The positive LR represents the odds ratio that a positive test result will be observed in an infected population compared to the odds that the same result will be observed among a noninfected population. The negative LR represents the odds ratio that a negative test result will be observed in an infected population compared to the odds that the same result will be observed among a noninfected population.
The terms &quot;odds of disease&quot; and &quot;probability of disease&quot; get thrown around a lot like they’re the same thing, but they’re not. Let’s consider a group of 10 patients, 3 of whom have strep and 7 of whom don’t. If we randomly choose a patient, the probability that they will have strep is 3/10 or 0.3 or 30%. On the other hand, the odds of having strep in this group are 3 : 7. for an odds of a : b, probability = a / (a + b) for a probability of x%, the odds are x : (100-x) Thus, if the odds are 4:9, the probability is 4 / (4+9) = 4/13 = 0.31 (or 31%). Similarly, if the probability is 15%, then the odds are 15 : (100-15) = 15 : 85. With a little practice, you can easily convert from probability to odds and back again in your head.
The post-test probability can be used to determine whether or not clinical certainty is sufficient to go ahead and treat the patient (disease is ruled in), or if additional testing is needed (disease is neither ruled in nor out), or if no further testing is needed and no treatment is required (disease is ruled out). Mrs. B’s diagnosis may be sufficiently certain (high enough post-test probability) to treat her for pulmonary embolism. However, Mr. A will need additional testing to confirm his diagnosis (e.g. D-dimer testing, lower extremity ultrasound or pulmonary angiogram or helical CT).
Transcript of "Evidence-based diagnosis"
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Evidence Based Diagnosis
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When a Patient Has a Problem <ul><li>The doctor reaches a diagnosis by: </li></ul><ul><ul><ul><ul><ul><li>Clinical data </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Diagnostic tools </li></ul></ul></ul></ul></ul>
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Increasing use of Diagnostic tests: - Availability. - The urge to make use of new technology.
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The evaluation of diagnostic techniques is less advanced than that of treatments ( NO phase I, II, III, IV). New Diagnostic tests
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Relevance <ul><li>First, the test should be one that is feasible for you in your community </li></ul><ul><li>Example: brain biopsy is an accurate test for diagnosing dementia, it’s not practical for my (living) patients! </li></ul><ul><li>Can I apply the test to my patients? (Availability, Cost) e.g MRI </li></ul>
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Validity <ul><li>The degree to which the results of a study are likely to be true and free from bias. </li></ul><ul><li>It should be compared to a gold reference standard </li></ul>
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Caution <ul><li>reference standard used should be acceptable (e.g HSG vs DL) </li></ul><ul><li>Both reference standard and test should be applied to all patients </li></ul>
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Independent <ul><li>the decision to perform the reference standard should ideally be independent of the results of the test being studied. </li></ul>
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Ask yourself <ul><li>the patient sample should include an appropriate spectrum of patients to whom the diagnostic test will be applied in clinical practice </li></ul>
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Rule of Thumb <ul><li>at least 100 participants to ensure an appropriate "spectrum" of disease </li></ul>
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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]
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sensitivity <ul><li>probability of a positive test among patients with disease </li></ul><ul><li>i.e Ability to diagnose </li></ul>
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specificity <ul><li>probability of a negative test among patients without disease </li></ul><ul><li>i.e Ability to exclude </li></ul>
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2 X 2 Table b (false positive) a (true positive) d (true negative) c (false negative)
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Keep in Mind <ul><li>sensitivity and specificity by themselves are only useful when either is very high (over typically, 95% or higher). </li></ul>
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Who wants what ? main interest Methodologist sensitivity specificity Doctor accuracy Patient Probability
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Likelihood Ratio <ul><li>The "positive likelihood ratio" (LR+) tells us how much to increase the probability of disease if the test is positive </li></ul><ul><li>The "negative likelihood ratio" (LR-) tells us how much to decrease it if the test is negative </li></ul>
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Likelihood Ratio <ul><li>LR+= </li></ul><ul><li>probability of a +ve test in those who have the disease___ probability of a +ve test in those who do not have the disease </li></ul><ul><li>= sensitivity 1-specificity </li></ul><ul><li>LR-= </li></ul><ul><li>probability of a -ve test in those who have the disease___ probability of a -ve test in those who do not have the disease </li></ul><ul><li>= 1-sensitivity specificity </li></ul>
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Interpretation LR Large and often conclusive increase in the likelihood of disease > 10 Moderate increase in the likelihood of disease 5 - 10 Small increase in the likelihood of disease 2 - 5 Minimal increase in the likelihood of disease 1 - 2 No change in the likelihood of disease 1 Minimal decrease in the likelihood of disease 0.5 - 1.0 Small decrease in the likelihood of disease 0.2 - 0.5 Moderate decrease in the likelihood of disease 0.1 - 0.2 Large and often conclusive decrease in the likelihood of disease < 0.1
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Why LR <ul><li>The LR+ corresponds to the clinical concept of "ruling-in disease" </li></ul><ul><li>The LR- corresponds to the clinical concept of "ruling-out disease“ </li></ul>
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Patient oriented !!!!!!! <ul><li>Your 45 year old patient has a mammogram. The study is interpreted as "suspicious for malignancy" by your radiologist. </li></ul><ul><li>Your patient asks you: "Does this mean I have cancer?", and you (correctly) answer "No, we have to do further testing." </li></ul>
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<ul><li>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?". </li></ul>
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Is it Easy!!! <ul><li>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% </li></ul>
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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
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Disease ruled IN Disease ruled OUT Disease not ruled in or out Determined by: Complications of untreated disease Risks of therapy Complications of tests Cost Above this point, treat Below this point, no further testing
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ROC curve is simply a graph of sensitivity vs (1-specificity)
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specificity specificity sensitivity sensitivity BW Mol: Meta-analysis of diagnostic test studies. TFO 8; 60-65, 2004 Serum progesterone in diagnosing ectopic pregnancy.
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Score Systematic Collaboration of Ovarian Reserve Evaluation <ul><li>systematic reviews of Diagnostic tests </li></ul>
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