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From The London Times -- Realistic Perspecitive of Recent CancerStudy
From The Times
November 3, 2007 Bacon. Be afraid? Or not very afraid? http://www.timesonline.co.uk/tol/lif...cle2796330.ece The sizzling debate over epistemology: can you still feel contented about eating bacon? The World Cancer Research Fund stigmatised bacon, along with other processed meats Nigel Hawkes, Health Editor Millions of people are confused by health advice. It appears so contradictory that the simplest thing is to disbelieve it all. Nowhere is this truer than in advice over diet. This week the World Cancer Research Fund stigmatised bacon – along with other processed meats – by advising those who want to avoid cancer to cut it out of their diet. What’s their beef? They have to be kidding, surely? At issue here is the whole question of how we know what we know – what philosophers call epistemology. So this is a page about epistemology, a lovely word that seldom creeps into even a newspaper as upmarket as The Times. Where do all these claims about diet and health come from? They come from studies launched by scientists to try to unravel the causes of disease. We know that many diseases are caused by germs, but thanks to vaccines and antibiotics most of these infectious diseases are now under control. We are left with the diseases caused by age, diet and lifestyle: principally heart disease and cancer, which between them are the cause of more than half of all deaths in developed countries. Hang on. You’ve just said that heart disease and cancer are caused by age, diet or lifestyle, without any evidence. How do we know that? Both are commoner in older people than younger ones. And both are commoner in some communities than in others, while some lifestyle links – between smoking and both cancer and heart disease, for example – have been well proven. So it is certainly a valid hypothesis that there are features of modern life and diet that contribute to disease and it is worth trying to find out what they are. What’s the best way to do that? The best way would be the way that new medicines are tested, in a double-blind placebo-controlled trial. One group would be fed on the food under suspicion, the other given a matching but harmless placebo, and they would be followed until they developed cancer, or died. Neither group would know which they were getting, nor would those responsible for running the trial, to avoid accidental bias. This is the gold standard, but it’s entirely impracticable in most cases for dietary studies in free-living human beings. Life’s too short, especially if you are in the group randomised to bacon. And the next best? There are many alternative ways of studying dietary effects, generally known as observational studies. They fall into two broad groups: cohort studies, and case-control studies. They have their strengths, and weaknesses. An example, please? The Framingham Study, based on a community in Massachusetts, and running since 1948, is a classic cohort study. It has provided most of the evidence doctors now rely on for estimating the effects of diet, exercise and drugs such as aspirin, on the risk of heart disease. In a cohort study a particular population – in this case just over 5,000 adults from Framingham – is closely examined at the start and details taken of every physical variable (such as blood pressure and cholesterol levels) as well as each individual’s diet, exercise and smoking habits. The participants are then followed to some predetermined end-point (death is the least ambiguous) and correlations drawn between the variables measured and the cause of death. And a case-control study? In this case, researchers identify people who already have the disease they are interested in – colon cancer, say - and compare them with another set of people as nearly matched as possible. By questioning the cases and the controls about their diet and lifestyle, they attempt to tease out differences that may explain why one group developed cancer, and the other didn’t. Which is better? Cohort studies are much the better, assuming that the data gathered at the beginning are complete and reliable. But they are expensive, take a very long time, and if you fail to ask at the beginning about some variable that subsequently turns out to be important, it’s too late. A sub-category of the cohort study is the nested case-control study. This adopts the case-control methodology, but using participants whose characteristics are already known because they are part of the cohort study. It is quite a powerful tool. Ordinary case-control studies are the commonest and, alas, the weakest. They are inexpensive and get results fast, but are unreliable because they rely on participants looking back and remembering how they ate and how they lived years before they developed the disease. People’s memories are poor, and are often influenced by what they think they ought to say. This is known as recall bias. Any other problems? Lots. It’s impossible to be certain that the controls really match the cases. In case-control studies of smoking or drinking, for example, people who claim to be nonsmokers or nondrinkers may in fact be ex-smokers or ex-drinkers, whose health was damaged before they gave up. This is misclassification