Reference no: EM131195311
Principles of Epidemiology-
Questions 1-4: In planning a case-control study of the relationship between smoking and cancer of the cervix, you need to determine if age is a confounder and/or an effect modifier in this relationship. Of 217 cases, 130 are smokers and 198 of the 243 controls are nonsmokers.
The age distribution for cases and controls who are smokers is as follows:
Smokers Age
|
Cases
|
Controls
|
Age 20-29
|
41
|
6
|
Age 30-39
|
66
|
25
|
Age 40+
|
23
|
14
|
The age distribution for cases and controls who are nonsmokers is as follows:
Nonsmokers Age
|
Cases
|
Controls
|
Age 20-29
|
13
|
53
|
Age 30-39
|
37
|
83
|
Age 40+
|
37
|
62
|
1. Complete the 2 x 2 table and calculate a crude odds ratio for the case-control study relating smoking to cervical cancer. Label the columns& rows and interpret the result.
2. Complete the series of 2 x 2 tables and calculate an odds ratio for each age strata. Label the columns& rows.
3. Is age an effect modifier? Explain your answer.
4. An age-adjusted odds ratio, the Mantel-Haenszel odds ratio (MHOR), was calculated using the data from the age stratified 2 X 2 tables. The MHOR was 6.3. Compare the crude odds ratio that you calculated in #1 above with this MHOR. Is age a confounder? Explain your answer.
Questions 5-8: Consider the following events in one man's life. Note that some events are hypothetical and some are real.
Event
|
Age (years)
|
Birth
|
0
|
Prostate cancer begins
|
45
|
Prostate cancer is detectable by screening
|
50
|
Man is screened, cancer is detected, and treatment begins
|
55
|
If no screening, symptoms would have developed and cancer would have been detected
|
60
|
If no screening, death would have occurred
|
70
|
Death occurs
|
85
|
5. Assume that this man did not get screened. Compute the total preclinical phase of this man's prostate cancer.
6. Assume that this man did not get screened. Compute the total detectable preclinical phase of this man's prostate cancer.
7. Compute the lead time for this patient.
8. Did screening increase the life span of this patient? Justify your answer.
Questions 9-12: Suppose a new screening test has been developed. The test was evaluated in a probability sample in three communities with the following results:
Mooreville
|
|
Health Problem
|
|
Present
|
Absent
|
Total
|
Test Result
|
Positive
|
887
|
888
|
1775
|
Negative
|
99
|
7989
|
8088
|
|
Total
|
986
|
8877
|
9863
|
|
Short City
|
|
Health Problem
|
|
Present
|
Absent
|
Total
|
Test Result
|
Positive
|
3634
|
269
|
3903
|
Negative
|
404
|
2423
|
2827
|
|
Total
|
4038
|
2692
|
6730
|
|
Epiville
|
|
Health Problem
|
|
Present
|
Absent
|
Total
|
Test Result
|
Positive
|
2866
|
56
|
2922
|
Negative
|
318
|
506
|
824
|
|
Total
|
3184
|
562
|
3746
|
9. Calculate the prevalence of the health problem in each of these communities.
10. Calculate and interpret the sensitivity of the test for each community.
11. Calculate and interpret the specificity of the test for each community.
12. Calculate and interpret the predictive value positive for each community.
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: Assume that this man did not get screened. Compute the total preclinical phase of this man's prostate cancer. Assume that this man did not get screened. Compute the total detectable preclinical phase of this man's prostate cancer
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