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Epidemiology > Unit 2 > Flashcards

Unit 2 Flashcards

1
Q

What are the factors and examples of a quantitative design?

A

Numbers are used to represent data

ex: scales, surveys, pain scales

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2
Q

What are the factors and examples of a qualitative design?

A

Words are used to represent data

ex: word clouds, small group open ended commentary session

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3
Q

What are the 2 types of quantitative designs?

A

Interventional and Observational

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4
Q

Interventional Design

A

Forced allocation into groups
- researchers intervene when assigning groups

Experimental design

Investigator selects the intervention

The only research design that can be used to show causation

Types: Phase 0, Phase 1, Phase 2, Phase 3, Phase 4

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5
Q

Observational Design

A

No forced allocation into groups

Natural design
- can do experimental type things

Researchers observe subjects/ elements occurring naturally or selected naturally by the individual

Used when it could be unethical to assign people to groups based on what you’re studying

Cannot be used to prove causation

Types: Cross-sectional, Case- control, Cohort

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6
Q

When would one use an observational design over an interventional design?

A

When it could be unethical to assign people to groups based on what you’re studying

When cost needs to be considered

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7
Q

What is the most useful and appropriate study design?

A

The one that answers the research question

Depends on question being asked and the desired perspective

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8
Q

What are the elements of a study design?

A

Research Question
Research Hypothesis
Selecting study subjects
Sampling Schemes

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9
Q

Research Question

A

“I wonder if …” statement

Frames study intent

Directs researcher to selecting and developing an effective study design to answer a question

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10
Q

Null Hypothesis

A

Research perspective that states there will be no true difference between the groups being compared

 - says there is no association 
 - will either reject or not reject this perspective based on results

Most conservative and most commonly used hypothesis

Statistical Perspectives = Superiority vs Noninferiority vs Equivalency

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11
Q

What are the 3 statistical perspectives of the Null Hypothesis?

A

Superiority
Noninferiority
Equivalency

Studies usually only look at 1 of these

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12
Q

Superiority

A

Used in drug vs placebo experiments

Asks “is this better?”

Null = this drug will not be superior to the placebo

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13
Q

Noninferiority

A

Used to compare drug to an efficient, gold standard drug already on the market

Asks “am I at least as good?”

Null = I am worse than the other.

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14
Q

Equivalency

A

Null = I am not equal

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15
Q

How to select study design?

A

Perspective of research question (hypothesis)
Ability/ desire of researcher to force group allocation (randomization)
Ethics of methodology
Efficiency and practicality (time and resource commitment)
Costs
Validity of acquired information (internal validity)
Applicability of acquired information to non-study patients (external validity)

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16
Q

Population

A

All individuals making up a common group

Can be divided into a smaller set (sample)

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17
Q

Sample

A

Subset or portion of the full, complete population
- representatives

Useful when studying the complete population is not feasible

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18
Q

How is the study population different from the population?

A

SP = the final group of individuals selected for a study

SP is a sample of the larger population

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19
Q

What is study subject selection based on?

A 
Research hypothesis/ question 
Population of interest 
     - people who are most useful and applicable to answer the research question 
Group selection criteria
     - Inclusion and exclusion group 
     - Case and control group 
     - Exposed and non-exposed group 
     - Desired vs logical vs plausible selection criteria 
     - Impacts generalizability
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20
Q

What are the two broader examples of Sampling Schemes?

A

Probability Samples

Non-probability Samples

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21
Q

Probability Samples + examples

A

Every element in the population has a known probability of being included in sample
- non-zero probability

Simple Random, Systematic Random, Stratified Simple Random, Stratified Disproportionate Random, Multi-stage Random, Cluster Multi-stage Random

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22
Q

Simple Random Sampling

A
  1. Assign random numbers then take randomly- selected numbers to get desired sample size
  2. Assign random numbers then sequentially list numbers and take desired sample size from top/ bottom of listed numbers
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23
Q

Systematic Random Sampling

A

Systematically sampling within groups

Assign random numbers then randomly sort the numbers and select the highest or lowest number
- systematically and by a pre-determined sampling interval take every Nth number to get desired sample size

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24
Q

Stratified Simple Random Sampling

A

Stratify sampling frame by desired characteristic
- use simple random sampling to select desired sample size

Desired characteristic may be a confounder

Have an equal number of strata in each group

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25
Q

Stratified Disproportionate Random Sampling

A

Disproportionately uses stratified simple random sampling when baseline population is not at the desired promotional percentages to the referent population
- stratified sample is weighted to return the sample population back to baseline population

Used for over- sampling

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26
Q

Multi-stage Random Sampling

A

Uses simple random sampling at multiple stages towards patient selection
- SRS at different levels

Regions/ counties = primary sampling unit
City blocks/ zip codes = secondary sampling unit
Clinic/ hospital/ household
Individual/ occurrence

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27
Q

Cluster Multi-Stage Random Sampling

A

Same as multi-stage random sampling but all elements clustered together (at any stage)
- ex: all clinics in a zip code, all households in a community

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28
Q

Non-probability Sampling

A

Quasi-systematic/ Convenience Sampling

Not completely random or fully probabilistic

Researchers decide what fraction of the population is to be sampled and how they will be sampled

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29
Q

What is a concern with using non-probability sampling?