bias. It is also difficult to rule out confounding factors, where an association is found but does not prove anything. For example, in observational studies people who take vitamin pills appear to suffer less cancer and heart disease, but in double-blind trials, this benefit disappears. Why? Probably because vitamin-taking is simply a marker for people who are health-conscious generally. The benefit comes from some other aspect of their behaviour which cannot be adequately corrected for. Finally, there are statistics. A result can claim to be statistically significant if the odds of it arising by chance are one in 20. Those are not especially long odds, so plenty of spurious results get published. If these kinds of studies are so useless, why do people do them? They are not useless, entirely. They are a good way of forming hypotheses, and building up knowledge. They just fall a long way short of proof. Can’t we do better? The obvious thing to do is to combine lots of studies together in a meta-analysis. This is especially popular, as it is a desk job not requiring any new research, or much in the way of grants. The strength of the technique is that an accumulation of studies may have greater statistical power to detect small effects, but its weaknesses comes from selection bias (which studies are included and which aren’t) and its close relation, publication bias (you can’t include unpublished studies, which are usually the ones that show no effect). How does all this relate to the WCRF study? This was a meta-analysis that included studies of every sort, from double-blind trials to observational studies. It was highly selective, boiling down 500,000 papers to the final 7,000 that were used to draw conclusions. So while it was a useful distillation of the literature, it was no more than that. Another group might have chosen a different 7,000 papers, and reached different conclusions. So should we chew bacon, or eschew it? It’s unlikely, despite the WCRF, that occasional consumption of processed meats will make any perceptible difference to an individual. Across the population as a whole it may be detectable, but to an individual a small change to a small risk is beneath the threshold of detection. WCRF is on stronger ground when it advises people to stay thin. Why do I say that? Oh, just a gut feeling. |
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From The London Times -- Realistic Perspecitive of Recent Cancer Study
However, questionable the research may be, from the selection of studies in
the research, it is interesting that they would point the finger at *processed* meats. If this were just another Vegan inspired attack, they would target all meats. My intuition supports the idea of avoiding all Frankenfoods. -So, I like this WCRF idea. I work so hard at controlling my macronutrient ratios and calories, but I have often neglected the care needed to avoid Frankenfoods. I have avoided the 50 ingredient labels. Maybe I need to avoid the dozen ingredient labels too. "Jim" wrote in message ... From The Times November 3, 2007 Bacon. Be afraid? Or not very afraid? http://www.timesonline.co.uk/tol/lif...cle2796330.ece The sizzling debate over epistemology: can you still feel contented about eating bacon? The World Cancer Research Fund stigmatised bacon, along with other processed meats Nigel Hawkes, Health Editor Millions of people are confused by health advice. It appears so contradictory that the simplest thing is to disbelieve it all. Nowhere is this truer than in advice over diet. This week the World Cancer Research Fund stigmatised bacon – along with other processed meats – by advising those who want to avoid cancer to cut it out of their diet. What’s their beef? They have to be kidding, surely? At issue here is the whole question of how we know what we know – what philosophers call epistemology. So this is a page about epistemology, a lovely word that seldom creeps into even a newspaper as upmarket as The Times. Where do all these claims about diet and health come from? They come from studies launched by scientists to try to unravel the causes of disease. We know that many diseases are caused by germs, but thanks to vaccines and antibiotics most of these infectious diseases are now under control. We are left with the diseases caused by age, diet and lifestyle: principally heart disease and cancer, which between them are the cause of more than half of all deaths in developed countries. Hang on. You’ve just said that heart disease and cancer are caused by age, diet or lifestyle, without any evidence. How do we know that? Both are commoner in older people than younger ones. And both are commoner in some communities than in others, while some lifestyle links – between smoking and both cancer and heart disease, for example – have been well proven. So it is certainly a valid hypothesis that there are features of modern life and diet that contribute to disease and it is worth trying to find out what they are. What’s the best way to do that? The best way would be the way that new medicines are tested, in a double-blind placebo-controlled trial. One group would be fed on the food under suspicion, the other given a matching but harmless placebo, and they would be followed until they developed cancer, or died. Neither group would know