Notes
Slide Show
Outline
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Step 3:
  • Critically Appraising
    the Evidence:
  • Statistics for Diagnosis
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Table of Contents
  • Clinical Statistics Calculator (Excel)
  • Statistics for:
    • Diagnosis
      • Sensitivity (Sn)
      • Specificity (Sp)
      • Likelihood Ratios (LR)
      • Pre-test Probabilities/Prevalence
      • Post-Test Probabilities/Predictive Values
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Making It Easier
  • If available, find the best evidence in secondary sources where analysis has already occurred.
  • If not pre-assessed, use critical appraisal worksheets to help you through the process.
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Importance of Critically
Appraising the Evidence
  • Understanding the Limitations of the Author’s Analyses and Interpretations of the Data
  • Assessing Internal Validity
  • Assessing External Validity
  • Identifying Potential Confounding Variables
    • Simpson’s Paradox
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Critical Appraisal Basics
  • View movie as:
    • QuickTime (.mov)
    • Flash (.swf)






  • Double-click on video for full-screen mode.
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Generalized 2x2 Clinical Table
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Sensitivity and Specificity
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Diagnostic Table
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Sensitivity
  • Answers the question:  When the target disorder was present, what fraction of the time did the diagnostic test produce positive results?
    • Excludes all trials where the diagnostic test produced negative results
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Try it Yourself:
Calculating Sensitivity 1
  • Step 1:
  • How many times was the target disorder actually present?
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Calculating Sensitivity 2
  • How many of these times did the diagnostic test produce positive results?
    • Note:  We do not count the number of times the diagnostic test produced positive results when the target disorder was absent (b). We are only interested in the cases where target disorder was present .
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Try it Yourself:
Calculating Sensitivity 2
  • Step 2:
  • How many of these times did the diagnostic test produce positive results?:
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Try it Yourself:
Calculating Sensitivity 3
  • Step 3:
  • So what fraction of the total number of times the target disorder was present did the diagnostic test produced positive results?:
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Specificity
  • Answers the question:  When the target disorder was not present, what fraction of the time did the diagnostic test produce negative results?
    • Excludes all trials where the diagnostic test produced positive results
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Calculating Specificity 1
  • How many times was the target disorder absent?:  b+d
  • How many of these times did the diagnostic test produce negative results?:  d
    • Note:  We do not count the number of times the diagnostic test produced negative results when the target disorder was present (c). We are only interested in the cases where the target disorder was absent.
  • So what fraction of the total number of times the target disorder was absent did the diagnostic test produced negative results?:  b/(b+d)
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Helpful Acronyms
  • Specificity – SpPin (spin)
    • When a test has a high Specificity, a Positive test rules in the diagnosis.

  • Sensitivity – SnNout (snout)
    • When a test has a high Sensitivity, a Negative test rules out the diagnosis.
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Another Way of Looking at It
  • Specificity
    • 1 - α
    • Probability of  not getting a Type I Error/α Error/False Positive
  • Sensitivity
    • 1 - Β
    • Probability of  not getting a Type II Error/Β Error/False Negative
    • Also know as the statistical power of the test
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Sensitivity/Specificity Example
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Likelihood Ratios
  • Likelihood Ratio for a Positive Result (LR+)
    • The number of patients testing positive for the target disorder who have the disease for every patient testing positive that does not have it
  • Likelihood Ratio for a Negative Result (LR-)
    • The number of patients testing negative for the target disorder who have the disease for every patient testing negative that does not have it
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Calculating Likelihood Ratios

  • Likelihood Ratio for a Positive Result (LR+)
    • sensitivity/(1-specificity)


  • Likelihood Ratio for a Negative Result (LR-)
    • (1-sensitivity)/specificity
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Likelihood Ratios Video
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    • Flash (.swf)






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How to use Likelihood Ratios
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Likelihood Ratio Example
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Prevalence and Probability
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Prevalence
  • Fraction of the population at risk at a given time who have the target disease
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Pre-Test Probability
  • Probability that a patient has the target disease without knowing the results of a diagnostic test
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Calculating Prevalence
  • (a+c)/(a+b+c+d)


  • The number of those with the disease divided by the total number of people
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Post-Test Probabilities
  • Positive Predictive Value
    • Probability that a patient with a positive diagnostic test actually has the disease
  • Negative Predictive Value
    • Probability that a patient with a negative diagnostic test actually does not have the disease
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Calculating Predictive Values

  • Positive Predictive Values (+PV)
    •  a/(a+b)


  • Negative Predictive Values (-PV)
    • c/(c+d)
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Predictive Values
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Try it on your own.
  • Critical Appraisal Practice Exercises
    • From CEBM
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Links to Other Websites
and Hands-On Activities
  • EBM Glossary
    • From CEBM
  • Critical Appraisal Practice Exercises
    • From CEBM
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Congratulations!
You have successfully completed Step 3.
The End