Epidemiology (IX) Miscellaneous

Question 1

Increasing the cutoff will do what to specificity & sensitivity?

Answer 1

Increasing the cutoff decreases sensitivity but increases specificity (fewer false positives, but more false negatives)

Decreasing it would do the opposite.

Question 2

PPV increases if ___ or ___ increases

Answer 2

prevalence or specificity

Question 3

Calculating net sensitivity in sequential testing?

Answer 3

of people who tested positive on test2/# of people who truly had the disease

Question 4

Calculating net sensitivity in parallel testing?

Answer 4

# of people who tested positive on BOTH tests + ppl who tested positive on test1 + ppl who tested positive on test2 
/
# of people who truly have disease

Question 5

Calculating net specificity in sequential testing?

Answer 5

# of people who tested negative on first test + # of people who tested negative on second test
/
# of people who actually don't have disease

Question 6

Calculating net specificity in parallel testing?

Answer 6

# of people  who tested negative on BOTH tests
/
# of people who actually don't have disease

Question 7

In calculating the kappa statistic,

How do you find “observed agreement (%)”?

Answer 7

It’s overall percent agreement (a+d)/(a+b+c+d)

Question 8

In calculating the kappa statistic,

How do you find “Agreement expected from chance alone (%)”?

Answer 8

Apply Observer A’s percentages for positive and negative to Observer B’s totals for positive and negatives.

Now, add these results and divide by the total # of cases.

Question 9

Kappa can have no agreement better than chance alone, poor agreement, intermediate agreement, or excellent agreement. What is the range for intermediate agreement?

Answer 9

0.4 - 0.75

Question 10

Epidemic Curve

Answer 10

# of disease cases on Y-axis
Time on the X-axis

Question 11

Investigation of an outbreak

Answer 11

define the epidemic
examine the distribution of cases
look for combinations of relevant variables
develop hypotheses
test hypotheses
recommend control  measures

Question 12

Annual incidence rate

Answer 12

of new cases in a specified population during a given year
/
Midyear population estimate

Question 13

Mortality rate/ Annual Crude Mortality

Answer 13

of deaths in a specified population during a specified time period
/
Person-time contributed by the population during the time period OR midyear population

*Either way, this is a RATE- never expressed as a percentage

Question 14

Indirect adjustment tells us how risk compares between one population and a standard population. How do you calculate it?

Answer 14

SMR/SIR =

Observed # of deaths or disease per year
/
Expected # of deaths or diseases per year

where expected # is determined by multiplying a known population’s rates by the study population size

Question 15

What’s the difference between mortality rate from disease X and case fatality from disease X?

Answer 15

Both have the numerator as the people who died from disease X, but

Mortality rate has the entire population in the denominator.
Case fatality has only those who were diagnosed with disease X in the denominator.

Question 16

Increasing proportionate mortality doesn’t necessarily mean the disease-specific risk has increased because

Answer 16

People may simply be dying of other causes, which makes the denominator (total all-cause deaths in population during time period) larger.

Question 17

The first step in forming a cohort study’s study population is

Answer 17

to exclude prevalent cases from the reference population!

Question 18

Confounding

Answer 18

Exposure is associated with other factors that might influence the outcome, thus distorting the association between exposure and risk

Question 19

Information bias

Answer 19

AKA measurement error.

Systematic mis-measurement of exposure or disease, especially if the quality or extent of information obtained is different between groups.

Question 20

Selection bias

Answer 20

Including nonparticipants or people lost to follow-up

Question 21

Total population vs defined population vs study population

Answer 21

Total population: overall population group

Defined/source/reference population: Population that the trial is meant to be applied to

Study population: people actually in the study

Question 22

Primary goals of randomization in cohort studies

Answer 22

• Removing investigators’ biases
• Increase study groups’ comparability in target and non-target characteristics (can also be done by having a larger sample size), though not always guaranteed

Question 23

How can you guarantee comparability in cohort study arms/groups?

Answer 23

Stratify before randomizing!

Ex) Distribute half the men and half the women to the control group and the other halves to the experimental group so that both groups have equal amts of men and women.

Question 24

Data and safety monitoring boards must:

Answer 24

• Ensure that any risks to participating are minimized
• Ensure integrity of data
• Stopping trials for safety reasons; if objectives won’t be met; or if it becomes clear objectives will be met and it’s unethical to continue

Question 25

Factorial design

Answer 25

There are two treatments, so you have to randomize twice into four possible treatment groups.

Question 26

Problems with randomized controlled trials

Answer 26

Nonparticipation Noncompliance Crossover Loss to follow up

Question 27

What are the two forms of noncompliance and how do you deal with it?

Answer 27

Drop-ins: subjects switch from control to treatment group Dropouts: subjects stop adhering to their treatment Deal with it by "intention to treat analysis", which analyzes all patients together, regardless of whether or not they received the prescribed regimen. Avoid breaking randomization by excluding/reclassifying noncompliancers (on-treatment analysis)

Question 28

Efficacy vs effectiveness vs efficiency

Answer 28

Efficacy: how well does it work in the study environment Effectiveness: how well does it work in the real world Efficiency: cost-benefit analysis of a treatment once implemented in the real world

Question 29

Number needed to treat

Answer 29

The number of patients who need to be treated to prevent one adverse event over a specified time period NNT = 1/(CI control - CI treatment)

Question 30

Preclinical vs clinical phase

Answer 30

Preclinical is before signs and symptoms start, but clinical is after.

Question 31

Case fatality is not appropriate for what types of disease?

Answer 31

Long term chronic disease where death from other causes is likely

Question 32

What is the issue with mortality rates?

Answer 32

Like incidence, it assumes that risk is constant such that person-time is contributed equal, regardless of WHEN it was contributed. Ex) The experience of 1 person observed for 10 years = 10 ppl observed for one year each. It may look like risk of death is greater in the 10 people.

Question 33

Ecologic studies

Answer 33

Are descriptive; they study the association between an exposure and an outcome in which the unit of analysis is groups of people, often defined by geography. May be at one point in time or over several time points.

Question 34

Ecological fallacy

Answer 34

erroneously assuming that aggregate (population) data applies to individuals.

Question 35

You can never infer ___ from ecological studies because there's no individual level data. It's hypothesis-generating.

Answer 35

Causation

Question 36

Two measures of association in ecological studies

Answer 36

Risk/rate ratio Correlation coefficient (r or r^2): measures the strength of a linear relationship

Question 37

Cross-sectional studies

Answer 37

Are observational and sometimes descriptive; they study exposure, disease, and/or the association between them all at the same point in time using individual-level data.

Question 38

The measure of cross-sectional studies is

Answer 38

Prevalence ratio = Prevalence of disease among the exposed / Prevalence of disease among the nonexposed (Similar to cohort studies, but uses prevalence instead of incidence, so it uses existing, not new, cases)

Question 39

Problems with cross-sectional studies

Answer 39

1) Temporality- Can't tell if exposure came before disease, so you can't confirm causation 2) Prevalent cases estimate both risk AND duration/survival. We may wrongly attribute exposure to risk, when it really might be causing survival. 3) Incidence-prevalence bias: because severe-disease samples will die more quickly than moderate-disease samples, we're less likely to capture them.