Health History Might Predict Life Expectancy in Seniors with Diabetes
Physicians might be able to predict the five- and 10-year life expectancy of older adults with diabetes by examining their health history, including other chronic diseases and prescription medicines they use, according to a study published Friday in the journal Diabetes Care.
Thirty-seven factors linked with, or suspected to impact, risk for death in older adults with diabetes -- including demographic variables and metrics such as blood pressure and blood sugar levels -- had "high predictive validity," researchers said.
Researchers say they were accurately able to identify those who would die within five years, within 10 years or more than 10 years later.
"Our results identify multiple common conditions that can easily be identified in clinical practice and assist clinicians in shared decision-making with patients," study co-author Dr. Paul Conlin, chief of medical service at the VA Boston Healthcare System, said in a statement.
More than 34 million people in the United States are living with diabetes, according to the American Diabetes Association.
Research indicates that type 1 diabetes reduces life expectancy by 20 years, while the far more common type 2 form shortens life expectancy by 10 years.
The ability to predict life expectancy can help doctors and their patients develop personalized treatment goals that balance risks and benefits, according to Conlin and his colleagues.
Key factors that influence diabetes treatment goals include co-existing health conditions -- such as severe mental illness or cancer -- as well as diabetes complications such as chronic kidney disease and heart failure, they said.
For the study, researchers from the Boston Healthcare System reviewed electronic health record data for more than 275,000 veterans with diabetes who were at least 65 years old.
They developed a predictive model using 37 factors that might influence life expectancy in older adults with diabetes, including demographic variables such as age, gender, and marital status; prescriptions for insulin or sulfonylureas, a class of diabetes drugs; and biomarkers such as hemoglobin A1C levels, blood pressure, body mass index and cholesterol, and triglyceride levels.
The predictive factors also included inpatient and outpatient medical history and more than 20 medical procedures and co-occurring health disorders.
The final predictive models demonstrate the importance of several individual and condition-specific characteristics that might inform clinicians and patients about life expectancy, the researchers said.
These results could assist clinicians in using shared decision-making to establish A1C target ranges that balance treatment benefits and risks, the researchers suggested.
For example, they said the benefits of lowering blood sugar can take several years to develop, and it may not be worth it for some older adults with limited life expectancy due to other health problems.
"Our goal was to use the best available information to inform decision-making in setting glucose control targets," Conlin said. "Doctors and patients, of course, can then use their own judgment to make a decision."
The Department of Veterans Affairs recently launched an Understand Your Diabetes Numbers campaign to assist beneficiaries with treatment decisions.