounds really promising – but there are problems.

 

Surrogate outcome

They’re not measuring how many cases of malaria or Zika were prevented, and they’re not counting the number of bites people received. They are only counting the number of mosquitoes were captured in a trap near a person – which might be a very poor surrogate for measuring how many cases of malaria or Zika were prevented.

 

Study site

They chose one of the three villages they studied in Ethiopia. Is this relevant to Zika transmission in cities in Brazil? Is it representative of the other populations in which mosquito repellents might be used?

 

Mosquitoes

The species of mosquito examined is one that transmits malaria in some areas, but does not transmit Zika – how certain are we that these findings would be replicated in other mosquito species?

 

Control group

The control they used was solvent – the same solvent that some of the tested compounds were solubilised in. Perhaps it would have been more useful to know how the test compounds compared to existing repellents. I’m not sure what a good control for a live chicken would be…

 

Statistical analysis

The statistical analysis was carried out post-hoc (with no mention of the analysts being blinded to the treatment groups) – the data was examined, then a method for analysing it was devised – this is known to lead to bias giving more positive findings.

 

Other sources of bias

Randomisation method, allocation concealment, blinding of personnel and outcome assessment, missing data and selective reporting – none were adequately described by the paper, but none seemed likely to be the source of a high risk of bias.

 

In summary, I think the findings of the RCT are likely to be fairly accurate. But they don’t justify the hype and the hope. This is not evidence that chickens prevent cases of Zika or malaria. When we have an RCT that looks at the mosquito species relevant to both diseases, in a variety of settings in which a repellent would be used, examining the effect of the repellent compared to the current best repellent, and examining the number of deaths, disabilities and infections, and finding at least one of the first two significantly reduced, then we can get really excited.

What’s the evidence: can cranberry products prevent UTIs?

No.

But for more detail read this systematic review of RCTs. It’s a Cochrane systematic review, so it has a good abstract and an excellent plain language review if you don’t have much time.

cochrane cranberries

How good it the evidence?

It’s a systematic review with meta-analyses, so it’s at the top of the quality of evidence pyramid:

Evidnec pyramid

This review scores 10/11 using the AMSTAR tool to assess the quality of the systematic review. The AMSTAR tool identifies good practices that reduce the introduction of bias – all 11 areas are evidenced to be important sources of bias in systematic reviews. 10 is good. The other reviews I’ve appraised recently have scored 2-4. It gets a 10 because:

  • The review provides an a priori design
  • Duplicate study identification and data extraction were carried out
  • It undertook a comprehensive literature search
  • The review didn’t exclude unpublished data
  • A list of included and excluded studies was provided
  • Characteristics of the included studies were provided
  • Scientific quality of the included studies was assessed and documented
  • Quality of the included studies was used appropriately in formulating conclusions
  • Methods used to combine the findings of studies were appropriate
  • Conflict of interest was stated

However

  • The likelihood of publication bias was not assessed

Overall, we can be pretty sure that the systematic review can be trusted to give us the true answer based on the available (crappy, better than nothing, see figure 2 for their risk of bias assessment) data.

cranberries no

Not these chaps

cranberries yes

These chaps

What are the results?

The summary of results is that “cranberry products do not significantly reduce the risk of repeat symptomatic UTI compared to placebo or no treatment in groups of people at risk of repeat UTI (overall RR 0.86, 95% CI 0.71 to 1.04) or for any of the subgroups analysed.”

RR (relative risk or risk ratio) of 0.86 means that if you compared people who didn’t have cranberry with people who did have cranberry, for every 100 cases in people who didn’t get cranberry, 86 cases occurred in people who did have cranberry. However, this doesn’t mean cranberry works – take a look at the confidence intervals (CI). They span 1.00, which means that the difference seen between these groups may well have arisen by chance.

If this study was repeated, each time it was done, there would be a 95% chance that the 95% CI included the true risk. These 95% CI (0.71 to 1.04) do not show a statistically significant difference and do not exclude the possibility that cranberry products might be making things worse (104 people get cystitis instead of 100) rather than better.

The absolute risk (AR) and number needed to treat (NNT) would be much more informative than RR, but the review doesn’t provide them. Given that the reviewers used a random effects model, it would take me a bloody age to calculate them. And, the results show no difference between people taking cranberry products and those not, so calculating AR and NNT would be an academic exercise and clinically useless. And, the risk for different people in the general population varies hugely, so even if the results were statistically significant, and I could be arsed to calculate the AR and NNT, it still wouldn’t provide a useful statistic for the general population to use to understand our risk.

