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Research Evaluation > Review Slides plus class review > Flashcards

Review Slides plus class review Flashcards

1
Q

A narrative in the professional literature that identifies a single incident and discusses pertinent factors related to the patient

Brings a novel or unusual patient to the attention of colleagues

Information is preliminary and unrefined in terms of research methodology
Important nonetheless

A

Case Report

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2
Q

Case Report

A

single incident and discusses pertinent factors related to the patient

novel or unusual patient

info preliminary / unrefined

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3
Q

this type of study analyzes a number of individual cases that share a commonality

-Usually relatively low numbers of subjects

A

Case Series

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4
Q

Case Series are used to

A

Examine adverse events or effects

Catalog new diseases or outbreaks

Determine the feasibility or safety of a new treatment or intervention

Discuss the potential efficacy of a new treatment

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5
Q

Data does not necessarily extrapolate to larger populations

Evidence may be circumstantial

Confounding factors may be present

A

Case reports and case series lack “sufficient methodological rigor”

But – both typically indicate the need for further study

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6
Q

Examine the relationship between exposures and diseases as measured in a population rather than in individuals.

A

Ecologic Studies

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7
Q

Can often be done by utilizing data from surveys or registries without having to interview, examine, or even identify individual subjects.

A

Ecologic Studies

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8
Q

After describing an association at the population level, the next step would be to do a an analytic study to see if the association holds true in individuals.

A

Ecologic Studies

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9
Q

Is a type of bias specific to ecological studies. Occurs when relationships that exist for groups are assumed to also be true for individuals.

A

Ecological Fallacy

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10
Q

Examines the relationship between outcomes and other variables of interest as they exist in a defined population at one particular time.

Determines prevalence (% of population) not incidence (rate)

Enrolls a large number of individuals

“The chicken or the egg?”: cannot show causality, does not separate cause/effect

Does not establish a temporal relationship between risk factors and disease because they are measured at the same time

A

Cross-sectional studies

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11
Q

Examines the relationship between outcomes and other variables of interest as they exist in a defined population at one particular time.

A

Cross-sectional studies

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12
Q

Determines prevalence (% of population) not incidence (rate)

A

Cross-sectional studies

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13
Q

can a cross-sectional study show causality?

A

NO!!! does not separate cause and effect

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14
Q

Look at slide 8 for the flow chart of the cross-sectional study

A

Boy you betta!

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15
Q

Strengths-

Can assess multiple outcomes and exposures simultaneously

Can be completed quickly

Data generated can lead to further studies

Can generate prevalence

A

Cross-sectional studies

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16
Q

Strengths of Cross-sectional studies?

A

Can assess multiple outcomes and exposures simultaneously

Can be completed quickly

Data generated can lead to further studies

Can generate prevalence

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17
Q

Limitations-
No time reference
-“Snapshot In Time”- like looking at a photograph

Only useful for common conditions

Cannot calculate incidence, it is a prevalence study

Results are dependent on the study population

We assume that the exposure rate is constant over time.

A

Cross-sectional studies

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18
Q

Cross-sectional studies Limitations?

A

Limitations-
No time reference
-“Snapshot In Time”- like looking at a photograph

Only useful for common conditions

Cannot calculate incidence, it is a prevalence study

Results are dependent on the study population

We assume that the exposure rate is constant over time.

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19
Q

Studies in which patients who already have a specific condition (cases) are compared with people who do not have the condition (controls).

The researcher looks back to identify factors or exposures that might be associated with the illness.

This type of study design may follow a case-series (as a retrospective look at causes).

Tries to capture the cause and effect relationship by comparing frequency of a risk factor among those how are exposed and not-exposed.

A

Case-control studies

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20
Q

Case-control studies

A

Studies in which patients who already have a specific condition (cases) are compared with people who do not have the condition (controls).

The researcher looks back to identify factors or exposures that might be associated with the illness.

This type of study design may follow a case-series (as a retrospective look at causes).

Tries to capture the cause and effect relationship by comparing frequency of a risk factor among those how are exposed and not-exposed.

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21
Q

Studies in which patients who already have a specific condition (cases) are compared with people who do not have the condition (controls).

A

Case-control studies

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22
Q

The researcher looks back to identify factors or exposures that might be associated with the illness.

This type of study design may follow a case-series (as a retrospective look at causes).

A

Case-control studies

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23
Q

Tries to capture the cause and effect relationship by comparing frequency of a risk factor among those how are exposed and not-exposed.

A

Case-control studies

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24
Q

Look at review slide 12/13 for flow chart

A

don’t be a slacker

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25
Q

Strengths-

Good for studying rare outcomes

Can evaluate many exposures
Ideal for initial, explanatory idea

Simple & fast – we already know the outcomes

Efficient-no waiting for outcome to occur
Inexpensive

A

Case-control studies

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26
Q

Case-control studies Strengths

Strengths-

Good for studying _____

Can evaluate many ____

Ideal for ___ idea

Simple & fast – we already know the ____

_____-no waiting for outcome to occur

cost?

A

Case-control studies
Strengths-

Good for studying rare outcomes

Can evaluate many exposures

Ideal for initial, explanatory idea

Simple & fast – we already know the outcomes

Efficient-no waiting for outcome to occur

Inexpensive

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27
Q

Limitations-

Single outcome

High risk for bias

High risk for confounding variables

Other factors may exist that influence outcomes

Can’t determine prevalence

Temporality

  • –Can’t make causal interpretations
  • –Can’t determine incidence
  • –Can’t calculate Relative risk
A

Case-control studies

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28
Q

Case-control studies Limitations

___ outcome

High risk for ___

High risk for ____ variables

Other factors may exist that influence outcomes

Can’t determine ____

Temporality

  • –Can’t make ___ interpretations
  • –Can’t determine ___
  • –Can’t calculate ____
A

Limitations-

Single outcome

High risk for bias

High risk for confounding variables

Other factors may exist that influence outcomes

Can’t determine prevalence

Temporality

  • –Can’t make causal interpretations
  • –Can’t determine incidence
  • –Can’t calculate Relative risk
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29
Q

Potential Biases in Case-Control Studies?

