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Evidence Based Medicine Workshop

Evidence Based Medicine Workshop. Diagnosis March 18, 2010. Objectives - Diagnosis. At today’s end you’ll be able to… consider rationale for diagnosis define and calculate test characteristics state the ideal research design for studying diagnostic tests

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Evidence Based Medicine Workshop

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  1. Evidence Based MedicineWorkshop Diagnosis March 18, 2010

  2. Objectives - Diagnosis • At today’s end you’ll be able to… • consider rationale for diagnosis • define and calculate test characteristics • state the ideal research design for studying diagnostic tests • critically appraise articles about diagnostic testing

  3. Seemingly Dumb Question… • Why make a diagnosis?

  4. Why Diagnose?Heart Failure Therapy / Prognosis

  5. What are advantages and disadvantages of diagnostic testing?

  6. Diagnostic Testing • Advantages • can assess parameters beyond the 5 senses • can be more ‘objective’ than clinical data • Disadvantages • test results can be incorrect • test results may lead you in the wrong direction • tests cost money • tests may confer risk • some diseases have no diagnostic test • tests may add little to what is already known

  7. Issues in Diagnostic Testing • Invasiveness • urine sample versus brain biopsy versus autopsy • Cost • glucoscan strip ~ $1.00 versus MRI $900.00 • Availability • hemogram versus Positive Emission Tomogram • Patient Acceptability • urine sample versus 3 day fecal fat collection

  8. Let’s Back Up…

  9. What type of ‘testing’ is the cheapest, lowest risk, available anywhere, and needs no requisitions?

  10. Clinical Scenario • A 70 year old man • presents to the ED • 1 hr x chest pain & shortness during 10 hr car trip • PMH • prostate cancer • Exam • distressed with splinting respiration (pleuritic cp) • HR 130 / min, RR 32 / min. • What’s your working diagnosis?

  11. Test for Pulmonary Embolism • Gold Standard: pulmonary angiogram • invasive • costly • not readily available • risky • Other tests: • D-dimer, V/Q scans, Spiral CT scan • ? may be helpful in right setting with right results - complex

  12. PE - diagnosis Pulmonary angiogram - gold standard

  13. PE - diagnosis (spiral CT scan)

  14. PE - diagnosis (V/Q scan) • high probability V/Q scan (2 defects)

  15. Pulmonary Thromboembolism

  16. How well does the test perform? • Welcome to the world of TEST CHARACTERISTICS

  17. Take a deep breath...

  18. Test Characteristics • Sensitivity • Specificity • Positive predictive value • Negative predictive value • Accuracy • Likelihood ratio

  19. Cross-sectional survey: measure disease status & test status at same time point. Individual A Individual B Inidividual C Inidividual D D+ & T+ D+ & T- D- & T+ D- & T-

  20. Hypothetical Test Results

  21. SensitivityProbability that test is positive given that disease is present. 80 / (80 + 10) = 88.9%

  22. Specificity Probability that test is negative given that disease is absent. 90 / (90 + 20) = 81.8%

  23. Sensitivity / Specificity Trade-off Sensitivity Decreases Specificity Increases

  24. Test Characteristic Issues • Highly Sensitive Tests: • tend to be less invasive, less risky, less costly • best for screening programs • best for ruling out disease: “SNOUT” • Highly Specific Tests: • tend to be more invasive, more risky, more costly • best for confirming (ruling in) disease: “SPIN”

  25. Positive Predictive ValueProbability that disease is present given that the test was positive. 80 / (80 + 20) = 80.0%

  26. Negative Predictive ValueProbability that disease is absent given that the test was negative. 90 / (90 + 10) = 90.0%

  27. Issue Sensitivity / Specificity versus Positive / Negative Predictive Values

  28. Change Disease Prevalence from 90 to 110 per 200 prevalence = 110 / 200 = 0.55 = 55% (was 45%) sensitivity = 97.7 / 110 = 88.8% (unchanged) specificity = 73.6 / 90 = 81.7% (unchanged) positive predictive value = 86.5% (was 80%) negative predictive value = 85.8% (was 90%)

  29. Accuracy (80+90) / (80+ 20 + 10 + 90) = 85.0%

  30. Positive (test) Likelihood Ratio • Ratio of: probability of positive test when disease is present -------------------------------------------------------------------- probability of positive test when disease is absent

  31. Positive Likelihood Ratio (80 / 90) / (20 / 110) = 4.89

  32. Pretest odds x Likelihood Ratio = Posttest odds Utility of LR Palpable 5.6 Screen 2.2

  33. Critical Appraisal of an Article about Diagnosis Validity Results Applicability

  34. Validity • Primary Guides • Was there an independent, blind comparison with a reference standard? • Did the patient sample include an appropriate spectrum of patients to whom the diagnostic test will be applied in clinical practice? • Secondary Guides • Did the results of the test being evaluated influence the decision to perform the reference standard? • Were the methods for performing the test described in sufficient detail to permit replication?

  35. Results • Are likelihood ratios for the test results presented or data necessary for their calculation provided? LRs >10  generate large changes from pre- to post-test probability; LRs 5-10  generate moderate changes in pre- to post-test probability; LRs 2-5  generate small (but sometimes important) changes in probability; LRs 1-2  alter probability to a small (and rarely important) degree.

  36. Applicability • Will the reproducibility of the test result and its interpretation be satisfactory in my setting? • Are the results applicable to my patient? • Will the results change my management? • Will patients be better off as a result of the test?

  37. Sensitivity: 670 / 744 = 0.90 or 90% Specificity: 640 / 842 = 0.76 or 76% PPV: 670 / 872 = 0.77 or 77% NPV: 640 / 714 = 0.90 or 90% Accuracy: (670 + 640) / 1586 = 0.83 or 83% Positive Likelihood Ratio (670 / 744) / (202 / 842) = 3.75

  38. Let’s Design a Study…

  39. End of the Line…

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