PSA-based tool improves decision-making in early detection and treatment of prostate cancer

PSA-based tool improves decision-making in early detection and treatment of prostate cancer

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

About one in eight men will be diagnosed with prostate cancer during their lifetime, with the risk varying depending on age and race.

Prostate cancer is primarily detected by the concentration of prostate-specific antigen in the blood.

Although an estimated 10 million PSA tests are performed annually, few tools are available to interpret the results and help patients decide how to proceed.

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

“Current tools do not take into account potential life expectancy or the benefit a patient may receive from treatment,” said Kristian Stensland, MD, MPH, MS, assistant professor of urology.

“Our model is the first to take all of these factors into account and help people understand whether they need further testing or treatment.”

Existing risk calculators are less accurate or predict prostate cancer risk through biopsy-based tests that rely on biopsies, requiring tissue samples and additional processing time.

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

With this model, they hope that only patients who could benefit from further evaluation and treatment will receive a referral.

The new model is based on PSA levels and was developed using data from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Study, which included more than 33,000 patients aged 55 to 74 from 1993 to 2001.

Researchers also considered family history of prostate cancer, race, age, body mass index, smoking status and a history of high blood pressure, diabetes or stroke.

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

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

“It's important to remember that we built and tested the model with data from two decades ago and a lot has changed since then,” Stensland said.

“While treating prostate cancer is different now, our model is an improvement over previous tools and can be used to decide how we perform PSA screenings.”

The researchers are now working on implementing their model in clinical settings.

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