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Investigators propose to determine whether knowing details about how a person's genes affect the way medicines work in the brain and body will help doctors pick more effective or safer medicine for that person. Target symptoms are restlessness, agitation, depression and related problems common in people with memory loss and dementia.
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This project offers an innovative approach to improving treatment outcomes for people with Behavioral and psychiatric symptoms of dementia (BPSD), as well as a novel electronic health record (EHR) -compatible means of assessing treatment response. To date, there has been limited investigation of pharmacogenomic testing among people with dementia. Testing has mostly been focused on testing a single Cytochrome P450 (CYP)polymorphism to guide treatment decisions for cognitive enhancing cholinesterase inhibitor medications in patients with Alzheimer disease. Pharmacogenomic guidance of prescribing decisions for psychotropic medications has not been studied for BPSD but there is growing evidence that such analyses can assist in effective prescription decisions for treatment of depression. Since affective symptoms are among the most prominent drivers of BPSD and associated distress, and the highest level evidence for successful treatment of BPSD is with the antidepressant drug citalopram, investigators believe that pharmacogenomic guidance for selection of drugs to treat BPSD is truly innovative, and will provide new insights on implementing safer and more effective treatment for BPSD.
Additionally, investigators will explore the use of the NIH-sponsored Patient Reported Outcomes measurement Information System (PROMIS) as an outcome measure for BPSD. PROMIS is a system of highly reliable, valid, flexible, precise, and responsive assessment tools that measure patient-reported health status. PROMIS measures are available for typical BPSD like anger, anxiety, and depression, but their utility has not been studied in a sample of dementia patients. They offer the potential, through patient-portal EHR interfaces, for clinicians to track treatment responses in a more timely and efficient manner than traditional clinic-based instruments, placing less burden on patients and families to present for in-clinic assessments.
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Data sourced from clinicaltrials.gov
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