COM Professor Nananda Col participates in NIH consensus panel on prostate cancer
Nananda Col, M.D., M.P.H., a professor of medicine in the University of New England's College of Osteopathic Medicine, has recently returned from Washington D.C. where she served on a Consensus Development Panel making recommendations for the care of prostate cancer.
The National Institutes of Health (NIH) hosted the state-of-the-science conference to discuss the role of active surveillance in managing localized prostate cancer in low-risk patients.
An upcoming edition of the American Society of Clinical Oncology's ASCO Post will feature the contributions made by Dr. Col and other experts in an upcoming article titled, "NIH Panel Endorses Active Surveillance in Low-Risk Prostate Cancer," by Caroline McNeal.
As a panel member, Dr. Col shared her expertise in the field of decision science and the influence that a physician's recommendation has in their patients' intervention plan.
Dr. Col is quoted stating, "if a patient goes to a urologist, he is more likely to be offered surgery, if he first sees a radiation oncologist, he is more likely to be offered radiation." This, the article explains, is why many qualified patients opt for immediate intervention, over active surveillance. The complete article will be viewable through the website after January 15, 2012.
Dr. Col is a graduate of Dartmouth College, The Kennedy School of Government (MPP), and the University of Massachusetts Medical School (MD, MPH). Her clinical training is in internal and preventive medicine, and she completed a fellowship in clinical decision鈥毭劽琺aking, informatics, and telemedicine at Tufts.
She joined 色香视频 as a professor of medicine in the Departments of Family Medicine and Geriatric Medicine in 2011. She is also a member of the Center for Excellence in the Neurosciences at 色香视频.
A national expert in women's health and clinical decision-making, Dr. Col pioneered work in the area of risk modeling and personalized decision support, developing patient-specific risk models and strategies for developing and integrating sophisticated computerized decision support into primary care to help doctors and patients make more informed treatment decisions.