Download Case Study: Cigarette Smoking and Lung Cancer

Allison Erickson
Case Study: Cigarette Smoking and Lung Cancer
1. What makes the first study a case-control study?
The first study was a case-control study because Doll and Hill studied individuals with
the disease who were smokers (cases) and individuals who were smokers with a different
disease diagnosis (controls). Also, the unit of observation in this study was the individual with
one observation point.
2. What makes the second study a cohort study?
The second study was a cohort study because the unit of observation was a group of
data obtained from a secondary source before investigators sent questionnaires. Also, the
information obtained about smoking behaviors was obtained from multiple sources and times.
3. Why might hospitals have been chosen as the setting for this study?
In a case-control study, there should be one observation point. Given that the disease of
interest was regarding cancer, the most appropriate place for observation would be hospital
where the sick go for treatment.
4. What other sources of cases and controls might have been use?
Another source that could have been used for this case-control study could have been
an elder care or nursing home facility. Now, I am not saying that only older adults are diagnosed
with lung cancer, but because lung cancer can be the result of long years of smoking, doing a
similar study in this type of facility may be beneficial. I would say that the same technique could
be used in terms of having cases be lung cancer patients who are, or have been, smokers,
compared to smokers with other health disease diagnosis.
5. What are the advantages of selecting controls from the same hospital as cases?
The advantages of selecting controls from the same hospital include have a consistent
form of care received, treatment options being similar, and knowledge about the patients from
a medical staff that works together. Similarly, health records would be in the same location
creating less need for searching elsewhere for information.
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6. How representative of all persons with lung cancer are hospitalized patients with lung
cancer?
This is not fully representative because there are many stages of lung cancer. I would
presume that the only patients hospitalized are those in later stages of cancer, close to death.
Therefore, for many of the lung cancer patients in the hospital do not accurately represent all
cases of lung cancer present in a given community.
7. How representative of the general population without lung cancer are hospitalized patients
without lung cancer?
This representation would be even less than those with lung cancer not hospitalized.
With a vast amount of medical diagnosis and concerns in which people go to the doctor for, it
would still not be a good representation of the general population. However, if there are more
people hospitalized for something other than lung cancer, which may lead investigators to
another environmental or social health concern that would need attention.
8. How may these representativeness issues affect interpretation of the study results?
The representativeness issues could affect the interpretation of the study results by
giving a false or inaccurate sense of a true health problem. In essence, the results could be
skewed to represent smoking to not be attributed to lung cancer based on the number of
patients hospitalized with lung cancer. On the other hand, if a lot of smokers are admitted for
other health concerns, then that would open the door for additional research not related to lung
cancer and smoking.
9. From this table, calculate the proportion of cases and controls who smoked.
Proportion smoked, cases: 51.0%
Proportion smoked, controls: 49.0%
10. What do you infer from these proportions?
The inferences that can be made from the proportions is that smoking results in many
other health concerns besides just lung cancer.
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11.
a. Calculate the odds of smoking among the cases.
99.5%
b. Calculate the odds of smoking among the controls.
95.5%
12. Calculate the ratio of these odds. How does this compare with the cross-product ratio?
9.08. This compares by showing that the exposure to smoking was high for both the
cases and the controls. In addition, this indicates that the risk of smoking affects other areas of
health diagnosis, as well as lung cancer.
13. What do you infer from the odds ratio about the relationship between smoking and lung
cancer?
The odds ratio allows me to infer that there is a strong and significant relationship
between smoking and lung cancer.
14. Compute the odds ratio by category of daily cigarette consumption, comparing each
smoking category to nonsmokers.
Daily Number of
Cigarettes
# Cases
# Controls
Odds Ratio
0
7
61
Referent
1-14
565
706
6.97
15-24
445
408
9.50
25+
340
182
16.3
15. Interpret these results.
Although the number of cases and controls decreased as number of cigarettes
increased, the odds ratios indicated a stronger association between lung cancer, or other health
concerns, and more cigarettes smoked per day.
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16. What are the other possible explanations for the apparent association?
Another possible explanation of the apparent association could be that the study results
came from a hospital where people are ill and seeking treatment. Yes, there is a clear
association between smoking and lung cancer; however, there could be other factors for the
result of illness or disease. Many times with one lifestyle behavior aiding in the ill-diagnosis,
there are usually other environmental, social, or behavioral factors that aid as well.
17. How might the response rate of 68% affect the study’s results?
This response rate could provide fairly significant results about associations between
smoking and health concerns because it is over 50%. However, it may limit the clear conclusions
the investigators can make in regards to a large population. Nevertheless, having a response
rate of 68% is strong to help formulate conclusive evidence about smoking and disease
development.
18. Compute lung cancer mortality rates, rate ratios, and rate differences for each smoking
category. What do each of these measures mean?
(Please refer to attached table from case study at the end of the document for
computed numbers.) First, the mortality rate indicates how many individuals died from lung
cancer who smoked and who did not smoke. Secondly, the rate ratio gives an indication
regarding how an exposure impacts the risk of the disease. In the case of the smokers who
smoke 15 to 24 cigarettes per day, for example, the rate ratio indicates that they have a high risk
of developing lung cancer. Lastly, the rate difference indicates the disease burden in the two
groups (lung cancer death and no death). The rate difference gives representation of the
incidence rate of a particular disease with an exposure as a component cause.
