Given the example of breast cancer screening in the Lecture note 1, compute the

Question

Given the example of breast cancer screening in the Lecture note 1, compute the positive predictive value (PPV) and negative predictive value (NPV) if we assume that the prevalence of breast cancer in female is 0.01. (hint: use Bayes? Rule) Sensitivity, Specificity and Screening Tests Consider the following example of a diagnostic test: Breast Diagnostic Test Cancer Positive Negative Total Yes 0.82 0.01 0.18 0.99 Pr(TestDiseas+) Pr(Disease+) Pr(Test| Disease+) Pr(Disease+) +Pr(Test+ Disease-) Pr(Disease-) Pr(Test | Disease-) Pr(Disease-) Pr(Test- | Disease+) Pr(Disease+) Pr(Test Disease-) Pr(Disease-) NPV = In our example .82(1)/(82(1) +01(.9))=0.63 .99(.9)/(.99(.9) .18(1))=0.98 PPV = NPV

Explanation / Answer

PPV=100*0.82/(0.82+0.18)=82%

NPV=100*0.99/(0.99+0.01)=99%

after usingin bayes rules the

PPV=82*0.01=0.82% and

NPV=99*0.99=98.01%

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