Screening

Positive and negative predictive value

Predictive value in screening

Cancer screening can be confusing and overwhelming, and there is an abundance of data available on the various screening methods, often without clarity on what that data means. Sensitivity and specificity is one important metric of any screening test, but the likelihood that an individual test result–whether positive or negative–is accurate is more complex than those values. In order to determine that likelihood, we use positive and negative predictive values.

In technical terms, the positive predictive value (PPV) is the proportion of positive results in diagnostic tests that are true positives. If an individual were to test positive using a cancer screening test that has a 75% PPV, there is a 75% chance that the individual does in fact have cancer. Conversely, negative predictive value (NPV) is used to measure confidence in negative results, i.e. true negatives.

It’s clear why this is an important concept to keep in mind when undertaking cancer screening, as it adds vital context to test results. A screening exam with just a 30% PPV can give valuable information, but 70% of individuals who receive a positive result do not actually have cancer. 

PPV and NPV combine information about test sensitivity and specificity with the overall prevalence of a specific disease in the population. Mathematically, they’re calculated as: 

Let’s take an example from colorectal cancer.  The most basic form of colorectal cancer screening for individuals at average risk is the at-home Fecal Immunochemical Test (FIT). This test has 74% sensitivity and 94% specificity. The average prevalence for colorectal cancer is approximately 4% (i.e., 4% of the population can expect to be accurately diagnosed with this cancer at some point in their lives). That means the NPV and PPV of a FIT test for someone at average risk are: 

PPV = 74% x 4% / (74% x 4%) + (1-94%) x (1-4%) = 34%

NPV = 94% x (1-4%) / 94% x (1-4%) + (1-74%) x 4% = 99%

This means that if a person at average risk for colorectal cancer receives a positive result on a FIT test, there is only a 34% chance they in fact have colorectal cancer. If they receive a negative result, there is a 99% chance they do not in fact have the disease–overwhelming odds would say this was a true negative. 

However, PPV and NPV change as disease prevalence changes, and disease prevalence is based on personalized risk factors. That’s where the Catch risk assessment comes into play.

For a 45-year-old individual with a first-degree relative who had previously been diagnosed with colorectal cancer, personalized disease risk may be higher than the population average of 4%; if it were to jump to 7%, the PPV and NPV of the FIT test shift to 63% and 96% respectively. A positive result would be a bit more concerning, and a negative result should not connote quite as much confidence. 

At Catch, we provide this vital context for all the screening tests we recommend, which can help you not only interpret your own test results, it can help you make informed decisions about frequency of testing, which tests to pursue, and your own comfort level with the results you receive. Providing the information you need to make informed decisions, and using your personalized risk assessment to recommend a screening plan, will give you the best chance of catching cancer early.

The Verdict
Sources
Legal
Tags

Join the movement.

Complete the Catch assessment and discover your cancer score now.

Get Started