A study to be presented at RSNA 2016 indicates that in addition to the known lung cancer connection, smoking can put people with diabetes at greater risk of dying from other causes.
More than 29 million people in the U.S. have diabetes, according to data from the U.S. Centers for Disease Control and Prevention. What's more, one in four people with diabetes don't know they have the disease.
A group of researchers from the University of Colorado in Denver wanted to research the connections between diabetes and death from lung cancer and other illnesses. They examined all-cause mortality for people with and without diabetes who participated in the National Lung Screening Trial (NLST).
In a population of 5,174 people, they found a statistically significant link between diabetes and all-cause deaths, non-lung cancer deaths, and lung cancer deaths in women. There were 3,936 total deaths, including 1,021 from lung cancer and 826 from cancers outside of the lung.
Participants with diabetes were older, had more pack-years of smoking, and had a higher body mass index (BMI) than people without diabetes. There were 650 deaths -- 12.6% of patients -- among study participants with diabetes, and 3,286 deaths -- 6.8% -- among those without diabetes.
The researchers advised that smokers with diabetes should manage their disease if they want to take full advantage of the benefits of CT lung cancer screening.

















![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&fit=crop&h=112&q=70&w=112)


