A Novel Model Can Predict Death in Older Adults with Dementia

A new study sought to assess the accuracy of a novel model to predict death in community-dwelling older adults suffering from dementia. The findings were reported in JAMA Internal Medicine.

To conduct this study, researchers used two national cohorts comprised of a total of 6,671 community-dwelling older adults with dementia; one from 1998 to 2016 (n = 4,267), and another from 2011 to 2019 (n = 2,404). The prognostic model analyzed for mortality using such predictors as chronic conditions, demographics, health factors, and functional measures such as activities of daily living (ADL) and instrumental activities of daily living (IADL).

The primary outcome of interest was time to all-cause death, which was analyzed using Cox proportional hazards regression. The model’s performance was judged using integrated area under the receiver operating characteristic curve (iAUC) and calibration plotting.

According to the results, the modeled assessed for age, sex, body mass index, smoking status, ADL dependency count, IADL difficulty count, difficulty walking several blocks, participation in vigorous physical activity, and chronic conditions such as cancer, heart disease, and diabetes.

The researchers observed positive results in the iAUC validation, which was 0.76 (95% CI, 0.75-0.76) with time-specific AUC of 0.73 (95% CI, 0.70-0.75) at 1 year, 0.75 (95% CI, 0.73-0.77) at 5 years, and 0.84 (95% CI, 0.82-0.85) at 10 years. The researchers noted that calibration plots suggested “good” calibration across the range of predicted risk from 1 to 10 years.

The researchers concluded that: “The mortality risk estimates may help guide discussions regarding treatment decisions and advance care planning.”