A

There is some known or unknown order to the sample generated by the selected scheme which may introduce bias
- selection bias

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30
Q

Outcomes of Study

A

Patient oriented vs disease oriented

PO is more important and useful

Patients want to know what an influence will be on them (don’t care about numbers)

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31
Q

What are the easiest outcomes to generate?

A

Physiological Outcomes (numbers, levels, etc)

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32
Q

What do are the characteristics of the assessments we want to use to ensure internal validity?

A

Scientifically rigorous and standardized

Objective assessments are between than subjective assessments

Accurate, reproducible, and scientifically

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33
Q

What is the study population selection based on?

A

Ethics

Principles of bioethics must be met

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34
Q

What is equipoise?

A

Genuine confidence that an intervention may be worthwhile in order to use it in humans

Worthwhile = risk vs benefit

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35
Q

What are the 4 key principles of bioethics?

A

Autonomy
Beneficence
Justice
Nonmaleficence

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36
Q

Autonomy

A

Self-rule/ self- determination

Patients must decide for ones-self without outside influences
- no coercion, reprisal, financial manipulation

Patients need to have full and complete understanding of risks and benefits

- no misinformation, incomplete information, or ineffectively- conveyed information 
 - need to account for language and education level
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37
Q

Beneficence

A

To benefit or do good for the patient

Not society

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38
Q

Justice

A

Equal and fair inclusion and treatment regardless of patient characteristics

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39
Q

Nonmaleficence

A

Do no harm

Researchers must no withhold information, provide false information, exhibit professional incompetence

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40
Q

Belmont Report

A

Issued in 1978 by National Commission for Protection of Human Subjects of Biomedical and Behavioral Research

Based on Tuskegee Syphilis Study

Principles:

  1. Respect for persons
    • research should be voluntary and subjects should remain anonymous
  2. Beneficence
    • research risks are justified by potential benefits
  3. Justice
    - risks and benefits of the research are equally distributed
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41
Q

Consent

A

Agreement to participate, based on being fully and completely informed

Given by mentally-capable individuals of legal consenting age
- adults; age 18

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42
Q

Assent

A

Agreement to participate, based on being fully and completely informed, given by mentally- capable individuals not able to give legal consent
- ex: children and adolescents

Children or adults not capable fo giving consent requires the consent of the parent or legal guardian and the assent of the potential study subject

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43
Q

IRB

A

Institutional Review Board

Determines if a study is ethical and safe

Role = protect human subjects from undue risk

All human subject studies must be reviewed by an IRB prior to study initiation
- observational and interventional studies

Regulated by federal statutes developed Department of Health and Human Services (DHHS)

Rules referred to by Common Federal Rules (CFR)

Applies to all studies funded by federal government

Regulations enforced by Office of Human Research Protections

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44
Q

Office of Human Research Protections (OHRP)

A

The agency that administers and enforces the regulations

Can sanction/ close down/ stop

The teeth of the IRB

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45
Q

What are the levels of IRB review and what are the main differences between the levels?

A

Full Board
Expedited
Exempt

Number of members for committee review/ approval
Time for committee review/ approval
Level of detail in documentation needed for review

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46
Q

Full Board

A

Used for all interventional trials with more than minimal risk to patients

Needs more time and is labor intensive

Used when researchers are interacting with people

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47
Q

Expedited

A

Used for minimal risk and when there are no patient identifiers

Risk/ trauma can be triggered
- ex: survey brings up a traumatic past experience

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48
Q

Exempt

A

Used when there are no patient identifiers, low/ no risk, de-identified dataset analysis, environmental studies, use of existing data/ specimens

Data already exists in records

  • could be preexisting data
  • may not have contact with patient
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49
Q

Who determines the level of review?

A

Data Safety and Monitoring Board (DSMB)

Semi-independent committee not involved with the conduct of the study but charged with reviewing study data as study progresses to assess for undue risk/ benefit between groups

Use pre-determined review periods

Can stop study early, for overly positive or overly negative findings in 1+ groups compared to the others

This was the group that shut down women’s postmenopausal study in estrogen/ testosterone group

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50
Q

What is the key difference between interventional and observational studies?

A

Investigator selects interventions and allocates study subjects to forced intervention groups

More rigorous in ability to show cause- and- effect
- can demonstrate causation

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51
Q

What differs between each phase of interventional studies?

A

Purpose/ Focus
Population studied (healthy/ diseased)
Sample Size
Duration

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52
Q

Pre- Clinical Stage

A

Prior- to human Investigation

Bench or animal research

Occurs before human receives intervention

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53
Q

Phase 0

A

Exploratory, Investigational New Drug
Not to see if drug is effective or safety
Does it do what we said it did?
Most phase 0 studies are used for oncology

Purpose/ Focus:

 - assess drug- target actions and possibly pharmacokinetics in single or a few doses
 - first in human use

Population studied:
- healthy or disease patients (oncology) volunteers

Sample Size:
- very small N ( < 20)

Duration:
- very short duration (single dose to just a few days)

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54
Q

Do all interventional studies start at phase 0?

A

No

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55
Q

Phase 1

A

Investigational New Drug

Purpose/ Focus:

 - assess safety/ tolerance and pharmacokinetics of 1+ dosages 
 - can be first in human use/ early in human use 
 - primary purpose is not to look at the efficacy of disease

Population studied:

 - healthy or disease patients volunteers 
 - depends on the disease

Sample Size:
- small N (20 - 80)

Duration:

 - short duration (few weeks) 
 - variable
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56
Q

What does pharmacokinetics look at?