A

Selection Bias

Information Bias

Researcher/Observer Bias

Voluntary Response Bias`

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30
Q

Case-Control Studies

Selection Bias?

A

Selection Bias: inappropriate selection of cases or controls.

Cases: Can be selected from a variety of sources: Hospitals, Clinics, Registries. If cases are selected from a single source, and risk factors from that facility may not be generalizable to all patients with that disease.

Controls: Ideally, you want controls to come from the same reference population that cases are derived from. An inappropriate control group can have the opposite effect and obscure an important link between disease and its cause.

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31
Q

Case-Control Studies

Information Bias?

A

Information Bias

Recall Bias (Subject Bias) is the main form of information bias in case-control studies. Occurs when there is a differential recall of exposure between cases and controls.

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32
Q

Case-Control Studies

Researcher/Observer Bias:

A

Researcher/Observer Bias:

Occurs when the researcher/observer evaluates cases vs controls differentially.

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33
Q

Case-Control Studies

Voluntary Reponses Bias

A

Voluntary Reponses Bias

Arises when case subjects who think they have been exposed to responds at a higher rate to controls.

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34
Q

case may not be generalizable to all patients with that disease

A

Selection Bias of the CASE

Potential Biases in Case-Control Studies

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35
Q

where do you want your controls to come from ideally?

Why?

A

Ideally, you want controls to come from the same reference population that cases are derived from. An inappropriate control group can have the opposite effect and obscure an important link between disease and its cause.

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36
Q

What is the main form of information bias in case-control studies?

A

Recall Bias (Subject Bias)

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37
Q

Information bias with a recall bias (subject bias) occurs when…

A

Occurs when there is a differential recall of exposure between cases and controls.

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38
Q

Potential Biases in Case-Control Studies:

Occurs when the researcher/observer evaluates cases vs controls differentially.

A

Researcher/Observer Bias:

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39
Q

Potential Biases in Case-Control Studies:

Arises when case subjects who think they have been exposed to responds at a higher rate to controls.

A

Voluntary Reponses Bias

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40
Q

Control Biases:

Process of selecting the controls so they are similar to the cases in certain characteristics, such as age, race, sex, socioeconomic status, and occupation.

A

Matching:

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41
Q

two subcategories of matching (a type of control bias)?

A

Individual: For each case selected for the study, a control is selected who is similar to the case in terms of the specific variable.

Group-based: Select controls with a certain characteristic that is identical to the proportion of cases with same characteristic.

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42
Q

Problems with matching:

A

If you select too many matching characteristics it is difficulty to find an appropriate control.

You lose the ability to study a matched variable.

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43
Q

Offers independent estimates of exposure among different samples of non-cases. Increases strength of the study.

A

Multiple Controls: Employ multiple control groups

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44
Q

Other Types of Case-Control Studies?

A

Case-crossover

Nested Case-Control

Case-Cohort

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45
Q

A variant of a case-control study

Each case becomes their own individual control

Used for transient exposures during a discrete occurrence

A

Case-crossover

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46
Q

A case control study within a large cohort

Typically seen with large enrollment studies

Controls are a sample of individuals who are at risk for the disease/outcome at the time each case of the disease develops.

A

Nested Case-Control

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47
Q

Same as nested case-control design, expect controls are randomly chosen from the cohort at the beginning of the study.

A

Case-Cohort

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48
Q

Cohort studies

A

Cohort – a group of people who share a common characteristic or experience and all remain in the group for a period of time

Cohort Study – an epidemiologic investigation that follows groups with common characteristics, strongest observational study

Prospective – identify a group of patients who are already taking a particular treatment or have an exposure, follow them forward over time, and then compare their outcomes with a similar group that has not been affected by the treatment or exposure being studied

Retrospective – start with a cohort and go back in time to evaluate past exposures to risk factors

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49
Q

– a group of people who share a common characteristic or experience and all remain in the group for a period of time

A

Cohort

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50
Q

– an epidemiologic investigation that follows groups with common characteristics, strongest observational study

A

Cohort Study

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51
Q

– identify a group of patients who are already taking a particular treatment or have an exposure, follow them forward over time, and then compare their outcomes with a similar group that has not been affected by the treatment or exposure being studied

A

Prospective

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52
Q

– start with a cohort and go back in time to evaluate past exposures to risk factors

A

Retrospective

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53
Q

Look at slide 20 to reinforce cohort studies

A

Job well done

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54
Q

Potential Biases in Cohort Studies

A

Selection Bias - (lost to follow up)

Information Bias - quality of info between exposed vs non-exposed AND Observer bias

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55
Q

Potential Biases in Cohort Studies

Selection Bias -

Lost to follow up ?

A

People with disease are selectively lost to follow-up, and those lost to follow-up differ from those not lost to follow-up.

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56
Q

Potential Biases in Cohort Studies

Information Bias?

A

Quality and extent of information is different for exposed person than for non-exposed person, a significant bias can be introduced.

OBSERVER BIAS – Occurs when the observer decides whether the disease has developed in each subject also knows whether that subject was exposed.

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57
Q

Strengths of cohort studies?

A

Temporal relationships identified

Confirm Cause and Effect (& magnitude of effect)

Measures Incidence Rate

  • Can calc Relative Risk
  • HIGHEST VALIDITY OF OBSERVATIONAL STUDY DESIGN**
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58
Q

Highest validity of observational study design?

