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基于横断面数据的首发精神病发病率的人群预测工具:转化流行病学。

A population-level prediction tool for the incidence of first-episode psychosis: translational epidemiology based on cross-sectional data.

机构信息

Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain & Mind Sciences, Cambridge, UK.

出版信息

BMJ Open. 2013 Feb 11;3(2). doi: 10.1136/bmjopen-2012-001998. Print 2013.

Abstract

OBJECTIVES

Specialist early intervention services (EIS) for people aged 14-35 years with first episodes of psychosis (FEP) have been commissioned throughout England since 2001. A single estimate of population need was used everywhere, but true incidence varies enormously according to sociodemographic factors. We sought to develop a realistically complex, population-based prediction tool for FEP, based on precise estimates of epidemiological risk.

DESIGN AND PARTICIPANTS

Data from 1037 participants in two cross-sectional population-based FEP studies were fitted to several negative binomial regression models to estimate risk coefficients across combinations of different sociodemographic and socioenvironmental factors. We applied these coefficients to the population at-risk of a third, socioeconomically different region to predict expected caseload over 2.5 years, where the observed rates of ICD-10 F10-39 FEP had been concurrently ascertained via EIS.

SETTING

Empirical population-based epidemiological data from London, Nottingham and Bristol predicted counts in the population at-risk in the East Anglia region of England.

MAIN OUTCOME MEASURES

Observed counts were compared with predicted counts (with 95% prediction intervals (PI)) at EIS and local authority district (LAD) levels in East Anglia to establish the predictive validity of each model.

RESULTS

A model with age, sex, ethnicity and population density performed most strongly, predicting 508 FEP participants in EIS in East Anglia (95% PI 459, 559), compared with 522 observed participants. This model predicted correctly in 5/6 EIS and 19/21 LADs. All models performed better than the current gold standard for EIS commissioning in England (716 cases; 95% PI 664-769).

CONCLUSIONS

We have developed a prediction tool for the incidence of psychotic disorders in England and Wales, made freely available online (http://www.psymaptic.org), to provide healthcare commissioners with accurate forecasts of FEP based on robust epidemiology and anticipated local population need. The initial assessment of some people who do not require subsequent EIS care means additional service resources, not addressed here, will be required.

摘要

目的

自 2001 年以来,英国各地为首次出现精神病发作(FEP)的 14-35 岁人群提供了专业的早期干预服务(EIS)。每个地方都使用了单一的人口需求估计值,但根据社会人口因素,实际发病率差异很大。我们试图根据流行病学风险的精确估计,为 FEP 开发一个现实复杂的基于人群的预测工具。

设计和参与者

从两项基于人群的 FEP 横断面研究的 1037 名参与者中获取的数据,拟合了几个负二项回归模型,以估计不同社会人口和社会环境因素组合下的风险系数。我们将这些系数应用于处于风险中的人群,该人群位于第三个具有不同社会经济状况的地区,以预测未来 2.5 年内的预期病例数,同时通过 EIS 同时确定了 ICD-10 F10-39 FEP 的实际发生率。

地点

来自伦敦、诺丁汉和布里斯托尔的实证基于人群的流行病学数据预测了英格兰东安格利亚地区处于风险中的人群的病例数。

主要结果

将观察到的病例数与 EIS 和东安格利亚地方当局区(LAD)的预测病例数(95%预测区间(PI))进行比较,以确定每个模型的预测有效性。

结果

一个包含年龄、性别、种族和人口密度的模型表现最为出色,预测了东安格利亚地区 EIS 中的 508 名 FEP 参与者(95%PI 为 459,559),而观察到的参与者为 522 名。该模型在 6 个 EIS 中的 5 个和 21 个 LAD 中的 19 个中预测正确。所有模型的表现均优于英格兰 EIS 委托的当前黄金标准(716 例;95%PI 为 664-769)。

结论

我们已经开发了一种用于预测英格兰和威尔士精神障碍发病率的预测工具,该工具可在网上免费获得(http://www.psymaptic.org),为医疗保健委员会提供基于可靠流行病学和预期当地人口需求的 FEP 准确预测。对于一些不需要后续 EIS 护理的人进行初步评估意味着需要额外的服务资源,这里没有涉及。

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