which they were getting, nor would those responsible for running the trial, to avoid accidental bias. This is the gold standard, but it’s entirely impracticable in most cases for dietary studies in free-living human beings. Life’s too short, especially if you are in the group randomised to bacon. And the next best? There are many alternative ways of studying dietary effects, generally known as observational studies. They fall into two broad groups: cohort studies, and case-control studies. They have their strengths, and weaknesses. An example, please? The Framingham Study, based on a community in Massachusetts, and running since 1948, is a classic cohort study. It has provided most of the evidence doctors now rely on for estimating the effects of diet, exercise and drugs such as aspirin, on the risk of heart disease. In a cohort study a particular population – in this case just over 5,000 adults from Framingham – is closely examined at the start and details taken of every physical variable (such as blood pressure and cholesterol levels) as well as each individual’s diet, exercise and smoking habits. The participants are then followed to some predetermined end-point (death is the least ambiguous) and correlations drawn between the variables measured and the cause of death. And a case-control study? In this case, researchers identify people who already have the disease they are interested in – colon cancer, say - and compare them with another set of people as nearly matched as possible. By questioning the cases and the controls about their diet and lifestyle, they attempt to tease out differences that may explain why one group developed cancer, and the other didn’t. Which is better? Cohort studies are much the better, assuming that the data gathered at the beginning are complete and reliable. But they are expensive, take a very long time, and if you fail to ask at the beginning about some variable that subsequently turns out to be important, it’s too late. A sub-category of the cohort study is the nested case-control study. This adopts the case-control methodology, but using participants whose characteristics are already known because they are part of the cohort study. It is quite a powerful tool. Ordinary case-control studies are the commonest and, alas, the weakest. They are inexpensive and get results fast, but are unreliable because they rely on participants looking back and remembering how they ate and how they lived years before they developed the disease. People’s memories are poor, and are often influenced by what they think they ought to say. This is known as recall bias. Any other problems? Lots. It’s impossible to be certain that the controls really match the cases. In case-control studies of smoking or drinking, for example, people who claim to be nonsmokers or nondrinkers may in fact be ex-smokers or ex-drinkers, whose health was damaged before they gave up. This is misclassification bias. It is also difficult to rule out confounding factors, where an association is found but does not prove anything. For example, in observational studies people who take vitamin pills appear to suffer less cancer and heart disease, but in double-blind trials, this benefit disappears. Why? Probably because vitamin-taking is simply a marker for people who are health-conscious generally. The benefit comes from some other aspect of their behaviour which cannot be adequately corrected for. Finally, there are statistics. A result can claim to be statistically significant if the odds of it arising by chance are one in 20. Those are not especially long odds, so plenty of spurious results get published. If these kinds of studies are so useless, why do people do them? They are not useless, entirely. They are a good way of forming hypotheses, and building up knowledge. They just fall a long way short of proof. Can’t we do better? The obvious thing to do is to combine lots of studies together in a meta-analysis. This is especially popular, as it is a desk job not requiring any new research, or much in the way of grants. The strength of the technique is that an accumulation of studies may have greater statistical power to detect small effects, but its weaknesses comes from selection bias (which studies are included and which aren’t) and its close relation, publication bias (you can’t include unpublished studies, which are usually the ones that show no effect). How does all this relate to the WCRF study? This was a meta-analysis that included studies of every sort, from double-blind trials to observational studies. It was highly selective, boiling down 500,000 papers to the final 7,000 that were used to draw conclusions. So while it was a useful distillation of the literature, it was no more than that. Another group might have chosen a different 7,000 papers, and reached different conclusions. So should we chew bacon, or eschew it? It’s unlikely, despite the WCRF, that occasional consumption of processed meats will make any perceptible difference to an individual. Across the population as a whole it may be detectable, but to an individual a small change to a small risk is beneath the threshold of detection. WCRF is on stronger ground when it advises people to stay thin. Why do I say that? Oh, just a gut feeling. |
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