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开发和验证一种用于估计社区居住的痴呆症患者生存的临床预测工具的方案。

Development and validation of a clinical prediction tool to estimate survival in community-dwelling adults living with dementia: a protocol.

机构信息

Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada

Sunnybrook Research Institute, Toronto, Ontario, Canada.

出版信息

BMJ Open. 2024 Nov 17;14(11):e086231. doi: 10.1136/bmjopen-2024-086231.

DOI:10.1136/bmjopen-2024-086231
PMID:39551579
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11574448/
Abstract

INTRODUCTION

A clinical prediction tool to estimate life expectancy in community-dwelling individuals living with dementia could inform healthcare decision-making and prompt future planning. An existing Ontario-based tool for community-dwelling elderly individuals does not perform well in people living with dementia specifically. This study seeks to develop and validate a clinical prediction tool to estimate survival in community-dwelling individuals living with dementia receiving home care in Ontario, Canada.

METHODS AND ANALYSIS

This will be a population-level retrospective cohort study that will use data in linked healthcare administrative databases at ICES. Specifically, data that are routinely collected from regularly administered assessments for home care will be used. Community-dwelling individuals living with dementia receiving home care at any point between April 2010 and March 2020 will be included (N≈200 000). The model will be developed in the derivation cohort (N≈140 000), which includes individuals with a randomly selected home care assessment between 2010 and 2017. The outcome variable will be survival time from index assessment. The selection of predictor variables will be fully prespecified and literature/expert-informed. The model will be estimated using a Cox proportional hazards model. The model's performance will be assessed in a temporally distinct validation cohort (N≈60 000), which includes individuals with an assessment between 2018 and 2020. Overall performance will be assessed using Nagelkerke's R, discrimination using the concordance statistic and calibration using the calibration curve. Overfitting will be assessed visually and statistically. Model performance will be assessed in the validation cohort and in prespecified subgroups.

ETHICS AND DISSEMINATION

The study received research ethics board approval from the Sunnybrook Health Sciences Centre (SUN-6138). Abstracts of the project will be submitted to academic conferences, and a manuscript thereof will be submitted to a peer-reviewed journal for publication. The model will be disseminated on a publicly accessible website (www.projectbiglife.com).

TRIAL REGISTRATION NUMBER

NCT06266325 (clinicaltrials.gov).

摘要

简介

为了辅助医疗决策并促进未来规划,我们需要制定一个能预估居住在社区中的痴呆患者预期寿命的临床预测工具。现有的安大略省老年人群用工具在针对痴呆患者时效果不佳。本研究旨在为居住在社区中的接受安大略省家庭护理的痴呆患者开发并验证一个临床预测工具,以预估其生存情况。

方法和分析

这将是一个基于人群的回顾性队列研究,使用安大略省临床评估科学研究所(ICES)的相关链接医疗行政数据库的数据。具体来说,将使用定期进行的家庭护理评估中常规收集的数据。研究将纳入 2010 年 4 月至 2020 年 3 月期间任何时间点接受家庭护理的居住在社区中的痴呆患者(N≈200000)。该模型将在推导队列(N≈140000)中进行开发,其中包括 2010 年至 2017 年期间随机选择的家庭护理评估中的个体。结果变量将是从索引评估开始的生存时间。预测变量的选择将是完全预先确定的,并基于文献和专家建议。该模型将使用 Cox 比例风险模型进行估计。该模型的性能将在一个时间上明显不同的验证队列(N≈60000)中进行评估,其中包括 2018 年至 2020 年期间接受评估的个体。整体性能将通过 Nagelkerke 的 R 进行评估,通过一致性统计数据进行区分,通过校准曲线进行校准。过度拟合将通过视觉和统计学进行评估。将在验证队列和预定义的亚组中评估模型性能。

伦理和传播

该研究已获得 Sunnybrook 健康科学中心(SUN-6138)的伦理审查委员会的批准。该项目的摘要将提交给学术会议,并将其论文提交给同行评议期刊进行发表。该模型将在一个公共可访问的网站(www.projectbiglife.com)上发布。

试验注册编号

NCT06266325(clinicaltrials.gov)。

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本文引用的文献

1
Developing clinical prediction models: a step-by-step guide.临床预测模型的建立:分步指南。
BMJ. 2024 Sep 3;386:e078276. doi: 10.1136/bmj-2023-078276.
2
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods.TRIPOD+AI 声明:报告使用回归或机器学习方法的临床预测模型的更新指南。
BMJ. 2024 Apr 16;385:e078378. doi: 10.1136/bmj-2023-078378.
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Evaluation of clinical prediction models (part 1): from development to external validation.临床预测模型的评估(第 1 部分):从建立到外部验证。
BMJ. 2024 Jan 8;384:e074819. doi: 10.1136/bmj-2023-074819.
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Improving Clinical Applicability of Mortality Prediction Models Among Persons With Dementia.提高痴呆症患者死亡率预测模型的临床适用性。
JAMA Intern Med. 2023 May 1;183(5):498. doi: 10.1001/jamainternmed.2023.0173.
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Effects of Palliative Care for Progressive Neurologic Diseases: A Systematic Review and Meta-Analysis.姑息治疗对进行性神经疾病的影响:一项系统评价与荟萃分析
J Am Med Dir Assoc. 2023 Feb;24(2):171-184. doi: 10.1016/j.jamda.2022.11.001. Epub 2022 Dec 5.
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Development and External Validation of a Mortality Prediction Model for Community-Dwelling Older Adults With Dementia.社区居住的老年痴呆症患者死亡率预测模型的建立和外部验证。
JAMA Intern Med. 2022 Nov 1;182(11):1161-1170. doi: 10.1001/jamainternmed.2022.4326.
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Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer's disease.阿尔茨海默病全谱患者机构化和死亡的多变量预测模型的开发。
Alzheimers Res Ther. 2022 Aug 5;14(1):110. doi: 10.1186/s13195-022-01053-0.
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Accuracy of two prognostic indexes to predict mortality in older adults with advanced dementia.两种预后指标预测晚期痴呆老年人死亡率的准确性。
Dement Neuropsychol. 2022 Jan-Mar;16(1):52-60. doi: 10.1590/1980-5764-DN-2021-0028.
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A national study of disenrollment from hospice among people with dementia.一项针对痴呆症患者退出临终关怀的全国性研究。
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Association of Diagnosed Dementia with Post-discharge Mortality and Readmission Among Hospitalized Medicare Beneficiaries.诊断为痴呆症与住院 Medicare 受益人的出院后死亡率和再入院率的关联。
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