Cognitive screening with functional assessment improves diagnostic accuracy and attenuates bias
Abstract Introduction Cognitive screening measures often lack sensitivity and are hampered by inequities across ethnoracial groups. A multitrait multimethod (MTMM) classification may attenuate these shortcomings. Methods A sample of 7227 participants across the diagnostic spectrum were selected from...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/dad2.12250 |
| _version_ | 1797975563125653504 |
|---|---|
| author | David Andrés González Mitzi M. Gonzales Kyle J. Jennette Jason R. Soble Bernard Fongang |
| author_facet | David Andrés González Mitzi M. Gonzales Kyle J. Jennette Jason R. Soble Bernard Fongang |
| author_sort | David Andrés González |
| collection | DOAJ |
| description | Abstract Introduction Cognitive screening measures often lack sensitivity and are hampered by inequities across ethnoracial groups. A multitrait multimethod (MTMM) classification may attenuate these shortcomings. Methods A sample of 7227 participants across the diagnostic spectrum were selected from the National Alzheimer's Coordinating Center cohort. Random forest ensemble methods were used to predict diagnosis across the sample and within Black American (n = 1025) and non‐Hispanic White groups (n = 5263) based on: (1) a demographically corrected Montreal Cognitive Assessment (MoCA), (2) MoCA and Functional Assessment Questionnaire (FAQ), (3) MoCA and FAQ with demographic correction. Results The MTMM approach with demographic correction had the highest diagnostic accuracy for the cognitively unimpaired (area under curve [AUC] [95% confidence interval (CI)]): 0.906 [0.892, 0.920]) and mild cognitive impairment (AUC: 0.835 [0.810, 0.860]) groups and reduced racial disparities. Discussion With further validation, the MTMM approach combining cognitive screening and functional status assessment may serve to improve diagnostic accuracy and extend opportunities for early intervention with greater equity. |
| first_indexed | 2024-04-11T04:37:32Z |
| format | Article |
| id | doaj.art-ffbe1d03ca814570a5b74ce0b96c0eff |
| institution | Directory Open Access Journal |
| issn | 2352-8729 |
| language | English |
| last_indexed | 2024-04-11T04:37:32Z |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring |
| spelling | doaj.art-ffbe1d03ca814570a5b74ce0b96c0eff2022-12-28T09:12:14ZengWileyAlzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring2352-87292021-01-01131n/an/a10.1002/dad2.12250Cognitive screening with functional assessment improves diagnostic accuracy and attenuates biasDavid Andrés González0Mitzi M. Gonzales1Kyle J. Jennette2Jason R. Soble3Bernard Fongang4Department of Neurology University of Texas Health Science Center at San Antonio San Antonio Texas USADepartment of Neurology University of Texas Health Science Center at San Antonio San Antonio Texas USADepartment of Psychiatry University of Illinois College of Medicine Chicago Illinois USADepartment of Psychiatry University of Illinois College of Medicine Chicago Illinois USAGlenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases University of Texas Health Science Center at San Antonio San Antonio Texas USAAbstract Introduction Cognitive screening measures often lack sensitivity and are hampered by inequities across ethnoracial groups. A multitrait multimethod (MTMM) classification may attenuate these shortcomings. Methods A sample of 7227 participants across the diagnostic spectrum were selected from the National Alzheimer's Coordinating Center cohort. Random forest ensemble methods were used to predict diagnosis across the sample and within Black American (n = 1025) and non‐Hispanic White groups (n = 5263) based on: (1) a demographically corrected Montreal Cognitive Assessment (MoCA), (2) MoCA and Functional Assessment Questionnaire (FAQ), (3) MoCA and FAQ with demographic correction. Results The MTMM approach with demographic correction had the highest diagnostic accuracy for the cognitively unimpaired (area under curve [AUC] [95% confidence interval (CI)]): 0.906 [0.892, 0.920]) and mild cognitive impairment (AUC: 0.835 [0.810, 0.860]) groups and reduced racial disparities. Discussion With further validation, the MTMM approach combining cognitive screening and functional status assessment may serve to improve diagnostic accuracy and extend opportunities for early intervention with greater equity.https://doi.org/10.1002/dad2.12250cognitive screeningdiagnostic accuracyFunctional Activities Questionnaire (FAQ)Montreal Cognitive Assessment (MoCA)random forest |
| spellingShingle | David Andrés González Mitzi M. Gonzales Kyle J. Jennette Jason R. Soble Bernard Fongang Cognitive screening with functional assessment improves diagnostic accuracy and attenuates bias Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring cognitive screening diagnostic accuracy Functional Activities Questionnaire (FAQ) Montreal Cognitive Assessment (MoCA) random forest |
| title | Cognitive screening with functional assessment improves diagnostic accuracy and attenuates bias |
| title_full | Cognitive screening with functional assessment improves diagnostic accuracy and attenuates bias |
| title_fullStr | Cognitive screening with functional assessment improves diagnostic accuracy and attenuates bias |
| title_full_unstemmed | Cognitive screening with functional assessment improves diagnostic accuracy and attenuates bias |
| title_short | Cognitive screening with functional assessment improves diagnostic accuracy and attenuates bias |
| title_sort | cognitive screening with functional assessment improves diagnostic accuracy and attenuates bias |
| topic | cognitive screening diagnostic accuracy Functional Activities Questionnaire (FAQ) Montreal Cognitive Assessment (MoCA) random forest |
| url | https://doi.org/10.1002/dad2.12250 |
| work_keys_str_mv | AT davidandresgonzalez cognitivescreeningwithfunctionalassessmentimprovesdiagnosticaccuracyandattenuatesbias AT mitzimgonzales cognitivescreeningwithfunctionalassessmentimprovesdiagnosticaccuracyandattenuatesbias AT kylejjennette cognitivescreeningwithfunctionalassessmentimprovesdiagnosticaccuracyandattenuatesbias AT jasonrsoble cognitivescreeningwithfunctionalassessmentimprovesdiagnosticaccuracyandattenuatesbias AT bernardfongang cognitivescreeningwithfunctionalassessmentimprovesdiagnosticaccuracyandattenuatesbias |