Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study
Introduction In population-based research, disease ascertainment algorithms can be as accurate as, and less costly than, performing supplementary clinical examinations on selected participants to confirm a diagnosis of a neurocognitive disorder (NCD), but they require cohort-specific validation. To...
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BMJ Publishing Group
2023-11-01
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| author | Verena Menec Teresa Liu-Ambrose David B Hogan Megan E O’Connell Mary Thompson Andrew P Costa Eric E Smith Changbao Wu Aaron Jones Andrew Wister Christina Wolfson Parminder Raina Jinhui Ma Lauren E Griffith Christopher Patterson Alexandra J Mayhew Benoit Cossette David Hogan Howard Chertkow Susan Kirkland Megan O'Connell Vanessa Taler Andrew Costa Jacqueline McMillan Gerry Mugford Theone Paterson |
| author_facet | Verena Menec Teresa Liu-Ambrose David B Hogan Megan E O’Connell Mary Thompson Andrew P Costa Eric E Smith Changbao Wu Aaron Jones Andrew Wister Christina Wolfson Parminder Raina Jinhui Ma Lauren E Griffith Christopher Patterson Alexandra J Mayhew Benoit Cossette David Hogan Howard Chertkow Susan Kirkland Megan O'Connell Vanessa Taler Andrew Costa Jacqueline McMillan Gerry Mugford Theone Paterson |
| collection | DOAJ |
| description | Introduction In population-based research, disease ascertainment algorithms can be as accurate as, and less costly than, performing supplementary clinical examinations on selected participants to confirm a diagnosis of a neurocognitive disorder (NCD), but they require cohort-specific validation. To optimise the use of the Canadian Longitudinal Study on Aging (CLSA) to understand the epidemiology and burden of NCDs, the CLSA Memory Study will validate an NCD ascertainment algorithm to identify CLSA participants with these disorders using routinely acquired study data.Methods and analysis Up to 600 CLSA participants with equal numbers of those likely to have no NCD, mild NCD or major NCD based on prior self-reported physician diagnosis of a memory problem or dementia, medication consumption (ie, cholinesterase inhibitors, memantine) and/or self-reported function will be recruited during the follow-up 3 CLSA evaluations (started August 2021). Participants will undergo an assessment by a study clinician who will also review an informant interview and make a preliminary determination of the presence or absence of an NCD. The clinical assessment and available CLSA data will be reviewed by a Central Review Panel who will make a final categorisation of participants as having (1) no NCD, (2) mild NCD or, (3) major NCD (according to fifth version of the Diagnostic and Statistical Manual of Mental Disorders criteria). These will be used as our gold standard diagnosis to determine if the NCD ascertainment algorithm accurately identifies CLSA participants with an NCD. Weighted Kappa statistics will be the primary measure of agreement. Sensitivity, specificity, the C-statistic and the phi coefficient will also be estimated.Ethics and dissemination Ethics approval has been received from the institutional research ethics boards for each CLSA Data Collection Site (Université de Sherbrooke, Hamilton Integrated Research Ethics Board, Dalhousie University, Nova Scotia Health Research Ethics Board, University of Manitoba, McGill University, McGill University Health Centre Research Institute, Memorial University of Newfoundland, University of Victoria, Élisabeth Bruyère Research Institute of Ottawa, University of British Columbia, Island Health (Formerly the Vancouver Island Health Authority, Simon Fraser University, Calgary Conjoint Health Research Ethics Board).The results of this work will be disseminated to public health professionals, researchers, health professionals, administrators and policy-makers through journal publications, conference presentations, publicly available reports and presentations to stakeholder groups. |
| format | Article |
| id | doaj-art-cc7f4e7d020d4a79a41a9e26c0f7bb18 |
| institution | OA Journals |
| issn | 2044-6055 |
| language | English |
| publishDate | 2023-11-01 |
| publisher | BMJ Publishing Group |
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| series | BMJ Open |
| spelling | doaj-art-cc7f4e7d020d4a79a41a9e26c0f7bb182025-08-20T01:48:14ZengBMJ Publishing GroupBMJ Open2044-60552023-11-01131110.1136/bmjopen-2023-073027Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study 0Verena MenecTeresa Liu-Ambrose1David B HoganMegan E O’ConnellMary Thompson2Andrew P Costa3Eric E Smith4Changbao Wu5Aaron Jones6Andrew Wister7Christina Wolfson8Parminder Raina9Jinhui Ma10Lauren E Griffith11Christopher PattersonAlexandra J Mayhew12Benoit CossetteDavid Hogan13Howard Chertkow14Susan Kirkland15Megan O'Connell16Vanessa Taler17Andrew Costa18Jacqueline McMillanGerry MugfordTheone PatersonSPRinG Network, Severn and Peninsula Deaneries, UKDepartment of Physical Therapy, University of British Columbia, Vancouver, British Columbia, CanadaDepartment