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).
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]
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-=
probability of a -ve test in those who have the disease___ probability of a -ve test in those who do not have the disease
= 1-sensitivity specificity
20.
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
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?".
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%
26.
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.
30.
Score Systematic Collaboration of Ovarian Reserve Evaluation
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