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Review Question - QID 210433

QID 210433 (Type "210433" in App Search)
Study X examined the relationship between coffee consumption and lung cancer. The authors of Study X retrospectively reviewed patients' reported coffee consumption and found that drinking greater than 6 cups of coffee per day was associated with an increased risk of developing lung cancer. The same study in lab mice; however, did not come to a similar conclusion. Which of the following most likely explains the difference between these 2 studies?

Confounding

60%

9/15

Lead time bias

0%

0/15

Measurement bias

0%

0/15

Observer bias

0%

0/15

Selection bias

40%

6/15

Select Answer to see Preferred Response

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The described study was subject to confounding, because the increase in coffee consumption was associated with increased cancer; however, there was an additional variable that more likely caused the increase in lung cancer (most likely smoking) which could not be present in lab mice.

Confounding occurs when a third factor is either positively or negatively associated with both the exposure and outcome of interest. Confounding can distort the true association between exposure and outcome. In non-observational studies, randomization is an important tool to help reduce or remove confounding bias. An example of confounding would be if there was increased lung cancer with alcohol consumption. The confounding variable would likely be smoking (which is associated with alcohol consumption) which causes the increased lung cancer. If this variable was controlled for, then there likely would be a minimal/absent association between alcohol and lung cancer.

Incorrect Answers:
Answer 2: Lead time bias occurs with earlier detection of a disorder which makes the prognosis seem better when in reality the disease was merely detected earlier. For example, if a new test diagnosed pancreatic cancer earlier, but patients still ended up dying at roughly the same age, the apparent mortality benefit is actually only the result of early detection of the disease and not an actual mortality benefit.

Answer 3: Measurement bias is a systematic bias with regards to classifying subjects and measuring the data of interest. Measurement bias can be reduced by using validated measurement techniques.

Answer 4: Observer bias occurs when the observer is aware of which arm of the study the subject is in, and the observer interprets results in light of this awareness. Double blind analysis helps reduce observer bias.

Answer 5: Selection bias occurs when the selected subjects are not representative of the population to be studied and can be controlled by randomization and random sampling.

Bullet Summary:
Confounding variables are associated with the variable of interest and distort the actual outcome unless controlled for.

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