of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, CanadaICES, Toronto, Ontario, CanadaDepartment of Clinical Neurosciences & Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, CanadaDepartment of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, CanadaDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, CanadaDepartment of Gerontology, Simon Fraser University, Vancouver, British Columbia, CanadaDepartment of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montreal, Quebec, CanadaDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, CanadaDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, CanadaDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, CanadaLabarge Centre for Mobility in Aging, McMaster University, Hamilton, Ontario, CanadaBrenda Strafford Centre on Aging, `O’Brien Institute for Public Health, University of Calgary, Calgary, Alberta, CanadaDepartment of Medicine (Neurology), University of Toronto, Toronto, Ontario, CanadaDepartment of Community Health & Epidemiology, Dalhousie University, Halifax, Nova Scotia, CanadaDepartment of Psychology, University of Saskatchewan, Saskatoon, Saskatchewan, CanadaSchool of Psychology, University of Ottawa, Ottawa, Ontario, Canada1 Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, CanadaIntroduction In population-based research, disease ascertainment algorithms can be as accurate as, and less costly than, performing supplementary clinical examinations on selected participants to confirm a diagnosis of a neurocognitive disorder (NCD), but they require cohort-specific validation. To optimise the use of the Canadian Longitudinal Study on Aging (CLSA) to understand the epidemiology and burden of NCDs, the CLSA Memory Study will validate an NCD ascertainment algorithm to identify CLSA participants with these disorders using routinely acquired study data.Methods and analysis Up to 600 CLSA participants with equal numbers of those likely to have no NCD, mild NCD or major NCD based on prior self-reported physician diagnosis of a memory problem or dementia, medication consumption (ie, cholinesterase inhibitors, memantine) and/or self-reported function will be recruited during the follow-up 3 CLSA evaluations (started August 2021). Participants will undergo an assessment by a study clinician who will also review an informant interview and make a preliminary determination of the presence or absence of an NCD. The clinical assessment and available CLSA data will be reviewed by a Central Review Panel who will make a final categorisation of participants as having (1) no NCD, (2) mild NCD or, (3) major NCD (according to fifth version of the Diagnostic and Statistical Manual of Mental Disorders criteria). These will be used as our gold standard diagnosis to determine if the NCD ascertainment algorithm accurately identifies CLSA participants with an NCD. Weighted Kappa statistics will be the primary measure of agreement. Sensitivity, specificity, the C-statistic and the phi coefficient will also be estimated.Ethics and dissemination Ethics approval has been received from the institutional research ethics boards for each CLSA Data Collection Site (Université de Sherbrooke, Hamilton Integrated Research Ethics Board, Dalhousie University, Nova Scotia Health Research Ethics Board, University of Manitoba, McGill University, McGill University Health Centre Research Institute, Memorial University of Newfoundland, University of Victoria, Élisabeth Bruyère Research Institute of Ottawa, University of British Columbia, Island Health (Formerly the Vancouver Island Health Authority, Simon Fraser University, Calgary Conjoint Health Research Ethics Board).The results of this work will be disseminated to public health professionals, researchers, health professionals, administrators and policy-makers through journal publications, conference presentations, publicly available reports and presentations to stakeholder groups.https://bmjopen.bmj.com/content/13/11/e073027.full |
| spellingShingle | Verena Menec Teresa Liu-Ambrose David B Hogan Megan E O’Connell Mary Thompson Andrew P Costa Eric E Smith Changbao Wu Aaron Jones Andrew Wister Christina Wolfson Parminder Raina Jinhui Ma Lauren E Griffith Christopher Patterson Alexandra J Mayhew Benoit Cossette David Hogan Howard Chertkow Susan Kirkland Megan O'Connell Vanessa Taler Andrew Costa Jacqueline McMillan Gerry Mugford Theone Paterson Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study BMJ Open |
| title | Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study |
| title_full | Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study |
| title_fullStr | Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study |
| title_full_unstemmed | Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study |
| title_short | Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study |
| title_sort | protocol for validating an algorithm to identify neurocognitive disorders in canadian longitudinal study on aging participants an observational study |
| url | https://bmjopen.bmj.com/content/13/11/e073027.full |
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