Unit 1.3

Question 1

What is the purported truth of a test? Is that all to the story?

Answer 1

1) Positive means they have it
Negative means the don’t
2) No; actually. . . There’s much more to the story

Question 2

What clinical evidence should you consider when deciding if to test?

Answer 2

-Honing your differential with tests
-Considering the “treatment/ test threshold

Question 3

What is the zone of clinical uncertainty? What do the margins of this zone depend on?

Answer 3

-The area in between where one might consider testing.
-The margins of this zone are dependent upon a few factors:
-How much uncertainty do you need to rectify before you initiate treatment?
-How invasive is the test?
-How serious is the treatment?
-How serious is the illness?

Question 4

What questions should you consider when deciding the testing/ treatment threshold?

Answer 4

-What is the level of-uncertainty based on history and physical alone?
-Are you almost certain that your patient has the disease in question?
-If so, then why bother testing?
-Move on to treatment

Question 5

What questions should you consider when deciding how invasive a test is?

Answer 5

-Is this a matter of a simple blood draw?
-Just hooking up an EKG?
-Or does this require sedation and placement of a scope internally?
-Does it involve contrast dye, or other measures with possible side effects?

Question 6

What questions should you consider when figuring out how serious a treatment is?

Answer 6

-If we begin treatment without a definitive test, what are the possible negative outcomes?
-Are we giving a little ibuprofen OTC?
-Are we initiating lifestyle modifications?
-Or are we initiating life-long immunosuppressants?

Question 7

What is the final thing you should consider when deciding what is beneath the treatment threshold? Give an example

Answer 7

The severity of the disease
Ex: How low would you make the testing threshold for ruling out MI vs bacterial sinus infection.
In plain terms, you will likely hesitate less when testing for something severe

Question 8

What are the factors of the treatment/ testing threshold?

Answer 8

1) What is the level of uncertainty based on history and physical alone?
2) Hone your differential with tests
3) How invasive is this test?
4) How serious is the treatment?
5) Severity of the disease

Question 9

If you’ve determined you’re above the testing threshold, what’s the next step?

Answer 9

We must next consider whether the test we are performing has the ABILITY to rule disease in or out!

Question 10

How do you determine the efficacy of a test? (5 things)

Answer 10

1) Does the test accurately identify whether a patient has a disease?
2) The gold standard test
3) Sensitivity and Specificity
4) Positive and negative predictive values
5) Prevalence of disease

Question 11

1) What question should you ask when evaluating test validity? What does this involve?
2) After that question is answered, what’s the next question?

Answer 11

1) Does the test accurately identify whether a patient has a disease?
2) This involves comparing the test against a gold standard.
-The question becomes, how does the test in perform against our best means of establishing true diagnosis

Question 12

Define gold standard test and give an example

Answer 12

The gold standard test is the modality that best demonstrates accuracy (ex: the full psychiatric eval in pt screened for depression)

Question 13

What is the significance of the gold standard? What should you compare it to?

Answer 13

-Let the gold standard represent whether the patient has or does not have the disease.
-Consider how the test we are scrutinizing does against this

Question 14

What does sensitivity of a test mean? What is the formula?

Answer 14

1) The probability that a person with a disease tests positively; aka true positives
2) A/(A+C)
True positives divided by all the folks with the disease

Question 15

What does specificity of a test mean? What is the formula?

Answer 15

1) Does a person without the dz test negative?
2) D/(D+B)
True negative divided by all the folks without the disease

Question 16

1) Do very sensitive tests rule diseases in, or out?
2) Why?

Answer 16

1) Out
2) A “sensitive” test has given you a negative result, which means your patient does not have the disease

Question 17

Why does a sensitive test mean a patient doesn’t have the disease it’s testing for?

Answer 17

-The sensitive test is very SENSITIVE; it’s good at going off anytime someone has the disease
-Therefore, if your patient DID have the disease, the test would have been positive!
-It DIDN’T show up positive. So, your patient is cleared!

Question 18

Why not just use highly sensitive tests?

