{"id":6943,"date":"2023-10-09T08:49:00","date_gmt":"2023-10-09T12:49:00","guid":{"rendered":"https:\/\/new.www.purdue.edu\/newsroom\/?p=6943"},"modified":"2024-08-20T12:37:20","modified_gmt":"2024-08-20T16:37:20","slug":"predicting-prostate-cancer-recurrence-15-months-faster","status":"publish","type":"post","link":"https:\/\/www.purdue.edu\/newsroom\/2023\/Q4\/predicting-prostate-cancer-recurrence-15-months-faster","title":{"rendered":"Predicting prostate cancer recurrence 15 months faster"},"content":{"rendered":"

WEST LAFAYETTE, Ind. —<\/p> \n

A Purdue University mechanical engineer and his international collaborators have developed a patent-pending method and algorithm to predict the recurrence of prostate cancer in patients treated by radiation therapy.\u00ad<\/p>\n<\/div>\n\n\n

Hector Gomez<\/a>, a professor in Purdue University\u2019s School of Mechanical Engineering<\/a>, said data indicates the model-based predictors can identify relapsing patients a median of 14.8 months earlier than the current clinical practice.<\/p>\n\n\n\n

Gomez said radiation is an effective treatment for patients of all ages to treat tumors ranging in risk from low to very high. According to Johns Hopkins Medicine<\/a>, between 20% to 30% of patients will experience a recurrence after the five-year period, post-therapy.<\/p>\n\n\n\n

\u201cThe detection of prostate cancer recurrence after radiation relies on the measurement of a sustained rise of the serum levels of a substance called prostate-specific antigen, or PSA,\u201d Gomez said. \u201cHowever, the recurrence may take years to occur, which delays the delivery of a secondary treatment to patients with recurring tumors.\u201d<\/p>\n\n\n\n

Gomez and his collaborators at the University of Pavia in Italy and the University of Castilla \u2014 La Mancha in Spain have developed novel, patient-specific forecasts of PSA dynamics to predict cancer recurrence. Their research has been published online in iScience<\/a>, an open access journal.<\/p>\n\n\n\n

The algorithm is based on a patient-specific mechanistic model, informed by the periodic PSA measurements for an individual patient. These measurements are part of the standard monitoring for prostate cancer patients who have undergone radiation.<\/p>\n\n\n\n

\u201cThe PSA data is used in conjunction with the model to obtain patient-specific parameters that determine the PSA dynamics and serve as classifiers for recurrence,\u201d Gomez said. \u201cIn addition to recurrence identification, our model can be used for designing personalized PSA monitoring strategies. It can tell physicians the right time to investigate tumor recurrences and maximize the window of curability.\u201d<\/p>\n\n\n\n

Gomez and his collaborators tested the method using retrospective data from a cohort of 166 patients.<\/p>\n\n\n\n

\u201cFor each of these patients, we compared the time when our model first identified the recurrence with the standard medical practice,\u201d Gomez said. \u201cWe found that our method predicted recurrence a median of 14.8 months earlier.\u201d <\/p>\n\n\n\n

Gomez said the model will be further developed to expand the population of patients who can benefit from it.<\/p>\n\n\n\n

\u201cOur current model can be used only for patients who do not receive any treatment additional to radiation,\u201d Gomez said. \u201cSome patients receive radiation and hormone therapy simultaneously and cannot benefit from our method right now. We plan to extend the method to make it applicable also to patients who receive radiation and hormone therapy simultaneously.\u201d<\/p>\n\n\n\n

Gomez disclosed the innovation to the Purdue Innovates Office of Technology Commercialization<\/a>, which has applied for a patent from the U.S. Patent and Trademark Office to protect the intellectual property. Industry partners interested in developing and commercializing the innovation should contact Patrick Finnerty<\/a>, senior business development and licensing manager in life sciences, at pwfinnerty@prf.org<\/a>.<\/p>\n\n\n\n

Hector Gomez is among the Purdue University faculty whose work is supported by the Purdue Institute for Cancer Research<\/a>.<\/p>\n\n\n\n

\u201cThere is an important need for prognostic technology like Hector\u2019s to be further developed to begin to predict which prostate cancer patients are at high risk so they can be followed more closely and monitored to verify the recurrence,\u201d said Timothy Ratliff<\/a>, former director of the Purdue Institute for Cancer Research and Distinguished Professor of Comparative Pathobiology in the College of Veterinary Medicine<\/a>. \u201cI am proud that Purdue University has outstanding organizations like the Institute for Cancer Research that bring together faculty to generate new technologies that impact people\u2019s lives.\u201d <\/p>\n\n\n\n

Facts about prostate cancer<\/h2>\n\n\n\n

In its Cancer Facts & Figures 2023 report<\/a>, the American Cancer Society estimates that more than 288,000 new cases of prostate cancer will be diagnosed in the United States in 2023. <\/p>\n\n\n\n