Some drugs frequently prescribed in the older population for the treatment of diseases like depression, Parkinson disease, hypertension, schizophrenia, overactive bladder, or seasonal allergies may increase the risk of dementia. However, this is still uncertain as only two studies on people using these medications have reported this potential risk. These medications are used for long periods of time in the elders which poses some challenges to the conduct of any study aiming to evaluate this long-term potential risk. These include the loss of patients over the course of the study, changes of treatment and how to estimate the cumulative effect of the use of these medications.
We propose to add to the body of evidence by conducting a similar design as the one used in clinical trials to test new drugs. We will take advantage of the wealth of information in a large health dataset, the Clinical Practice Research Datalink, which we will combine with novel analytical and statistical methods.
This study aims to evaluate the risk of dementia in patients initiating treatment with AC drugs. We will evaluate this in two different drug classes: antidepressants and antihypertensive drugs. We will compare patients initiating treatment with AC drugs compared with untreated patients and, with patients initiating treatment with similar drug classes but without AC properties. We will use a target trial emulation approach to ease interpretability, avoid selection bias and yield absolute estimates of risk of dementia, as opposed to the currently existing case-control studies.
We will use CPRD GOLD data (1999-2018) linked to HES and ONS data through an existing institutional licence to examine the effect of sustained exposure to AC drugs on the risk of dementia. We will estimate the observational analogue of an intention-to-treat effect and of a per-protocol effect using g-methods.
Health Outcomes to be Measured:
HES Admitted;ONS;Patient IMD;Practice IMD (Standard)