Biostats Flashcards

1
Q

What is frequency of disease in population?

A

prevalence, incidence, and attack rate

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

How well does test differentiate sick from healthy?

A

sensitivity and specificity

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Of those in population who test as sick or healthy, how true is that?

A

Predictive value

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What is impact of medicine/treatment?

A

Risk reduction/increase

NNT, NNH

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Prevalence

A

helps understand disease burden or extent of health problem

= # of people with disease at specific point/# of people AT RISK for illness at same point in time

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Period prevalence

A

during a period of time (specific)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Lifetime prevalence

A

over course of a lifetime

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Incidence

A

helps understand risk of specific health event
= # of NEW people with disease during time period/# of people at risk for illness during time period
if you already have disease -> not at risk anymore

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Cumulative incidence

A

total number reported over time

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Attack Rate

A

type of incidence used during short period of time (specific exposures/outbreaks)
= # new cases/#exposed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Secondary Attack Rate

A

= # of new cases/(# exposed - primary cases)

- measures person-to-person spread of disease after initial exposure

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What affects prevalence and incidence?

A
Duration of illness (higher prevalence)
Number of new cases (higher prevalence)
Ill people coming in (higher prevalence)
Healthy people leaving (higher prevalence)
Recovery/death (lower prevalence)
Prevention (lower incidence)
Changes in diagnostic criteria
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Relationship between prevalence and incidence

A

Chronic illness –> prevalence = incidence x average duration
Acute illness –> prevalence = incidence

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Sensitivity

A

probability that diseased person will be ID correctly (true-positive)
= true positives/ total # ill people (TP and FN)
True positives = ill people ID as ill
False negative = ill people ID as healthy

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Specificity

A

probability that well person will be ID correctly (true-negative)
= true negative/ total # well people (TN and FP)
True negative = healthy people ID as healthy
False positive = healthy people ID as ill

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Highly sensitive test

A

ID most of all possible disease cases

- will over-diagnose some people without disease

17
Q

Highly specific test

A

ID most or all well people

- will under-diagnose some people that do have disease

18
Q

Predictive value

A

probability that test will give correct diagnosis

  • depends on sensitivity and specificity
  • will vary from population to population (depends on prevalence of disease in population)
  • looking at rows of 2x2 table
19
Q

Positive predictive value

A

probability that person who tests positive for disease truly has it
= TP/TP+FP

20
Q

Negative predictive value

A

probability that person who tests negative for disease truly is healthy
= TN/TN+FN

21
Q

Predictive value with high disease prevalence

A

higher PPV

lower NPV

22
Q

Predictive value with low disease prevalence

A

lower PPV

higher NPV

23
Q

Risk reduction/NNT

A

relevant when comparing effects of RCT

  • interest in understanding risk of treatment vs no treatment
  • what is frequency of bad outcomes in group being treated compared to group not being treated?
24
Q

Randomized control trials

A

1 treatment group and 1 control group

- groups can respond positively or negatively

25
Q

Control Event Rate

A

proportion of control group participants who have bad outcome after “treatment” (placebo)

26
Q

Experimental Event Rate

A

proportion of treatment group participants who have bad outcome after treatment (drug)

27
Q

Absolute Risk

A

probability of developing disease or undesired outcome

28
Q

Absolute Risk Reduction

A

control event rate is HIGHER than experimental event rate

CER - EER > 0

29
Q

Absolute Risk Increase

A

control event rate is LOWER than experimental event rate

CER - EER < 0

30
Q

NNT

A

number of patients who need to be treated to get 1 additional patient a favorable outcome
NNT = 1/ARR

31
Q

NNH

A

number of patients who, if treated, would result in 1 additional patient being harmed
NNH = 1/ARI