A

How does the body handle the drug?

How does the drug get in?

How long does it take to get in?

Where does it go?

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57
Q

Phase 2

A

Investigational New Drug

Purpose/ Focus:

 - assess effectiveness
 - continues to assess for safety/ tolerance but this isn’t the primary purpose 
 - Need to use placebo/ comparison group

Population studied:

 - diseased volunteers 
 - may have narrow inclusion criteria for isolation of effects

Sample Size:
- larger N ( 100 - 300)

Duration:
- short to medium duration (few weeks to a few months)

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58
Q

Phase 3

A

Investigational new drug or indication/ population study

Last phase before FDA approval
- need minimum of 3 out of 5 trials to be positive to show that it wasn’t any better than the equivalent or comparison

Purpose/ Focus:

 - assess effectiveness
 - continues to assess for safety and tolerability

Population studied:

 - diseased volunteers 
 - may expand inclusion criteria and comparison groups for delineation of effects
 - can use different statistical procedures 
       - superiority vs noninferiority vs equivalency

Sample Size:
- larger N (500 - 3000)

Duration:
- longer duration (a few months to a year or more)

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59
Q

Why can various statistical perspectives be taken in phase 3 studies?

A

In some studies, it is unethical to give placebo vs something else. In this case, both groups would get a baseline pharmacological drug

Ex: you wouldn’t ask someone with asthma to stop taking their medication

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60
Q

Phase 4

A

Post marketing and FDA approval

Purpose/ Focus:
- assess long-term safety, effectiveness, optimal use (risk/ benefits)

Population studied:

 - diseased volunteers 
 - expand use criteria (comorbidities/ concomitant medication) for delineation of long-term safety/ effects

Sample Size:
- Population N (few hundred to a few thousand)

Duration:

 - wide range of durations (few weeks to several years) 
 - ongoing 
 - used in interventional/ observations designs 
 - FDA may make companies use a registry in order to follow patients/ effects/ outcomes
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61
Q

Advantage of Interventional Trials

A

Cause precedes effect (can prove causation)

Only designs used for FDA approval process

Controlling exam environment

Can avoid certain biases

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62
Q

Disadvantages of Interventional Trials

A

Cost
Complexity/ time
Ethical considerations (risk vs benefit)
Generalizability

Can be over controlling and not true clinical practice
Very regimented and prescriptive in what we do

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63
Q

Pragmatic Studies

A

Explanatory

Intervention- like but tells us how to treat patient and disease

Gives us flexibility to change dose/ care to treat each patient as needed
- more flexible in exam environment and makes it closer to clinical practice

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64
Q

What are limitations of pragmatic studies?

A

Makes it hard to compare groups at the end

Flexibility can introduce extraneous factors/ confounds/ etc

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65
Q

What are differences between simple and factorial interventional designs based on?

A

Differ based on number of randomization steps patient goes through before being put into final study group

Comes down to how much control should we really give to researchers

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66
Q

Simple Interventional Design

A

Randomizes subjects exclusively into 2+ groups

1 randomization process (no subsequent randomization)

Commonly used to test a single hypothesis at a time

Asks if drug A is better/ worse/ equal to drug B

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67
Q

Factorial Interventional Design

A

Randomizes subjects into 2+ groups and then further randomizes each of the groups into 2+ additional subgroups

Allows us to ask more research questions

 - is drug A better/ worse/ equal to drug B?
 - is drug A alone better?
 - are additional combinations better than 1 drug alone?

Used to test multiple hypotheses at the same time

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68
Q

What does testing multiple hypotheses at the same time do for a factorial interventional design?

A

Improves efficiency for answering clinical questions

Increases study population sample size
- due to increased group number

Increases complexity

Increases risk of drop outs

May restrict generalizability of results

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69
Q

Parallel Interventional Design

A

Regardless of simple/ factorial, once patients get into final study group, they do not change groups

Groups are simultaneously and exclusively managed

No switching of intervention groups after initial randomization

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70
Q

Cross- Over Interventional Designs

A

Also known as self- control

Groups serve as their own control by crossing over from 1 intervention to another during the study

- subjects get to be their own control 
- works because they are matched on demographics because it is themselves

Allows for smaller total sample size

 - caveat: participants have longer participation time 
 - each participant contributes additional data

Uses wash-out and lead- in

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71
Q

Wash- out

A

Period of time where we don’t give patients drugs

Allows drug to wash out from system so they can start subsequent trials/ treatment

Washes out pharmacological/ psychological effects of study before subsequent treatments

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72
Q

Lead- in

A

Wash out period that occurs before the study starts

Ex: when patient is on drugs but cannot necessarily take them during the study. This allows drug to leave the system before the study starts

Way to test patients ability to follow directions and see if they meet requirements
- if cannot meet requirements, they can be dropped from the study

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73
Q

Disadvantages of Cross- over designs

A

Only suitable for long-term conditions which are not curable or which treatment provides short-term relief

Duration of study for each subject is longer

Carry-over effects during cross- over
- wash out is required when prolongs study duration

Treatment- by- period interaction
- differences in effects of treatments during different time periods

Smaller N requirement only applicable if within-subject variation is less than between- subject variation

Complexity in data analysis

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74
Q

Run in/ lead in phase

A

All study subjects blindly given 1+ placebos for initial therapy (defined time period) to determine baseline of new disease

Standardization

Can assess study protocol compliance

Can wash out existing medication
- reduces at least 1 possible common exclusion criteria

Can determine amount of placebo- effect

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75
Q

What is the difference between primary and secondary outcomes?