An aside, I think it’s worth thinking about why we aren’t more skeptical of magical fruit. Consider not buying expensive urine until there’s evidence that for you there are useful benefits (less cystitis) that outweigh harms (expending a finite financial resource, having to drink vast quantities of bitter super-staining juice every day for ever, or eat tablets every day for ever (not fun, as anyone who actually has to knows) and propping up quack shops and drug companies that prey on the trusting, vulnerable and desperate).

cranberries.png

Should wear a mask and a striped jumper

What’s the evidence: Does Ibuprofen cause skin and blood infections in children with chickenpox?

NOT A DOCTOR. NOT MEDICAL ADVICE. Only for thought.

Does Ibuprofen cause skin and blood infections in children with chickenpox?

What are doctors told?

The National Institute for Health and Clinical Evidence (NICE) Clinical Knowledge Summary “Scenario: management of an otherwise healthy child or adult with chickenpox”:1

NICE Clinical Knowledge Summary “Analgesics / Antipyretics”:2

What evidence is used to tell doctors this?Evidnec pyramid

What we’re hoping for is the highest quality of evidence to answer our question so we can be more certain in the answer. Mostly, the best evidence is at the top of the pyramid, and the quality of the evidence decreases as you move down the pyramid.

The guidelines reference three papers to support their recommendations:

Heininger and Seward, 2006

Bilj, 2010

Mikaeloff et al., 2008

Heininger and Seward, 2006 is a review, but it isn’t a systematic review, so it isn’t at the top of the evidence pyramid. We need to look at where they got their evidence from.

They reference two papers:

Lesko et al., 2001

Zerr et al., 1999

So, we can see that the guidelines for doctors are based on 4 original research papers (although these papers reference other papers too). What is the quality of this evidence?

Bilj, 2010

I couldn’t access this paper. This is very annoying. It means we can’t assess the quality of the research. It is also completely unreasonable that guidelines for treating us are based on evidence we can’t see.

Mikaeloff et al., 2008

The study design

A case-control study, half-way down the quality of evidence pyramid. Using the General Practice Research Database it looked at UK patients with chickenpox or shingles for at least two days, between 1994 and 2005. 386 patients with chickenpox had “severe skin or soft tissue complications”. They matched each of these patients with 10 of the patients who had chickenpox but no skin or soft-tissue infections. Then they worked out how much more likely the patients with skin infections were to have been given a prescription for ibuprofen.

The results

12 of 386 patients with severe skin or soft tissue complications took ibuprofen. 14 of 2402 patients without severe skin or soft tissue complications took ibuprofen. The relative risk is 5.2 (patients taking ibuprofen were 5x more likely to have severe skin or soft tissue complications). The absolute risk increase is 0.025 (patients taking ibuprofen increased their risk of severe skin or soft tissue complications by 0.025). The number of patients that would have to be prescribed ibuprofen for one patient to be harmed is 40.

The problems

Case-controls studies are subject to more and greater biases than research further up the pyramid. The patients in this study are adults and children – they have an average age of about 11 years old, but we don’t know the age of the patients who developed skin or soft-tissue infections – and we want to know the answer for children. They found 386 patients with severe skin or soft tissue complications, of whom only 26 had taken ibuprofen. This is very few patients if you want to work out the role of ibuprofen, which, if it is a risk factor, is likely to be a very small risk factor. With numbers this small the results are highly subject to chance. The way that they found out who took ibuprofen was to look at who had been prescribed ibuprofen – this will over-count patients who received a prescription but didn’t collect it from the pharmacy or didn’t take it, and will not count patients who buy their ibuprofen over the counter (30p a packet).

Can we trust the results?

I think not. This study ignored patients who took ibuprofen bought over the counter, which is how almost all of us access ibuprofen. Patients who were more ill, and more likely to develop skin or soft-tissue infections would have been more likely to see a GP and to have a record of a prescription for ibuprofen. These factors will make ibuprofen look much worse than it is. The number of patients is very very small (26 who were prescribed ibuprofen). It is highly likely that this result has arisen by chance.

