Clinical trial NCT06114290: Personalised Medicine in the Identification of Preclinical Cognitive Impairment. Development of a Predictive Risk Model
Official title: Personalised Medicine in the Early Identification of Preclinical Cognitive Impairment. Development of a Predictive Risk Model.
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Cognitive Dysfunction
Keywords: Cognitive Dysfunction
Early Diagnosis
Primary Health Care
Biomarkers
Artificial Intelligence
Precision Medicine
Care
Lead sponsor: Instituto de Salud Carlos III
Sponsor class: OTHER_GOV
Collaborators: name: Instituto de Investigación Biomédica de Salamanca
name: Carlos III Health Institute
name: Universidad Complutense de Madrid
name: Biomedical Research Networking Centre on Frailty and Healthy Ageing
name: Biomedical Research Networking Centre on Mental Health
name: Institute of Biomedical Research of Lleida
name: Institute of Health and Biomedical Research of Alicante
name: Carlos III University of Madrid
name: University of Vigo
name: Foundation for Biosanitary Research and Innovation in Primary Health Care
name: Biomedical Research Networking Centre on Epidemiology and Public Health
name: Research Network on Chronicity, Primary Care and Health Prevention and Promotion
First posted: 2023-11-02
Enrollment: 1150
Sex: ALL
Minimum age (years): 55
Maximum age (years): 70
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: OTHER
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: The study will be carried out on non-institutionalised subjects in the study locations, aged 55 to 70 years, attached to the PC centres of the territories included in the study, with a living history (at least one record in the last 12 months). The individuals will be selected from lists of patients from the participating practices in the 7 geographical locations, each of them providing 150 patients. The sample will be obtained by stratified by age (5-year wide strata) and sex who do not include any diagnosis of mild CD in their clinical records (MMSE= 24-27 points). Any refusal to participate after screening will be replaced by the next subject on the sampling list from the same centre and stratum. Samples will be collected at baseline and at 16 months.

Brief summary: The goal of this observational study is to use the combined power of the integration of clinical, molecular, proteomic, genomic, care, social, environmental and behavioural data in patients, using advanced artificial intelligence techniques for data processing and analysis, in order to generate predictive models for the preclinical detection of CI in the population aged 55-70 years.

Detailed description: The "Comprehensive Plan for Alzheimer's and other Dementias" shows that more than 50% of cases of cognitive impairment (CI) in population-based studies are undetected. The figure is particularly striking in the case of mild dementias, of which up to 90% are undiagnosed. The aim is to use the combined power of the integration of clinical, molecular, proteomic, genomic, care, social, environmental and behavioural data in patients, using advanced artificial intelligence techniques for data processing and analysis, in order to generate predictive models for the preclinical detection of CI in the population aged 55-70 years.

Multicentre, non-interventional, convergent mixed methods observational study, with a prospective observational design part and a qualitative design part. Sample recruited randomly among users of the public health system in the participating geographical locations. Data will be collected in 6 regions (Andalucia, Castilla-Mancha, Catalonia, Valencia, Madrid and the Basque Country) and their rural and urban Primary Care (PC) networks.

Non-institutionalised subjects, aged between 55 and 70 years, assigned to PC centres in the territories included in the study, with a "living history" (recorded in the last 12 months) and without an established diagnosis of CI.

A descriptive analysis of the characteristics of the population will be carried out using frequencies and percentages or measures of central tendency and dispersion, with their 95% confidence intervals. Baseline socio-demographic and clinical characteristics will be compared in order to study the homogeneity of the sample. For the comparison of qualitative variables, the Chi-square test or Fisher's exact test will be used and for the comparison of quantitative variables, the t-test or Wilcoxon test will be used. Logistic regression models are proposed to analyse health outcome factors associated with mild cognitive impairment. All models will include repeated measures for each individual. All models will adjust for different risk factors, and for those factors that may change over time, the interaction between time and that factor will be studied.

Initially, multivariate linear latent models will be used for the predictive model of cognitive impairment risk. The integration of data from multiple sources of information will be done using multivariate probabilistic models, in order to find a representation of the patient in a feature space influenced by all data sources (visits).

Web tools such as Ingenuity Pathway Analysis will allow the integration of data at different molecular levels (genetic, protein and autoantibody), while artificial intelligence tools will allow the integration of such data, data derived from electrochemical sensors and data related to clinical and behavioural data with cognitive impairment in order to obtain a predictive model of cognitive impairment, neurodegeneration and AD.

Eligibility criteria: Inclusion Criteria:

* Non-institutionalised subjects from the study locations.
* Aged between 55 and 70 years, attached to the PC centres of the territories included in the study
* Living history (at least one record in the last 12 months)
* Without an established diagnosis of CI.

Exclusion Criteria:

* Participants with significant difficulties in completing self-reported questionnaires
* Those in whom genetic or biological testing may be affected by an underlying genetic or health condition.
* Underlying genetic or health condition.
* Patients who are hospitalised or institutionalised during follow-up will be excluded.

Primary outcomes:
measure: Cognitive level
timeFrame: 16 months
Secondary outcomes:
measure: multi-omics biomarkers
timeFrame: 16 months
measure: Social support network.
timeFrame: 16 months
measure: social interactions
timeFrame: 16 months
measure: personalised behavioural patterns.
timeFrame: 16 months
measure: Gait speed
timeFrame: 16 months
measure: The fluency and content of speech
timeFrame: 16 months
Other outcomes:
Locations:
city: San Vicente Del Raspeig
country: Spain
facility: Sant Vicent I Health Center
state: Alicante
city: Sant Boi De Llobregat
country: Spain
facility: Camps Blanc Health Center
state: Barcelona
city: Albacete
country: Spain
facility: Zone 8 Health Center
state: Castilla-La Mancha
city: Gibraleón
country: Spain
facility: Gibraleón Health Center
state: Huelva
city: Punta Umbría
country: Spain
facility: Punta Umbría Health Center
state: Huelva
city: Bilbao
country: Spain
facility: Irala Health Center
city: Lleida
country: Spain
facility: Onze de Setembre Health Center
city: Madrid
country: Spain
facility: San Andres Health Centre
Study officials:
affiliation: Consejo Superior de Investigaciones Científicas (CSIC)
name: Angeles Almeida, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: Instituto de Salud Carlos III
name: Rodrigo Barderas, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: Nursing and Healthcare Research Unit (Investén-isciii). Instituto de Salud Carlos III. Madrid
name: MARIA TERESA MORENO-CASBAS, PhD
role: PRINCIPAL_INVESTIGATOR
References: