Computer‐assisted prediction of clinical progression in the earliest stages of AD

Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring

Rosalinde E.R. Slot¹  Sander C.J. Verfaillie¹  Philip Scheltens¹  Linda M.P. Wesselman¹  Betty M. Tijms¹  Wiesje M. van derFlier¹  Sietske A.M. Sikkes¹  Hanneke F.M. Rhodius‐Meester¹  José Luis Molinuevo²  Nina Coll‐Padros²  Lorena Rami²  Jyrki Lötjönen³  Steffen Wolfsgruber⁴  Luca Kleineidam⁴  Johannes Kornhuber⁵  Oliver Peters⁶  Frank Jessen⁷  Frederik Barkhof⁸  Charlotte E. Teunissen⁹  Hilkka Liedes^1,10  Juha Koikkalainen^1,10 

[1] Alzheimer CenterDepartment of NeurologyVU University Medical CentreAmsterdam NeuroscienceAmsterdamthe Netherlands;Alzheimer's Disease and Other Cognitive Disorders UnitHospital Clínic, IDIBAPSBarcelonaSpain;Combinostics Ltd.TampereFinland;Department for Neurodegenerative Diseases and Geriatric PsychiatryUniversity of Bonn, Germany, and German Center for Neurodegenerative DiseasesBonnGermany;Department of Psychiatry and PsychotherapyUniversitätsklinikum Erlangen and Friedrich‐Alexander University Erlangen‐NürnbergErlangenGermany;Department of PsychiatryCharité BerlinCampus Benjamin FranklinBerlinGermany;Department of PsychiatryUniversity of CologneCologneGermany;Department of Radiology and Nuclear MedicineVU University Medical CentreAmsterdam NeuroscienceAmsterdamthe Netherlands;Neurochemistry Lab and BiobankDepartment of Clinical ChemistryVU University Medical CentreAmsterdam NeuroscienceAmsterdamthe Netherlands;VTT Technical Research Centre of Finland Ltd.TampereFinland;

关键词: Alzheimer's disease;    Prognosis;    Diagnostic test assessment;    Clinical decision support system;    Subjective cognitive decline;   

DOI  :  10.1016/j.dadm.2018.09.001

来源: DOAJ

【 摘 要 】

Abstract Introduction Individuals with subjective cognitive decline (SCD) are at increased risk for clinical progression. We studied how combining different diagnostic tests can help to identify individuals who are likely to show clinical progression. Methods We included 674 patients with SCD (46% female, 64 ± 9 years, Mini–Mental State Examination 28 ± 2) from three memory clinic cohorts. A multivariate model based on the Disease State Index classifier incorporated the available baseline tests to predict progression to MCI or dementia over time. We developed and internally validated the model in one cohort and externally validated it in the other cohorts. Results After 2.9 ± 2.0 years, 151(22%) patients showed clinical progression. Overall performance of the classifier when combining cognitive tests, magnetic resonance imagining, and cerebrospinal fluid showed a balanced accuracy of 74.0 ± 5.5, with high negative predictive value (93.3 ± 2.8). Discussion We found that a combination of diagnostic tests helps to identify individuals at risk of progression. The classifier had particularly good accuracy in identifying patients who remained stable.

【 授权许可】

Unknown