 

Lesko et al., 2001

The study design

The study design is a case-control study, half-way down the quality of evidence pyramid. They included children who had been admitted to hospital in the USA, with chickenpox and “invasive or necrotising soft tissue infection”, between 1996 and 1998. 52 patients with chickenpox had invasive Group A streptococcal infection. They matched each of these patients with 4 of the patients who had chickenpox but invasive Group A streptococcal infection. Then they worked out how much more likely the patients with skin infections were to have been given a prescription for ibuprofen.

The results

18 of 52 patients with invasive Group A streptococcal infection took ibuprofen. 36 of 172 patients without invasive Group A streptococcal infection took ibuprofen. The relative risk is 1.7 (patients taking ibuprofen were nearly 2x more likely to have invasive Group A streptococcal infection). The absolute risk increase is 0.14 (patients taking ibuprofen increased their risk of severe skin or soft tissue complications by 0.14). The number of patients that would have to be prescribed ibuprofen for one patient to be harmed is 7.

The problems

Case-controls studies are subject to more and greater biases than research further up the pyramid. The cases in this study have been hospitalised but control patients haven’t. It seems likely that sicker children are more likely to be hospitalised, and more likely to have been given more medication (including ibuprofen). They found 52 patients with severe skin or soft tissue complications, of whom only 18 had taken ibuprofen. This is very few patients if you want to work out the role of ibuprofen, which, if it is a risk factor, is likely to be a very small risk factor. With numbers this small the results are highly subject to chance. The way that they found out who took ibuprofen was either to examine medical records (cases) or to interview the parents (controls). Asking people what they remember giving to their child before something dramatic (hospitalisation) didn’t happen, is not likely to be a reliable source of data, and exposure (to ibuprofen) may well be underreported.

Can we use and trust the results?

Maybe. If sicker children are more likely to be hospitalised and more likely to have been given more medication then these results will make ibuprofen look worse than it is. The number of patients is very small (54 who took or reported taking ibuprofen). It is quite possible that this result has arisen by chance.

 

Zerr et al., 1999

The study design

A case-control study, half-way down the quality of evidence pyramid. It compares children hospitalised for necrotising fasciitis who recently had chickenpox, with children hospitalised for a “different soft tissue infection” who recently had chickenpox. Between 1993 and 1994 48 patients were examined. Then they worked out how much more likely the patients with necrotising faciitis were to have taken ibuprofen.

The results

9 of 19 patients with necrotising fasciitis took ibuprofen. 4 of 26 patients with a different soft tissue infection took ibuprofen. The relative risk is 3.2 (patients taking ibuprofen were 3x more likely to have necrotising faciitis than a different soft tissue infection). The absolute risk increase is 0.32 (patients taking ibuprofen increased their risk of necrotising fasciitis by 0.32). The number of patients that would have to be prescribed ibuprofen for one patient to get necrotising fasciitis is 3.

The problems

Case-controls studies are subject to more and greater biases than research further up the pyramid. All these patients had an infection – so we are comparing different types of infections – but what we want to know is whether ibuprofen causes any infection. They found 48 patients with skin or soft tissue complications, of whom only 13 had taken ibuprofen. This is very very few patients if you want to work out the role of ibuprofen, which, if it is a risk factor, is likely to be a very small risk factor. And, as we saw before, this study isn’t even asking the question we want to answer – which is whether ibuprofen increases any infection. With numbers this small the results are highly subject to chance. This study tests 20 different risk factors. The more risk factors you look at, the greater the chance of one of them giving a positive result by chance. P=0.05 is commonly used as a measure of significance. Using this p value there is a 1/20 chance that a positive result will arrive by chance. This paper has looked at 20 outcomes… so we would expect that one would be positive just by chance.

Can we use and trust the results?

I think not. The question being tested is related to, but is not the question we want to answer. The number of patients is very very small (13 who were prescribed ibuprofen), and the authors examined 20 risk factors. It is highly likely that this result has arisen by chance.

In summary

I don’t think that any of these three studies is reliable. The hidden study might be better, but how do we know? All three visible studies give a hint that ibuprofen might be a problem. But none of them show that ibuprofen is a risk-factor for skin and blood infections in children with chickenpox, and they don’t demonstrate that ibuprofen causes skin and blood infections. The clinical guidelines (which doctors often rely upon) are based on very unreliable evidence. There is other evidence out there but it will take longer than I have to trawl through. Bearing in mind that NICE are probably better equipped for this than me, and that these are the papers they referenced, I think it is unlikely that any better quality research exists.

