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21 Cards in this Set

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  • Back

What is Pre-test Probability?

1. The probability of the target condition being present before the results of a diagnostic test are known.

What are Pre-test Odds?

1. Odds that the patient has the target disorder before a diagnostic test is carried out.

What is Post-test Probability?

1. Probability of the target condition being present after the results of a diagnostic test are known.

What are post-test Odds? How is it calculated?

1. Odds that the patient has the target disorder after the test is carried out.




Post-test odds= (Pre-test Odds X Likelihood Ratio)

What is the difference between probability and odds? Explain.

1. Prob= Count(x)/TotalCount
*The Ratio of Observed over total options


2. Odds= Count(x)/(Total Count - count(x))
*Ratio of Success to failure

1. Prob= Count(x)/TotalCount


*The Ratio of Observed over total options




2. Odds= Count(x)/(Total Count - count(x))


*Ratio of Success to failure

What are the conversions between odds and probability?

1. Odds=Pr/(1-Pr)


2. Pr= Odds/(1+Odds)

What is sensitivity?

1. The proportion of people who truly have a designated disorder who are so identified by the test.


2. Sensitivity tests have few false negatives




*SnOUT= Test with high sensitivity is Negative, rule out the diagnosis.

What is specificity?

1. The proportion of people who are truly free of a designated disorder who are so identified by a test.


2. Specific Tests have few false positives




*SpIN= WHen a test is highly Specific, a Positive result can rule in the diagnosis.

What is the equation for sensitivity (Sn)?

Sn= True Positives/(True Positives + False Negatives)




# of people correctly caught by the test over that number plus those that should have been caught.

What is the equation for selectivity (Sp)?

Sp= True Negatives/(True Negatives + False Positives)




# of people correctly shown to not have the disease over that number plus those that were shown to have the disease but really didnt.

Use the table to explain Sensitivity and Specificity.

Use the table to explain Sensitivity and Specificity.

1. Sn=a/(a+c)


2. Sp=d/(d+b)

Among women without breast cancer the clinical breast exam correctly identifies 94% as not having breast cancer. What term describes this finding?

1. Specificity




*Always considered with identifying correctly those without the disease

At age 40 approximately 1 in every 800 women will develop breast cancer within one year? What term describes this statement?

1. Incidence




***Always has a time increment

The clinical breast exam is able to correctly detect 54% of all women with breast cancer. What term describes this finding best?

1. Sensitivity




***Always concerned with correctly detecting those with a condition.

What is a Positive Predictive Value? What is the equation?

1. Proportion of people with positive test results who have the disorder.


PPV= a/(a+b)


PPV= True Positives/(True Positives + False Positives)

1. Proportion of people with positive test results who have the disorder.




PPV= a/(a+b)




PPV= True Positives/(True Positives + False Positives)

What is the Negative Predictive Value? What is the equation?

1. The proportion of people with negative test results who are free of the disorder.


NPV= d/(d+c)


NPV= True Negatives/(True Negatives + False Negatives)

1. The proportion of people with negative test results who are free of the disorder.




NPV= d/(d+c)




NPV= True Negatives/(True Negatives + False Negatives)

What is a likelihood ratio and how is it determined?

1. Relative likelihood that a given test result would be expected in a patient with (as opposed to one without) a disorder of interest.

1. Relative likelihood that a given test result would be expected in a patient with (as opposed to one without) a disorder of interest.





Using the table, how are Positive and Negative Likelihood Ratios Determined?

Using the table, how are Positive and Negative Likelihood Ratios Determined?

LR+= True Positive Rate/False Positive Rate


LR-= False Negative Rate/True Negative Rate

LR+= True Positive Rate/False Positive Rate




LR-= False Negative Rate/True Negative Rate

What are the significant numbers for a likelihood ratio to affect the probability of disease?

1. LR>10= Disease More Likely (3-10)


2. LR<0.10= Disease is Less Likely (0.3-0.1)




*LR=1 is no effect on likelihood

Memorize this Table