Borrowing strength from clinical trials in analysing longitudinal data from a treated cohort: Investigating the effectiveness of acetylcholinesterase inhibitors in the management of dementia

Knight, Ruth, Stewart, Robert, Khondoker, Mizanur ORCID: https://orcid.org/0000-0002-1801-1635 and Landau, Sabine (2022) Borrowing strength from clinical trials in analysing longitudinal data from a treated cohort: Investigating the effectiveness of acetylcholinesterase inhibitors in the management of dementia. International Journal of Epidemiology. ISSN 0300-5771

	Microsoft Word (OpenXML) (SupplementaryMaterial) - Accepted Version Restricted to Repository staff only until 11 October 2023. Request a copy
	PDF (Knight_etal_AAM) - Accepted Version Restricted to Repository staff only until 11 October 2023. Request a copy

Abstract

Background: Health care professionals seek information about effectiveness of treatments in patients who would be offered them in routine clinical practice. Electronic medical records (EMRs) and randomized controlled trials (RCTs) can both provide data on treatment effects; however, each data source has limitations when considered in isolation. Methods: A novel modelling methodology which incorporates RCT estimates in the analysis of EMR data via informative prior distributions is proposed. A Bayesian mixed modelling approach is used to model outcome trajectories among patients in the EMR dataset receiving the treatment of interest. This model incorporates an estimate of treatment effect based on a meta-analysis of RCTs as an informative prior distribution. This provides a combined estimate of treatment effect based on both data sources. Results: The superior performance of the novel combined estimator is demonstrated via a simulation study. The new approach is applied to estimate the effectiveness at 12 months after treatment initiation of acetylcholinesterase inhibitors in the management of the cognitive symptoms of dementia in terms of Mini-Mental State Examination scores. This demonstrated that estimates based on either trials data only (1.10, SE = 0.316) or cohort data only (1.56, SE = 0.240) overestimated this compared with the estimate using data from both sources (0.86, SE = 0.327). Conclusions: It is possible to combine data from EMRs and RCTs in order to provide better estimates of treatment effectiveness.

Item Type:	Article
Faculty \ School:	Faculty of Medicine and Health Sciences > Norwich Medical School
Depositing User:	LivePure Connector
Date Deposited:	21 Sep 2022 10:30
Last Modified:	28 Oct 2022 09:26
URI:	https://ueaeprints.uea.ac.uk/id/eprint/88546
DOI:	10.1093/ije/dyac185

Actions (login required)

View Item