Mathematical Model May Predict Relapse Times in Prostate Cancer Surgery Patients

Mathematical Model May Predict Relapse Times in Prostate Cancer Surgery Patients
A mathematical model based on four consecutive measures of prostate-specific antigen (PSA) levels can be used to predict the time to relapse in patients who underwent prostate cancer surgery, according to a study published in Cancer Research. The method detailed in the study, "A Simple PSA-Based Computational Approach Predicts the Timing of Cancer Relapse in Prostatectomized Patients," was developed in University of Turin, Italy, and may help clinicians improve follow-up care of prostate cancer patients who undergo prostatectomy. "One in four patients who undergo prostate cancer surgery experiences a relapse. Predicting, and possibly preventing a relapse with adjuvant therapies is a major goal; however, overtreatment is a risk as well, because Androgen Deprivation Therapy (ADT) given after surgery, for instance, may promote the occurrence of new hormone-resistant tumor clones," Ilaria Stura, a mathematician and a doctoral candidate in the Complex Systems for Life Sciences program at the university, said in a press release. "Algorithms that use easily obtainable biological data to accurately predict prognosis can help clinicians and patients make more informed choices." Stura believes the mathematical model can improve a patient's quality of life, as it provides important clinical information to the urologists. Knowing the tumor's growth rate or that a relapse is expected with a certain number of months will inform clinicians as to when patients should receive therapy, such as hormone treatment or radiotherapy, to halt the spread of the tumor, or when such therapies should be delayed, avoiding overly excessive treatment. "Obviously, clinicians already try to do this based on their experience, but our method provides further confidence in their 'investiga
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