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Spring 2022 > BIOL 437 Ch. 12 (Clinical Epidemiology) > Flashcards

BIOL 437 Ch. 12 (Clinical Epidemiology) Flashcards

1
Q

clinical epidemiology

A

-focuses on patients and application of epidemiolgoic methods to assess efficacy of screening, diagnosis and treatment

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2
Q

clinical epidemiology is used to

A

-identify health consequences of employing a test or administering treatment

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3
Q

secondary prevention

A

-health screening and detection activities used to identify disease

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4
Q

examples of screening methods

A
  • pap test
  • mamograms
  • blood tests
  • biopsy
  • small blood sample
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5
Q

medical screening

A

-used to suggest or detect disease among individuals in a population without signs or symptoms of the health problem

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6
Q

why do we do screening?

A

-promote the detection of disease in their earliest stages, when treatment has the greatest chance of working
>to reduce morbidity and mortality

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7
Q

mass screening

A
  • not selective

- involves application of screening tests to the total population

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8
Q

selective screening

A

-applying the screening tests to high risk groups

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9
Q

screening guidelines (WHO 1968)

A
  • major medical problem
  • acceptable treatment
  • access to health care services
  • recognizable course
  • suitable and effective test
  • testing process acceptable to general population
  • natural history known
  • procedures for those who need further testing
  • simple process
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10
Q

evaluating screening guidelines using descriptive and analytical epidemiology

A
  • extent of public health problem
  • efficacy of treatment
  • access to health care
  • natural course of disease
  • efficacy of screening or diagnostic test
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11
Q

validity

A

-how well the test actually measures what it is supposed to measure

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12
Q

reliability

A
  • how well the test performs in use over time

* repeatability

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13
Q

yield

A

-amount of screening the test can accomplish in a period of time

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14
Q

validity refers to

A

-accuracy and trustworthiness of instruments, data and findings in research

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15
Q

2 ways to view and assess validity

A
  1. Content validity

2. Construct validity

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16
Q

content validity

A

-achieved when instrument has appropriate content for measuring a complex concept or construct

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17
Q

construct validity

A

-the measues ‘get at’ or actually measure what you are actually studying

18
Q

accuracy

A
  • degree to which measurement represents what it is intended to represent
  • important influence on validity
19
Q

sensitivity

A
  • ability of a test to correctly identify those WITH the disease
  • proportion of subjects with the diease who have a positive test
20
Q

sensitivity equation

A

=TP/ (TP+FN)

21
Q

specificity

A
  • ability of a test to correctly identify those WITHOUT the disease
  • proportion of subjects without the disease who have a negative test
22
Q

specificy equation

A

=TN/ (TN+FP)

23
Q

overall accuracy

A

-ability of a test to predict the presence or absence of a disease

24
Q

PV+

A

-proportion of people with a positive test result who have the disease (relates to sensitivity)

25
Q

PV-

A

-proportion of people with a negative test result who do not have the disease (relates to specificity)

26
Q

likelihood ratios

A

-2 additional measures of appraising screening and diagnostic evidence
>LR+
>LR=
-less sensitive to variations in base rate than specificity and sensitivity

27
Q

base rate

A

-percentage of people in a sample with the health-related state or event of interest

28
Q

LR+

A

=sensitivity/(1-specificity)

-level of convidence that a person who obtains a score in the affected range truly DOES have the health problem

29
Q

LR-

A

=(1-specificity)/sensitivity

-confidence that a score in the unaffected range comes from a person who truly DOES NOT have a health problem

30
Q

prognosis

A

-prediction of the course of the disease based on anticipation from the natural hisotry of the disease

31
Q

prognostic indicators

A

-tell the doctor the likely behaviour of the cancer and its responsiveness to treatment

32
Q

measures of prognosis

A
  • case fatality rate

- survival rate

33
Q

case fatality rate

A

-proportion of newly diagnosed cases that die from a given disease in a specified period

34
Q

survival rate

A

-proportion of persons surviving, regardless of cause of death

35
Q

Cox proportional hazards regression model

A

-useful for analyzing survival data
-indicates probability that a person will experience an event
-estimate relative risk, adjusted for potential prognositc factors
>minimizes threat of confounding

36
Q

lead time

A

-difference in time between the date of diagnosis with screening and date of diagnosis without screening

37
Q

lead time bias

A
  • when lead time is counted in the survival time of patients

- gives a misleading picture of the benefit of treatment

38
Q

selection bias

A
  • choosing data that distorts the outcome of a test

- may make a test look better or worse than it really is, in terms of survival

39
Q

over-diagnosis bias

A
  • when screening identifies an illness that would not have shown clinical signs before a person’s death from other causes
  • makes screening efforts look good because of increased identifications of abnormalities
  • individual may undergo unnecessary treatment with its accompanying risk
40
Q

avoiding bias

A
  • randomized controlled trial= GOLD standard

- different prognositc factors are balanced between groups and “true” screening or treatment effect can be determined

41
Q

outcome research

A
  • a relatively new field that seeks to understand the end results of clinical practices and interventions
  • combines info about the care people are getting
  • important in developing better ways to monitor and improve clinical care
42
Q

clinical epidemiology conclusion

A
  • involves application of epidemiologic methods to improve quality and value of patient care
  • involves assessment of the efficacy of screening, diagnosis and treatment strategies in clinical settings

Spring 2022 (54 decks)

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