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FDN3 By Nathan and Minnie > MDM > Flashcards

MDM Flashcards

1
Q

Why do we perform diagnostic tests?

A

Reduce uncertainty about the true condition of the patient

  • Distinguish between disease and no disease
  • Provide prognostic information
  • Determine response to therapy
  • Provide reassurance
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2
Q

What is an index test?

Why is it used?

A

The test that we are studying

Always want easier and cheaper tests that give same info as gold standard

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3
Q

What is a gold standard test?

A

A test generally accepted to be definitive in diagnosis of disease, reference test

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4
Q

Which tests do participants in a diagnosis study receive?

A

Every patients gets both index test and gold standard test

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5
Q

Why is diagnostic dilemma a criteria for performing a test?

A

A test is most helpful when it helps reduce uncertainty

Performing a test in a patient whose diagnosis is known is not helpful

Tests are most helpful when they distinguish between 2+ likely diagnoses

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6
Q

What is spectrum bias?

A

Performance of diagnostic test varies because the people tested are not part of a clinically relevant population

Occurs if a study population does not represent a true diagnostic dilemma

Affects external validity

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7
Q

Draw a 2x2 table for a diagnostic study

A
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8
Q

What is sensitivity?

How do you calculate sensitivity?

A

Given the presence of disease, the probability that a test will be positive

Sensitivity = TP / (TP+FN)

(use left column)

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9
Q

What is specificity?

How do you calculate specificity?

A

Given the absence of disease, the probability that a test will be negative

Specificity = TN / (FP+TN)

(use right column)

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10
Q

What is the formula for sensitivity?

A

Sensitivity = TP / (TP+FN)

Use left column

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11
Q

What is the formula for specificity?

A

Specificity = TN / (FP+TN)

Use right column

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12
Q

Is sensitivity used to rule in or out?

A

SNOUT - sensitivity, rule out

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13
Q

Is specificity used to rule in or out?

A

SPIN - specificity, rule in

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14
Q

Is sensitivity more useful for screening or confirming a diagnosis?

A

Sensitivity is useful for screening

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15
Q

Is specificity more useful for screening or confirming a diagnosis?

A

Specificity is useful for confirming a diagnosis

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16
Q

Increased sensitivity is related to [direction, sign] predictive value

A

Increased sensitivity is related to increased negative predictive value

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17
Q

Increased specificity is related to [direction, sign] predictive value

A

Increased specificity is related to increased positive predictive value

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18
Q

Describe the important points about sensitivity

A

Given the presence of disease, the probability that a test will be positive

Minimize false negatives

SNOUT - sensitivity, rule out

Most useful when test is negative

Increased negative predictive value

Screening

Sensitivity = TP / (TP+FN)

(use left column)

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19
Q

Describe the important points about specificity

A

Given the absence of disease, the probability that a test will be negative

Minimize false positives

SPIN - specificity, rule in

Most useful when test is positive

Increased positive predictive valuie

Confirming a diagnosis

Specificity = TN / (FP+TN)

(use right column)

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20
Q

What is the likelihood ratio?

What advantages does it have over sensitivity and specificity?

What is it used to calculate?

What is the formula for likelihood ratio?

A

Another way to describe the performance of a test

Can be used across a spectrum of test

Used to calculate post-test probability of a disease

LR = P(result in diseased person) / P(result in non-diseased person)

= true rate / false rate

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21
Q

What is the formula for positive likelihood ratio?

A

LR+ = P(positive result in diseased person) / P( positive result in non-diseased person)

= true positive rate / false positive rate

= [TP/(TP+FN)] / [FP/(FP+TN)]

= sensitivity / (1 – specificity)

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22
Q

What is the formula for negative likelihood ratio?

A

LR- = P(negative result in diseased person) / P(negative result in non-diseased person)

= false negative rate / true negative rate

= [FN/(TP+FN)] / [TN/(FP+TN)]

= (1 – sensitivity) / specificity

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23
Q

In calculating a likelihood ratio, sensitivity is in the _____ and specificity is in the _____

A

In calculating LR,

  • sensitivity is in the numerator
  • specificity is in the denominator
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24
Q

Negative LR is influenced by ______

A

Sensitivity

(important to rule out disease)

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25
Q

Positive LR is influenced by ______

A

Specificity

(important to rule in diseasea)

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26
Q

What is the best negative LR?

A

0

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27
Q

What is the best positive LR?

A

Infinity

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28
Q

What is a completely unhelpful LR?

A

1

29
Q

What is the relationship between pre-test odds, LR, and post-test odds?

A

Pre-test odds x LR = Post-test Odds

30
Q

How can you convert probability into odds?

A

Odds = probability / (1 – probability)

31
Q

How can you convert odds into probability?

A

Probability = odds / (1 + odds)

32
Q

What is a receiver operating curve?

A

Visual representation of the relationship between sensitivity and specificity

Slope = positive LR

X-axis: false positive rate = 1 – specificity

Y-axis: true positive rate: sensitivity

33
Q

What do you look at to see if a test is a good test on an ROC?

A

Area under the curve

(the higher the AUC, the better the test)

34
Q

What is a useless test on a receiver operating curve?

A

Area under curve = 0.5

35
Q

What is a perfect test on a receiver operating curve?

A

Area under curve = 1

36
Q

What is the X-axis on a receiver operating curve?

A

False positive rate = 1 – specificity

37
Q

What is the Y-axis on a receiver operating curve?

