Retrospective Medical Record Review Study
Research type
Research Study
Full title
Identifying patterns in signs and symptoms preceding the clinical diagnosis of Alzheimer's Disease.
IRAS ID
212908
Contact name
FIDELIA BATURE
Contact email
Sponsor organisation
University of Bedfordshire
Duration of Study in the UK
1 years, 6 months, 0 days
Research summary
BACKGROUND: Alzheimer’s disease (AD) kills, and late diagnosis of the disease is a major challenge. Late diagnosis has been documented worldwide; one in four individuals in the UK has received a formal diagnoses, it sometimes takes between two to three years before a diagnosis is reached (1). Worldwide, 78% of individuals with AD are suggestively yet to receive a formal diagnosis. Findings indicate that this could be due to under-reporting (2), concealment of the symptoms (3), with the current diagnostic criteria based on biomarkers rather than observable symptoms (4,5). Late diagnosis may accelerate the cognitive and functional decline that leads to institutionalization, burden on caregivers, financial and health care sectors.
SIGNIFICANCE: This study collects data on the signs and symptoms preceding the clinical diagnosis of AD, to identify patterns and to develop a predictive model for early detection of AD, as no study has been undertaken on this. Early diagnosis and intervention is beneficial by reducing the cognitive and functional decline and gives individuals the opportunity to live independent lives.
METHOD: A retrospective medical record review , to identify patterns in signs and symptoms preceding the clinical diagnosis of AD for the development of a predictive model, using the latent class logistic regression for the analysis.
TIME FRAME: The RMRRS takes place within six months to a year after the approval of the study
FUNDING: No individual is funding this research, which is part of requirement for a Ph.D. degree.
CONCLUSION: This study will support the current diagnostic criteria based on biomarkers, by using the predictive model in the primary care setting to improve the early detection rate.REFERENCES
1. Health & Social Care Information Centre, HSCIC, 2014. Quality Outcomes Framework (QOF) Recorded Dementia Diagnoses Provisional 2013/14. http://www.hscic.gov.uk/catalogue/PUB14624/qual-outc-fram-rec-dem-diag-2013-2014-prov-rep.pdf. Accessed 20/05/2014.
2. Jones RW, Romeo R, Trigg R, Knapp M, Sato A, King D, Niecko T, Lacey L. 2015. Dependence of Alzheimer's disease and service use costs, quality of life, and caregiver burden: The DADE study’ Alzheimer's & Dementia. The Journal of the Alzheimer's Association; Elsevier B.V. (3), 280.
3. Marquer C, Laine J, Dauphinot L, Hanbouch L, Lemercier-Neuillet C, Pierrot N, Potier MC. 2014. Increasing membrane cholesterol of neurons in culture recapitulates Alzheimer’s disease early phenotypes. Molecular neurodegeneration, 9, 1-13.
4. Jack CR, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW. 2010. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade’, Lancet Neurol, 9, 119–128.
5. Dubois B, Feldman HH, Jacova C, Hampel H, Molinuevo JL, Blennow K, DeKosky ST, Gauthier S, Selkoe D, Bateman R. 2014.Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria', The Lancet Neurology, 13, 614-629.REC name
London - Central Research Ethics Committee
REC reference
16/LO/1521
Date of REC Opinion
27 Sep 2016
REC opinion
Further Information Favourable Opinion