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A case study

A case study. Investigation: What causes colon cancer? What is the effect of diet on colon cancer?. Observational studies. 1971 Dr. Denis Burkitt, British surgeon, studies disease patterns in poor, rural, African sites Rural Africans: Much less colon cancer, diet rich in higher fiber

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A case study

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  1. A case study Investigation: What causes colon cancer? What is the effect of diet on colon cancer?

  2. Observational studies • 1971 Dr. Denis Burkitt, British surgeon, studies disease patterns in poor, rural, African sites • Rural Africans: Much less colon cancer, diet rich in higher fiber • Don’t Forget Fibre in Your Diet (1979) • Mounting evidence in 1970s, 1980s • Societies/cultures with high fiber diets have low rates of colon cancer

  3. Observational evidence • Observation leads to hypothesis • Biological reasons to suggest fiber • Fiber adds bulk in intestines to help absorb and excrete cancer-causing substances • Experiments with animals • Rats fed carcinogens get less colon cancer if fed lots of fiber • Observational studies of humans inconsistent • Observational study of 88,000 nurses failed to detect effect of diet • Nurses chose their own diet and were observed. Were those who chose high fiber different in other ways from those who did not?

  4. How to find the truth? • Based on the evidence would you advocate a high fiber diet to those at risk for colon cancer? • Does the evidence suggest that a high fiber diet leads to lower rates of colon cancer?

  5. Confounding variables High Fiber Reduced Cancer High Fiber Reduced Cancer Confounding Variables ??? Pollution Low sugar Socio-economic Genetic

  6. Experiments needed to settle the issue • Two clinical trials in 2000 • “Both trials are well conceived, well designed, well implemented, and clearly presented.” (New England Journal of Medicine)

  7. Clinical Trial #1 • Alberts et al. Lack of effect of a high-fiber cereal supplement on the recurrence of colorectal adenomas. N Engl J Med 2000: 342: 1156-1162 • 2,079 subjects • Lasted 4 years • Subjects randomly assigned to either eat low-fat, high fiber diet or to follow their usual diet

  8. Clinical Trial #2 • Polyp Prevention Trial • Schatzkin et al. Lack of effect of a low-fat, high-fiber diet on the recurrence of colorectal adenomas. N Engl J Med, 2000:342:1149-1155. • 1,429 subjects • Lasted 3 years • Subjects randomly assigned to either eat high-fiber cereals and food bars or to eat cereal and food bars that looked and tasted the same but were low in fiber.

  9. Clinical trials • Results: • Trial #1 (7 cases in fiber group, 2 in control group) • Trial #2 (10 cases in fiber group, 4 in control group) • “What is disappointing . . . is that the findings of both trials are negative.” (New England Journal of Medicine) • “2 Fiber Studies Find No Benefit For The Colon” (New York Times headline, April 20, 2000) • “I think we’ve definitely disproved the fiber hypothesis for colon cancer,” Dr. David Alberts

  10. Some room for caution, but . . . • All subjects had had a benign polyp removed • Perhaps different results for “clean” subjects • Length of study at most 4 years • Perhaps different results over longer time frame • Perhaps fiber works earlier or later • In any case, experiments show there is no evidence that fiber lowers cancer rates

  11. Conclusion • “Randomized controlled trials have now shown us that the use of some of the diets and nutritional supplements thought to lower the risk of colorectal cancer has no short-term benefits with respect to preventing adenomas. There may be many reasons to eat a diet that is low in fat and high in fiber, fruits, and vegetables . . . but preventing colorectal adenomas, at least for the first three to four years, is not one of them. With regard to questions about diet and colorectal cancer, though, definitive answers still seem to be beyond the reach of both observational epidemiologic studies and randomized, controlled trials.” (New England Journal of Medicine, April 20, 2000)

  12. Randomized, controlled experiment • The three key ingredients • Compare two or more variables (often a treatment versus placebo) • Control for lurking, confounding variables • Isolate the causative factor • Randomize Assign subjects to treatment by chance • Goal: Make groups as similar as possible except for the treatment • Repetition Use enough subjects to reduce chance variation in the results

  13. Language of experiments • Response variable A variable that measures an outcome or result of study • Explanatory variable A variable we think explains or causes changes in the response variable • Subjects Individuals studied in an experiment • Treatment Experimental condition applied to subjects • Two variables are confounded when their effects on response variable cannot be distinguished from each other • Statistical significance An observed effect so large that it would rarely occur by chance

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