A

Primary are the most important/ key outcomes.
-main research question used for developing/ conducting study

Secondary/ tertiary are less important and can be used for future hypothesis generation

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76
Q

What is a composite outcome?

A

Combines multiple endpoints into single outcome

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77
Q

Patient- Oriented Endpoints

A

Most clinically relevant

Death

Stroke/ Myocardial Infarction

Hospitalization

Preventing need for dialysis

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78
Q

Disease- oriented endpoints

A

Surrogate markers
- elements used in place of evaluating patient- oriented end points

Blood pressure - for risk of stroke

Cholesterol - for risk of heart attack

Change in SCr- for worsening of renal function

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79
Q

Non- Random Group Allocation

A

Subjects don’t have an equal probability of being selected or assigned to each intervention group

Ex: the first 100 patients admitted to the hospital
- patients attending morning clinic = group 1, patients attending evening clinic assigned to group 2

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80
Q

Random Group Allocation

A

Most commonly utilized

Subjects have an equal probability of being assigned to each intervention group

Ex: random number generating program

81
Q

Randomization

A

Purpose: to make groups as equal as possible based on known and unknown important factors/ confounders

Attempts to reduce systematic differences (bias) between groups which could impact results/ outcomes

Equality of groups is not guaranteed

Documentation of equality of groups reported as p values

Only used in interventional studies, not observational

We want groups to be as equal as possible except on 1 thing

82
Q

Simple Randomization

A

Equal probability for allocation within one of the study groups

83
Q

Blocked Randomization

A

Ensures balance within each intervention group

Used when researchers want to assure that all groups are equal in size

Used when you can’t run the risk of having unequal groups

Equality is usually assessed for in blocks of 10

84
Q

Stratified Randomization

A

Ensures balance with known confounding variables

Want groups to be equal based on a characteristic
- ex: gender, age, disease severity

Can pre-select levels to be balanced within each interfering factor

85
Q

Masking - Single- blind

A

Study subjects not informed which intervention group they are in

Investigators are permitted to know

86
Q

Masking- Double Blind

A

Neither investigators nor study subjects are informed which intervention group subjects are in

Post-study surveys used to assess adequacy of blinding

87
Q

Masking- Open label

A

Unmasked/ unblinded

Study subjects and researchers know what intervention is being received

88
Q

Masking- Placebo

A

Dummy Therapy

Inserts treatments made to look identical in all aspects to the active treatments

Improvement in condition by power of suggestion of being treated

89
Q

Post- Hoc sub-group analysis

A

Not accepted by most when not prospectively planned

Is accepted when it is prospectively planned for or performed for hypothesis generation and development of future studies

90
Q

Managing Drop outs/ lost to follow ups

A

Want drop outs to be equal between groups

Intention to treat
- most conservative decision

Ignore them

  • per protocol or efficacy analysis
  • compliance must be pre-defined

Treating them as treated

  • ignores group assignments
  • allows subjects to switch groups and be evaluated in groups they moved to, end in, or stay in most
91
Q

Impact of Drop out decisions

A

Intention to treat results in:

  • preserved randomization process
  • preserves baseline characteristics and group balance at baseline which controls for known and unknown confounders
  • maintains statistical power

Per- protocol results:

  • biases estimates of effect
  • reduces generalizability
92
Q

How to assess for adherence (compliance)?

A

Drug levels
Pill counts at each visit
Bottle counter tops

93
Q

Methods of improving adherence

A

Frequent follow-up visits/ communications

Treatment alarms/ notifications

Medication blister packs or dosage containers

94
Q

What is a case- control study?

A

Observational study

Allows researcher to be a passive observer of natural events occurring in individuals with the disease/ condition of interest compared to people who do not have the condition of interest

95
Q

How are people assigned to groups in case- control studies?

A

Put into groups based on disease status

No forced allocation into groups

Case = diseased
Control = non- diseased
96
Q

What information do controls in case- control studies provide us?

A

Gives information about the expected baseline risk factor profile in the population from which cases are drawn

97
Q

What caveat to randomization do case-control studies create?

A

In any observational study, the pool of people to draw from may be bigger than needed so we randomly select people from this

We only need some of these people on order to represent the full population

98
Q

Why should we use case- control study design?

A

Unable to force group allocation
- due to ethics/ feasibility

Limited resources

  • time/ money/ subjects
  • time to completion is shorter because we have data that has already been collected

Disease of interest is rare in occurrence

  • little is known about its associations/ causes
  • case- control studies directly assess perspective of the hypothesis

Prospective exposure data is difficult/ expensive to obtain and/ or time inappropriate

99
Q

Case- control studies are usually conducted in what kind of fashion? Why?

