# ABIM Exam Review Practice Question of the Week: Best Biostatistics Review

If you’ve ever been even slightly confused by prevalence, sensitivity, specificity, positive predictive value or other biostatistics calculations needed for the ABIM Internal Medicine board exam, this post was written just for you. It’s actually a practice question directly from Knowmedge’s **Internal Medicine Board (ABIM) Exam ** QVault. Plenty more where this came from!

**Question**

A test has 80% sensitivity, 90% specificity and a disease prevalence of 10%. What is the positive predictive value?

A. 33% B. 47% C. 61% D. 20% E. 55%

## ABIM Exam Question Explanation

**Based on the tables and diagrams, this explanation is most effective when viewed as a video rather than simple text so click above**

Before we get to calculating our positive predictive value, let’s review the basics of biostatistics needed to get there.

Let’s begin by understanding

**prevalence**, which is the

*percentage of people in a population who have the disease*. In the equation, prevalence equals the sum of true positives (TP) and false negatives (FN) divided by the sum of all four boxes. If we make the total number of our patients equal 1000, then with a disease prevalence of 10%, the number of people with the disease is 10% multiplied by 1000, or 100, and the number of patients without the disease is 900.

**Sensitivity**is the ability of a

*test to detect disease*. It is the ratio of true positives (TP) to the number of people who actually have the disease or in the table, A divided by the quantity (A+C). In this problem, the test has 80% sensitivity. Therefore, since 100 people have the disease, 80 of them have a positive test. And the remaining 20 do not. Those are our false negatives (FN).

Let’s consider the people without the disease. Here we deal with

**specificity**, the ability of a

*test to detect non-disease*. It is the number of true negatives divided by the number of people without the disease or D divided by the quantity (B+D). This test has a specificity of 90%. We already know from previous calculations that the number of people without the disease is 900. Therefore, the True Negatives are 810. False Positives are 90.

With this information, we can calculate the

**positive predictive value**. The PPV is defined as the

*likelihood of disease when the test is positive*, or the true positives divided by the sum of true positives and false positives, which equals 47%, Choice B.

*You can see all the previous ABIM Exam Review Questions of the Week at the Knowmedge Blog. You can also find additional topics and questions directly from the Knowmedge Internal Medicine ABIM Board Exam Review Questions QVault.*