A

True positive rate = sensitivity

38
Q

What are three important uses of the receiver operating curve?

A
  • Comparing the performance of two or more tests
  • Determining the best cutoff value of a test to determine disease versus no disease
  • Understanding how good a test is overall (area under the curve)
39
Q

What is prevalence?

What is the formula for prevalence?

A

Proportion of individuals in a population who have a given clinical characteristic at a given point in time

At time point X: Prevalence = cases of disease / entire population

40
Q

What is incidence?

What is the formula for incidence?

A

The number of new cases of disease that accumulate during a specified time period divided by the number of persons in population at risk

From time period A to B: Incidence = new cases of disease / population without disease at time A

41
Q

What is post-test probability?

A

Given a certain test result, what is the probability of disease?

42
Q

What is the formula for positive post-test probability?

A

Positive post-test probability = TP / (TP+FP)

(use top row)

43
Q

What is the formula for negative post-test probability?

A

Negative post-test probability = FN / (TN+FN)

(use bottom row)

44
Q

What is positive post-test probability?

A

If patient has a positive test result, the probability a disease is present

Positive post-test probability = TP / (TP+FP)

45
Q

What is positive predictive value?

A

If test result is positive, the chances the patient has the disease

Positive predictive value = TP / (TP+FP)

46
Q

What is the relationship between positive predictive value and positive post-test probability?

A

Positive predictive value = positive post-test probability = TP / (TP+FP)

(use top row)

47
Q

What is negative post-test probability?

A

If patient has a negative test result, the probability the disease is still present but the test missed it

Negative post-test probability = FN / (TN+FN)

48
Q

What is negative predictive value?

A

If the test result is negative, the chance the patient does not have disease

Negative predictive value = TN / (TN+FN)

49
Q

What is the relationship between negative post-test probability and negative predictive value?

A

Negative post-test probability = 1 – negative predictive value

(use bottom row)

50
Q

Differentiate sensitivity/specificity from predictive value

A
  • Sensitivity and specificity are characteristics of the test itself
  • Predictive value tells us how the test will perform in the population
51
Q

Draw a 2x2 table with formulas for positive and negative likelihood ratio

A
52
Q

Draw a 2x2 table with formulas for positive and negative predictive value and positive and negative post-test probability

A
53
Q

If prevalence increases, what happens to positive and negative predictive value?

A

If prevalence (pre-test probability) increases:

Positiive predictive value increases

Negative predictive value decreases

54
Q

What types of bias can be present in a diagnostic study?

A
  • Spectrum bias (affecting external validity)
  • Selection bias (test referral bias, in which haveing a positive test makes it more likely that a subject also gets the gold standard test)
  • Measurement bias (non-blinding, inaccurate measurements, inaccurate gold standard)
55
Q

When would you want a more sensitive test?

A

When you cannot miss anyone with the disease

  • Dangerous, treatable illness
  • Screening
  • Early in workup when several diagnoses are being considered
56
Q

When would you want a more specific test?

A

When you do not want to falsely label someone

  • Late in diagnostic workup
  • When false positives can harm patient (label is harmful, treatment is risky)
57
Q

How do you convert pre-test probability to post-test probability?

A
  1. Pre-test probability to pre-test odds using odds = probability / (1 – probability)
  2. Pre-test odds to post-test odds using pre-test odds x LR = post-test odds
  3. Post-test odds to post-test probability using probability = odds / (1 + odds)
58
Q

What three things do you need to calculate post-test probability?

A
  • Sensitivity of the test
  • Specificity of the test
  • Pre-test probability (prevalence) of disease
59
Q

What is serial testing?

When is it used?

A

Do tests in sequence

Only do next test if first one is positive, so all tests done must be positive to label w/ diagnosis

  • Rapid assessment not needed
  • Tests are expensive or risky
  • Want to maximize specificity
60
Q

When is serial testing used?

A
  • Rapid assessment not needed
  • Tests are expensive or risky
  • Want to maximize specificity
61
Q

What occurs with each subsequent positive result in a serial testing strategy?

A

False positives decrease

Specificity increases

62
Q

What is parallel testing?

When is it used?

A

Do all tests at the same time

Need only one positive to label w/ diagnosis

  • Rapid assessment necessary
  • Patient cannot return easily
  • Costs of tests relatively low
  • Want to maximizine sensitivity
63
Q

When is parallel testing used?

A
  • Rapid assessment necessary
  • Patient cannot return easily
  • Costs of tests relatively low
  • Want to maximizine sensitivity
64
Q

What occurs if all tests are negative in a parallel testing strategy?

A

False negatives decrease

Sensitivity increases

65
Q

When is sensitivity prioritized in diagnostic testing?

A

When you cannot miss a diagnosis

  • Screening
  • Early in the work up
  • Terrible but treatable diseases (TB, syphillis, etc)
66
Q

When are sensitive tests most useful?

A

When they are negative

(rule out the disease in question)

67
Q

When is specificity prioritized in diagnostic testing?

A

When you need a very accurate diagnosis

  • Treatment is very morbid (e.g. chemo)
  • Label can be harmful (e.g. HIV)
  • Later in the work up
68
Q

When are specific tests most useful?

A

When they are positive and rule in the disease in question

69
Q

Say you use a serial testing strategy with three tests. How can you easily calculate the post-test odds?

A

Pre-test odds x LR1 x LR2 x LR3 = Post-test odds

FDN3 By Nathan and Minnie (14 decks)

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