A new study from the Predictive Analytics and Comparative Effectiveness (PACE) Center and the Center for the Evaluation of Value and Risk in Health (CEVR) at Tufts Medical Center, published in Annals of Internal Medicine on January 2, 2018, found that screening the highest risk patients can help prevent more lung cancer deaths for every scan done in the short term (seven years). However, since the highest risk patients are older, have pre-existing medical conditions, and generate more expense following screening, they did not experience appreciable benefits in long-term cost-effectiveness.
Lung cancer is the leading cause of cancer death in America, and screening for lung cancer with a specialized low dose CT scan can help to reduce lung cancer mortality. But screening is not without its risks and the researchers sought to determine which population would benefit most from screening.
One option is to use age and smoking exposure, like most guidelines recommend, while another option is to use a personalized approach - individual characteristics like age, sex, smoking exposure, and medical history - and combine them in a statistical model to calculate a patient’s specific risk of dying from lung cancer. The study, which was based on more than 50,000 patients enrolled in the National Lung Screening Trial, compared the two approaches. The study used novel modeling techniques to help physicians and policymakers gauge the differences in screening efficiency of the personalized approach both in the short and long term.
“With less than 5 percent of eligible patients actually being screened, our work raises the question on the need to further complicate patient selection for lung cancer screening given the benefits in the long term are attenuated,” said Vaibhav Kumar, MD, a Postdoctoral Fellow at Tufts Medical Center and the study’s primary author.
About Tufts Medical Center and Floating Hospital for Children
Tufts Medical Center is an exceptional, not-for-profit, 415-bed academic medical center that is home to both a full-service hospital for adults and Floating Hospital for Children. Conveniently located in downtown Boston, the Medical Center is the principal teaching hospital for Tufts University School of Medicine. The Medical Center features a level one trauma center with rooftop helipad, the largest heart transplant center in New England and a renowned research program, ranking among the top 10 percent of independent hospitals to receive federal research funding. A physician network of 1,800 New England Quality Care Alliance doctors represents our strong commitment to health in the community. Tufts Medical Center is a founding member of Wellforce, along with Circle Health and MelroseWakefield. For more information, visit www.tuftsmedicalcenter.org.
About the Center for the Evaluation of Value and Risk in Health (CEVR)
Since its inception in 2006, the Center for the Evaluation of Value and Risk in Health (CEVR) at the Institute for Clinical Research and Health Policy Studies at Tufts Medical Center in Boston has been a leader on issues pertaining to value, cost-effectiveness, and risk tradeoffs in health care decisions. Our mission is to analyze the benefits, costs, and risks of strategies to improve health and health care and to communicate the findings to clinicians and policymakers.
About the Predictive Analytics and Comparative Effectiveness (PACE) Center
The Predictive Analytics and Comparative Effectiveness (PACE) Center within the Institute for Clinical Research and Health Policy Studies at Tufts Medical Center seeks to better understand and address the limitations of using group-derived evidence as the basis for decision making in individual patients, with the goal of providing clinicians and patients with evidence better tailored to their particular circumstances.
Cayla Saret | 617-636-2850 | email@example.com
Predictive Analytics and Comparative Effectiveness (PACE) Center
Jennifer Lutz | 617-636-7405 | firstname.lastname@example.org
Center for the Evaluation of Value and Risk in Health
Anna Legassie | 617-636-7746 | email@example.com