Biostatistics

Question 1

Cross-sectional study

Answer 1

What is happening at a particular point in time? Good for determining disease prevalence and risk factors.

Question 2

Case-control study

Answer 2

What happened in the past? Compares a group with disease to a matched group without disease and searches for associations. Calculate Odds Ratio (OR).

Question 3

Cohort study

Answer 3

Can be prospective (Who will develop disease?) or retrospective (Who developed disease?). Compares a group with a certain exposure/risk to a group without that exposure and asks who developed or will develop disease? Calculate Relative Risk (RR).

Question 4

Phase I of drug trial

Answer 4

Small number of healthy volunteers. Is it safe?

Assesses safety, toxicity, pharmacokinetics.

Question 5

Phase II of drug trial

Answer 5

Small number of patients with the disease of interest. Does it work?

Question 6

Phase III of drug trial

Answer 6

Large number of patients randomly assigned either to treatment or to best available treatment (standard of care). Is it as good as or better?

Question 7

Phase IV of drug trial

Answer 7

Post-marketing surveillance of patients after treatment FDA approved. Can it stay? Detects rare or long-term adverse effects.

Question 8

Evaluation of diagnostic tests for sensitivity and specificity

Answer 8

———Dz+ Dz-
Test+ TP (a) | FP (b)
Test- FN (c) | TN (d)

Question 9

Sensitivity

Answer 9

= a/a+c

Question 10

Specificity

Answer 10

= d/b+d

Question 11

Positive predictive value (PPV)

Answer 11

= a/a+b = true positive/all positives

Question 12

Negative predictive value (NPV)

Answer 12

= d/c+d = true negative/all negatives

Question 13

Contingency table for quantifying risk

Answer 13

——–Dz+ Dz- (Disease/outcome)
Ex + a b
Ex - c d
(Exposure/Risk factor/Intervention)

Question 14

Odds Ratio (OR)

Answer 14

= (a/c)/(b/d)= ad/bc
=Odds that the cases were exposed to risk versus the controls.
Used for case-control studies.

Question 15

Relative Risk (RR)

Answer 15

= [a/(a+b)] / [c/(c+d)]
= Risk of developing dz in the exposed group/ risk of developing dz in the unexposed group.
Used for cohort studies.
IF prevalence of disease is low, then OR approximately equals RR.
RRR= 1-RR

Question 16

Attributable risk (Absolute Risk Increase)

Answer 16

= [a/(a+b)] - [c/(c+d)]
= The difference in risk between the exposed group and unexposed group (or the difference in risk attributable to the exposure).
Used to calculate the NNH.

Question 17

Relative risk reduction (RRR)

Answer 17

= 1 - RR
= 1- [a/(a+b)] / [c/(c+d)]
= Proportion of risk reduction attributable to the intervention.

Question 18

Absolute Risk Reduction (ARR)

Answer 18

= [c/(c+d)] - [a/(a+b)]
= The difference in risk between the unexposed group and the exposed group (or the difference in risk attributable to the intervention).
Used to calculate the NNT.

Question 19

Number Needed to Treat (NNT)

Answer 19

NNT = 1/ Absolute Risk Redution

= the number of patients that need to undergo an intervention for 1 patient to benefit.

Question 20

Number Needed to Harm (NNH)

Answer 20

NNH = 1/ Attributable Risk

= the number of patients that need to be exposed to a risk factor (or intervention) for 1 patient to be harmed.

Question 21

Incidence

Answer 21

= # new cases in a time period/# of ppl at risk

Question 22

Prevalence

Answer 22

= # existing cases at one point in time/ # of ppl at risk

Question 23

True negative

Answer 23

=Specificity * # pts without disease

= [d/b+d]*(b+d)

Question 24

True positive

Answer 24

=Sensitivity * # pts with disease

=[a/a+c] *(a+c)

Question 25

Positive likelihood ratio

Answer 25

=Sensitivity/ (1 - Specificity)

Question 26

Negative likelihood ratio

Answer 26

=(1 - Sensitivity)/Specificity

Question 27

95% Confidence Interval

Answer 27

= mean +/- 1.96 *SD/sqrt(n)

Question 28

Type I error

Answer 28

Occurs when research rejects the null hypothesis (finds a difference), but the null hypothesis is true (there is no real difference). Aka a FALSE POSITIVE ERROR.

Question 29

Alpha

Answer 29

The probability of making a Type I error

Question 30

Type II error

Answer 30

Occurs with research fails to reject a null hypothesis (find a difference), but the null hypothesis is false (there is a real difference). Aka a FALSE NEGATIVE ERROR.

Question 31

Beta

Answer 31

The probability of making a Type II error. Power of a study = 1 - beta

Question 32

Statistical power

Answer 32

= (1 - beta). It represents a study’s ability to detect a difference (reject the null hypothesis) when on truly exists. Power is typically set at 80% and depends on the sample size and difference between outcomes.