Graphical methods for understanding changes in states: Understanding medication use pathways.

Area of Science:

• Epidemiology
• Gerontology
• Psychopharmacology

Background:

• Large-scale, long-term epidemiological studies require advanced visualization techniques for complex longitudinal data.
• Understanding medication use patterns, particularly antidepressant switching, is crucial in managing chronic conditions like mild cognitive impairment (MCI).

Purpose of the Study:

• To introduce Slinkyplot, a novel longitudinal crosstabulation method.
• To illustrate complex patterns of antidepressant use and switching in a prospective cohort of older adults with MCI.

Main Methods:

• Utilized data from the National Alzheimer's Coordinating Center.
• Employed Slinkyplot to track transitions between different states and types of antidepressant use over time.
• Slinkyplots were populated with medication use states at each timepoint and subsequent visits.

Main Results:

• Visualized common practices of switching antidepressant medications on and off over the study period.
• Identified citalopram, sertraline, and bupropion as frequently used initial treatments.
• Observed a common pattern of switching to selective serotonin reuptake inhibitors (SSRIs) or serotonin-norepinephrine reuptake inhibitors (SNRIs) as second-line therapies.

Conclusions:

• Slinkyplots offer an innovative graphical approach for visualizing intricate transition patterns in longitudinal data.
• This method is particularly valuable for large-scale studies examining changes in medication use or health states over time.