Hurry up!
: : Get The Offer
Unlimited Access Step ( one, two and three ).
Priority Access To New Features.
Free Lifetime Updates Facility.
Dedicated Support.
1
Question:

A new estrogen receptor agonist is being evaluated for the treatment of postmenopausal symptoms.  A prospective study shows that the drug increases the risk of deep vein thrombosis (DVT) in treated women who smoke compared to untreated women who smoke, with a relative risk (RR) of 1.70 and p-value of 0.01.  In nonsmokers, no increased risk of DVT is evident with use of the drug (RR = 0.96; p-value = 0.68).  Which of the following describes this phenomenon?

Hurry up!
: : Get The Offer
Unlimited Access Step ( one, two and three ).
Priority Access To New Features.
Free Lifetime Updates Facility.
Dedicated Support.


Explanation:

There are many explanatory sources, such as pictures, videos, and audio clips to explain these explanations and questions and explain the answers, but you must subscribe first so that you can enjoy all these advantages. We have many subscription plans at the lowest prices. Don't miss today's offer. Subscribe

Effect modification occurs when the effect of an exposure on an outcome is modified by another variable.  It can be identified using stratified analysis (analyzing the cohort as different subgroups), as the different strata will have different measures of association.  In this scenario, smoking status modified the effect of the new estrogen receptor agonist (exposure) on deep vein thrombosis (DVT) incidence (outcome).  Using stratified analysis by smoking status:

  • Among smokers, there was a statistically significant association between taking the new estrogen receptor agonist and risk of developing DVT with a relative risk of >1, indicating higher risk, and a p-value of <0.05, indicating statistical significance.
  • In contrast, among nonsmokers, there was no statistically significant association between taking the medication and risk of DVT (p-value >0.05).

Effect modification is not a bias (Choices D and E), as it is not due to flaws in the design or analysis phases of the study.  It is a natural phenomenon that should be described, not corrected.

Effect modification is most easily confused with confounding (Choice A), but stratified analysis can help distinguish between these 2 scenarios.  With effect modification, the different strata will have different measures of association, as seen in this example of the association between taking the estrogen receptor and the risk of DVT among smokers compared to nonsmokers.  In contrast, with confounding, stratification usually reveals no significant difference between the strata.  For instance, in an analysis of primary school students (of all grade levels), age can be a confounder that muddies the association between shoe size and intelligence.  Children with bigger shoe sizes may appear to be more intelligent on initial analysis.  However, this association is likely not due to shoe size but rather to age because older children tend to have both bigger feet and more intelligence.  When older and younger children are analyzed separately (stratification based on the confounder), the association between shoe size and intelligence disappears.

(Choice C)  The latent period is the time required for an exposure to begin having an effect.  However, there is no information on how latency was handled in this study.

Educational objective:
Effect modification is present when the effect of the main exposure on the outcome is modified by the presence of another variable.  Effect modification is not a bias.