Biostats

Question 1

Prevalence

Answer 1

of existing cases of a disease at a specified time / # of people in base population at that time

Question 2

Incidence

Answer 2

new cases occurring in a specific time period / # people initially at risk

Question 3

Case fatality

Answer 3

of people who die of a disease / total # people with the disease

Question 4

Mortality

Answer 4

people dying of a disease in a specified time period / # people alive during that time period

Question 5

Years of Potential Life Lost (YPLL)

Answer 5

Calculated by multiplying the number of cause-specific deaths in an age group by the difference between the midpoint of the age group and the average age at death (assumed to be 75)

Question 6

Reasons for an association betweeen a factor and a disease

Answer 6

Bias in the sampling of subjects
Bias in the measurement of the factor
Confounding 
Chance
Transposition of cause and effect
Causal

Question 7

Relative Risk

Answer 7

Incidence of disease in the exposed / incidence of disease in the unexposed

Ex: 3.5x more likely to have cancer if you smoke

Question 8

Attributable Risk

Answer 8

The difference between incidence of the disease in individuals with a risk factor and in those without a risk factor

AR = risk in the exposed - risk in the unexposed

Ex: In population X, 500 per 1,000 cases are due to smoking

Question 9

Number Needed to Treat (NNT)

Answer 9

NNT = 1 / attributable risk

If 10 cases out of 50 are due to risk factor X, then NNT = 1 / (10/50) = 5 needed to treat in order to gain 1 outcome

Question 10

Population Attributable Risk (PAR)

Answer 10

The proportion of cases that would be prevented if the risk factor could be eliminated from the population

PAR = total incidence - incidence in unexposed / total incidence

Question 11

Cross-Sectional study

Answer 11

Usually large surveys of a representational sample group; assesses both risk factors and disease status in the present in order to draw correlations; can give information about the relative risk for certain diseases given exposure to different risk factors

Question 12

Case-control (retrospective study)

Answer 12

A sample of cases and controls are examined for past history of risk factors; association of the disease with the risk factor is assumed to correlate with an association between the risk factor and the disease

Susceptible to sampling bias and re-call bias

Question 13

Cohort Study

Answer 13

AKA Prospective, longitudinal study

A cohort (exposed and unexposed) is assembled and followed over time to determine who develops disease

Limited utility for very rare diseases or very long latencies, vulnerable to bias if loss-to-follow up is unequal in exposure vs. unexposure groups

Question 14

Randomized Controlled Trial (RCT)

Answer 14

Participants are randomized to trial arm (exposed) or control arm (unexposed) and followed to assess outcomes

High internal validity, lower external validity (groups were artificially designed and so are not representative)

Vulnerable to cross-over; must use an intent-to-treat analysis

Question 15

Sensitivity

Answer 15

Describes how good a screening test is at detecting true positives.

Sensitivity = TP / (TP + FN)

Question 16

Specificity

Answer 16

Describes how often a test shows true negatives.

Specificity = TN / (TN + FP)

Question 17

Positive Predictive Value (PPV)

Answer 17

Describes how often individuals with positive test results actually have the disease

PPV = TP / (TP + FP)

PPV increases with higher disease prevalence. Increased test specificity increases PPV.

Question 18

Negative Predictive Value (NPV)

Answer 18

Describes how often individuals with negative test results are actually disease-free

NPV = TN / (TN + FN)

NPV increases with lower disease prevalence and increased sensitivity.

Question 19

Lead-time bias

Answer 19

If a new screening test diagnoses a disease one year earlier but treatment has no effect on survival, data will show a false 1-year improvement in survival; this is an artifact of lead-time bias

Question 20

Length time bias

Answer 20

Screening tests are likely to pick up individuals with longer asymptomatic phases (because symptomatic patients have already been diagnosed, we assume); therefore, those cases detected by screening are more likely to have longer disease regardless of whether it is detected by screening or not

Question 21

2 methods for combining screening tests

Answer 21

1. Parallel testing - The overall screening result is positive if any one test is positive; increases sensitivity at the expense of specificity
2. Series testing - The overall screening result is positive only if all tests are positive; increases specificity at the expense of sensitivity

Question 22

2 types of quantitative variables

Answer 22

1. Continuous, i.e. weight, BP, serum levels, etc.
   Continuous data are compared with t-test
2. Categorical (ordinal), i.e. no disease vs. disease
   Categorical data are compared with Chi Square test

Question 23

Mode

Answer 23

The most commonly observed value

Question 24

Median

Answer 24

The middle value in a data set arranged lowest to highest

Question 25

Mean

Answer 25

The arithmetic average

Mean = sum(x) / n

Question 26

Range

Answer 26

The highest value minus the lowest value

Question 27

Variance

Answer 27

Variance = sum (x - mean)^2 / (n - 1)

Question 28

Standard deviation

Answer 28

The square root of the variance

Question 29

Characteristics of a normal distribution

Answer 29

Mean = median
67% of values lie within 1 standard deviation from the mean
95% of values lie within 2 standard deviations of the mean

Question 30

Type I error

Answer 30

False Positive

The investigator wrongly concludes that there is a difference, when the difference actually occurred as a result of chance or bias

Question 31

Type II error

Answer 31

False Negative

The investigator concludes that there is no difference, when actually there is a true difference obscured by chance or bias

Question 32

P value

Answer 32

The probability that chance alone caused the observed association

.05 is a conventional threshold

Question 33

Confidence Interval

Answer 33

The range of values within which you are X% confident that the true value lies

95% CI identical to P = .05

Question 34

Effect Modification

Answer 34

Occurs when the effect of a risk factor on an outcome is different at different levels of a third factor; the third factor is known as the effect modifier

Ex: age, gender

Question 35

Beta Value

Answer 35

Beta is the acceptable risk of making a type II (false negative) error, arbitrarily set at .2

Power = 1 - B x 100

Therefore, a study that accepts the null should be able to shower a power of 80% or higher