PSA-based tool improves decision making for prostate cancer screening and treatment

Prostate cancer is the second-leading cause of cancer death in American men.

About 1 in 8 men will be diagnosed with prostate cancer in their lifetime, and the risk varies depending on age and race.

Prostate cancer is primarily screened by the levels of prostate-specific antigen in the blood.

Although an estimated 10 million PSA tests are performed annually, there are few tools available to interpret the results and help patients decide what course of action to take.

University of Michigan researchers have developed a model that can help doctors and patients understand their PSA results and what they mean for patient life expectancy.

"Current tools don't take into account how long someone may live or the benefit a patient may receive from treatment," said Kristian Stensland, M.D., M.P.H., M.S., Assistant Professor of Urology.

"Our model is the first to incorporate all these factors and help people understand whether they need further screening or treatment."

Existing risk calculators are less accurate or predict prostate cancer risk through biopsy-based tests based on biopsy, which requires tissue samples and extra processing time.

In a previous study, the researchers showed that PSA scores can impact both doctor and patient behavior, leading to biopsy referrals even when the risk of harm from prostate cancer is low.

With this model, they hope that only patients who might benefit from further screening and treatment will receive referrals.

The new model relies on PSA scores and was developed using data from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, which recruited more than 33,000 patients aged 55 to 74 years from 1993 to 2001.

The researchers also took family history of prostate cancer, race, age, body mass index, smoking status and a history of hypertension, diabetes or stroke into account.

After building the model, they tested it using PSA scores from more than 200,000 patients who received care in the Veterans Affairs Healthcare System in the same age range from 2002 to 2006.

The model was able to predict the risk for prostate cancer-specific mortality and highlight which patients would benefit from further 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."

The researchers are now working to implement their model in clinical settings.