19. What proportion of lung cancer deaths among all smokers can be attributed to smoking?
What is this proportion called?
9.77 --- known as a cause-specific rate
20. If no one had smoked, how many deaths from lung cancer would have been averted?
133 given that in the study only 136 of the people who died from lung cancer reported
number of cigarettes smoked per day and 3 of the individuals who died from lung cancer did not
smoke.
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21. Which cause of death has a stronger association with smoking? Why?
Lung cancer death has a stronger association with smoking because the rate ratio
indicates a high risk of developing lung cancer from smoking. Also, although the number of
deaths from smoking for cardiovascular disease is high, the number of deaths from
cardiovascular disease in nonsmokers is also high.
22. Calculate the population attributable risk percent for lung cancer mortality and for
cardiovascular disease mortality. How do they compare? How do they differ from the
attributable risk percent?
Lung Cancer = 92.6%
Cardiovascular Disease = 17.5%
These results indicate that there is a substantial amount of evidence that smoking
clearly contributes to lung cancer mortality. Although smoking can lead to death from
cardiovascular disease, there are other factors that also contribute greatly to that disease. With
this PAR percentage for lung cancer, it would prompt community intervention to reduce
smoking. Compared to the attributable risk percent, these numbers provide information about
the population as a whole, both smokers and nonsmokers.
23. How many lung cancer deaths per 1,000 persons per year are attributable to smoking
among the entire population? How many cardiovascular disease deaths?
Lung Cancer = .87 per 1,000 persons
Cardiovascular Disease = 1.55 per 1,000
24. What do these data imply for the practice of public health and preventative medicine?
This data implies that quitting smoking for just less than five years greatly reduces the
risk for developing and dying from lung cancer. Even though there are individuals who have still
died from lung cancer after 20 plus years being smoke-free, the rate ratio indicates it is much
lower than current smokers. In regards to public health practice, health officials can put into
place programming for nonsmokers to avoid picking up a cigarette, especially in younger aged
individuals. Quitting smoking will, no doubt, help health outcomes, but abstaining from smoking
all together will reduce the risk of lung cancer greatly.
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25. Compare the results of the two studies. Comment on the similarities and differences in the
computed measures of association.
Both studies indicate that there is risk in developing lung cancer from smoking. In both
studies, the rate ratio and odds ratio for cigarettes smoked 0 to 14 per day are similar. However,
once the cigarette use increases the rate ratio and odds ratio start become less similar. In the
cohort study the rate ratio clearly gives strong association between lung cancer death and
smoking. The case-control study gives a similar result in that the exposure of smoking is a major
risk factor for developing lung cancer.
26. What are the advantages and disadvantages of case-control vs. cohort studies?
Case-Control
Sample Size
Costs
Study Time
Rare disease
Rare exposure
Multiple exposures
Multiple outcomes
A: Smaller, can gather results in
a timely manner
D: May not fully represent a
population
Cohort
A: more cost effective with less
participant
A: Can give a more accurate
picture of exposure and disease
risk
D: Difficult to gather a large
amount of people
D: Can be expensive, requiring
grants sometimes
A: One observation point, which
requires less time
D: may not report on all risk
factors prior to the study
A: Can be small enough to gather
quality information about a rare
disease
A: Provides a more accurate
picture of risk and disease
association
D: takes a long time
D: If it’s rare, then the
participation would not be high
enough for cohort
D: It would be difficult to get
both cases and controls
A: Able to gather a large group of
people to observe regarding the
rare exposure
A: With both cases and controls,
there will be availability of
evaluation multiple exposures at
the one observation point
D: With a small sample size,
there would be no indication of a
risk factor
D: With many points of
evaluation, it would be more
time consuming to have more
than one exposure being studied
A: Ability to recognize where the
outcomes occurred and make
inferences of when they
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occurred
D: one point of observation
A: multiple points of observation
Are not measured in casecontrol studies
A: disease rates take into
account data from multiple
observation points
D: can be a problem because
case-controls do not measure
past exposure
D: can be a problem, but not as
much as for a case-control study
because the investigator can
potentially use some of that
information for the results
D: Because follow-up is a large
part of cohort studies, therefore
this can lead to skewed results
Progression, spectrum of illness
Disease Rates
Recall Bias
Loss to follow-up
Selection bias
A: not much of a problem due to
no real follow-up for the study
outcomes
D: can lead to skewed results
especially for a pharmaceutical
drug
D: can provide differential
results based on who was
selected
A: can be a little less of a
problem, but should still be
avoided for clear results
27. Which type of study (cohort or case-control) would you have done first? Why? Why do a
second study? Why do the other type of study?
I would have done a case-control study first because it is more efficient and costeffective. If the first case-control study yielded a significant relationship between an exposure
and disease, then I would perform a second study to validate the results further. The purpose of
doing a cohort study would be to confirm results of a smaller case-control study over a larger
population of individuals or groups of people. Also, it would be advantageous to do a cohort
study after a case-control study to evaluate disease rates.
28. Which of the following criteria for causality are met by the evidence presented from these
two studies?
Strong Association - Met
Consistency among studies - Met
Exposure precedes disease - Met
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Dose-response effect - Met
Biologic plausibility – Not met
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Computations
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