A

Retrospective
- going back to look at exposure

We already know the outcomes so we want to look at the exposures

100
Q

Strengths of Case- Control Studies

A

Good for assessing multiple exposures of 1 outcome

Useful when diseases are rare

Useful in determining associations

Less expensive (money/time) than interventional trials and prospective studies

Useful when ethical issues limit interventional studies

Useful when disease has long induction/ latent period (ex: cancer)

101
Q

Weaknesses of Case- control studies

A

Can’t show causation

Can be impacted by unassessed confounder

Retrospective
- can’t control for other exposures or potential changes in amount of study- exposure during study frame

Can be impacted by biases
- especially selection and recall/ assessment bias

Limited by available data

102
Q

Selection of cases in case- control study

A

Author needs to tell how they picked patients/ cases

Defined by investigator using accurate, medically- reliable, efficient data sources

Selection must be made objectively, consistently, accurately, and with validity

Must use clinically supportable and definable criteria

Classifying patients is ideal but can be misclassified

  • prefer non-differential misclassification
  • balanced error - moves OR closer to 1.0 (no association)
103
Q

Control selection in case- control studies

A

Most difficult part

Expectation: control represents baseline risk of exposure in general or referenced population

Way controls are selected is a major determinant in whether any conclusion is valid

Want groups to be as equal as possible except the presence of disease of interest

Must be selected irrespective of exposure status
- cannot look at past exposure prior to picking controls

104
Q

What are the three control group sources?

A

Population

  • state/ community/ neighborhood
  • general, brand
  • can be obtained several ways (randomly)

Institutional/ Organizational/ Provider
- illnesses of controls should be unrelated to exposures being studied

Spouses/ Relatives/ Friends
- genetics, environment, SES, etc

Can be specific or general

105
Q

Describe selecting control study population via Outbreak sources of control

A

Choose people who participated in the same event as the cases but did not get the outcome

ex: people at picnic who did vs did not get food poisoning

106
Q

Can someone be exposed and unexposed individual in the same study? Explain.

A

Yes

Can be both exposed and unexposed in studies where looking at different exposures of a single outcome

Associated with an outbreak investigation with multiple exposures or in a situation of brief change in risk of the outcome of interest

107
Q

Case- Crossover Design

A

Used in a situation of brief change in risk of the outcome of interest

Observational Design

Subjects are their own controls during the other times they don’t have the acute change in risk
- comparing people to themselves

The only case- control design able to adequately attempt to address issue of temporality

108
Q

Nested Case- Control Studies

A

Case- control study conducted after or out of a prospective previous study type

Subjects in cohort study, ultimately developing the disease/ outcome, are defined as cases for the subsequent case- control study

- diseased used in a new/ different study 
    - used to evaluate other exposures

A subsequent study that comes from a different, already completed case control study

A secondary outcome from one study that leads to the development of this subsequent study

109
Q

What are the sampling techniques for controls used in nesting case- control studies?

A

Survivor Sampling
Base Sampling
Risk- set Sampling

110
Q

Survivor Sampling

A

Sample of non-diseased individuals at end of study period

The “survivors” of the study who didn’t get the same outcome as previous cases

Most commonly used technique

111
Q

Base Sampling

A

Sample of non-diseased individuals at start of study period

Go back to the beginning

112
Q

Risk- Set Sampling

A

Sample of non-diseased individuals during study period at the same time when case was diagnosed

Taken from a time based during the study

113
Q

Describe the 2 common biases found in Case- Control Studies

A

Selection Bias

  • Related to the way subjects are chosen for the study
  • less of a concern during case- crossover study designs

Recall Bias

  • Related to the amount/ specificity that cases or controls recall past events differently
  • more common that cases are more likely to recall past exposures and levels of exposure or their timing
114
Q

Matching- Case- Control Studies

A

Cases are matched to controls in 1:1 or higher ratio

Cannot match on anything that might be a risk factor

Individual

  • matches individuals based on specific patient- based characteristics
  • useful for controlling confounding characteristics

Group

  • proportion of cases and proportion of controls with identical characteristics are matched
  • requires cases to be selected first
115
Q

What observational study design gives us the strongest evidence?

A

Cohort Studies

116
Q

What are cohort studies?

A

Observational studies that allow the researcher to be a passive observer of natural events occurring in naturally exposed and unexposed groups

Used when studying a rare exposure

Trying to determine of the exposed people, what number of them will get the outcome or not?
- we know the total exposed

Generates risk of disease/ outcome for each group

117
Q

What are other names for cohort studies?

A

Incidence studies or longitudinal studies

118
Q

What is group allocation in cohort studies based on?

A

Based on exposure status or group membership (having something in common with others)

119
Q

What is a cohort?

A

A group of people that have something in common

We can allocate groups after we have our cohort

120
Q

Birth Cohort

A

Individuals assembled based on being born in a geographic region in a given time period

ex: everyone born in KC city limits in 2014

121
Q

Inception Cohort

A

Individuals assembled at a given point based on some common factor
- common factor examples: where people live/ work

Useful for single- group assessments for incidence rate determination
- ex: single healthcare system

Ex: Framingham Heart Study

  • began in 1948
  • selected on being a stable population with updated annual population lists and other unique attributes

Ex: Nurses’ Health Study, COB class of 2019

122
Q

Exposure Cohort

A

Individuals assembled based on some common exposure

Frequently connected to environmental or other one time events
- usually one time exposures or single events

Ex: 9/11

123
Q

Can cohort size change over time?

