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Diana Pinney Case Study Week 5 1. The first study is a case study because it was relatively small, compromising around 20 hospitals. Also, the cases were chosen as individuals that had been diagnosed with lung cancer and the controls where chosen from patients occupying the hospital at the same time but diagnosed with a different disease. 2. The second study is a cohort study because a population group (doctors in England) was chosen to self-report on smoking habits via questionnaire and this reporting was followed each physician who smoked until they turned into a death certificate. 3. It is more feasible to perform a case control study on a population that is fixed or has something in common, such as patients in hospital. Hospital settings also provide quick access to subjects for interview or study, which saves time and money. 4. Other sources of controls in the case control study could have been nuclear family members of the lung cancer patient whom did not smoke. 5. The advantages of selecting controls from the same hospital as the cases include efficiency and willingness to participate. 6. Lung cancer patients in the hospital are significantly representative of all patients with lung cancer. It would not be a stretch to generalize that hospitalized lung cancer patients are indicative of the exposure and future that most people with lung cancer in this era would face. 7. People without lung cancer that are hospitalized are not very representative of the general population without lung cancer. A majority of the general population does not have lung cancer, while a majority of the population is not hospitalized. Hospitalized people without lung cancer to represent the general population because both are less likely to be smokers. 8. There is an issue of external validity and representativeness between the cases and control group because it is easy to seethe control group is much more likely to not to be smokers. This glaring fact may influence bias. 9. Proportion smoked, cases: 1350/1357 or 99% Proportion smoked, controls: 1296/1357 or 96% 10.I infer that the population of cases had 4% more smokers than the population of controls. 11a. 99% 11b. 96% 12.The odds ratio = 9.6. The cases are 9.6 times more likely to be smokers than the controls. The cross product of the ratio is the relative risk, which is 5.2. The smokers in the case population have more than 5 times more risk in getting lung cancer than the controls. 13. I would infer than lung cancer is made 9.6 times more likely to occur in smokers than non-smokers and that smokers have 5 times more risk of getting lung cancer than non-smokers. 14. Daily # of cigarettes 0 1-14 15-24 25+ All smokers OR x 7 9.5 16.3 9.6 15. All smoking holds a higher risk than not for lung cancer, but the more cigarettes that are smoked per day, the higher the odds of developing lung cancer are. 16. I would assume that someone that has the time to smoke 25+ cigarettes in a day is failing in other areas of personal wellbeing. Perhaps heavy smokers get less exercise and have an improper diet. 17. Even though this study’s questionnaire may have been anonymous, it might not be easy for a physician (even in the name of health and science) to fill out a survey admitting to being a smoker. Only 6,192 of the respondents were female, which may be an accurate ratio of female physicians, but is not an accurate ratio of females in the general population. 18. # Cigs Daily 0 1-14 15-24 25+ All smokers Total MR/1,000 yrs. 0.07 0.6 1.4 2.2 1.3 0.9 RR x 8.6 20 31.4 18.6 12.9 Rate difference X 0.53 1.33 2.13 1.23 0.83 Mortality rate calculates the disease ratio. For example, 1.4 cases of lung cancer will arise (in people who smoke 15-24 cigarettes per day) per 1,000 people per year. Rate ratio calculates the risk that cases have of developing a disease per exposure. Rate difference calculates disease burden. 19. This is called a cause specific mortality rate. The proportion of lung cancer deaths among all smokers that can be attributed to smoking is 133/136. 20. Assuming that every case of cancer in smokers was due to them smoking, if no one had smoked, 133 deaths would have been prevented. 21. Death from cardiovascular disease has a stronger association with smoking. The actual mortality rate and deaths due to cardiovascular disease are higher than lung cancer. Risks associated with smoking and lung cancer are higher than heart disease, but more actual deaths come from heart disease. 22. PAR% Lung Cancer: 92% PAR % Cardiovascular Disease: 17% These 2 measures vary greatly, but are similar to the Attributable risk percent. 23. Lung Cancer: 1.3 deaths Cardiovascular disease: 9.51 deaths 24. These data imply that the sooner one quits smoking, the less chance they have of dying from lung cancer. It implies that the field of public health and preventative medicine could benefit the population greatly by instating as many tobacco cessation programs as possible. 25. It appears that the cohort study makes smoking seem the most dangerous. This is a more accurate study design for this kind of query as it has followed a cohort through time for a more accurate picture of an exposure association. 26. Case Control Advantages Sample size Cost Study time Rare disease Disease rates Disadvantages Multiple outcomes Recall bias Cohort Advantages Rare exposure Progression, spectrum of illness Multiple exposures Disadvantages Sample size Cost Study time Selection bias Loss to follow-up 27. I would have done a case control study first. Completing a quick and cheap study could be a first step in finding an association with a disease and exposure. A strong association could lead an investigator to completing a longer and more accurate study such as the cohort study. 28. Strong association: yes Consistency among studies: yes Exposure precedes disease: yes Dose-response effect: yes Biologic plausibility: yes