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SBM II December > Biostatistics > Flashcards

Biostatistics Flashcards

(69 cards)

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1
Q

What does Prevalence, Incidence and Attack Rate tell us?

A

What is the frequency of disease in a population?

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2
Q

What does Sensitivity and specificity tell us?

A

How well does a test differentiate sick from healthy people?

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3
Q

What does predictive value tell us?

A

Of those in a population who test as sick of healthy, how many are truly sick or healthy?

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4
Q

What does Risk Reduction/Increase and Number-needed-to-treat/harm tell us?

A

What is the impact of a medicine/treatment?

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5
Q

What does point prevalence help us understand?

A

Disease burden or extent of a health problem.

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6
Q

What is prevalence?

A

[Number with a disease at a specific point in time]/[Number at risk of illness during that time period]

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7
Q

What is period prevalence?

A

Prevalence during a period of time

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8
Q

What is lifetime prevalence?

A

Prevalence over the course of a lifetime

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9
Q

What does incidence help us understand?

A

The risk of a specific health event

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10
Q

What is incidence?

A

[Number of NEW people with DZ during a time period]/[Number at risk of illness during that time period]

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11
Q

What is the main measure of acute diseases?

A

Incidence

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12
Q

What helps determine causation?

A

Incidence

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13
Q

What is cumulative incidence?

A

Total number reported over time

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14
Q

What is Attack Rate?

A

Refers to outbreaks - similar to prevalence over a very short period of time

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15
Q

When is Attack Rate used?

A

When the nature of disease is acute and population observed for short period of time (ex. outbreaks, specific exposures)

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16
Q

How do you calculate Attack Rate?

A

[Number new cases]/[Number exposed]

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17
Q

How do you calculate Secondary Attack Rate?

A

[Number new cases]/[Number exposed - primary cases]

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18
Q

What does Secondary Attack Rate measure?

A

Person to person spread of disease after initial exposure

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19
Q

What is Secondary Attack Rate similar to over a very short period of time?

A

Incidence

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20
Q

What affects prevalence and incidence?

A
  • Duration of illness (longer –> higher prevalence)
  • Number of new cases (more new cases –> higher prevalence) - incidence high
  • Migration - In (ill –> higher prevalence); Out (well –> higher prevalence)
  • ->Recovery and death –> lower prevalence
  • Prevention –> lower incidence
  • Changes in diagnostic criteria or reporting
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21
Q

What is the relationship between prevalence and incidence if the disease is long term (ex. diabetes)?

A

Prevalence > Incidence

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22
Q

What is the relationship between prevalence and incidence if the illness is acute (ex. flu)?

A

Prevalence ~ Incidence

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23
Q

What is sensitivity?

A

The probability that a diseased person will be identified correctly by a diagnostic/screening test

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24
Q

What is another name for sensitivity?

A

True-positiive probability or true-positive rate

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25
What is the equation for sensitivity?
True Positives/ Total # of ill people
26
What should you remember with Sensitivity?
SNOUT - High sensitivity rules disease out
27
What is the total number of ill people?
True positives + False negatives
28
What is Specificity?
Probability that a well (non-diseased) person will be identified correctly by a diagnostic/screening test
29
What is another name for specificity?
True-negative probability
30
What is the equation for specificity?
True negatives/total # of well people
31
What should you remember with Specificity?
SPIN - High specificity disease rules in
32
What is the total # of well people?
TN + FP
33
What does a high sensitivity test err on the side of?
Over-diagnosing
34
What does a high specificity test err on the side of?
Under-diagnosing
35
What should you remember with high sensitivity tests?
- Identify most or all possible disease cases; may identify some healthy people as sick - Most useful when under-diagnosing may lead to severe consequences (ex. fast developing cancers)
36
What should you remember with high specificity tests?
- Identify most or all well people; may miss some of the sick people - Most useful when over-diagnosing leads to dangerous, painful or unnecessary treatment
37
What is a predictive value?
Probability that a test will give the correct diagnosis
38
What does predictive value depend on?
- Test sensitivity and specificity; prevalence of the DZ in the population being tested - Predictive values will vary from population to population and study to study
39
What is Positive Predictive Value?
Probability that a person who tests positive for a disease truly has it (is really sick)
40
What is the equation for PPV?
PPV = TP/(TP + FP) --> Top row of a 2x2 table
41
What is the equation for NPV?
NPV = NP/(NP + FN) --> Bottom row of a 2x2 table
42
What is Negative Predictive Value?
Probability that a person who tests negative for a disease truly is well
43
How does High prevalence relate to predictive value?
- Higher disease prevalence --> Higher PPV (greater chance that positive test result reflects true illness) - -> Lower NPV (lower change that negative test reflects disease-free status)
44
How does Low prevalence relate to predictive value?
- Lower disease prevalence --> Lower PPV (lower chance that positive test result reflects true illness) - -> Higher NPV (greater chance that negative test result reflects disease-free status)
45
When is Risk Reduction and Number-Needed-To-Treat relevant?
When comparing effects in randomized controlled trials.
46
Why are we interested in Risk Reduction and Number-Needed-To-Treat?
Interested in understanding risk of treatment vs. no treatment
47
What are we asking in Risk Reduction and Number-Needed-To-Treat studies?
What is the frequency of bad outcomes in group being treated compared to the group not being treated?
48
Randomized Controlled Trials (RCT):
- Have at least one treatment group and one control group - People in both groups may have positively (placebo effect) or negatively (harmful effects) - How do we compare different group response rates?
49
What is Control Event Rate (CER)?
Proportion of control group participants who have a bad outcome after "treatment" (ex. placebo or no rx)
50
What is the CER if 10 of 30 control group participants become sicker?
CER = 10/30 = 33% have adverse outcomes
51
What is Experimental Event Rate (EER)?
Proportion of treatment group participants who have a bad outcome after treatment (ex. new drug)
52
What is the EER if 4 of 30 treatment groups become sicker?
EER = 4/30 = 13% had adverse outcomes
53
What is Absolute Risk?
"risk difference" = difference in risk of developing a DZ or undesired outcome after treatment
54
How do you calculate Absolute Risk?
CER-EER
55
What is an Absolute Risk Reduction (ARR)?
When CER > EER - higher rate of adverse outcomes in control group --> sometimes referred to as "attributable risk"
56
What is an Absolute Risk Increase (ARI)?
When EER > CER - higher rate of adverse outcomes in treatment group
57
What is Relative Risk?
"risk ratio" = proportion of treatment group risk to control group risk
58
How do you calculate Relative Risk?
EER/CER
59
How does risk of bad outcome change in the treatment group with RR?
Risk Increases when RR > 1 | Risk Decreases when RR
60
What is Relative Risk reduction/increase?
Difference in 2 event rates, as a proportion of the event rate in the control group
61
What is the equation for Relative Risk Reduction/Increase?
1-RR or AR/CER
62
What is the equation for Relative Risk Reduction?
CER > EER
63
What is the equation for Relative Risk Increase?
EER > CER
64
What is Number Needed To Treat (NNT)?
Number of patients who need to be treated to get 1 additional patient a favorable outcome
65
What is the equation for NNT?
NNT = 1/ARR
66
Explain what NNT = 5 means?
For every 5 people treated, 1 more person would respond to the drug
67
What is Number Needed to Harm (NNH)?
Number of patients who, if they were treated, would result in 1 additional patient being harmed
68
How does NNH relate to ARI?
NNH = 1/ARI
69
Explain wheat NNH = 3 means?
If 3 people were treated, 1 more person would not respond compared with the control group.

SBM II December (11 decks)

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