A Case Study of Lung Cancer and Smoking
Order ID 53563633773 Type Essay Writer Level Masters Style APA Sources/References 4 Perfect Number of Pages to Order 5-10 Pages
Here’s some information to help you with the last case study’s questions. Make sure all equations are included in your answers.
#4. Where else could cases be located (apart from a hospital)? Where else (outside a hospital) could you find controls for this study? Use Chapter 6 to help you answer these questions.
#7. Is the general population (without lung cancer) closely matched to hospitalized patients (without lung cancer)? Give an explanation for your response. (Hint: Look at the percentage of smokers among the controls.) Is this degree of exposure something you’d see in the general population [even back then]?)
#8. This question is mostly aimed at: If the controls have a very high exposure level (smoking), even if it is not as high as the cases (lung cancer patients), how might this effect the results of this case-control study (Odds Ratio)?
#9. Here’s the formula for calculating the proportion of instances that smoked: 1522/1530 multiplied by 100 equals 99.48% Calculate the proportion of smokers among the controls in the same way.
#11. For the cases, the probabilities of smoking are 1522/8 = 190.25:1. Do the same for the controls’ chances of smoking.
#12. To find the OR, divide the odds by two. You’ll also be required to perform the ‘cross-product ratio.’ This is just another name for the calculation you used in Chapter 6 for the Odds Ratio. Set up your 2×2 and see whether you get the same OR out of the equation. For this, post both the equations and the answers.
#14 On this one, you’ll end up with four Odds Ratios: one for each cigarette dosage (1-14), 15-24, 25+, and ALL. These aren’t age groups; they’re doses (number of cigarettes smoked per day). For each category, set up a 2×2 table. For all 2×2 tables, the ‘no exposure’ row (0 cigarettes) will be the same.
#15. Examine the four different ORs and note any dose changes. Do exposure and disease have a dose-response relationship? #16. This question pertains to what you learned in Chapter 10 about how the outcomes of a study might be influenced (like certain types of bias). List a few of the factors.
#18. The ‘incidence rate’ is the death rate in the cohort section. The population size is measured in person-years. To get the death rate for individuals who smoked 1-14 cigarettes (Table 3), divide 23 by 38,600 and multiply by 1000. As a result, the death rate is 0.60 per 1000 person-years. #18. Relative Risk is also known as Rate Ratio. To calculate this, divide the mortality rate among exposed people by the mortality rate among non-exposed people. This would be 0.60 divided by 0.07 for the 1-14 cigarette group (mortality rate among the nonexposed). #18. Rate Difference and Risk Difference are the same thing. You may get this for the 1-14 cigarette group by subtracting 0.07 from 0.60. (incidence among exposed – incidence among the nonexposed).
#19. This percentage is known as the ‘attributable risk percent,’ or the more familiar ‘etiologic fraction,’ as described in Chapter 9 of your book. You could use the mortality rate or the RR for ‘All Smokers’ from #18 in your equation because there are two alternative formulae for EF.
#20. Multiply the number of deaths among All Smokers (from Table 3) by your answer for #19 to get the total number of deaths (EF percent ). This is how many fatalities could have been avoided if no one had smoked.
#21. Since the RR is the most powerful indicator of association, utilize those data to figure out which disease has a stronger link to smoking. As a second explanation, use the AR percent (EF). Give an explanation for your response.
#22. The ‘population etiologic fraction’ is the same as the ‘population attributable risk percent’ (from Ch. 9). For these computations, you’d use the ‘All’ mortality rate (given in Table 4). There will be two equations (Lung Cancer & CVD) for your solution, and don’t forget to answer the compare/differ questions as well.
#23. Multiply the Mortality Rate for ‘ALL’ from Table 4 by your responses from #22 You’ll do this for both lung cancer and cardiovascular disease. “lung cancer (or CVD) fatalities per 1000 person-years” will follow your responses.
#24. In order to solve this question, use the RRs from Table 5. Note the differences in RRs between current smokers, ex-smokers (by number of years since quitting), and non-smokers (never smoked). After that, talk about what this means for public health and preventative medicine. #26. Choose the study design that has the largest sample size, costs the most, and takes the longest to complete. The remaining factors are classified as benefits or drawbacks.
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