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 sh
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