Exam 2 lecture 11 Flashcards

1
Q

genetic info can help:

A
  • develop gene therapy
  • predict disease risk
  • guide therapy
  • guide drug development
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2
Q

stake holders involved

A

patients, healthcare providers, industry, insurers, government, society

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3
Q

patient perspective

A

using it to guide therapy was more widely accepted that predict disease risk

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4
Q

provider perspective

A

using to guide therapy was more widely accepted

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5
Q

pharmaceutical industry perspective

A

mixed incentives

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6
Q

positives for pharmaceutical industries

A

new drug targets
drugs with better side effects
more efficient drug developments
salvage drugs

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7
Q

negatives for pharmaceutical industry

A

decreased market share
fewer blockbuster drugs
orphan popilations

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8
Q

diagnostic industry perspective

A

positive incentive: increased market share

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9
Q

insurer perspective

A
  • predicting disease not widely accepted

- guide therapy more accepted (HER2)

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10
Q

government perspective

A

safety and efficacy
medicare/medicaid reimbursement
regulations

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11
Q

society perspective

A

maximize benefits for all stakeholders

minimize risks and costs

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12
Q

cost

A

genetic testing
subsequent intervention
genetic counseling

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13
Q

benefits

A

improved therapeutic response
avoid adverse effects
avoid unnecessary treatments
improved quality of life

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14
Q

clinical validity

A

how consistently and accurately the test detects or predicts the outcomes of interest
how true something is

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15
Q

clinical utility

A

how likely the test is to significantly improve patient outcomes

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16
Q

dose limiting toxicity for TMPT polymorphism

A

myelosuppression (neutropenia)

17
Q

as prevalence goes up

A

cost effectiveness goes up

18
Q

genotyping prevalence has to be

A

at least 1% to be cost effective

homozygous TMPT

19
Q

cost effectiveness

A

<$50.000 per QALY

20
Q

if frequency is 0.5% or less, the cost of the genetic test becomes important & cost effectiveness is retained if

A

the cost of the genetic test is <$100

21
Q

warfarin

A

oral anticoagulant for treatment/prevention of thromboembolism

22
Q

dosing algorithm of warfarin

A

-start at 5 or 10 mg
- check INR day 3
- adjust dose
- check INR day 5
- adjust dose
etc

23
Q

current warfarin challenges

A
  • narrow therapeutic range (INR)
  • patients are in therapeutic range only about 66% of the time
  • up to 20-fold variability in dose requirements
24
Q

INR too low

A

ineffective anticoagulation->thromboembolism

25
Q

INR too high

A

too much anticoagulation->hemorrhage

26
Q

higher dose of warfarin required

A
  • low age, high weight, high Vitamin K intake, smoking, hypothyroidism, CYP2C9 inducers, blacks
27
Q

lower dose of warfarin required

A
  • high age, low weigh, low vitamin K intake, cancer, liver disease heart disease, hyperthyroidism, factor VII or X mutation, female, drugs (amiodarone, statins, azoles, sulfa)
28
Q

genetic factors affecting warfarin

A
  • CYP2C9 polymorphism
  • VKORC1 polymorpism
  • others (gamma glutamyl carboxylase, CYP4F2
29
Q

CYP2c9 polymorphism with warfarin

A
  • can be impaired a little or a lot

- variants more likely to require lower doses

30
Q

CYP2C9 study results

A

study group using pharmacogenetic algorithm reached therapeutic & stable INRs sooner than control group

31
Q

VKORC1 polymorphisms

A
  • ## can cause less warfarin sensitivity, intermediate or more sensitivity
32
Q

VKORC1 study results

A
  • Primary endpoint not significantly different

- PG algorithm predicted dose better w/ fewer & smaller adjustments but no different in adverse effects

33
Q

precision medicine

A

an emerging approach for disease prevention & treatment that takes into account people’s individual variations in genes, environment & lifestyle

34
Q

the precision medicine initiative

A

will generate the scientific evidence needed to move the concept into clinical practice

35
Q

research based upon the cohort data will”

A
  • advance PG, the right drug for the right patient at the right dose
  • ID new targets for treatment & prevention
  • test whether mobile devices can encourage healthy behavior
  • lay scientific foundation for precision medicine for many diseases