2 - Association in Medicine Flashcards

1
Q

Understand the concepts of rate and risk.

A

RATE: A measure of event frequency; the speed with which events happen, relative to the size of the population experience observed

RISK: The probability that an event will occur in a defined period of time

  • -For uncommon events, a rate of X per 100 person-years implies a one-year risk of X percent
  • -Neonatal/infant mortality is a RISK, not a rate
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Understand the different uses and implications of relative risk and risk differences.

A

RELATIVE RISK: risk exposed/risk unexposed

  • -The farther RR is from 1.0, the stronger the evidence for a causal relationship
  • -Tend to be similar across populations, but does NOT indicate causality unless very high (-> increases suspicion)
  • -Doesn’t capture what you stand to gain or lose
  • -No units!

RISK DIFFERENCE: risk assumed (or avoided) with risk factor [risk exposed - risk unexposed]

  • -Measures clinical effect (“you increase your risk by 2.5%” rather than “you’ve doubled your risk”)
  • -Smaller if background risk is small
  • -Larger if background risk is large
  • -Always has units (e.g. per 1,000 person years)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Understand how confounding can distort assessment of associations; describe the strategies that can be used in research to deal with confounding.

A

Ex: alcohol intake is associated with smoking. If you are looking at smoking as a relative risk for cancer, but alcohol use is very common in smokers (>3x as common as in non-smokers, perhaps) and alcohol increases your risk of cancer by a lot, then alcohol is a confounding factor that could explain all of the risk for cancer.
–Lifestyle habits run in packs, so you need to deal with confounding

Dealing with confounding:

  • -MATCH on confounder: match population (people who drink 3x a day + people who smoke and drink 3x a day, or age matching, etc.)
  • -ADJUST for confounder: using statistical methods or weighted stratification
  • -RESTRICT analysis: study effects of coffee-lung cancer association only among life-long non-smokers so smoking doesn’t confound risk
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Define adjusted analysis.

A

An analysis in which statistical account is made for potential confounding factors, so that an estimate of the independent effect of a risk factor can be made

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

Define cohort.

A

A group of subjects followed over time

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

Define competing risks.

A

Events that prevent the observation of a possible endpoint

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

Define confounding.

A

An indirect association of an exposure with a disease

Due to the association of the exposure with a confounding factor which is also related to the disease

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

Define effect.

A

The magnitude of a difference or relationship

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

Define event. List four examples.

A

A clinical outcome of importance

–Ex: onset of a disease, onset of a particular symptom, disease recurrence, or death

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

Define incidence.

A

The risk or rate or occurrence of new cases of a disease
Inherent time element!
–Ex: incidence of HTN is low, but prevalence is quite high

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

Define matched analysis.

A

Choosing exposed and unexposed subjects to have the same or similar values of some trait or exposure
Typically done to control confounding

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

Define prevalence.

A

The proportion of individuals who have a particular disease or trait in a given population
EXISTING cases at a point in time
Cross sectional - affected by disease incidence and duration

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Define rate.

A

A measure of event frequency

The speed with which events happen, relative to the size of the population experience observed

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

Define relative risk (aka rate ratio, risk ratio)

A

A ratio of risks
Also used to refer to any relative measure of association
Numerator = occurrence of events (risk, rate, odds, hazard) in an exposed group
Denominator = occurrence of events in an unexposed group

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

Define restricted analysis.

A

Confining the analysis to one group of subjects to minimize confounding

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

Define risk.

A

The probability that an event will occur in a defined period of time

17
Q

Define risk difference.

A

The difference between the risks of an exposed group and an unexposed group during a defined period of time
The risk of disease attributable to the exposure

18
Q

Define risk factor.

A

An exposure associated with the occurrence of a disease or outcome

19
Q

Define stratum.

A

A grouping of subjects, typically formed for the purposes of adjustment
–Ex: age groups

20
Q

What is confounding by indication?

A

Disease severity associated with treatment
–Ex: use treatment Y for very severe disease and treatment Z for mild disease. Treatment Y will be associated with worse outcomes

21
Q

T/F: Risk factors strongly related to a disease are virtually always causal.

A

FALSE - can just be associated

22
Q

T/F: Risk difference is the most scientific way to understand an exposure/disease relationship.

A

FALSE - only important in communicating with patients

23
Q

T/F: An association with a high relative risk will always be clinically important.

A

FALSE - must be meaningful (can take you from 0.00000001 to 0.0000001)

24
Q

T/F: Risk differences tend to be more or less constant across populations with different disease rates.

A

FALSE. Increase with increasing disease rate, decrease with decreasing disease rate

25
Q

T/F: A risk factor with a high risk difference will almost always be causal.

A

FALSE - can have a strong association only or confounding factors
–It is inappropriate to look at risk differences as causal relationships

26
Q

T/F - An association confounded in real life cannot ever be investigated properly.

A

FALSE - can adjust via matching, adjusting, or restricting analysis

27
Q

T/F: The number of babies in NH born with neural tube defects per 1000 live births in 2009 is a measure of prevalence not incidence.

A

TRUE. Birth conditions reported as PREVALENCE at birth.