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Behavioral Science > Epidemiology > Flashcards

Epidemiology Flashcards

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1
Q

Regression to the Mean

A

Natural tendency for a variable to change with time and return towards population average.

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2
Q

Prevalence

A

% of people at one iven time that have the disease.

TP + FN) / (sample/population
or
Incidence x Duration (average)

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3
Q

Sensitivity

A

Proportion of those with the disease who have a positive test.

TP / (TP+FN)

SnNOUT:
If sensitivity is high and patient has a NEGATIVE test you can rule OUT the disease

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4
Q

Specificity

A

Proportion of those WITHOUT disease who have a negative test

TN/ (TN+FP)

SpPIN:
If Specificity is high and the patient has a POSITIVE test you can rule IN the disease

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5
Q

Positive Predictive Value

A

Closely related to PREVALENCE

The proportion of those with a POSITIVE test who actually have the disease.

TP/ (TP+FP)

Test the likely hood of a true result

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6
Q

Negative Predictive Value

A

The proportion of those with a NEGATIVE test who do NOT have the disease.

TN / (TN+FN)

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7
Q

Likelihood Ratios

A

How likely a test is to be positive among those with disease as opposed to those without.

LR+ = Sensitivity / 1-Specificity
LR- = 1-Sensitivity / Specificity
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8
Q

Parallel Testing

A

Several tests performed at once
Used for rapid assessment situations
Maximized Sensitivity and Negative Predictive Value
(captures all including false positives)

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9
Q

Serial Testing

A

Order nest test on basis of prior test results
Useful in clinical situations
Maximizes Specificity and Positive Predictive Value
(more sure the patient has the disease)

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10
Q

Point Prevalence

A

Existing cases at a point in time.

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11
Q

Incidence

A

Proportion of a population, initially free of outcome, that develops the condition over a given period of time.

measured by cumulative incidence or incidence density.

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12
Q

Cumulative Incidence

A

aka RISK

Probability of an individual developing the disease during a specific period of time.

Number new cases of disease during a given time period DIVIDED BY Total persons initially AT RISK for the same time period.

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13
Q

Incidence Density

A

Number of new cases of disease during a given time DIVIDED BY population (TOTAL person time)

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14
Q

Risk Factors

A

Characteristics that are either directly related or likely lead to the target condition.

Relative importance is assessed by frequency and magnitude.

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15
Q

Criteria for causation argument

A

Statistically significant association and:

  • exposure preceding disease
  • strength of association (high relative risk, RR)
  • dose-response relationship
  • consistency from study to study
  • cofounders considered

Impairments:
same effect from other causes
more than one causal factors to produce effect.
long interval between cause and effect.

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16
Q

Case Report

A

Experience of a single patient with a unique finding

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17
Q

Case series

A

experience of a group of patients with similar diagnosis

18
Q

Cross-sectional studies

A

Prevalence study

Relationship between exposure and disease prevalence at a single point in time.

Strengths
• May generate new etiologic hypotheses
• Relatively easy and inexpensive
• Can use data collected for other purposes

Weaknesses
• No cause-effect
• Measures at one point in time; No temporality
• Prevalent cases are survivors

(see notes for set-up)

19
Q

Case-Control sudies

A

Key comparison: Disease vs. No Disease
Measure the risk of exposure in the Disease group vs. the No Disease group.

*looking at those with disease and without and trying to determine risk factors, exposures, etc.

Strengths:

  • Smaller in size
  • Useful for rare or unusual diseases
  • Can evaluate multiple risk factors at once.

Weaknesses:

  • Cannot determine incidence directly (estimated RR)
  • Uncertainty in exposure-disease time relationship
20
Q

Cohort Studies

A

Key comparison: Risk Factor or No Risk Factor
Longitudinal study
Group of people who have something in common; observed over time to see what happens to them

Strengths:

  • directly determines incidence & risk
  • reduced bias by measuring exposure first.

Weaknesses:

  • requires large sample size
  • long time to complete
  • expensive
21
Q

Cross-sectional Analysis

A

Point Estimate,
Confidence intervals,
P-value (less valuable than CI)

22
Q

Cohort Analysis

A

Risk Ratio
Abolute Risk
Confidence Interval,

23
Q

Case Control Analysis

A

Odds Ratio

Confidence Interal

24
Q

Relative Risk

A

Used in Cohort Studies

Risk Ratio [a/(a+b)] / [c/(c+d)] = 1- no association, >1 increased risk, <1 decreased risk

25
Q

Absolute Risk

A

Used in Cohort Studies

(exposure - no exposure) or [a/(a+b)] - [c/(c+d)] = 0 - no association, >0 excess amount of disease in exposed group, <0 decreased amount of disease.

26
Q

Odds Ratio

A

Used in Case control studies

(ad/bc) = >1 - increased risk of disease,
<1 - decreased risk of disease, 1 - no association

27
Q

Confounding Bias

A

Occurs when two factors are associated with each other and the effect of a third factor confuses the association.

Controlled in the study via randomization, restriction of inclusion criteria, and control matching.

Controlled in analysis via stratification, multivariate analysis

28
Q

Relative Risk Reduction

A

Used in experimental studies
Describes the magnitude of the effect. % Reduction in risk of studied outcome.

may overestimate clinical relevance, varies across populations.

[(control event rate - experimental event rate)/ control event rate]

29
Q

Absolute Risk Reduction

A

Describes the risk difference in outcomes between patients who have undergone one therapy and those who have not.

How many patients are spared the adverse outcome, varies with underlying risk

[control event rate - experimental event rate]

30
Q

Number Needed to Treat

A

Describes how many patients need to be treated to prevent one of them from experiencing the outcome

[1 / (control - experimental event rate)]

If the absolute risk reduction is large few patients are needed to observe benefit.

31
Q

Intention-to-Treat analysis

A

analysis according to group assigned (randomization) regardless of treatment received.

Tests efficacy (desired effect) as well as Effectiveness (does it work in usual practice)

32
Q

Explanatory analysis

A

Analysis according to treatment actually received regardless of randomization.

Tests efficacy

33
Q

Randomized Clinical trials

A

Strengths:

  • control over study situation
  • control of exposure
  • random assignment (reduced bias)

Weaknesses:

  • external validity (real world application?)
  • adherence to protocols
  • ethics
34
Q

Experimental Event Rate

A

Risk of outcome event in experimental group

= a/(a+b)

35
Q

Control Event Rate

A

Risk of outcome event in control group

= c/ (c+d)

36
Q

Survival Curves

A

Area under cure = number of person-years lived by the population studied.

A death at time t causes curve to drop by the following amount:

(current height) x (N-1) / N [N=no. of survivors]

37
Q

Crude mortality rate

A

new deaths / total population (in given time)

38
Q

Age specific mortality

A

No. deaths in specified age / population in that age group (in a given time, usually 1 year)

39
Q

Disease specific morality

A

No. death of specified cause/ Total population

40
Q

Proportionate morality rate

A

No. deaths from specific disease / total number of deaths during same time period

41
Q

Case fatality rate

A

no. who died from disease / no. who have the disease

Behavioral Science (3 decks)

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