VZV+thCHJUU1Q8=thP0IRT37F

So, what’s the evidence? Does Ibuprofen cause skin and blood infections in children with chickenpox?

We don’t know. There is very shaky clinical evidence to suspect it might, and no reliable clinical evidence to show it does.

STILL NOT A DOCTOR. STILL NOT MEDICAL ADVICE. Hope it makes you think though.

Grosse Point Blank

While visiting Eccles with my brother, I found this plaque on a pub.

IMG_20160124_112854

It’s a reminder of one of the outbreaks of cholera that occurred in the UK, many of which were epidemics killing hundreds or thousands of people. The pub isn’t lovely, but that’s the current-Eccles-factor rather than the past-cholera-factor.

The story of cholera in the UK is special, because it is also the story of the birth of epidemiology, and a part of the story of the development of our understanding of disease transmission.

In 1854 there was an outbreak of cholera in Soho, in London. As a skeptic of the miasma theory (that bad air caused disease), John Snow (a doctor from York, handy with anaesthetics) proposed an alternative theory; that it might be transmitted by polluted water. His skepticism and theory were shared by others working contemporaneously with him, and before him, although he was not aware of much of their work.

Not this Jon Snow.

jon-snow2

Not this Jon Snow.

jon-snow

This John Snow.

John SNow

 

John Snow wrote an essay on this theory of cholera outbreaks in 1849, helped found the Epidemiological Society of London in 1850, and by observing and graphing the pattern of the outbreak in 1854 was able to prove the source of the outbreak. He used a new(ish) type of graph (used years before by Thomas Shapter) – a dot map – with a dot in the geographical location of each case of cholera. By observing the distribution of the dots (cases) and by interviewing residents he was able to find a pattern in the location and behaviour of people who had contracted cholera – they all used a public water pump on Broad Street.

Snow-cholera-map-1

The outbreak was subsiding by the time John Snow had enough evidence to act (people tend not to stick around if there’s a reasonably high chance of a horrible death). He had the handle of the pump removed, and the cases of cholera stopped. Later it was discovered that a cesspit was leaking into the public well. Drinking faeces was not a fashionable hobby then (unlike today), so rather than admit that was what had been happening, the pump handle was replaced so that everyone could quietly keep doing it.

And we’re still doing it! In the last two months there have been cholera outbreaks in Mozambique (Mocuba), Iraq (Baghdad), Muscat (Iran), Uvinza, Mwanza and Dar es Salaam (Tanzania), Kye-thi (Myanmar), Naivasha (Kenya) and South Kivu (Democratic Republic of the Congo). Those in Iraq and Tanzania have been particularly bad, killing many thousands of people.

Outbreaks of cholera can mostly be prevented by separating sewage (dirty) from the drinking water supply (ideally clean), but clean water and toilets are not exciting. Money invested in development projects and given to charities providing these facilities goes a long way. The problem is we’re not into evidence-based giving. And we like donkeys better than people anyway. And cholera is not glam. It’s been around for a very long time. It’s not exciting looking. It’s totally preventable. It’s totally treatable. BORING. And you basically vomit and poo yourself to death. GROSS.

Zika anyone? zika

We’d rather the antimicrobial apocalypse than be denied useless antibiotics

Apocalypse_vasnetsov

This research came out this week…

Antibiotic prescribing and patient satisfaction in
primary care in England:
cross-sectional analysis of national patient survey data and prescribing data

…showing that antibiotic prescribing volume is a significant positive predictor of ‘doctor satisfaction’ and ‘practice satisfaction’…

and

…antibiotic prescribing volume is the single strongest positive predictor (of 13 prescribing variables) of overall satisfaction.

Table 3 has some other interesting data on prescribing practise and patient satisfaction.

This is an observational study, and can’t prove a relationship, but it is a good clue. More research required, as (almost) ever…

Apocalypse Now (no, really)

I woke up yesterday morning to a litany of death… because Pete has changed the radio station to BBC4.

Every single story was death; refugees fleeing death, a child found dead, babies dying unexpectedly, and people, all of us, who are going to die because complete antibiotic resistance has been found and it’s just a matter of time before it spreads and kills us all.

I’ve changed the radio station (thank you BBC6).

The scientific paper portending antibiotic-resistance doom, is this one:

Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study

Snappily named, but what does that mean, and should BBC4 be scaring me at 7am? Is the fear-mongering justified? What did the research actually find, and what is the context?