A

measure of the incidence (rate) of disease

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59
Q

Strengths-
May study multiple effects of a single exposure

Can identify a temporal relationship between exposure and disease (outcome)

Help confirm cause and effect of disease and the magnitude of the effect

Can measure incidence (rate) of disease

  • –Can calculate Relative Risk
  • –Highest validity of observational study design
A

Cohort studies

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60
Q

Limitations-

Expensive and time consuming

Inefficient for studying rare diseases

Case-control more appropriate for rare diseases

Lose participants to follow-up

Risk of confounding variables

Retrospective studies require presence of records or recall

A

Cohort studies

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61
Q

Limitations of Cohort Studies?

A

Expensive and time consuming

Inefficient (rare diseases)

Lose participants (to follow up)

Risk of confounding variables

Require presence of records or recall

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62
Q

Which study is better for rare diseases… cohort or case control?

A

CASE-CONTROL

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63
Q

Study comparison

Cohort vs. Case Control

A

Cohort studies:

Start with exposure, look for disease

Prospective or retrospective

Common diseases

High risk for drop out

$$$

Case-Control studies:

Start with disease, look for exposure

Retrospective

Rare disease

Recall and selection bias

$

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64
Q

Randomized control studies

“Randomized” Allocation/Assignment

The main purpose of randomization is to prevent any potential biases on the part of…

A

the investigators from the influencing the assignment of participants into different treatment groups.

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65
Q

May be done by assigning random numbers or by a program that generates random assignments

A

Randomized control studies

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66
Q

Each subject has an equal chance of being assigned to each group (control or intervention)

A

Randomized control studies

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67
Q

Randomized control studies

Randomization strives for comparability of the different treatment groups; however…

A

its not guaranteed.

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68
Q

Randomized control studies

“Controlled” implies predefined:

A

Specified hypotheses

Primary and secondary endpoints to address hypotheses

Methods for enrollment and follow up

Eligibility/Exclusionary criteria

Rigorous monitoring

Analysis plans and stopping rules

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69
Q

Randomized control studies

Why Controlled?

A

Seek to eliminate confounding variables

Attempt to minimize bias

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70
Q

Look at table on slide 28

A

Did ya?

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71
Q

As far as enrollment,

Criteria for determining selection must be specified

A

before the study is begun.

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72
Q

As far as enrollment,

Want to ensure that participants actually

A

have the disease of interest.

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73
Q

As far as enrollment,

Carefully select sample based on

A

a reference population.

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74
Q

As far as allocation,

______ is the best approach in the design of a trial, and the critical element of _____ is the unpredictability of the next assignment.

A

Randomization

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75
Q

the critical element of _____ is the unpredictability of the next assignment.

A

Randomization

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76
Q

As far as allocation,

If conducted properly we don’t have to worry that any….

A

subjective biases of the investigator, either overt or covert, may be in introduced into the process of selecting patients.

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77
Q

How is randomization accomplished:

A

Computer programs

Envelope System – The treatment assignment that is designated by a random number is written on a card, and this card is placed inside an envelope. Each envelope is labeled on the outside: Patient 1, Patient 2, Patient 3…..etc. When the first patient is enrolled and consented the investigator opens the envelope and the treatment assignment is determined.

Only open the enveloped after a subject is consented and meets eligibility criteria!

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78
Q

When do we open the envelope in the randomization process of the envelope system?

A

Only open the enveloped after a subject is consented and meets eligibility criteria!

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79
Q

We hope that randomization achieves comparability of characteristics between the treatment groups

A

however, this not guaranteed!

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80
Q

– utilized when we are concerned about the comparability of the groups in terms of one or a few important characteristics. This is conducted by stratifying our study population by each variable that we consider important, and then randomize participants to treatment groups within each stratum.

A

Stratified Randomization

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81
Q

Treatment (Assigned vs Received)

A

Important to know if the patient was assigned to receive treatment A, but did not comply.

A subject may agree to be randomized, but may later change his or her mind and refuse to comply.

Conversely, it is also clearly important to know whether a patient who was not assigned to receive treatment A may have taken treatment A on his or her own, often without realizing.

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82
Q

As far as Outcome,

Comparable measurements in all study groups.

A

Improvement

Side Effects or Adverse Reaction

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83
Q

As far as Outcome,

___ ___ ____ for all outcomes to be measured in a study

A

Explicitly stated criteria

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84
Q

As far as Outcome,

Potential pitfall is outcomes being measured more carefully in…

How is this prevented?

A

those receiving a new drug than in those receiving currently available therapy must be avoided.

Blinding can prevent much of this problem; however, blinding is not always possible.
Behavioral Interventions

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85
Q

As far as Randomized control studies,

What is blinding?

A

The concealment of group allocation from one or more individuals involved in a clinical research study.

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86
Q

As far as Randomized control studies,

Usually is used in research studies that compare two or more types of interventions.

A

Blinding

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87
Q

As far as Randomized control studies,

Blinding is Used to make sure that knowing the type of treatment does not affect:

A

A participant’s response to the treatment

A health care provider’s behavior

The assessment of the treatment effects

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88
Q

After being observed for a certain period of time on one therapy; any changes are measured; patients are switched to the other therapy.

A

Planned Crossover

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89
Q

Planned Crossover

Each patient can serve as his or her own ____

A

control

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90
Q

Planned Crossover

holding constant the variation between individuals in many characteristics that could potentially affect…

A

a comparison of effectiveness of two agents.

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91
Q

Planned Crossover

Must have a

A

washout period!

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92
Q

Unplanned crossover

Occurs when subjects who are randomized

A

cross-over to the other group.

