New tool helps men make sense of PSA test results
University of Michigan researchers say the model could reduce unnecessary biopsies
Updated:

Photo by Vitaly Gariev on Unsplash
Key Insights
- Prostate cancer is the second-leading cause of cancer death among American men, with about 1 in 8 expected to be diagnosed during their lifetime.
- Screening usually relies on prostate-specific antigen (PSA) blood tests, but millions of men receive results each year without clear guidance on what those numbers really mean for their health.
- Researchers at the University of Michigan have developed a new model designed to help doctors and patients better understand PSA results and decide whether further testing or treatment is actually beneficial.
Prostate cancer screening has long been a balancing act. On one hand, early detection can save lives. On the other, elevated PSA levels can lead to biopsies and treatments that may not improve outcomes—and can sometimes do more harm than good.
Now, a new tool developed by University of Michigan researchers aims to bring more clarity to that decision-making process.
The model uses PSA test results along with personal health factors to estimate a patient’s risk of dying specifically from prostate cancer and whether treatment is likely to extend their life. According to the researchers, existing tools don’t adequately address those questions.
Weakness of current tools
“Current tools don’t take into account how long someone may live or the benefit a patient may receive from treatment,” said Dr. Kristian Stensland, an assistant professor of urology at the University of Michigan. “Our model is the first to incorporate all these factors and help people understand whether they need further screening or treatment.”
Each year, an estimated 10 million PSA tests are performed in the U.S. Yet interpreting the results can be challenging. PSA levels can rise for reasons other than cancer, and higher numbers don’t always mean aggressive disease. Previous research by the same team found that PSA scores alone can influence doctors and patients to pursue biopsies—even when the likelihood of serious harm from prostate cancer is low.
Unlike many existing risk calculators, which rely on biopsy results and tissue samples, the new model is based primarily on PSA levels combined with other patient characteristics. These include age, race, family history of prostate cancer, body mass index, smoking status, and medical conditions such as hypertension, diabetes, or a history of stroke.
The study
To build the model, researchers analyzed data from more than 33,000 men ages 55 to 74 who participated in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial between 1993 and 2001. They then tested it using PSA data from over 200,000 patients treated in the Veterans Affairs Healthcare System from 2002 to 2006.
The results showed that the model could predict prostate cancer–specific mortality and identify which patients were most likely to benefit from additional screening or treatment.
“It is important to remember that we created and tested the model using data from two decades ago and a lot has changed since then,” Stensland said. “Even though prostate cancer treatment is different now, our model improves on previous tools and can be used to decide how we do PSA screens.”
Reduce unnecessary procedures
The researchers hope the tool will ultimately reduce unnecessary biopsies and treatments, focusing care on patients who stand to gain the most. They are now working to implement the model in real-world clinical settings, where it could help men have more informed conversations with their doctors about prostate cancer screening and next steps.
For older adults, the takeaway is simple but important: a PSA test is just one piece of the puzzle. Tools like this new model may soon help ensure that follow-up care is guided not just by test results, but by what truly matters—whether treatment is likely to improve both length and quality of life.