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PHARM 155 - Drug info fundamentals > Week 5 > Flashcards

Week 5 Flashcards

1
Q

EBM levels of evidence pyraamid

A 
meta analysis
systemic review
RCT
cohort study
case control study
case series and case reports
animal studies/laboratory studies
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2
Q

What is a RCT used for

A

treatment questions and diagnosis questions

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3
Q

Cohort studies

  • type Q
  • when use
A
  • answer questions of prognosis and etiology/harm

- use when no RCT

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4
Q

Case control studies

  • what Q
  • when use
A
  • answer questions of prognosis, etiology/harm

- used when no cohort studies

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5
Q

case series and case reports

  • what Q
  • when use
A
  • answer questions of prognosis or etiology/harm

- when no case control studies

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6
Q

4 classifications of research

A

Nature of research
time frame of research
investigator approach
type of data

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7
Q

what are the 2 natures of research

A

descriptive and explanatory

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8
Q

what are the 3 time frames of research

A

prospective, retrospective, cross sectional

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9
Q

what are the 2 types of investigator approach

A

observational and experimental

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10
Q

what are the types of data

A

qualitative and quantitative

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11
Q

Observational investigator approach

A

investigator not influence what subjects exposed to

-track natural course/progression

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12
Q

Experimental investigator approach

A

-investigator controls exposures that may influence outcome of interest

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13
Q

4 components of true experimental design

A

1) manipulation
- investigator controls what happens during study

2) control
- presence of group that does not receive intervention being studied
- accounts for outside factors that may affect study

3) random assignment
- study subjects randomly allocated to intervention or control

4) random selection
- study subjects randomly chosen from total eligible population

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14
Q

are experimental studies randomized wrt selection of control/intervention subjects from population

A

yes

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15
Q

are observational studies randomized wrt selection of control/intervention subjects from population

A

no

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16
Q

why is non-random allocation to exposure/control a problem in observational studies

ie. what is the problem with non-randomized studies

A

-variable may be due to selection
+ex. physician chose more sick people for exposure rather than healthier
-characteristics heavily influence outcome

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17
Q

Characteristics of observational studies (3)

A

exposure –> outcome

less rigid than controlled studies

ASSOCIATIONS NOT CAUSE AND EFFECT

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18
Q

why observational studies?

A

not possible have RCT to support every intervention
-still accept some interventions in spite of no RCT
+parachute example

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19
Q

necessity of observational studies (3)

A
  • extent of disease (distribution/epidemiology)
  • etiology of diseases (risk factors)
  • evaluate interventions (such as medications) in large populations to detect rare outcomes
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20
Q

Exposure event rate

A

EER - proportion of subjects in exposure group experiencing the event

EER = a/(a+b) ; a= outcome, b=no outcome where a and b are in the exposure group

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21
Q

Control event rate (CER)

A

CER - proportion of subjects in control group experiencing event

CER = c/(c+d) ; c= outcome and d = no outcome where c and d occur in control group

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22
Q

Relative risk

A

risk of developing disease or adverse event in participants EXPOSED to specific variable compared to those not