Answer 18

1) Because if they are only sensitive, they’re not good at ruling IN.
2) The test is good at being positive. . . But if it’s not also specific then other things besides the disease you’re looking for can make your test positive

Question 19

1) Do very specific tests rule diseases in, or out?
2) Why?

Answer 19

1) Very specific tests rule IN
2) Your “specific” test has given you a positive result.
This means your patient has this disease.

Question 20

Why does a specific test mean a patient has the disease it’s testing for?

Answer 20

-These tests are good at being negative.
-So, if your patient was disease free, the test would have been negative.
-It wasn’t negative. So, your patient probably has the disease.

Question 21

1) Define predictive value
2) Define positive predictive value
3) Define negative

Answer 21

1) Predictive value, in a phrase, determines the percent of the time that a test is “right”
2) Positive predicative value looks at probability that person with + test has the disease
3) Negative predictive value does the opposite

Question 22

Define positive predictive value in mathematical terms

Answer 22

-PPV = A/(A+B)
-The true positives divided by all the positive tests
-In other words, “How many of these positive tests were right”

Question 23

Define negative predictive value in mathematical terms

Answer 23

-NPV = D/(D+C)
-True negatives divided by all the negative tests.
-“How many of these negative tests were right?”

Question 24

What is the catch when it comes to prevalence?

Answer 24

-Seems like a good way of evaluating tests, but there is a skew in the data.

Question 25

When prevalence is LOW there are a great many FALSE _________ TESTS

Answer 25

POSITIVE

Question 26

When there are a bunch of false positive tests, what does this mean about prevalence?

Answer 26

Prevalence is low

Question 27

What is the cost if there’s a lot of false positives?

Answer 27

-The cost that society pays for this is very high
-Often, these false positives are followed by confirmation testing with gold standard tests which are often invasive, expensive, and potentially harmful. Only to ultimately show that the patient never had the disease in the first place

Question 28

Define likelihood ratios
What do they show us?
What do they represent?

Answer 28

1) Defined as probability of obtaining a positive test result in diseased patient divided by probability of obtaining positive test in non-diseased patient
2) What it shows us is how much test results change the pre-test probability (the prevalence) and post-test probability
3) Likelihood ratios represent a change in the odds before and after a test!

Question 29

1) What is the likelihood ratio of a positive test?
2) How could this also be written?

Answer 29

1) Probability of getting a positive test in a diseased person divided by the probability of getting a positive test in a non-diseased person
2) This is just the sensitivity / (1-specificity)

Question 30

What is the positive test likelihood ratio in words?

Answer 30

Folks who have it and test positive
___________________________
Folks who don’t have it and test positive

Question 31

What does a positive test ratio indicate?

Answer 31

A ratio well above 1 indicates that a positive test is likely to come from a true positive; we have confidence in such a test

Question 32

What is the likelihood ratio of a negative test? How could this also be written?

Answer 32

Negative likelihood ratio (for negative tests):
False negative rate / true negative rate
(1-sensitivity)/specificity

Question 33

What is the negative test likelihood ratio in words?

Answer 33

Folks who have it and test negative
____________________________
Folks who don’t have it and test negative

Question 34

What does a negative test ratio indicate?

Answer 34

A ratio much less than 1 indicates that the negative tests are from folks without disease, which increases our confidence

Question 35

Why are likelihood ratios important?

Answer 35

This is important because we are asking, “How will the likelihood of my patient having the disease change after performing this test

Question 36

What should you use to interpret your test?

Answer 36

Fagan nomogram to interpret your test

Question 37

Describe the fagan nomogram

Answer 37

-Take pretest probability (again, this is the prevalence)
-Draw a line through the likelihood ratio (this you would calculate for a positive/negative result)
-Positive = sensitivity/(1-specificity)
-Negative = (1-sensitivity)/specificity

Question 38

Give an example of a fagan nomogram

Answer 38

-Take patient with prevalence of dz of 1%
+ likelihood = 10
- likelihood = 0.1
-If you have a likelihood ratio above 10 or less than 0.1, you have a test that makes a difference in your practice
–Before her test, likelihood was 1%
–After a positive result, it was 10%
–Before her test, likelihood was 1%
–After a negative result, it is 0.1%