A

Yes - depends on if fixed vs closed vs open/ dynamic cohort

124
Q

Fixed Cohort

A

Cohort is derived from an irrevocable event and can’t gain members but can have loss-to-follow-ups

Long evaluation time

125
Q

Closed Cohort

A

A fixed cohort with no loss-to-follow-ups

Short evaluation time

126
Q

Open/ Dynamic Cohort

A

Cohort with new additions and some loss- to- follow- ups

Cohorts can increase or decrease over time as people immigrate or emigrate in and out of the population being studied

127
Q

When should we use cohort studies?

A

Unable to force group allocation (randomize)
- unethical/ not feasible

Limited resources
- time/ money/ subjects

Exposure of interest is rare in occurrence and little is known about its associations/ outcomes
- directly assesses the perspective of the hypothesis

More interested in incidence rates or risks of outcome of interest
- more than effects of interventions

128
Q

Can any type of cohort study be used to prove causation?

A

No

Prospective studies that are well- controlled can approximate causation

129
Q

Prospective Cohort Study

A

Exposure group is selected on basis of a past or current exposure

Both groups are followed into future to assess for outcomes of interest which have yet to occur

130
Q

Retrospective Cohort Study

A

At start of study, both exposure and outcome of interest have already occurred
- groups are still allocated based on past history of exposure

Retrospectively start at time of exposure and follow forward to the point of outcome occurrence in the present
- exposure still has to occur before outcome of interest

131
Q

Ambidirectional Cohort Study

A

Uses retrospective design to assess past differences up to present while also adding future data that is collected prospectively from start of study

Ex: Vietnam War and Agent Orange Exposure

132
Q

How to select an exposed study population?

A

Allocate subjects base on pre-defined criteria of exposure

Criteria needs to be scientifically and consistently determined

133
Q

How to select an unexposed study population?

A

Make the groups as close as possible

  • coming from same cohort/ population yet not exposed
  • if exposure truly has no effect, risk will be exactly the same for both groups and RR = 1.0

Unexposed group sources: internal, general population, and comparison cohort

134
Q

Internal unexposed Study population source

A

Best option, if feasible

Patients from the same cohort yet are unexposed

If there are only levels of exposure, you may have to use lowest exposure group as comparator

135
Q

General Population unexposed study population source

A

Used as a second choice when the best possible comparison group is not realistically possible

Ex: everyone is exposed or exposure subjects were drawn from general population

136
Q

Comparison Cohort unexposed study population source

A

Least acceptable group

Attempt to match groups as close as possible on numerous personal characteristics

Cannot control for other potentially harmful exposures in comparison cohort

137
Q

Strengths of Cohort Studies in general

A

Good for assessing multiple outcomes of 1 exposure

Useful when exposures are rare

Useful in calculating risk and risk ratios

Less expensive than interventional trials

Good when ethical issues limit use of interventional study

Good for long induction/ latent periods
- retrospective

Able to represent temporality
- prospective

138
Q

Weaknesses of Cohort Studies in general

A

Can’t demonstrate causation

Hard to control for other exposures if more than 1 is plausible for being associated with an outcome

Can be impacted by unassessed confounders (retro)

Can be impacted by various biases (retro)

Limited by available data

139
Q

Advantages of Prospective Cohort Studies

A

Can obtain a greater amount of study- important information from patients

More control over specific data collection process

Follow- up and tracking of patients may be easier if planned for

Gives better answer to temporality

May look at multiple outcomes from a supposed single exposure

Can calculate incidence and incidence rates

140
Q

Disadvantages of Prospective Cohort Studies

A

Time

Expense

Lost- to- follow- ups

Not efficient for rare diseases
- use case- control studies instead

Not suited for long induction/ latency conditions

Exposure/ amount of exposure may change over time

141
Q

Loss- To - Follow- Ups

A

Possible with prospective cohorts

Lowers sample size

  • decreases power
  • increases risk of type 2 error
  • loss of study participation may not be equal between groups

Need to limit loss-to-follow-ups via time, energy, and resources

142
Q

Advantages of Retrospective Cohort Studies

A

Best for long induction/ latency conditions

Able to study rare exposures

Useful if the data already exists

Saves time and money

143
Q

Disadvantages of Retrospective Cohort Studies

A

Requires access to charts, databases, employment records which may not be complete/ thorough enough for study

Information may not factor in or control for other exposures to harmful elements during study period or over time

Patients may not be available for interview if contact is necessary for missing/ incomplete data

Exposure/ exposure amount may have changed over time

144
Q

Matching- Cohort Studies

A

Way to strive to makes groups as equal as possible on known/ potential confounders

145
Q

What are the biases that affect cohort studies?

A

Healthy- Worker Effect

  • if health, you work, even if you are exposed
    • if too ill to work, you may be unemployed
  • looks at those that are healthy enough to work and ignores those that are dead/ sick
  • concern because most of cohort studies are environmental in nature

Selection Bias
- How is exposure status defined/ determined?

146
Q

What are Cross- Sectional Studies?

A

Observational studies that capture health/ disease and exposure statuses at the same time

Collects health records/ information at the same time

Prevalence study
- can be used to estimate elements of prevalence

Focuses simultaneously on disease and population characteristics

147
Q

Why are designs called cross- sectional?

A

Information gathered represents what is occurring at a point in time or time- frame across a large population acquired without regard to exposure or disease outcome/ status

Looking at a snap shot in time of all elements

148
Q

Who are the study subjects in a cross- over design?

A

The entire population or a sample of the population

149
Q

By focusing simultaneously on disease and population characteristics, what are three things that are looked at in cross- sectional designs?

