Epi/Biostats Flashcards
(53 cards)
Negative predictive value
Chances that a person does not have disease when test is negative.
TN/(TN+FN)
Inversely proportional to pretest probability (and prevalence)
Incidence
Looks at new cases
Number of new cases per year / total population at risk (not including those who already have it)
How are prevalence and incidence related?
Prevalence = (incidence) x (time)
- This is given a stable population with little migration
How can a population have a stable incidence but a rising prevalence?
Improved quality of care means higher survival, so the same number of people get it but fewer die each year.
Number needed to harm
Number of pts exposed for 1 pt to be harmed.
NNH = 1/attributable risk
Attributable risk
The difference in risk between exposed and unexposed groups. Proportion of disease occurrences that are attributable to exposure.
AR = (event w risk factor / total w risk factor) - (event w no risk factor / total w no risk factor)
Absolute risk reduction
Control event rate minus treatment event rate. Difference in risk attributable to intervention, compared to control.
Just subtract the percentages!
Which of the following are affected by disease prevalence: sensitivity, specificity, positive predictive value, negative predictive value.
Only PPV and NPV
What kind of bias is loss to follow up, aka attrition bias?
This is a form of selection bias. Common when studying diseases with early mortality
Selection bias
Bias involved in recruiting and assignment to study group. Includes Berkson bias, attrition bias, and healthy worker/volunteer bias.
Berkson bias
A type of selection bias where a study only looks at inpatients
Healthy worker/volunteer bias
Selection bias where study populations are healthier than general population
Recall bias
Inaccurate recall of past exposure status based on having disease. Common in retrospective studies.
Can be reduced by getting info very soon after exposure.
Measurement bias
Information is gathered in a way that distorts it. Hawthorne effect is when people behave differently when being studied.
Reduced by using placebos and blinding
Procedure bias
Subjects in different groups are not treated the same
Observer bias
Researcher’s beliefs change outcome. Self-fulfilling prophecy. Prevented by blinding investigators
Confounding bias
A factor is related to exposure and outcome, but not on the causal pathway.
Pulmonary disease common in coal workers confounded by smoking, which is also more common in coal workers.
Reduce with multiple studies, crossover studies, and matching treatment and control groups
Lead-time bias
A screening test diagnoses a disease sooner than it would appear clinically. Falsely increases survival time, seen with improved screening tests.
Reduce by adjusting survival according to severity at diagnosis.
Cohort study
Compare a group with a given exposure to one without the exposure. Can be prospective or retrospective. Observational.
Given this exposure, who will develop disease?
Cohort study is good for measuring
Relative risk
Case-control study
Observational and retrospective. Compares a group with disease and group without disease.
Given disease status, who had exposure?
Case control study is good for measuring:
odds ratio
Cross sectional study
aka prevalence study. A snapshot in time, measures exposure and outcome simultaneously. Good for measuring prevalence. Inexpensive and easy to do.
Note: can show association, but NOT causality
Attributable risk percentage (ARP)
The excess risk in the exposed population that can be attributed to the risk factor.
ARP = (RR-1)/RR