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93
Q

Unplanned crossover

If we analyze according to treatment that the patient actually receive, we will have

A

broken and therefore lost the benefits of randomization.

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94
Q

Unplanned crossover

Current practice to perform the analysis by ____ _ ___-according to the original randomized assignment.

What happens if bias occurs?

A

intention to treat

If bias occurs typically biases towards the null; typically provides a more conservative estimate

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95
Q

If bias occurs typically biases towards the null; typically provides a more conservative estimate

A

Unplanned crossover

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96
Q

Randomized control studies

Blinding types?

A

Single

Double

Triple

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97
Q

Allocation is concealed from only one group (researchers or subjects)

A

Single blinding

Randomized control studies

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98
Q

Allocation is concealed from both groups (researchers and subjects)

A

Double blinding

Randomized control studies

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99
Q

Allocation is unknown to the subjects, the individuals who administer the treatment or intervention, and the individuals who assess the outcomes.

A

Triple blinding

Randomized control studies

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100
Q

Subjects may agree to be randomized, but following randomization they may not comply with the assignment treatment.

May be Overt or Covert!

A

Noncompliance

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101
Q

The net effect of non-compliance on the study results will be to reduce __________, because the treatment group will include some who did not receive the therapy, and the no-treatment group may ____________

A

any observed differences

include some who received the treatment.

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102
Q

Randomized control studies

Strengths?

A

When combined-

Double-blinded Randomized Control Trial is typically referred to as the Gold-standard

Minimizes the chance for bias if randomization and blinding are done correctly

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103
Q

what is the gold standard of randomized control studies?

A

Double-blinded Randomized Control Trial is typically referred to as the Gold-standard

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104
Q

Randomized control studies

Limitations-

A 
Large trials (may affect statistical power)
Long term follow-up (possible losses)
Compliance
Expensive
Possible ethical questions	
Primum Non Nocere / ‘First Do No Harm’
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105
Q

– Attempted to learn if the drug, surgical procedure, or administrative program works under ideal circumstance.

A

Efficacy Trial

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106
Q

– Within the confines of the study, results appear to be accurate and the interpretation of the investigators I supported.

A

Internal Validity

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107
Q

– Ability to apply results obtained from a study population to a broader population. Also called generalizability.

A

External Validity

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108
Q

Also called generalizability.

A

External Validity

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109
Q

External Validity also called…

A

generalizability.

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110
Q

Look at slide 41 to understand external vs. internal validity

A

It’s a PHENOMENAL visual reference

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111
Q

Designs that summarize the work of other studies

—-Takes the results of a large numbers of primary research studies and combines them into one

A

Systematic Reviews and Meta-analyses

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112
Q

The top two levels of the EBM pyramid

Generally represents the strongest evidence

A

Systematic Reviews and Meta-analyses

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113
Q

Both are subject to bias based on the inclusion and/or exclusion criteria

A

Systematic Reviews and Meta-analyses

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114
Q

What is the difference between a “systematic review” and a “meta-analysis”?

A

A “systematic review” is a thorough, comprehensive, and explicit way of interpreting the medical literature

A “meta-analysis” is a statistical approach to combine the data derived from several selected studies

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115
Q

A “_______” is a thorough, comprehensive, and explicit way of interpreting the medical literature

A

systematic review

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116
Q

A “_______” is a statistical approach to combine the data derived from several selected studies

A

meta-analysis

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117
Q

Both are used for the development of Clinical Practice Guidelines (CPGs)

A

Systematic reviews and Meta-analyses

118
Q

Appraise and synthesize all the empirical evidence to answer a given research question!

A

Systematic reviews

119
Q

Systematic reviews

Methodology? (9 Steps)

A

State objectives and outline eligibility criteria

Search for trials that meet criteria

Establish methods for assessing methodological quality of each study

Apply eligibility criteria and justify exclusions

Assemble the most complete collection possible

Analyze results using synthesis of data

Compare alternate analyses, if necessary

Prepare a critical summary of the review
Restate aims, methods, and results

120
Q

Systematic reviews

Strengths

A

Exhaustive review of the current literature and other sources

Less costly to review prior studies than to create a new study

Less time required than conducting a new study

Results can be generalized and extrapolated into the general population more broadly than individual studies

More reliable and accurate than individual studies

Considered an evidence-based resource

121
Q

Strengths systematic reviews…. things in bold only

A

can be generalized

evidence-based resource

122
Q

Systematic reviews

Limitations?

A

Limitations

Very time and labor consuming
May not be easy to combine studies

123
Q

greater statistical power

A

Meta-analyses

124
Q

A method for combining pertinent study data from several selected studies that are similar enough to justify a quantitative summary to develop a single conclusion that has greater statistical power

A

Meta-analyses

125
Q

A statistical synthesis of the numerical results of several trials which all addressed the same research question

A

Meta-analyses

126
Q

Meta-analyses

The conclusion is statistically stronger than any single study due to:

A

increased numbers of subjects

greater diversity among subjects

accumulated effects and results

127
Q

Meta-analyses

Strengths

A

Greater statistical power

Confirmatory data analysis

Greater ability to extrapolate to the general population

128
Q

Meta-analyses

Limitations

A

Difficult and time consuming to identify appropriate studies

Not all studies provide adequate data for inclusion and analysis

Requires advanced statistical techniques

Heterogeneity of study populations

Age, gender, etc.

