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January 2010

Another anti-obesity pill bites the dust

Ami Banerjee
Last edited 17th March 2010

If you search PubMed for articles relating to body-mass index, obesity, and mortality you will see an explosion in the number of articles in the last 5 years, as scientists try to characterise and explain the long-term effects of obesity. Perhaps the most impressive data came from an analysis from Oxford, which collaborated data from nearly 900 000 patients in 57 trials. It found that BMI above 25 increases the risk of death, predominantly due to vascular diseases, like coronary heart disease. A BMI of 30-35 reduced survival by 2-4 years; and a BMI of 40-45 reduced survival by 8-10 years, which the authors compared to the effects of smoking. I have written before about the huge public health cost of obesity, estimated at £3 billion per year in the NHS.

Now search PubMed for “anti-obesity” and “weight loss” and you will get 2544 and 71550 hits respectively. This tells you about the research going into finding a cure for obesity and the potential profits from such a cure. These two search terms in Google will give you literally millions of hits from dietary fads and “mandometers” to prescription pills promising to shed those pounds.

This week, two stories relating to fat have dominated the headlines. Firstly, a Royal College of Surgeons conference heard that around one million people meet NICE criteria for weight loss surgery (also known as “bariatric” surgery) with around 240,000 wanting surgery yet only 4,300 NHS weight-loss operations were carried out last year. The Medical Defence Union has also reported a rise in the number of claims against doctors whose patients have suffered complications of obesity-related surgery.

The second story relates to sibutramine (“Reductil”), the weight loss pill that the European Medicines Agency suspended, and the US Food and Drug Administration restricted from its list of licensed drugs. The reason for these decisions is that sibutramine causes a 14% increase in the risk of heart attacks and strokes, compared with placebo. The way in which these decisions have been made raises concerns about the discrepancies between judgments of different drug regulating authorities and how quickly such data should be made available to these regulating authorities. As the BMJ notes, European doctors are now left with only one anti-obesity pill, orlistat (“Xenical”), for use in the treatment of obesity.

It is high time for a dose of reality. Whilst I agree that unequal care to any treatment across the NHS is unethical, we are never going to be able to provide a quarter of a million people bariatric surgery, or to provide everybody with weight-loss pills in a tax-funded, public healthcare system. We need to have a proper debate about personal versus social responsibilities for health and for healthcare, and start talking about the simple public health measures of diet and exercise again.

The horrors of the recent earthquake in Haiti have dominated the news media worldwide, making the UN label it as the “worst disaster it has ever faced”. Obama has enlisted the help of his two immediate Presidential predecessors (Bush and Clinton) to tackle this tragedy. Given George W Bush’s success in global conflict creation and resolution, I am not sure why President Obama felt that he was the best man to deal with such a humanitarian catastrophe. Estimates of the number of deaths in Haiti are around 200 000 at this point and the human toll in terms of future ill health and further deaths is likely to be much more. A massive, international fundraising and humanitarian mission is being mobilised to try to help what was already a troubled state, but is now literally a state of emergency.

It got me thinking about the scale of other public health emergencies that the world has recently faced. Ten years ago, at the turn of the millennium, the UN first recognised that a disease could be a threat to human security with respect to HIV/AIDS. A vicious circle connects ill health, poverty and lack of development, and there is no doubt that the global scale of HIV/AIDS and several other diseases such has coronary heart disease causes a massive burden that threatens the security of whole populations. UNAIDS, the UN’s only organisation devoted to a specific disease, was founded in 1996. Whether or not you agree with the prioritisation of one disease over another, this move by the UN definitely increased the profile of the disease in political, health and wider spheres, in a way that had not been seen before. AIDS is the fourth leading cause of death world-wide (2.9 million deaths per year) and the leading cause in Africa. The top three causes of death globally are ischaemic heart disease (7.2 million deaths), stroke (5.5 million) and lower respiratory diseases (3.9 million).

5 years ago, the South Asian tsunami resulted in “more than 150,000 people dead, tens of thousands of people missing, thousands of miles of destroyed coastline, and loss of livelihood for millions of distraught survivors”. The humanitarian responses to the tsunami in the short and long-term will hopefully give our leaders lessons in how best to deal with the terrible situation in Haiti. There were concerns regarding better data collection in the humanitarian disaster setting and whether the funds raised by the relief effort were: (a) reaching the desired targets, and (b) being spent on long-term as well as short-term healthcare provisions. These concerns are there with respect to the Haitian earthquake as well, making some people very sceptical of fundraising by the many charities that are now clamouring to support Haiti’s crumbled infrastructure.

Conflict and civil war are the other massive killers of our time. For example, in Darfur 1.3 million people were displaced from their homes and least 30,000 people were killed. The Iraq war is estimated to have killed 100 000 civilians. It is very difficult to get similar figures for the conflict in Afghanistan.

This quick comparison leads to two conclusions. Firstly, the devil is in the detail. We have to pay attention to the numbers to get an idea of scale of tragedy, especially in the weeks and months following such disasters. Better data and surveillance is always required. Secondly, although development assistance for improving health in countries of low and middle income has greatly increased in the past 20 years, the scale of the response often does not match the scale of the tragedy. The gap between the scale of the problem and the response cannot be better illustrated by the case of swine flu, and the hunt for the culprit has already begun.

