Cancer

Iams honored by National Comprehensive Cancer Network

Wade Iams, MD, MSCI, assistant professor of Medicine, is the recipient of a National Comprehensive Cancer Network Foundation Young Investigator Award.

Stomach bug hit-and-run

The H. pylori machinery that “injects” an oncoprotein into stomach cells contributes to the development of gastric cancer, Vanderbilt researchers demonstrate.

Criteria for lung cancer screens may be expanded

The U.S. Preventive Services Task Force (USPSTF) is recommending two changes that will nearly double the number of people eligible for lung cancer screening by lowering the age from 55 to 50 and reducing the number of smoking history pack years from 30 to 20.

Cellular antiviral defenses

A cellular RNA quality control mechanism was known to restrict replication of RNA viruses. Vanderbilt researchers have discovered it is also antiviral against DNA viruses.

New data offer insights on COVID treatments for people with cancer

Newly released data on treatment outcomes of people with cancer diagnosed with COVID-19 reveal a racial disparity in access to Remdesivir, an antiviral drug that has been shown to shorten hospital stays, and increased mortality associated with dexamethasone, a steroid that has had the opposite effect in the general patient population.

Friedman named associate director for Community Science and Health Outcomes at Vanderbilt-Ingram Cancer Center

Debra Friedman, MD, MS, E. Bronson Ingram Chair of Pediatric Oncology, is expanding her leadership role in improving cancer outcomes both within and beyond the Vanderbilt-Ingram Cancer Center (VICC) catchment area. She has been named associate director of Community Science and Health Outcomes.

May 7, 2020

Study finds AI can categorize cancer risk of lung nodules

by Tom Wilemon Computed tomography scans for people at risk for lung cancer lead to earlier diagnoses and improve survival rates, but they can also lead to overtreatment when suspicious nodules turn out to be benign. A study published in American Journal of Respiratory and Critical Care Medicine indicates that an artificial intelligence strategy can correctly assess and categorize these indeterminate pulmonary nodules (IPNs). When compared to the conventional risk models clinicians currently use, the algorithm developed by the team of researchers in a very large dataset (15,693 nodules) reclassified IPNs into low-risk or high-risk categories in over a third of cancers and benign nodules. “These results suggest the potential clinical utility of this deep learning algorithm to revise the probability of cancer among IPNs aiming to decrease invasive procedures and shorten time to diagnosis,” said Pierre Massion, MD, Cornelius Vanderbilt Chair in Medicine at Vanderbilt University, the study’s lead author. Currently, clinicians refer to guidelines issued by the American College of Radiology and the American College of Chest Physicians. Adherence to these guidelines can be variable, and how patient cases are classified can be subjective. With the goal of providing clinicians with an unbiased assessment tool, the researchers developed an algorithm based on datasets from the National Lung Screening Trial, Vanderbilt University Medical Center and Oxford University Hospital. Their study is the first to validate a risk stratification tool on multiple independent cohorts and to show reclassification performance that is significantly superior to existing risk models. With IPNs, clinicians are often faced with the dilemma of weighing whether to advise a patient to undergo an invasive surgical procedure, which may be unnecessary, against a watch-and-wait strategy, which may result in delaying needed cancer treatment. A definitive diagnosis of an IPN can take up to two years. Better assessment tools are needed by clinicians as screenings for patients at risk for lung cancer increase. Lung cancer is the leading cause of cancer-related death in the United States and globally. The overall five-year survival rate is 21.7%, but it is much greater (92%) for those patients who receive an early diagnosis of stage IA1 non-small cell cancer. n
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