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Bias in interpreting results of clinical studies
Bias in performing clinical studies
Attributable risk (AR)
DALY and QALY
Incidence and prevalence
Mortality rates and case-fatality
Relative and absolute risk
Positive and negative predictive value
Sensitivity and specificity
Test precision and accuracy
Modes of infectious disease transmission
Vaccination and herd immunity
Cross sectional study
Placebo effect and masking
Randomized control trial
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The word “interaction” can refer to biological interaction - which is where two exposures like radon gas and toxins in cigarettes work together to influence an outcome - like lung cancer.
But the word “interaction” can also refer to statistical interaction, also called effect modification, which is the statistical methodology used to find out if there’s a biological interaction.
Most diseases are caused by multiple exposures that work together, like our example of radon gas and smoking cigarettes leading to lung cancer.
Radon is a radioactive gas that gets released from the decay of elements like uranium and radium in rocks and soil.
It can be found in dust particles in the air, so most people breathe in a low level of radon every day.
Unfortunately, radon causes mutations in DNA and people who breathe in high levels of radon have an increased risk of lung cancer.
Similarly, people who smoke cigarettes have a higher risk of lung cancer because of tobacco contains various toxins that also mutate the DNA.
In addition, cigarette smoke harms the cilia in the lungs. Those are the little hairlike structures that normally clear out things like mucus, dust particles, and chemicals.
Damaged cilia is a big problem for people who are exposed to high levels of radon, because the lungs can’t get rid of radon-containing dust.
This is an example of biological interaction, because even though radon and smoking can both separately cause lung cancer, they also work together to amplify the risk.
Statistical interaction can help us figure out how much the risk increases for people who are exposed to both factors compared to people who are exposed to one factor or the other.
Statistical interaction can be assessed by comparing the effect of one exposure on the outcome in each strata or level of the other exposure.
For example, you could figure out how smoking affects the risk of lung cancer among people exposed to high levels of radon, and how it affects the risk of lung cancer among people exposed to low levels of radon.
To do this, you might start by looking at the crude or unstratified effect, so you’d recruit 100 people who smoke and 100 people who don’t smoke, and compare the proportion of people in each group who develop lung cancer in the next ten years.
Interaction can refer to biological interaction - which is where two exposures like radon gas and toxins in cigarettes work together to influence an outcome - like lung cancer. It can also refer to statistical interaction, also called effect modification, which is the statistical methodology used to find out if there's a biological interaction.
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