Six clinics across four U.S. states provided data for a newly validated clinical risk stratification model for lung cancer. The TREAT model (Thoracic Surgery, Research, Epidemiology, Diagnosis And Treatment) helps identify patients with suspicious lesions who are most likely to benefit from surgical biopsy. The aim is to mitigate unnecessary surgery for benign nodules and reduce delays for patients with early cancers.
Data published in the Journal of Thoracic Oncology show the model reliably predicted lung cancer prevalence in 1,402 patients with better accuracy and calibration than currently available alternatives. Now, researchers are refining the model to further increase its utility.
“This is one of the larger datasets used in lung cancer modeling and validation studies,” said senior author Eric Grogan, M.D., a thoracic surgeon at Vanderbilt University Medical Center. “It’s not just in our local population, it’s now validated in six different sites across the United States. It’s more broadly applicable to both pulmonary nodule and surgery clinics.”