Results are not always reproducible by other investigators

Subject publication Bias, Selection Bias, and Misclassification Bias

Can give a false sense of certantiy regarding the magnitude of risk

129
Q

Difficult

Not all studies provide adequate data

advanced statistical techniques

Heterogeneity

publication Bias, Selection Bias, and Misclassification Bias

A

Meta-analyses

Limitations

(That were bolded)

130
Q

Meta-analyses

Limitations

(That were bolded)

A

Difficult

Not all studies provide adequate data

advanced statistical techniques

Heterogeneity

publication Bias, Selection Bias, and Misclassification Bias

131
Q

Measures of Central Tendency

A

Mean, median, and mode

132
Q
  • the “average” – sum of the set divided by the number in the set
A

Mean

133
Q

– the middle point (arrange the data smallest to largest, then find the middle point)

A

Median

134
Q

– the score that occurs most frequently in a set of data

A

Mode

135
Q

May have two most common values = “bimodal distribution”

A

Mode

136
Q

Variance compared to standard deviation
quantifies the amount of variability, or spread, around the mean of the measurements.

To calculate?

A

Variance (σ2 )

To calculate: take each difference from the mean, square it, and then average the result

137
Q

a measure of variation of scores about the mean

To calculate?

A

Standard deviation (σ):

To calculate: take the √ of the variance
the “average distance” to the mean

138
Q

Variance compared to standard deviation

more frequently used?

A

In practice, the standard deviation is used more frequently than the variance.

Primarily because the standard deviation has the same units as the measurements of the mean.

139
Q

Variance compared to standard deviation

When comparing two groups, the group with the larger standard deviation exhibits….

A

… a greater amount of variability (heterogeneous) while the groups with smaller deviation has less variability (homogeneous).

140
Q

a greater amount of variability

A

(heterogeneous)

141
Q

while the groups with smaller deviation has less variability

A

(homogeneous)

142
Q

A useful summary of a set of bivariate data (two continuous variables)

A

Scatterplots

143
Q

Scatterplots

Gives a good visual picture of the relationship between…

and aids?

A

the two variables

and aids the interpretation of the correlation coefficient or regression model.

144
Q

Evaluates the strength of linear relationships or associations between variables

A

Scatterplots

145
Q

Scatterplots

How strongly is one variable related to another?

A

Are BP and weight correlated?

Is HIV risk and # of sexual partners correlated?

146
Q

Scatterplots

Direct or inverse relationship?

X increases and Y increases = ?

X increases and Y decreases = ?

0 is no correlation

A

X increases and Y increases = positive correlation

X increases and Y decreases = negative correlation

0 is no correlation

147
Q

Represented by “r ” (rho)

The absolute value of the coefficient (its size, not its sign) tells you how strong the relationship is between the variables.

Tells us how strongly two variables are related

“r” can not be > 1 or < -1

Closer to -1 or +1: the stronger the relationship

Closer to 0 : the weaker the relationship

A

Correlation Coefficient

148
Q

The most common measure of association. Results can misleading if the relationship is non-linear.

A

Pearson Correlation:

149
Q

Correlation Coefficient

Pearson’s correlation is very sensitive to?

A

outlying values.

150
Q

non-parametric version of Pearson’s correlation. The calculation is based on the ranks of the data points of the x and y values

A

Spearman Correlation:

151
Q

The statement that establishes a relationship between variables being assessed

Example: In a clinical trial the hypothesis states the new drug is better the placebo

A

Alternative hypothesis (Ha or H1)

152
Q

The statement of no difference or no relationship between the variables

Example: In a clinical drug trial the null hypothesis states that the new drug is no better than placebo

A

Null hypothesis (Ho)

153
Q

Hypothesis stating the expected relationship between independent and dependent variables.

If there IS a statistically significant difference, then the researchers “ACCEPT” the alternative hypothesis and “REJECT” the null hypothesis.

A

Alternative hypothesis

AKA the “research hypothesis”

154
Q

Alternative hypothesis

AKA the

A

“research hypothesis”

155
Q

If there IS a statistically significant difference, then the researchers “ACCEPT” the alternative hypothesis and “REJECT” the null hypothesis.

A

Alternative hypothesis

AKA the “research hypothesis”

156
Q

Hypothesis stating the expected relationship between independent and dependent variables.

If there IS a statistically significant difference, then the researchers “ACCEPT” the alternative hypothesis and “REJECT” the null hypothesis.

A

Alternative hypothesis

AKA the “research hypothesis”

157
Q

If there IS a statistically significant difference, then the researchers must “REJECT” the Null hypothesis

If there IS NOT a statically significant difference, then the researchers must “RETAIN” or “FAIL to REJECT” the Null hypothesis.

A

Null hypothesis

158
Q

If there IS a statistically significant difference, then the researchers must _____ the Null hypothesis

A

“REJECT”

159
Q

If there IS NOT a statically significant difference, then the researchers must _____ the Null hypothesis.

A

“RETAIN” or “FAIL to REJECT”

160
Q

Two kinds of errors can be made when we conduct a test of hypothesis.

A

Type I error (α error)

Type II error (β error)

161
Q

also known as a rejection error or an α error.

A

Type I error;

162
Q

A type I error is made if we

A

reject the null hypothesis when null hypothesis is true.

163
Q

The probability of make a type I error is determined by

A

the significance level of the test.

164
Q

The second kind of error that can be made during a hypothesis test is a Type II error, also known as

A

an acceptance error or an β error.

165
Q

A Type 2 error is made if we

A

fail to reject null hypothesis.

166
Q

The probability of committing a type II error is represented by

A

the Greek letter β.

167
Q

Look at the easy table on slide 60 for null hypothesis made EASY

A

Look at the easy table on slide 60 for null hypothesis made EASY

168
Q

The probability of finding an effect
The probability of correctly rejecting the null hypothesis
The probability of seeing a true effect if one exists
Designers of studies typically aim for a power of 80% or 0.8
Implies there is an 80% chance of getting it right
Generally speaking: More people = more power

A

Statistical Power

169
Q

A __ __ calculates the number of participants a study must have to draw accurate conclusions

A

Power Analysis

170
Q

A power analysis calculates the number of ____ a study must have to draw accurate conclusions

Takes into consideration: estimated effect size, sample means, etc.

