Clinical Epidemiology

Question 1

What is incidence?

Answer 1

Incidence is a measure of disease risk.

Incidence = (# of new cases in a time period) / (number of people in population at risk at the start of that time period)

Question 2

What is prevalence?

Answer 2

Prevalence is a measure of disease burden.

Prevalence = (# of existing cases in the population at a given point in time) / (number of people in the population at that same time)

Prevalence = Incidence x Duration

Question 3

How can multiple possible outcomes for a diagnostic test be represented in a table?

Answer 3

Question 4

What is sensitivity?

Answer 4

Sensitivity is the probability that a test correctly classifies individuals with the disease as positive.

Sensitivity = (# of individuals with disease who test positive) / (# of individuals with disease)

Sensitivity = TP / (TP + FN)

Sensitivity is an inherent characteristic of a test and is not related to prevalence.

Sensitivity rules out (SnOUT).

Question 5

What is specificity?

Answer 5

Specificity is the probability that a test correctly classifies individuals without disease as negative.

Specificity = (# of individuals without disease who test negative) / (# of individuals without disease)

Specificity = TN / (TN + FP)

Specificity is an inherent characteristic of a test and is not related to prevalence.

Specificity rules in (SpIN).

Question 6

What is a false positive rate?

Answer 6

A false positive rate is the proportion of healthy individuals who incorrectly get a positive result.

False positive rate = (# of individuals without disease who test positive) / (# of individuals without disease)

False positive rate = FP / (FP + TN)

Question 7

What is the false negative rate?

Answer 7

The false negative rate is the proportion of diseased individuals who incorrectly get a negative result.

False negative rate = (# of individuals with disease who test negative) / (# of individuals with disease)

False negative rate = FN / (FN + TP)

Question 8

What is the positive predictive value?

Answer 8

The positive predictive value is the probability of the disease given a positive test.

Positive predictive value = (# of individuals with disease who test positive) / (# of individuals who test positive)

Positive predictive value = TP / (TP + FP)

Positive predictive value is not inherent to a test. It depends on both the characteristics of the test and the prevalence of disease.

Question 9

What is the negative predictive value?

Answer 9

The negative predictive value is the probability of not having the disease given a negative test.

Negative predictive value = (# of individuals without disease who test negative) / (# of individuals who test negative)

Negative predictive value = TN / (TN + FN)

Negative predictive value is not inherent to the a test. It depends on both the characteristics of the test and the prevalence of the disease.

Question 10

What is absolute risk reduction?

Answer 10

Absolute risk reduction = [Risk in the control (unexposed) group] - [Risk in the treatment (exposed) group]

Risk is the incidence of the outcome in the group

Question 11

What is absolute risk increase?

Answer 11

Absolute risk increase = [Risk in the treatment (exposed) group] - [Risk in the control (unexposed) group]

Question 12

What is relative risk?

Answer 12

Relative risk = (Risk of the disease in the exposed) / (risk of disease in the unexposed)

Question 13

What is relative risk reduction?

Answer 13

Relative Risk Reduction = 1 - (Relative Risk)

Question 14

What is number needed to treat?

Answer 14

The number needed to treat is the absolute number of patients who would need to be treated to prevent one instance of the bad outcome.

Number Needed to Treat = 1/ (Absolute Risk Reduction)

Question 15

What is number needed to harm?

Answer 15

Number needed to harm is the absolute number of patients who would need to be treated for a bad outcome (usually a side effect) to occur.

Number Needed to Harm = 1 / (Absolute Risk Increase)

Question 16

What is a likelihood ratio?

Answer 16

Likelihood Ratio = (Probability of an individual with the condition having the test result) / (Probability of an individual without the condition having the same test result)

Question 17

What is the likelihood ratio of a positive test (LR+)?

Answer 17

Likelihood Ratio of a Positive Test (LR+) = (Probability of a person with disease having a + test) / (Probability of a person without disease having a + test)

Likelihood Ratio of a Positive Test (LR+) = Sensitivity / (1-Specificity)

The higher the LR+, the more likely the disease is present (rules in disease).

Question 18

What is the likelihood ratio of a negative test result (LR-)?

Answer 18

Likelihood Ratio of a Negative Test Result (LR-) = (Probability of a person with disease having a - test) / (Probability of person without disease having a - test)

Likelihood Ratio of a Negative Test Result (LR-) = (1 - Sensitivity) / Specificity

The lower the LR-, the more likely the disease is not present (rules out disease).

Question 19

What is diagnostic probability?

Answer 19

Diagnostic probability is the chance that a certain disease is the cause of a patient’s clinical findings.

Question 20

What is a heuristic?

Answer 20

A heuristic is a mental shortcut or a rule of thumb developed from prior experience that leads to rapid problem solving and decisions.

Question 21

What are the two most common heuristics doctors use to make diagnoses?

Answer 21

The two most common heuristics doctors use to make diagnoses are the availability heuristic and the representative heuristic.

Question 22

What is Bayes’ Theorem?

Answer 22

Bayes’ Theorem is used to calculate the post-test probability of an individual’s condition (disease or disorder) from the following three elements: the prevalence or pre-test probability of the condition in the population of that individual, the outcome of the test, and the psychometric characteristics of a test (sensitivity and specificity).

Bayes’ Theorem states the following:

Post-Test Probability = (Pre-Test Probability) * LR