Evidence that 'personalized medicine' leads to better outcomes
A statistical model can accurately predict which patients will have poor outcomes after bladder surgery and can determine the need for chemotherapy. The analysis, to be published in the December 1, 2009 issue of CANCER, a peer-reviewed journal of the American Cancer Society, concludes that the model, which considers both how far the cancer has spread and other information, such as how the cancer cells look under the microscope and the time between diagnosis and surgery, could better identify patients who need to undergo further treatment.
Many individuals with bladder cancer have surgery to remove the bladder as an initial treatment. Following surgery, doctors must decide whether to recommend that the patient receive chemotherapy to kill any remaining cancer cells. Chemotherapy is typically recommended only for patients with higher stage disease. However, it is widely accepted that while many patients receive chemotherapy unnecessarily, some patients with low stage disease who are not referred to chemotherapy nonetheless experience a cancer recurrence.
Researchers led by Andrew J. Vickers, PhD, of Memorial Sloan-Kettering Cancer Center in New York City set out to determine whether use of a previously published prediction model to inform medical decision making would lead to superior clinical outcomes. To demonstrate their findings, they compared the clinical outcomes of the different routes in which bladder cancer patients would be referred to chemotherapy: based only on cancer stage, as is current practice, or based on the bladder cancer prediction model.