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New Model Predicts Whether Patients Will Be Free of Renal Cancer 12 Years After Initial Treatment DALLAS -- June 3, 2008 -- A University of Texas (UT) Southwestern Medical Center physician and other researchers have developed a unique statistical model that predicts the probability of a patient being cancer-free 12 years after initial surgical treatment. The model, known as a nomogram, uses tumour and patient characteristics to maximise predictive accuracy. Scientists said that knowing the likelihood of the cancer's return could help clinicians counsel patients and customise treatment recommendations for individual patients. The researchers built the predictive model using data from more than 2,500 renal cancer patients in databases at Memorial Sloan-Kettering Cancer Center, New York, New York, and the Mayo Clinic, Rochester, Minnesota. The model is described in June's edition of the Journal of Urology. The nomogram relies on patient characteristics to make a statistical prediction. Gender, the presence or absence of symptoms, and the size of the mass are among the input data. "It is our hope that the nomogram will help physicians identify and counsel patients at high risk for cancer recurrence," said Ganesh Raj, MD, PhD, Assistant Professor of Urology, UT Southwestern Medical Center, Dallas, Texas, and lead author of the published study. "If the cancer appears only in the kidneys, it can often be treated with a partial or radical nephrectomy," Dr. Raj said. "This nomogram is designed for use in the initial counselling session after diagnosis and enables patients to have a clearer understanding of their cancer outcomes with surgery." "This model allows us to better predict a patient's chances of reoccurrence even before surgery," Dr. Raj said. "The nomogram is a prognostic tool physicians can use to better counsel patients on how curable their cancer may be with just surgery, or if alternative treatments will likely be needed." SOURCE: University of Texas Southwestern Medical Center E-mail this page to a friend or colleague! To print, use this version