Some of these scientists were carrying out a routine surveillance project on antimicrobial resistance in commensal Escherichia coli from food animals in China.

Antimicrobial resistance is when microorganisms which cause infections are not killed or their growth is not stopped by a medicine that would normally kill or stop them.

Commensal is from medieval Latin commensalis, from com- ‘sharing’ + mensa ‘a table’; these E.coli bacteria obtain food from the food animals, without affecting the food animal.

E coli Ag Res Mag

Food animals (simply, but oddly named) are animals bred to become human food.

So the scientists were checking, as they routinely do, to see if any E. coli living with (but not hurting) animals for our food, are not killed by medication that they are normally killed by.

They found an increase in the number of colistin resistant microorganisms in their food animals, and isolated (from a pig) a strain of E. coli with colistin resistance that could be transferred to another strain of E. coli that was not previously resistant.

Colistin is an antibiotic, first derived from bacteria in 1949. It’s a type of antibiotic called a Polymyxin. We don’t use it to treat infections in humans (unless we have to) due to its nephrotoxicity (from the Greek for kidney ‘nephros’) – it poisons kidneys. It is a last resort antibiotic for treating some bacterial infections which are resistant to other less harmful (to humans) antibiotics.

So they found more E. coli than they have found before, that are resistant to colisitin.

Resistance to colistin isn’t new – it was first described in vitro in 1960, and although it is rare in infections affecting humans, one paper last year described 13 cases in India. It is the mechanism of spread of resistance to colistin that is new here – that resistance can be transferred from one strain of E. coli to another, via horizontal gene transfer. Vertical gene transfer would be parent E.coli to baby E.coli, which we would expect. Horizontal gene transfer is parent E.coli straight to another parent E.coli. Before now, resistance to polymyxin antibiotics, including colistin, via horizontal gene transfer, has never been found.

Having found this resistance, and the pattern in which it could be transmitted, the researchers tried to identify how resistance was transmitted.

They found a plasmid-mediated resistance mechanism, MCR-1.

MCR-1 is a gene in a plasmid (a plasmid is a small DNA molecule, separate from the chromosomal DNA, that can replicate independently; they are commonly found in bacteria). This gene in the plasmid, in the E.coli bacteria, living happily in the pig, is responsible for the resistance to colistin.

Pig_USDA01c0116

This gene can be transferred to other bacteria, Klebsiella pneumoniae and Pseudomonas aeruginosa, and stay in these organisms, which leads to the theory that the gene might be (without our interference) transferring to other organisms and spreading in those populations too.

So why is this such as big deal?

Because we are running out of tools to treat infectious diseases. It isn’t just these cases, or these bacteria, or these drugs. People have been trying to raise awareness of this problem and the consequences for years. We know that we have resistance to antimicrobials in many diseases caused by infectious agents, including parasites, bacteria, viruses and fungi. Malaria. Tuberculosis. HIV. Candida. MRSA. Gonorrhea. Pneumonia. Cystitis. We know that resistance to more drugs is increasing. We know that resistance is spreading geographically. As antimicrobial resistance increases and spreads, we won’t be able to successfully treat these diseases. We are developing new antimicrobials, and finding new ways to discover them, but this progress needs to outpace resistance, and currently, it doesn’t.

Without effective antimicrobial agents we won’t be able to treat many diseases that are currently, rarely fatal. We won’t be able to continue to control the spread of diseases – currently contained(ish) disease will spread more quickly and widely.

It’s not just people with infectious diseases that this will affect. We won’t be able to undergo surgery safely, as any post-surgical infections may be fatal. Giving birth will become very dangerous. Some people – those at high risk of infection, and those who are unable to fight off of infections (babies, older people etc.) will be much less likely to survive.

There are many ways we could decrease the development and spread of antimicrobial resistance but we’re simply not doing many of them. We are all responsible for these actions. Preventing transmission by washing our hands, using condoms, and getting our vaccinations. Not demanding antibiotics from doctors unless they are effective against our illness, and always finishing a full course of antibiotics. Not prescribing antibiotics to keep your patients quiet, and keeping up with best clinical practise for reducing development of drug resistance. Not eating meat that has been routinely fed antibiotics. Supporting campaigns and research that will preserve and develop treatment options.

We’re not all doomed yet, but we will be unless we change. BBC4 should be scaring all of us at 7am. It isn’t fear-mongering. We all need to change the way we use antimicrobials.