A

Looks at associations

Generates and tests hypotheses

By repetition in different time periods, can be used to measure change/ trends

150
Q

Cross- sectional Approaches

A

Collect data on each member of the population

  • more frequently utilized in city/ state-level evaluations if data is already tracked
  • ongoing collection

Take a sample of the population and draw inferences to the remainder (generalizable)
- more frequent approach for large population data

151
Q

What are the 2 broad approaches used to collect study data/ information in cross-sectional studies?

A

Questionnaires/ Surveys
- directly collected from patients/ caregivers or their medical records

Physical Assessments

  • might involve laboratory, clinical, or psychological tests
  • great for assessing health / disease in similar population as time changes
  • not likely to be the same individuals year to year
    • due to immigration vs emigration rate
152
Q

Strengths of Cross- Sectional Designs

A

Quicker and easier for the researcher when using already collected data
- free and already available

Less expensive for researcher than any form of prospective study

Can be analyzed like a case- control or cohort study regarding group allocation

Useful for estimating prevalence rates

Useful for answering research questions about a myriad of exposures and diseases using the same data

153
Q

Weaknesses of Cross- Sectional Designs

A

Prevalent cases may represent survivors

Difficult to study diseases of low frequency (may not select for people with it since it is so infrequent)

Unable to generate incidence rates

Problems in determining temporal relationship of presumed cause and effect
- due to fact that exposure and disease histories are taken at the same time

154
Q

Where do we get cross-sectional surveys from?

A

National Center for Health Statistics

155
Q

National Health and Nutrition Examination Survey

A

NHANES

Assesses the health and nutritional status of adults and children

Combines interviews and physical examinations

  • interviews include demographics, SES, dietary, and health- related questions
  • examination component consists of medical, dental, physiological measurements, and laboratory tests

Survey sample is selected to represent US population of all ages
- oversampled people who are > 60, blacks/ African Americans, and Hispanics

Worry about selection bias

156
Q

National Health Interview Survey

A

NHIS

Principle source of information on health of the civilian, non-institutionalized population
- looks at global health of civilians outside of hospital

Survey sample is selected to represent the US population of all ages

Has central role in other surveys NSFG and NAMCS/ NHCS

Data collected through personal household interview (door to door)

Consists of a set of core questions that remain largely unchanged and a set of supplements used to respond to public health data needs as they arise

Bias: response bias

157
Q

National Ambulatory Medical Care Survey

A

NAMCS

National survey designed to meet the need for objective, reliable information about the provision and use of ambulatory medical care services in US

Based on a sample of visits to non-federal, non-institutional physicians primarily engaged in direct patient care

158
Q

National Hospital Care Survey

A

NHCS

Combined national survey designed to describe national patterns of healthcare delivery in non-federal hospital based settings

  • discharges from inpatient departments and institutions
  • visits to emergency departments, outpatient departments, and ambulatory surgery centers

Integrates other surveys

159
Q

Behavioral Risk Factor Surveillance System

A

BRFSS

State- based system of telephone health surveys that collects information on health risk behaviors, preventative health practices, and health care access primarily related to chronic disease and injury

Interviews adults aged 18 and older who can give consent

Largest landline telephone health survey in world

Youth survey conducted in schools with parental consent and child assent

Worry about responder bias

160
Q

What are weaknesses of the BRFSS?

A

Not everyone has landlines

Times of people calling
- may not answer during day bec they are at work, etc

Are people telling truth?

161
Q

What questions should patients ask their physicians when a medical screening test is recommended?

A

How accurate is the screening test you are about to recommend for me?

When the test results are announced, how confident will you be in your prediction of whether I do or don’t have the disease?

162
Q

What are the possible screening outcomes?

A

True Positive
True Negative
False Positive
False Negative

163
Q

True Positive

A

Test correctly reports a positive result in a patient that actually does have the disease

Corresponds to A in the 2x2 table

164
Q

True Negative

A

Test correctly reports a negative result in a patient that actually does not have the disease

Corresponds to D in the 2 x 2 table

165
Q

False Positive

A

Test incorrectly reports a positive result in a patient that actually does not have the disease

Ex: telling a man they are pregnant

Corresponds to B in 2x2 table

166
Q

False Negative

A

Test incorrectly reports a negative result in a patient that actually does have the disease

Ex: telling a pregnant women they are not pregnant

Corresponds to C in 2x2 table

167
Q

What answers the question of “How accurate is the screening test you are about to recommend for me”?

A

Sensitivity and Specificity

Describes accuracy of test result based on a known disease status from a gold standard

Trying to find the accuracy of test in people who are already diseased/ have drug in their system

168
Q

Sensitivity

A

How well a test can detect presence of disease when in fact disease is present

  • how well test comes back positive when person has disease
  • positivity of test in the diseased

Proportion of time that a test is positive in a patient that does have the disease

If test has high sensitivity, it has low false negative rate

169
Q

What are the 3 equations used to calculate Sensitivity?

A

= [True positive / (True positive + false negative)] * 100%

= [True positive / all diseased] * 100%

= A / (A + C)

170
Q

Specificity

A

How well a test can detect absence of disease when in fact the disease is absent
- negativity of test in the healthy

Proportion of time that a test is negative in a patient that does not have the disease

If a test has high specificity, it has a low false positive rate

171
Q

What are the 3 equations used to calculate Specificity?

