Fisher Stacey, Hsu Amy, Mojaverian Nassim, Taljaard Monica, Huyer Gregory, Manuel Douglas G, Tanuseputro Peter
Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
Institute for Clinical Evaluative Sciences, Ottawa, Ontario, Canada.
BMJ Open. 2017 Oct 24;7(10):e018018. doi: 10.1136/bmjopen-2017-018018.
The burden of disease from dementia is a growing global concern as incidence increases dramatically with age, and average life expectancy has been increasing around the world. Planning for an ageing population requires reliable projections of dementia prevalence; however, existing population projections are simple and have poor predictive accuracy. The Dementia Population Risk Tool (DemPoRT) will predict incidence of dementia in the population setting using multivariable modelling techniques and will be used to project dementia prevalence.
The derivation cohort will consist of elderly Ontario respondents of the Canadian Community Health Survey (CCHS) (2001, 2003, 2005 and 2007; 18 764 males and 25 288 females). Prespecified predictors include sociodemographic, general health, behavioural, functional and health condition variables. Incident dementia will be identified through individual linkage of survey respondents to population-level administrative healthcare databases (1797 and 3281 events, and 117 795 and 166 573 person-years of follow-up, for males and females, respectively, until 31 March 2014). Using time of first dementia capture as the primary outcome and death as a competing risk, sex-specific proportional hazards regression models will be estimated. The 2008/2009 CCHS survey will be used for validation (approximately 4600 males and 6300 females). Overall calibration and discrimination will be assessed as well as calibration within predefined subgroups of importance to clinicians and policy makers.
Research ethics approval has been granted by the Ottawa Health Science Network Research Ethics Board. DemPoRT results will be submitted for publication in peer-review journals and presented at scientific meetings. The algorithm will be assessable online for both population and individual uses.
ClinicalTrials.gov NCT03155815, pre-results.
随着痴呆症发病率随年龄急剧上升，且全球平均预期寿命不断增加，痴呆症导致的疾病负担日益引起全球关注。为老龄化人口制定规划需要对痴呆症患病率进行可靠预测；然而，现有的人口预测方法简单，预测准确性差。痴呆症人口风险工具（DemPoRT）将使用多变量建模技术预测人群中痴呆症的发病率，并将用于预测痴呆症患病率。
推导队列将由加拿大社区健康调查（CCHS）（2001年、2003年、2005年和2007年）中的安大略省老年受访者组成（18764名男性和25288名女性）。预先设定的预测因素包括社会人口统计学、一般健康状况、行为、功能和健康状况变量。通过将调查受访者与人群层面的行政医疗保健数据库进行个体关联来识别新发痴呆症（截至2014年3月31日，男性和女性分别有1797例和3281例事件，以及117795人和166573人年的随访）。以首次确诊痴呆症的时间作为主要结局，以死亡作为竞争风险，估计性别特异性比例风险回归模型。2008/2009年CCHS调查将用于验证（约4600名男性和6300名女性）。将评估总体校准和区分度，以及在对临床医生和政策制定者重要的预定义亚组内的校准情况。
渥太华健康科学网络研究伦理委员会已批准研究伦理。DemPoRT结果将提交至同行评审期刊发表，并在科学会议上展示。该算法将可供在线评估，用于人群和个体用途。
ClinicalTrials.gov NCT03155815，预结果。
