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| DOI | 10.3233/JAD-215660 | ||||
| Año | 2022 | ||||
| Tipo | artículo de investigación |
Citas Totales
Autores Afiliación Chile
Instituciones Chile
% Participación
Internacional
Autores
Afiliación Extranjera
Instituciones
Extranjeras
Background: Several epidemiological studies report a negative association between Cancer and Alzheimer's disease (AD). Objective: To characterize the trajectories of memory loss in individuals with early amnestic cognitive impairment with and without history of previous cancer. Methods: Cognitive deterioration was assessed using the Montreal Cognitive Assessment (MoCA) or MoCA-Memory Index Score (MoCA-MIS) biannually in subjects with early amnestic cognitive impairment followed-up retrospectively from 2007 to 2021. History of Cancer was obtained from clinical records. Simple linear regressions of MoCA-MIS scores were calculated for each subject and analyzed with K-means cluster analysis to identify subgroups with different cognitive decline trajectories. χ2 and t tests were used for descriptive categorical and continuous variables and mixed multiple linear regressions to determine cognitive decline covariates. Results: Analysis of the trajectory of cognitive decline in 141 subjects with early amnestic cognitive impairment identified two subgroups: Fast (n = 60) and Slow (n = 81) progressors. At baseline Fast progressors had better MoCA-MIS (p < 0.001) and functionality (CDR p = 0.02, AD8 p = 0.05), took less anti-dementia medications (p = 0.005), and had higher depression rates (p = 0.02). Interestingly, Fast progressors slowed their speed of memory decline (from 1.6 to 1.1 MoCA-MIS points/year) and global cognitive decline (from 2.0 to 1.4 total MoCA points/year) when Cancer history was present. Conclusion: Two trajectories of amnestic cognitive decline were identified, possibly derived from different neurophysiopathologies or clinical stages. This study suggests that a history of previous Cancer slows down amnestic cognitive decline, specifically in a subgroup of subjects with depression at baseline and accelerated deterioration at follow-up.
| Ord. | Autor | Género | Institución - País |
|---|---|---|---|
| 1 | Castillo-Passi, Rolando I. | Hombre |
Hospital Clínico Universidad de Chile - Chile
Universidad del Desarrollo - Chile Núcleo Milenio para Mejorar la Salud Mental de Adolescentes y Jóvenes - Chile Clínica Psiquiátrica Universitaria - Chile Universidad de Chile - Chile Millennium Nucleus Improve Mental Hlth Adolescent - Chile |
| 2 | VERGARA-ORTUZAR, RODRIGO CLEMENTE | Hombre |
Universidad Metropolitana de Ciencias de la Educación - Chile
Centro Nacional de Inteligencia Artificial (CENIA) - Chile |
| 3 | Rogers, Nicole | Mujer |
Universidad de Chile - Chile
Instituto de Neurocirugía Alfonso Asenjo - Chile |
| 4 | PONCE-RAMIREZ, DANIELA PATRICIA | Mujer |
Hospital Clínico Universidad de Chile - Chile
Universidad de Chile - Chile |
| 5 | BENNETT-MANZANO, MAGDALENA | Mujer |
McCombs School of Business - Estados Unidos
Univ Texas Austin - Estados Unidos |
| 6 | Behrens, Maria I. | Mujer |
Hospital Clínico Universidad de Chile - Chile
Universidad de Chile - Chile Universidad del Desarrollo - Chile |
| Fuente |
|---|
| Fondo Nacional de Desarrollo Científico y Tecnológico |
| Ministry of Science and Technology |
| Agencia Nacional de Investigación y Desarrollo |
| ANID - Millennium Science Initiative Program |
| National Center for Artificial Intelligence |
| ANID National Center for Artificial Intelligence |
| ANID - National Center for Artificial Intelligence |
| Chilean Ministry of Science and Technology through FONDECYT |
| Agradecimiento |
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| This work was funded by the Chilean Ministry of Science and Technology through FONDECYT (grant number 1190958; 2019-2023), ANID National Center for Artificial Intelligence (FB 210017) and ANID Millennium Science Initiative Program (NCS 17035). |
| This work was funded by the Chilean Ministry of Science and Technology through FONDECYT (grant number 1190958; 2019-2023), ANID National Center for Artificial Intelligence (FB 210017) and ANID Millennium Science Initiative Program (NCS 17035). |
| This work was funded by the Chilean Ministry of Science and Technology through FONDECYT (grant number 1190958; 2019-2023), ANID - National Center for Artificial Intelligence (FB 210017) and ANID - Millennium Science Initiative Program (NCS 17035). |