WBR0038

Author	[[PageAuthor::Associate Editor-In-Chief: Gonzalo A. Romero, M.D. [1]]]
Exam Type	ExamType::USMLE Step 1
Main Category	MainCategory::Biostatistics/ Epidemiology
Sub Category	SubCategory::Infectious Disease
Prompt	[[Prompt::A group of investigators developed a new diagnostic test for the detection of the serum marker Z-AWS, a structural component of the infectious organism CG-23. A study is evaluating the performance of the new test among 500 individuals who were followed up for the occurrence of the symptoms. In addition, blood was collected for PCR analysis, the gold standard test for this infectious disease. The infectious organism is detected in 100 individuals by PCR. The pre-test probabilities of the novel test are determined as follows: the sensitivity is 90% and the specificity is 80%. What is the probability that a subject with a positive result in the new diagnostic test actually has the disease?]]
Answer A	AnswerA::90/100
Answer A Explanation	[[AnswerAExp::The sensitivity of a test is the ability of a test to be positive when the subjects actually have the disease. The sensitivity can be calculated as follows: Sensitivity= True positive/(True positive + false negative) In this case, sensitivity=90/(90+10)= 90/100]]
Answer B	AnswerB::320/ 400
Answer B Explanation	[[AnswerBExp::The specificity of a test is the ability of a test to be negative when the subjects do not have the disease. The specificity can be calculated as follows: Specificity= True negative/(True negative+ false positive) In this case, specificity=320/(320+80)= 320/400]]
Answer C	AnswerC::90/170
Answer C Explanation	[[AnswerCExp::The positive predictive value (PPV) , or precision rate, is the proportion of individuals with a positive test result who actually have preclinical disease. It is considered the physician's gold standard, as it reflects the probability that a positive test reflects the underlying condition of interest. The PPV can be calculated as follows: PPV= True positive/(True positive + false negative) In this case, PPV= 90/(90+80)= 90/170]]
Answer D	AnswerD::320 / 330
Answer D Explanation	[[AnswerDExp::The negative predictive value is the proportion of individuals without preclinical disease who test negative using the specified testing modality. The NPV can be calculated as follows: NPV= True negative / (True negative+ false negative)]]
Answer E	AnswerE::90 + 320 / 500
Answer E Explanation	[[AnswerEExp::Accuracy “Trues divided by the sample size” or (TN + TP) / (TP + TN + FP + FN)]]
Right Answer	RightAnswer::C
Explanation	[[Explanation::Test taking strategy tip: It is important to read throughly this question scanning for the data that is vital which will help in answering the question correctly. USMLE Step 1 more often is including long stems, so being able to read quickly, yet carefully will enable the examinee to screen for the information necessary to aswer correctly. This question tests for basic statistical knowledge which is commony tested on STEP 1 and other USMLE examinations. A great tip is to read at the final lines to find what the question is really looking for. Explanation: at the end of the long stem the data is provided directly in a way that will enable construct the table which will orient the test taker to calculate what’s being asked; the Positive Predictive Value. The sample size is 500, it is given the number of people with the disease 100, which is the True Positive + False Negative (TP + FN). Also the sensitivity or the proportion of truly diseased persons is given 90%. From there it can be assumed that the True positives were 90 and False negatives were 10. The remainder 400 did not have the disease. The specificity (proportion of truly non-diseased persons who are identified as non diseased) is also given in the stem which is 80% so it can be established that the True Negatives (TN) is the 80% of this 400 or 320 and the False Positives were 80. The Positive Predictive Value is the probability that a positive test result is actually positive, being TP/(TP + FP) being calculated as 90 / 170. Disease No disease Total Positive test 90 80 170 Negative test 10 320 330 Total 100 400 500 Educational Objective: The positive predictive value (PPV) , or precision rate, is the proportion of individuals with a positive test result who actually have preclinical disease. It is considered the physician's gold standard, as it reflects the probability that a positive test reflects the underlying condition of interest. References: ]]
Approved	Approved::Yes
Keyword	WBRKeyword::Infectious disease, WBRKeyword::biostatistics, WBRKeyword::Positive predictive value
Linked Question	Linked::
Order in Linked Questions	LinkedOrder::