A

Participants

171
Q

The probability of rejecting a true H0

A

Signifigance

172
Q

α = .05 usually set, acceptable error

Chance that 5 times out of 100 the H0 would be falsely rejected

A

Signifigance

173
Q

How do we determine if the study result happened by chance alone

A

Signifigance

174
Q

What determines statistical “significance”?

A

Significance

The probability of rejecting a true H0

175
Q

The likelihood that the difference observed between two interventions could have arisen by chance

A

Probability Level

176
Q

If Accepted value is 5% risk (p = .05)

A

Means there is a 5% chance that the results happened by chance

Allows us to reject or accept the null hypothesis

177
Q

p is the chance of ___ ___

A

random error

178
Q

α is the ___ ___, usually = .05

A

acceptable error

179
Q

p ≤ α
reject the H0
the results (are/are not)? statistically significant

A

p ≤ α
reject the H0
the results are statistically significant

180
Q

p > α
fail reject the H0
the results (are/are not)? statistically significant

A

p > α
fail reject the H0
the results not statistically significant

181
Q

More important than p value – a better determination of significance

A

Confidence Interval (CI)

182
Q

Any statistic is simply an estimate of the true value of that statistic
___ ___ produces a range within which the true value most likely lies

A

Confidence Interval (CI)

183
Q

95% CI states that we can be 95% certain that the “true” value is within the CI range

A

Confidence Interval (CI)

184
Q

Is a wider or narrow CI better?

A

Narrower CI is better

185
Q

If the Confidence Interval include 1 (null value) then the results is ___ ___

A

Clinical insignificant

186
Q

A ___ ___ is used to separate from a large group of apparently well persons those who have a high probability of having the disease, so that they may be given a diagnostic work up, and if diseased can be treated.

A

Screening Test

187
Q

A screening test is used to separate from a large group of apparently well persons those who have a ___ ___ of having the disease, so that they may be given a diagnostic work up, and if diseased can be treated.

A

High Probability

188
Q

Screening Tests

In general, screening is performed only when the following conditions are met:

1)

2)

3)

A

1) The target disease is an important cause of mortality and morbidity.
2) A proven and acceptable test exists to detect individuals at an early stage of disease.
3) There is a treatment available to prevent mortality and morbidity once positives have been identified.

189
Q

The proportion of people with the disease who have a positive test for the disease.

A

Sensitivity

190
Q

The ability of the test to identify correctly those who have the test.

A

Sensitivity

191
Q

The proportion of people without the disease who have a negative test.

A

Specificity

192
Q

The ability of the test to identify correctly those who do not have the disease

A

Specificity

193
Q

Tends to rule OUT the disease

A

Sensitivity

194
Q

Tends to rule IN the disease

A

Specificity

195
Q

High Sensitivity means low probability of __ ___

A

False Negative

196
Q

High Specificity means low probability of __ ___

A

False Positive

197
Q

Screening test’s ability to identify presence of disease

A test with high ___ will not miss many patients who have the disease

A

Sensitivity

198
Q

Screening test’s ability to truly identify absence of disease

A

Specificity

199
Q

A highly useful test when NEGATIVE

A

Sensitivity

200
Q

A highly useful test when it is POSITIVE

A

Specificity

201
Q

Sensitivity and Specificity

A

Recap slide 70

graphs on 71-73

202
Q

Allows us to calculate the net sensitivity and net specificity of using both tests in sequence. After completing both tests there is a loss in net sensitivity and net gain in specificity

A

Sequential (two stage) testing

slide 74 or square chart

203
Q

When multiple tests are used simultaneously to detect a specific disease, the individual is generally considered to have tested “positive” if he or she has a positive result on any one or more of the tests. The individual is considered to have tested “negative” if he or she tests negative on all of the tests

A

Simultaneous tests

some colors on slide 75 for you to peruse

204
Q

proportion of patients who HAVE the disease and a positive test

A

Positive Predictive Value (PPV)

205
Q

proportion of patients who DO NOT HAVE the disease, and have a negative test

A

Negative Predictive Value (NPV)

206
Q

Negative Predictive Value (NPV) = proportion of patients who __ the disease, and have a negative test

A

DO NOT HAVE

207
Q

Positive Predictive Value (PPV) = proportion of patients who ___ the disease and a positive test

A

HAVE

208
Q

Assesses reliability of positive test

i.e. PPV 90% = positive test 90% of the time the test is correct

A

Positive Predictive Value

209
Q

With low prevalence (% of population) of disease:
Lower PPV
False positives increase
Less reliable positive test result

A

PPV

210
Q

Assesses reliability of a negative test

i.e. NPV 90% = negative 90% of the time the test is correct

A

Negative Predictive Value (NPV)

211
Q

With low prevalence(% of pop) of disease :
Higher NPV
False negative test decreased
A negative test result is more reliable

A

NPV

212
Q

the occurrence, rate, or frequency of a disease

A

Incidence

213
Q

Obtained from cohort studies

Must follow a cohort through time

A

Incidence

214
Q

the number of occurrences at one particular time

A

Prevalence

215
Q

Obtained from cross-sectional studies

No time line, only a snap shot

A

Prevalence

216
Q

Incidence is the occurrence, ___, or frequency of a disease

A

Rate

217
Q

Incidence calculations …

A

slide 80

218
Q

Relationship between incidence and prevalence

A

slides 81 to 84

219
Q

Nominal and Ordinal are:

A

Categorical Data

220
Q

Interval and Ratio are:

A

Continuous Data

221
Q

named categories with no implied order

Gender, race, ABO blood type, group

A

Nominal (categorical data)

222
Q

sequenced or ranked data

Smallest to largest, lightest to heaviest, easiest to most difficult

A

Ordinal (categorical data)

223
Q

intervals along the scale are equal to one another (i.e. integers)

A

Interval (continuous data)

224
Q

characterized by the presence of absolute zero on the scale

A

Ratio (continuous data)

225
Q

are statistical significance and clinical significance the same

A

NOT the same thing

226
Q

Once we determine the difference between the expected outcome and the actual outcome was NOT due to chance (statistical significance), we have to decide on ___ ___

A

Clinical Significance

227
Q

Clinically unimportant effects may be statistically significant if a study is large

A

Pay attention to effect size and confidence intervals.

