Evidence based diagnosis
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Evidence based medicine is now focusing on diagnostic tests: how accurate and useful could be ? sensitivity and specificity are no longer the important criteria for a test

Evidence based medicine is now focusing on diagnostic tests: how accurate and useful could be ? sensitivity and specificity are no longer the important criteria for a test

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Evidence based diagnosis Presentation Transcript

  • 1. Evidence Based Diagnosis
  • 2. When a Patient Has a Problem The doctor reaches a diagnosis by: • Clinical data • Diagnostic tools
  • 3. Increasing use of Diagnostic tests: - Availability. - The urge to make use of new technology.
  • 4. The evaluation of diagnostic techniques is less advanced than that of treatments (NO phase I, II, III, IV). New Diagnostic tests
  • 5. Relevance • First, the test should be one that is feasible for you in your community • Example: brain biopsy is an accurate test for diagnosing dementia, it’s not practical for my (living) patients! • Can I apply the test to my patients? (Availability, Cost) e.g MRI
  • 6. Validity The degree to which the results of a study are likely to be true and free from bias. • It should be compared to a gold reference standard
  • 7. Caution • reference standard used should be acceptable (e.g HSG vs DL) • Both reference standard and test should be applied to all patients
  • 8. Independent • the decision to perform the reference standard should ideally be independent of the results of the test being studied.
  • 9. Ask yourself • the patient sample should include an appropriate spectrum of patients to whom the diagnostic test will be applied in clinical practice
  • 10. Rule of Thumb • at least 100 participants to ensure an appropriate "spectrum" of disease
  • 11. 2 x 2 table comparing the results of a diagnostic test with a reference standard reference standard disease no disease test abnormal true pos. [a] false pos. [b] test normal false neg. [c] true neg. [d]
  • 12. sensitivity • probability of a positive test among patients with disease • i.e Ability to diagnose
  • 13. specificity • probability of a negative test among patients without disease • i.e Ability to exclude
  • 14. 2 X 2 Table b (false positive) a (true positive) d (true negative) c (false negative)
  • 15. Keep in Mind • sensitivity and specificity by themselves are only useful when either is very high (over typically, 95% or higher).
  • 16. 1000 individual 10% disease prevalenceS E N S I T I V I T Y S P E C I F I C I T Y +VE PREDICTIVE VALUE -VE PREDICTIVE VALUE = a/a+c 90/100 = 90% = d/b+d 720/900 =80% = a/a+b 90/720= 33% = d/c+d 720/730 = 99.6% +ve -ve disease No disease 90 10 180 720 100 900 270 730 a b c d
  • 17. Who wants what ? main interest Methodologist sensitivity specificity Doctor accuracy Patient Probability
  • 18. Likelihood Ratio The "positive likelihood ratio" (LR+) tells us how much to increase the probability of disease if the test is positive The "negative likelihood ratio" (LR-) tells us how much to decrease it if the test is negative
  • 19. Likelihood Ratio LR+= probability of a +ve test in those who have the disease___ probability of a +ve test in those who do not have the disease sensitivity= 1-specificity LR-= ve test in those who have the disease___-probability of a probability of a -ve test in those who do not have the disease sensitivity-1= specificity
  • 20. InterpretationLR Large and often conclusive increase in the likelihood of disease > 10 Moderate increase in the likelihood of disease5 - 10 Small increase in the likelihood of disease2 - 5 Minimal increase in the likelihood of disease1 - 2 No change in the likelihood of disease1 Minimal decrease in the likelihood of disease0.5 - 1.0 Small decrease in the likelihood of disease0.2 - 0.5 Moderate decrease in the likelihood of disease0.1 - 0.2 Large and often conclusive decrease in the likelihood of disease < 0.1
  • 21. Why LR • The LR+ corresponds to the clinical concept of "ruling-in disease" • The LR- corresponds to the clinical concept of "ruling-out disease“
  • 22. Patient oriented !!!!!!! • Your 45 year old patient has a mammogram. The study is interpreted as "suspicious for malignancy" by your radiologist. • Your patient asks you: "Does this mean I have cancer?", and you (correctly) answer "No, we have to do further testing."
  • 23. • Your patient then asks, "OK, I understand that the mammogram isn't the final answer, but given what we know now, what are the chances that I have breast cancer?".
  • 24. Is it Easy!!! • Assume that the overall risk of breast cancer in any 45 year old woman, regardless of mammogram result, is 1%. Assume also that mammography is 90% sensitive and 95% specific. Then, select your answer below: 1% 15% 60% 85% 95%
  • 25. If you know that the risk of breast cancer in any 45 year old woman is 1% and that mammography is 90% sensitive and 95% specific. What do you think your patient’s probability of having breast cancer is? LR+=Sens/100-Spec =90/5=18
  • 26. Disease ruled IN Disease ruled OUT Disease not ruled in or out Above this point, treat Below this point, no further testing Determined by: Complications of untreated disease Risks of therapy Complications of tests Cost
  • 27. ROC curve is simply a graph of sensitivity vs (1-specificity)
  • 28. Score Systematic Collaboration of Ovarian Reserve Evaluation systematic reviews of Diagnostic tests
  • 29. THANK YOU