| アブストラクト | INTRODUCTION: Health policy in the UK and globally regarding dementia, emphasises prevention and risk reduction. These goals could be facilitated by automated assessment of dementia risk in primary care using routinely collected patient data. However, existing applicable tools are weak at identifying patients at high risk for dementia. We set out to develop improved risk prediction models deployable in primary care. METHODS: Electronic health records (EHRs) for patients aged 60-89 from 393 English general practices were extracted from the Clinical Practice Research Datalink (CPRD) GOLD database. 235 and 158 practices respectively were randomly assigned to development and validation cohorts. Separate dementia risk models were developed for patients aged 60-79 (development cohort n = 616,366; validation cohort n = 419,126) and 80-89 (n = 175,131 and n = 118,717). The outcome was incident dementia within 5 years and more than 60 evidence-based risk factors were evaluated. Risk models were developed and validated using multivariable Cox regression. RESULTS: The age 60-79 development cohort included 10,841 incident cases of dementia (6.3 per 1,000 person-years) and the age 80-89 development cohort included 15,994 (40.2 per 1,000 person-years). Discrimination and calibration for the resulting age 60-79 model were good (Harrell's C 0.78 (95% CI: 0.78 to 0.79); Royston's D 1.74 (1.70 to 1.78); calibration slope 0.98 (0.96 to 1.01)), with 37% of patients in the top 1% of risk scores receiving a dementia diagnosis within 5 years. Fit statistics were lower for the age 80-89 model but dementia incidence was higher and 79% of those in the top 1% of risk scores subsequently developed dementia. CONCLUSION: Our models can identify individuals at higher risk of dementia using routinely collected information from their primary care record, and outperform an existing EHR-based tool. Discriminative ability was greatest for those aged 60-79, but the model for those aged 80-89 may also be clinical useful. |
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| 投稿者 | Reeves, David; Morgan, Catharine; Stamate, Daniel; Ford, Elizabeth; Ashcroft, Darren M; Kontopantelis, Evangelos; Van Marwijk, Harm; McMillan, Brian |
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| 組織名 | Division of Population Health, NIHR School for Primary Care Research, Centre for;Primary Care, Health Services Research and Primary Care, University of;Manchester, Manchester, United Kingdom.;Division of Population Health, Centre for Biostatistics, Health Services Research;and Primary Care, University of Manchester, Manchester, United Kingdom.;Computing Department, Goldsmiths, University of London, London, United Kingdom.;Department of Primary Care and Public Health, Brighton and Sussex Medical School,;Brighton, United Kingdom.;Division of Pharmacy and Optometry, NIHR Greater Manchester Patient Safety;Research Collaboration, University of Manchester, Manchester, United Kingdom.;Centre for Pharmacoepidemiology and Drug Safety, School of Health Sciences,;Faculty of Biology, Medicine and Health, University of Manchester, Manchester,;United Kingdom.;Division of Informatics, Imaging and Data Sciences, University of Manchester,;Manchester, United Kingdom. |
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