RER = EER/CER

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23
Q

RR (relative risk) = 1

A

no association

24
Q

RR (relative risk) < 1

A

negative association

-exposure/intervention decreases likelyhood of outcome

25
RR (relative risk) > 1
positive association | -exposure/intervention increases likelihood of outcome
26
When dealing with observational what wording must be used to identify a relationship in variables
Associated | -(NOT "CAUSED")
27
three types of observational studies
cohort studies case control studies cross-sectional studies
28
Cohort
-group of people who share one or more characteristic (treatment, disease, residence etc)
29
Cohort studies - who is the population - how population allocated
- the population is a cohort -there is NO RANDOM ALLOCATION +self selected
30
How collect data for cohort studies
1) retrospective 2) prospective +either or -
31
what is the risk of prospectively collecting data
-may induce additional bias | +people know they are being studied, change behaviour
32
Characteristics of cohort study
- can measure incidence (new diagnosis) and prevalence (new and old diagnosis) among population - can assess ASSOCIATION between exposure and outcomes
33
Measuring the effect size of an intervention involves what calculations (3)
relative risk reduction (RRR) Absolute risk reduction (ARR) Number needed to treat (NNT)
34
Relative Risk Reduction
RRR = (CER-EER)/CER ex interpretation: handwashing is associated with a relative reduction of childbed fever mortality of 56% compared to no handwashing
35
Absolute Risk Reduction (ARR)
ARR = CER - EER ex interpretation -handwashing is associated with an absolute reduction of childbed fever mortality by 9%
36
Number Need to Treat (NNT)
Applies meaning to ARR NNT = 1/ARR * if outcome is unwanted, NNH, number need to harm ex. 1 MD washing hands saves 0.09 life (ARR) xMD wash saves 1 life 11MD save one life
37
largest study ever recorded - type - name/what about
- prospective cohort study (1948) -Framingham Heart Study (FHS) +ID risk factors for heart disease
38
FHS ID'd risk factors
Age, Physcal activity, body weight, diabetes mellitus, hypertension, cholesterol smoking indivs dev CHD at larger rate
39
does association mean causation
no | -SO STUPID
40
can we establish causation without being able to manipulate exposure
- If we cannot manipulate exposure (randomization to exposure or control), several rules can establish causation - causality requires assess multiple pieces of evidence, NOT JUST STATISTICAL ASSOCIATION
41
Bradford Hill
-guideline for establishing causation - Temporal relation (ex. smoke first then get disease) - Biological plausibility - consistency - strength of the association (RR, OR) - Dose-response relationship - study design - judging the evidence
42
Can you establish causation from observational studies
-YES, with guidelines for causation such as bradford hill
43
Case-Control study | -5 key points
-start collecting CASES and assess exposure among them -Collect CONTROLS from the same (or similar) "original" population +must be very similar to the cases -MUST BE RETROSPECTIVE -cannot assess incidence or prevalence +we dont know the OG population -Can still assess association
44
What do you do when the outcome trying to be monitored in a study is rare
start small with a case control study | -ex. regional cancer centre
45
Measuring association in a case-control study
ODDS RATIO -what are the odds of cancer amoung smoking patients odds = (probability of success)/(Pfailure) ex. - roll 6 on dice - odds= 1/5
46
Odds Ratio
NUMERATOR Poutcome among intervention)/Pno outcome among intervention DENOMINATOR Poutcome among control/Pno outcome among control OR=num/denom
47
Interpreting odds ratio
OR = 0.63 non-smokers have 0.63 lower odds of developing cancer OR NOT smoking reduces the odds of cancer by 37%
48
How is OR an approximate estimation of RR
when a disease is rare a
49
OR vs RR - what does OR estimate - overestimate or underestimate - when is degree of estimate greater
- OR is an estimation of RR - OR always overestimates RR - this overestimation is greater when RR>1 -
50
how do you interpred the graph given %incidence (x) and odds ratio (y)
ALWAYS compare the 'overestimation' through the analysis of relative risk reduction example OR is 0.73 and RR is 0.75 The OR is considered an UNDERESTIMATION because: given OR=0.73, RRR= 27% given RR=0.75, RRR= 25% SO, based on RRR, OR is an overestimate
51
Case Control study: choosing controls - does it matter how many controls you chose - avoid
- NO, it does not matter how many controls you choose | - avoid biased controls such as people hospitalized due to accidents
52
Case-control study: bad control examples
- using pediatrics for smoking case-control studies | - having more smokers than non-smokers in controls than cancer cases grp etc
53
``` Bias types (4) -what do they do ```
selection bias information bias data analysis bias survival bias distort relationship between exposure and outcome
54
``` Confidence interval (95%) -when is there statistical significance ```
if the confidence interval does not cross 1 ex. 1.27 - 1.69 NOT STATISTICALLY SIG EXAMPLE -0.78 - 1.23
55
Confounding variables
things that influence the outcome that are not related to the exposure -such as the biases ex. post-menopausal women and estrogen - doctors prescribed the estrogen to healthier women - selection bias - confounding variable - result is due to selection bias NOT exposure
56
LOOK AT SECOND TO LAST SLIDE TABLE
EEEEEEE UNGA BUNGA

PHARM 155 - Drug info fundamentals (3 decks)

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