The 2016 update by the U.S. Preventive Services Task Force (USPSTF) of its CT colonography (CTC) guidance boosted CT colonography screening rates by 50%, according to a study conducted by the Harvey L. Neiman Health Policy Institute and published March 19 in the American Journal of Preventive Medicine.
The USPSTF included CTC on its list of recommended tests for colorectal cancer in June 2016. A team led by Steve Chen of Emory University in Atlanta used commercial claims data from between 2010 and 2018 to examine the effects of this update on monthly CTC use rates in privately insured patients 50 to 64 years of age. During the study timeframe, 3,773 screening CT colonography scans were conducted in 31.2 million individuals.
The use rate of CTC increased from 0.4 to 0.6 scans per 100,000 people after the USPSTF's 2016 recommendation -- a boost of 50%, the group found.
"The release of supportive evidence-based recommendations by a recognized credible body was associated with an immediate increase in CTC use for colorectal cancer screening," said senior author Michal Horný, PhD, also at Emory, in a statement released by Neiman Health Policy Institute. "The results of our study support the power of evidence-based recommendations to impact cancer screening rates among the U.S. privately insured population."
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)