228
Q

___ ___ addresses How much more likely are we to find that a test is positive among patients with disease compared with those without disease?

A

Likelihood Ration (LR)

229
Q

Summarizes the same kind of information sensitivity and specificity and can be used to calculate the probability of disease in a low prevalence setting.

A

Likelihood Ratio (LR)

230
Q

Low prevalence = Less reliable positive test result; therefore, use __ __

A

Likelihood Ratio (LR)

231
Q

LR provides indication of the test’s discriminatory power.

Predictive values are lower with a low prevalence

LR can be defined for the entire range of test result values

Low prevalence = Less reliable positive test result; therefore, use LR

A

Likelihood Ratio (LR)

232
Q

Mnemonic - W/WO

A

With / Without

Likelihood Ration (LR)

233
Q

Likelihood of a particular result in someone WITH the disease / Likelihood of the same result in someone WITHOUT the desiease

A

Likelihood Ratio

234
Q

A ___ is the ratio of the proportion of diseased people with a positive test result (sensitivity) to the proportion of non-diseased people with a positive result (1-specificity).

A

positive LR (LR+)

How good the test is at “Ruling in” disease!

235
Q

Range: 1.0 to infinity; Null value: 1.0 (no difference)

A

The bigger the better (Desirable: 5 or more)

236
Q

A negative LR (LR-) is the proportion of diseased people with a negative test result (1-sensitivity) divided by the proportion of non-diseased people with negative test results (specificity)

A

Negative LR (LR-)

How good the test is at “Ruling out” disease

237
Q

Range: 0.0 to 1.0; Null value: 1.0 (no difference)

A

The smaller the better (Desirable: 0.2 or less)

238
Q

Is one of the most common ways to examine relationships between two or more categorical variables.

A

Chi-Square

239
Q

Does Chi-square give any information about the strength of the relationship.

A

Does Not

240
Q

Odd ration interpretation

A

slide 94

241
Q

More on incidence

A

slide 95

242
Q

Basic risk statements express the likelihood that a particular event will occur within a particular population
What exposure is responsible for an illness or other outcome?
Identifies what in our environment can lead to beneficial or adverse medical outcomes

A

Relative Risk

243
Q

___ ___ measures the magnitude of an association between an exposed and non-exposed (control) group.

A

Relative Risk

244
Q

___ ___ is calculated using cumulative incidence data to measure the probability of developing disease

  • Must have incidence information to calculate
  • Cohort or clinical trials are conducted over time
A

Relative Risk

245
Q

Relative risk formula:

A

Experimental Event Rate (EER) /

Control Event Rate (CER)

246
Q

NNT= 1/ARR

A

Number needed to treat

247
Q

Expresses the likelihood of the treatment to benefit an individual patient

A

Number needed to treat

248
Q

There is NO absolute value for NNT that defines whether something is effective or not.
NNTs for treatments are usually low because we expect large effects in small numbers of people

A

NNT

249
Q

When an experimental treatment is detrimental, the term __ __ __ is often used.
The equations and approach are similar to those described above, except that NNH will have a negative absolute risk reduction

A

Number needed to harm

250
Q

AKA Student’s t-test
Generally is used to analyze ___ ___
Compares the means and standard deviations of two populations

A

Continuous data

251
Q

T-test Computes a ___ to test the null hypothesis

A

p-value

252
Q

is that the difference between the two group means is 0 or no difference

A

Null hypothesis

253
Q

The difference between the two group means is >0 or there is a difference.

A

Alternative Hypothesis

254
Q

what type of Error:

finding an effect that isn’t real
Rejecting the null when the association isn’t real
“Convicting an innocent man to prison”

A

Type 1 Error

255
Q

What type of Error:

Type II error: missing an effect that does exist
“Retaining” or “Failing to Reject” the null hypothesis when the association is real
“Not convicting a guilty man”

A

Type II Error

256
Q

What type of error is considered worse, Type I or Type II?

A

Type I error is considered worse than Type II, therefore more important avoid

257
Q

within the confines of the study results appear to be accurate and interpretation of the results are supported.

A

Internal Validity

258
Q

results and interpretations of the study apply outside the studied population. Also called generalizability

A

External Validity

259
Q

results and interpretations of the study apply outside the studied population. Also called generalizability

A

Validity of Data

260
Q

Degree to which the measurements are reproducible
Example:
How closely do repeated measurements on the same subject agree

A

Reliability

261
Q

Errors:

A

slide 105

262
Q

Condition, intervention or characteristic that will predict or cause an outcome

Age, gender, & marital status of participants are independent from the outcome

–the experimental treatment doesn’t change these values

A

Independent Variables

263
Q

AKA outcome variable

Response or effect that is presumed to vary depending on the independent variable

The measurable “outcome” variable
Example: blood pressure/rate in response to treatment

A

Dependent Variable

264
Q

Variables that correlates directly or indirectly with the dependent and independent variables.

