Statistics Related to InterventionalCardiology Procedures Flashcards
What is the primary endpoint in clinical trials?
The primary endpoint is the main question that the trial is designed and powered to answer.
How should subgroups of patients be viewed in clinical trials?
Subgroups should be viewed for consistency based on patient and disease characteristics.
What is likely to be seen in treatment effects among subgroups?
Quantitative differences in treatment effect may favor certain subgroups, but qualitative differences are unlikely.
Why are randomized clinical trials (RCTs) preferred over observational studies?
RCTs are preferred because they are designed to minimize bias and provide stronger evidence for treatment effectiveness.
What is a potential limitation when applying RCT results to different populations?
The results may not generalize if the trial was conducted in a different population than the patient of interest.
What is the significance of blinding in clinical trials?
Blinding reduces bias in treatment effect assessments by preventing investigators and patients from knowing the treatment assignments.
What does Type II error (β) represent in clinical trials?
Type II error occurs when no effect is seen when, in fact, a treatment effect truly exists.
What is the relationship between Type II error and trial power?
One minus the Type II error (1 - β) is known as the trial’s power.
What is the primary benefit of randomizing patients into treatment groups?
Randomization balances covariate information across groups, ensuring observed associations are due to treatment.
What are competing risks in statistical analysis?
Competing risks modify the chances of occurrence of an event of interest or hinder its occurrence.
What is Absolute Risk Reduction (ARR)?
ARR is the difference in event risk between the treatment and placebo groups.
How is the Number Needed to Treat (NNT) calculated?
NNT is calculated as 1 divided by the risk difference (ARR).
What are the key components of diagnostic test evaluation?
Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy.
What does high sensitivity in a diagnostic test indicate?
High sensitivity indicates a low chance of missing a disease.
What is the potential issue with using box plots for correlated data?
Box plots cannot adequately represent data with a correlation structure due to non-independence of data points.