A

= [True negative / (True negative + false positive)] * 100%

= [True negative / all not diseased] * 100%

= D / (D + B)

172
Q

What answers the question of “When the test results are announced, how confident will you be in your prediction of whether I do or don’t have the disease”?

A

Positive and Negative Predictive Value

Describes accuracy of prediction of disease based on known test results

173
Q

Positive Predictive Value

A

How accurately a positive test predicts the presence of disease
- What percentage of the time do people really have disease?

Proportion of true positives in patients with a positive test
- correct prediction

174
Q

What are the 3 equations used to calculate Positive Predictive Value?

A

= [True positives / (True positive + false positive)] * 100%

= [True positives / all positive tests] * 100%

= A / (A + B)

175
Q

Negative Predictive Value

A

How accurately a negative test predicts the absence of disease
- What percentage of the time do people really not have disease?

Proportion of true negatives in patients with a negative test
- correct prediction

176
Q

What are the 3 equations used to calculate Negative Predictive Value?

A

= [True negative / (True negative + false negative)] * 100%

= [True negative / all negative tests] * 100%

= D / (C + D)

177
Q

What happens to the value of PPV when you approach prevalence of 100%?

A

PPV skyrockets toward 100% because most things will be associated with the disease

178
Q

Why are specificity and sensitivity the same across all of the populations despite different prevalences (2% vs 20% vs 40%)?

A

We are using the same test to assess for both across all of the populations so the numbers aren’t going to change.

Specificity and Sensitivity reflect the test, not the community you use it on

179
Q

Why does PPV and NPV change across all of the populations despite different prevalences (2% vs 20% vs 40%)?

A

Number of diseased people increases so the number of errors increases

False positives and false negatives are changing because specificity and sensitivity are not equal to 100 (and not equal to each other)

Prevalence is not 100%

180
Q

What does a specificity of 97% mean?

A

Test is good at coming back negative when people don’t have the disease

181
Q

Why are PPV’s low for X-Rays?

A

Any visualization on an X-Ray does not automatically mean cancer/ disease. The image could be something else

182
Q

The more false positives = _______ the specificity = ______ the PPV. Why is this the case?

A

Lower
Lower

Due to the false positives being included in the denominator

183
Q

The more false negatives = _____ the sensitivity = _____ the NPV.

A

Lower

Higher

184
Q

When will PPV and NPV not change?

A

When the prevalence of disease or not disease = 100%

185
Q

Diagnostic Accuracy

A

Also known as diagnostic precision

Proportion of total screenings that a patient is correctly identified as either having a disease (true positive) or not having disease (true negative) with either a positive or negative test, respectively

= [(True positives + true negatives) / (true positive + false positive + true negative + false negative)] * 100%

= [(A+D) / (A+B+C+D)] * 100%

186
Q

Likelihood Probabilities

A

Ratio of 2 probabilities

Probability of a given test result for a person with disease / probability of the same test result for a person without disease

Probability of some test outcome in diseased / probability of some test outcome in non-diseased

187
Q

Likelihood Ratio Positive

A

Probability of a positive test in the presence of disease / probability of a positive test in absence of disease

Sensitivity / (1 - specificity)

= [(A / (A + C)) / (B / (B + D))]

Want numerator to be large and denominator to be small

Looking at the probability of getting positive test in the diseased and not diseased

If test is good/ useful, LR+ should be large

Should be > 10 to demonstrate test is most beneficial

188
Q

Likelihood Ratio Negative

A

Probability of a negative test in the presence of disease / probability of a negative test in absence of disease

(1 - Sensitivity) / Specificity

= [(C / (A + C)) / (D / (B + D))]

Looking at the probability of getting a negative test in the diseased and not diseased

If test is good/ useful, LR- should be small

Should be < 0.1 to demonstrate test is most beneficial

189
Q

What is the likelihood that people who have disease get a negative result?

A

0%

190
Q

What is the likelihood that people who don’t have disease get a negative result?

A

100%

191
Q

What is the likelihood that people who have disease get a positive result?

A

100&

192
Q

What is the likelihood that people who don’t have disease get a positive result?

A

0%

193
Q

What does LR+ = 1.0 and LR- = 1.0 mean for the beneficiality of test?

A

LR+ = 1.0 means that test is just as likely to be positive in people with disease as it is in people who don’t have disease

LR- = 1.0 means that test is just as likely to be negative in people with disease as it is in people who don’t have disease

194
Q

Validity

A

Ability to accurately discern between those that do and those that don’t have the disease

Precision in finding and reporting the truth

Internal or External

195
Q

Internal Validity

A

Extent to which results accurately reflect what was being assessed

Occurs inside study design

True situation of study population

196
Q

External Validity

A

Extent to which results are applicable to other populations

Populations are not those that were included in original study

Occurs outside study design

Generalizability

197
Q

Reliability

A

Ability of a test to give same result on repeated uses

Reproducibility/ Consistency

198
Q

A valid test is always ____.

A reliable test is not always ____.

A

Reliable

Valid

199
Q

Cutoff values

A

Not always dichotomous

Depends on disease and big picture impact

Want least amount of false negatives and false positives
- want something in the middle because if you target 1 or the other, will have more of the one you didn’t correct for

Cutoff of 50% because it minimizes FN and FP

Epidemiology (3 decks)

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