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  • Introduction Researchers have long followed the

    2019-04-16

    Introduction Researchers have long followed the strategy that in order to achieve a fuller understanding of the causes of disease and how they can be prevented, it is necessary to study the biochemical and physiological processes involved in the etiology of disease. As I have argued in previous papers this mechanistic strategy, often known as reductionism, has achieved little success in recent decades in terms of generating information that is of practical value with regard to human health and the prevention of disease. The reason for this is that because of the great complexity of the human body it is extraordinarily difficult to properly understand the exact details of the pathways leading to disease. Even with relatively “simple” disorders, such as hypertension, obesity, and type 2 diabetes, there are multiple pathways involved and the story of each disorder becomes steadily more complex as new discoveries are made. An alternative strategy is based on directly studying whether different variables related to lifestyle influence disease outcomes. Major types of research in this area are epidemiology (including cohort studies) and randomized controlled trials (RCTs). In this paper the hypothesis is discussed in relation to cancer.
    Research on cancer In a paper published in Science Tomasetti and Vogelstein compared cancer rates across 31 different tissues. They argued that the variation in cancer rates between tissues is best explained by the rate of reproduction of stem vip receptor and the accumulation of mutations. They concluded that: “These results suggest that only a third of the variation in cancer risk among tissues is attributable to environmental factors or inherited predispositions. The majority is due to ‘bad luck,’ that is, random mutations arising during DNA replication in normal, noncancerous stem cells.” Wu et al. then published a paper in Nature. In stark contrast to the previous paper their analyses led to the conclusion that at least 70%–90% of common cancers are caused by external factors. Their arguments are of two distinct types. One type of argument centers on the reproduction of cells and the accumulation of mutations. This line of reasoning is similar to that used by Tomasetti and Vogelstein except that here the reproduction of not only stem cells but also other cell types were considered. The other argument used by Wu et al. is based on epidemiology (i.e., comparisons of cancer rates between different populations, changes in cancer rates when people emigrate, and changes vip receptor in cancer rates within a population over time). We can now compare the two types of argument used in the above papers. The argument based on reproduction of cells and the accumulation of mutations is clearly prone to generating false conclusions. This is consistent with the hypothesis proposed here regarding the limitations of mechanistic research. But the alternative strategy, which in the case of the paper by Wu et al. refers only to epidemiology, has provided convincing evidence that most cancer is directly related to lifestyle and environmental factors. Indeed, this fact had already been well established by 1980. Research over the past 35 years has added a large weight of detail regarding the association between lifestyle, environmental factors, and cancer. This is illustrated by the following examples. This body of evidence opens up new routes by which the risk of cancer may be appreciably reduced, such as by recommending that people do not consume meat or alcohol in excessive amounts and that persons at relatively high risk of cancer routinely take supplements of selenium and vitamin D. However, before that stage of cancer prevention is reached, further research is required in order to confirm that these supplements are both safe and effective. The most appropriate form of that research is the carrying out of RCTs and cohort studies. In a recent paper I argue that cohort studies are at least as reliable as RCTs with regard to generating accurate findings. Case-control studies and population comparisons have also contributed a great deal of valuable information.