A

Confounding Variables

265
Q

Confounding factors AKA..

A

AKA confounding factor, hidden variable, lurking variable, a confound, or confounder

266
Q

An extraneous variable in a statistical model that correlates (positively or negatively) with both the dependent variable and the independent variable

A

Confounding factors

267
Q
  1. Optimal clinical decision making requires awareness of the best available evidence, which ideally will come from systematic summaries of that evidence.
  2. EBM provides guidance to decide whether evidence is more or less trustworthy—that is, how confident can we be of the properties of diagnostic test, or our patient’s prognosis, or of the impact of our therapeutic options?
  3. Evidence alone is never sufficient to make a clinical decision.
A

3 Fundamental Principles of Evidence Based Medicine (EBM)

268
Q

5 A’s of EBM

A
  1. Assess
  2. Ask
  3. Acquire
  4. Appraise
  5. Apply
269
Q

5 A’s of EBM

A
  1. Assess
  2. Ask
  3. Acquire
  4. Appraise
  5. Apply
270
Q

evidence pyramid, top down…

A

Filtered
unfiltered
background

see slide 113

271
Q

Five types of clinical questions:

A 
Therapy
Harm
Differential Diagnosis
Diagnosis
Prognosis
272
Q

Research involving formal, objective information about the world, with mathematical quantification; it can be used to describe test relationships and to examine cause and effect relationships.

A

Quantitative Research

273
Q

Research dealing with phenomena that are difficult or impossible to quantify mathematically, such as beliefs, meanings, attributes, and symbols; it may involve content analysis

A

Qualitative Research

274
Q

Comparison of design

Qualitative vs Quantitative?

A

QUALITATIVE

Subjectivity is expected
Descriptive
What is this phenomena?
Low Control

QUANTITATIVE

Objectivity is critical
Experimental
To what extent does A affect or cause B?
High Control

275
Q

Research Paradigms:Know that qualitative research is not less rigorous or easier –

A

just different!

276
Q

Comparison of questions:

Qualitative vs Quantitative:

A

Comparison of questions

Qualitative:
Why do you…?
What do you think of…?
When is it important…?
How does that make you feel…?
QUANTITATIVE
Who is at risk for…?
What is the effect of…?
How many will benefit from…?
How much improvement…?
277
Q

Comparison of methods:

Qualitative vs Quantitative:

A 
Qualitative:
Focus Groups 
Interviews
Surveys 
Self-reports 
Observations 
Document analysis
Sampling: Purposeful
Quantitative:
Observational
Experimental
Mixed 
Sampling: Random
278
Q

Basic level: a descriptive account of the data (i.e. this is what was said, but no comments or theories as to why or how)

A

Manifest Level

279
Q

Higher level: a more interpretive analysis that is concerned with the response as well as what may have been inferred or implied

A

Latent Level

280
Q

absolute risk reduction?

A

Absolute risk reduction (ARR) – also called risk difference (RD) – is the most useful way of presenting research results to help your decision-making. In this example, the ARR is 8 per cent (20 per cent - 12 per cent = 8 per cent). This means that, if 100 children were treated, 8 would be prevented from developing bad outcomes.

Another way of expressing this is the number needed to treat (NNT). If 8 children out of 100 benefit from treatment, the NNT for one child to benefit is about 13 (100 ÷ 8 = 12.5).

281
Q

Absolute risk reduction (ARR) – also called risk difference (RD) – is the most useful way of presenting research results to help your decision-making. In this example, the ARR is 8 per cent (20 per cent - 12 per cent = 8 per cent). This means that, if 100 children were treated, 8 would be prevented from developing bad outcomes.

Another way of expressing this is the number needed to treat (NNT). If 8 children out of 100 benefit from treatment, the NNT for one child to benefit is about 13 (100 ÷ 8 = 12.5).

How do you calculate NNT?

A

NNT = 1 / ARR

282
Q

Busy clinicians have an obligation to understand primary (original) research in order to maintain relevant, up to date practice.

Need to utilize information management to find:
Clinically applicable primary sources and appraise them critically.

Appropriate secondary sources that summarize the relevant literature and deliver a useful, actionable bottom line.

A

Evolution

283
Q

Clinicians must be able to decipher which studies are useful to their practice

—-Must be able to critically evaluate articles fairly quickly and efficiently.

Clinicians must also be able to sift through which articles have been evaluated with sufficient academic rigor.

Peer-reviewed?
Academic journal vs. “throwaway”
Sponsorship? (pharmaceutical company, etc.)

A

True

284
Q

New Definition of EBM

A

“The revised and improved definition of evidence-based medicine is a systematic approach to clinical problem solving which allows the integration of the best available research evidence with clinical expertise and patient values.”

285
Q

Evaluate how recently the summary was updated or revised

Not all topics are covered by filtered information resources

Meta-analyses, Cochrane Database of Systematic Reviews.

Clinical Practice Guidelines

A

Filtered Resources

286
Q

Examples of Filtered Resources?

A

Systematic Reviews

Meta Analysis

Evidence Summaries

Evidence Guidelines

287
Q

Better known as “primary literature”

It’s up to YOU to assess quality, validity and applicability to your patient

Requires time and experience

A

Unfiltered Resources

288
Q

Examples of Unfiltered Resources?

A

RCT’s

289
Q

To learn about a new topic or refresh knowledge

Provide a comprehensive overview of a disease, condition, or concept

Usually in a textbooks, Medline, Medscape, UpToDate

A

Background Resources

290
Q

Examples of Background Resources?

A

Background info, expert opinion

291
Q

Research Paradigms: Know that qualitative research is not less rigorous or easier – just different!

A

Cool

Research Evaluation (12 decks)

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