2010: call for reduced bias in clinical studies

Carl Heneghan
Last edited 17th March 2010

Understanding bias in clinical studies can help identify some of the reasons why we reach the wrong conclusions about the effects of interventions. Some of the biases we will be looking out for in 2010 include:

  1. Publication bias: Positive findings are more likely to be published in medical journals than negative findings (Tamiflu). Media coverage of health issues often tends to be biased towards publication of stories which will grab headlines (swine flu).
  2. Citation bias: This one is even more scary than publication bias: published articles tend to cite other articles that support their views rather than those articles which refute their views, and so have a negative impact on the scientific truth.
  3. Selection bias: If the population studied is not representative of the population we want to draw conclusions about, then the study has a selection bias. The Framingham Heart study, for example, studied coronary heart disease in volunteers from a largely white, middle class population, and so we cannot necessarily draw conclusions about heart disease in blacks or other ethnic groups, or in populations in other countries.
  4. Spectrum bias: A spectrum bias occurs when we overestimate how good a test is at picking up or excluding disease, because the test was evaluated in a biased sample of patients. The monofilament is a special tool, used to test whether diabetics have lost sensation in their feet. If it was only tested in people with mild sensory loss, then the monofilament may not be as good at picking up or excluding sensory loss, when it is used on people with severe sensory loss.
  5. Information bias: If the way in which we measure an outcome or an exposure within a study is flawed, then we have an information bias. Data regarding carbon emissions rely on the integrity of countries and companies in their reporting. However, there is some evidence to suggest that such self-reporting (surprise surprise) is leading to gross under-reporting of emissions.
  6. Recall bias: A special case of information bias is “recall bias”, where the ability of subjects to recall an exposure affects the results of a study. The difference between the amount of alcohol that people think that they drink and their actual alcohol consumption is a very good example.
  7. Measurement bias: It is important to know whether the outcome measurement of interest is inaccurate. This can be due to inaccuracy in the measurement instrument or bias in the study participants expectations or responses. Often the way round the latter of these is to ensure adequate blinding.
  8. Funding bias: an evaluation of solutions to sponsorship bias of more than 40 primary studies, and three recent systematic reviews and meta-analyses, have shown a clear association between pharmaceutical industry funding of clinical trials and pro-industry results. In 2010 elimination of such sponsorship bias should be a priority.

The final two biases are personal, in that when recognized, it may be possible to do something about them.

  • Cognitive bias: is the tendency to make errors in judgment based on the way we think. In terms of diagnosis expertise is not a matter of acquiring an all-inclusive reasoning strategy, as several strategies may lead to the same diagnosis. These diagnoses are often correct; however, Clinicians tend to under-appreciate the likelihood their diagnoses are wrong and this tendency to overconfidence is related to both intrinsic and systemically reinforced factors.
  • Reader Bias: Systematic errors of interpretation made during assumption by the user or reader of clinical information. These biases are due to the factors we put down to expertise: clinical experience, tradition, credentials, prejudice and human nature.

The last of these references by Richard Owen on reader bias is well worth a read, as it includes a whole host of further biases including: rivalry bias; personal habit bias, moral bias, clinical practice bias, do something bias. (The converse, do nothing bias, is common among academics), favoured design bias, prestigious journal bias, prominent author bias, famous institution bias (The converse: unrecognized institution bias), flashy title bias, friendship bias and my favourite “I am an epidemiologist" bias - Alternatively called bias bias - and is defined as repudiating a study containing any flaw in its design, analysis.

By Ami Banerjee and Carl Heneghan

After Christmas and in the run-up to Lent, people are often thinking about New Year’s resolutions and what to give up. One of the most common excesses that people want to address is food. This is the most common time of year to start new diets, exercise regimes and gym memberships, and yet obesity, particularly in childhood, is on the rise. The direct cost of overweight and obesity to the NHS has been estimated at over £3 billion. Inequalities in obesity have been identified between North and South, between men and women, and between social classes, and these inequalities seem to be worse for childhood obesity.

With the big public health problems of our age, whether smoking and high blood pressure, or diabetes and obesity, there are health inequalities, but there are also cheap, simple, population-wide interventions which can save thousands, if not millions, of lives. In the case of childhood obesity, it is not rocket science- healthier diet, less processed food, more exercise, and there are signs that the childhood obesity epidemic is levelling off. However, there is a constant push by device companies and drug companies to offer more complicated solutions which will produce big profits for them in these disease areas, because they affect so many people in the population.

This week’s BMJ includes a randomised controlled trial of a novel computerised device, the Mandometer, which provides feedback to participants during meals to slow down speed of eating and reduce total food intake. The trial ran for 12 months comparing the Mandometer with standard lifestyle modification advice and included 106 obese people aged 9 to 17 years. The Mandometer group had a BMI 0.24 units lower than the group receiving standard care. Not only does this seem a paltry difference in BMI; two of the study authors own 60% of the company which produces Mandometer, and so it is unsurprising that they found a positive effect for their device. It is hard to envisage a world where this device is going to be widely used or where it is going to make any difference to childhood obesity. If widely used, such devices will at best only increase the socioeconomic inequalities which already exist in childhood obesity. Surely the simple, population-wide policies of encouraging more exercise and better diet should be promoted instead?

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