Begashaw Melaku Gebresillassie , John Attia , Dominic Cavenagh , Melissa L. Harris
{"title":"开发、验证和临床应用的风险预测模型,以确定老年痴呆妇女主动姑息治疗","authors":"Begashaw Melaku Gebresillassie , John Attia , Dominic Cavenagh , Melissa L. Harris","doi":"10.1016/j.archger.2025.105853","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Accurately estimating one-year mortality risk in older women with dementia can inform clinical decision-making, facilitate timely advanced care planning, and optimise palliative care delivery. This study aimed to develop, validate, and assess the clinical utility of a prediction model for one-year all-cause mortality in this population using a nationally representative Australian cohort.</div></div><div><h3>Methods</h3><div>This prognostic study utilised data from the 1921–26 cohort of the nationally representative, population-based Australian Longitudinal Study on Women's Health (ALSWH) and linked national and state-based administrative health records. Candidate predictors were identified through a systematic review and expert consultation, then refined using a data-driven statistical approach. A multivariable binary logistic regression model was developed and validated to predict one-year all-cause mortality.</div></div><div><h3>Results</h3><div>The analysis included 1576 older women with dementia (mean age, 72.6 ± 1.5 years). The model demonstrated good discrimination (AUC: 75.1 %, 95 % CI: 72.7 %–77.5 %) and excellent calibration (slope = 1.00, 95 % CI: 0.87–1.13; intercept = 0.00, 95 % CI: 0.11 – 0.11). Model validation using both 10-fold cross-validation and 1000 bootstrap iterations showed minimal optimism in its predictive performance, with AUC optimism of 0.0047 and 0.0042, respectively. Decision curve analysis indicated a net benefit across probability thresholds from 0.24 to 0.88, supporting the model's clinical utility for guiding palliative care decisions.</div></div><div><h3>Conclusion</h3><div>This prediction model, incorporating readily available predictors, demonstrated compelling performance and clinical utility for identifying older women with dementia at high risk of one-year mortality. The model has the potential to facilitate timely palliative care interventions and is publicly accessible via a web-based calculator. Further external validation in diverse populations and healthcare settings is warranted to confirm its generalisability.</div></div>","PeriodicalId":8306,"journal":{"name":"Archives of gerontology and geriatrics","volume":"134 ","pages":"Article 105853"},"PeriodicalIF":3.5000,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development, validation, and clinical utility of a risk prediction model to identify older women with dementia for proactive palliative care\",\"authors\":\"Begashaw Melaku Gebresillassie , John Attia , Dominic Cavenagh , Melissa L. Harris\",\"doi\":\"10.1016/j.archger.2025.105853\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Accurately estimating one-year mortality risk in older women with dementia can inform clinical decision-making, facilitate timely advanced care planning, and optimise palliative care delivery. This study aimed to develop, validate, and assess the clinical utility of a prediction model for one-year all-cause mortality in this population using a nationally representative Australian cohort.</div></div><div><h3>Methods</h3><div>This prognostic study utilised data from the 1921–26 cohort of the nationally representative, population-based Australian Longitudinal Study on Women's Health (ALSWH) and linked national and state-based administrative health records. Candidate predictors were identified through a systematic review and expert consultation, then refined using a data-driven statistical approach. A multivariable binary logistic regression model was developed and validated to predict one-year all-cause mortality.</div></div><div><h3>Results</h3><div>The analysis included 1576 older women with dementia (mean age, 72.6 ± 1.5 years). The model demonstrated good discrimination (AUC: 75.1 %, 95 % CI: 72.7 %–77.5 %) and excellent calibration (slope = 1.00, 95 % CI: 0.87–1.13; intercept = 0.00, 95 % CI: 0.11 – 0.11). Model validation using both 10-fold cross-validation and 1000 bootstrap iterations showed minimal optimism in its predictive performance, with AUC optimism of 0.0047 and 0.0042, respectively. Decision curve analysis indicated a net benefit across probability thresholds from 0.24 to 0.88, supporting the model's clinical utility for guiding palliative care decisions.</div></div><div><h3>Conclusion</h3><div>This prediction model, incorporating readily available predictors, demonstrated compelling performance and clinical utility for identifying older women with dementia at high risk of one-year mortality. The model has the potential to facilitate timely palliative care interventions and is publicly accessible via a web-based calculator. Further external validation in diverse populations and healthcare settings is warranted to confirm its generalisability.</div></div>\",\"PeriodicalId\":8306,\"journal\":{\"name\":\"Archives of gerontology and geriatrics\",\"volume\":\"134 \",\"pages\":\"Article 105853\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of gerontology and geriatrics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167494325001116\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of gerontology and geriatrics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167494325001116","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
Development, validation, and clinical utility of a risk prediction model to identify older women with dementia for proactive palliative care
Background
Accurately estimating one-year mortality risk in older women with dementia can inform clinical decision-making, facilitate timely advanced care planning, and optimise palliative care delivery. This study aimed to develop, validate, and assess the clinical utility of a prediction model for one-year all-cause mortality in this population using a nationally representative Australian cohort.
Methods
This prognostic study utilised data from the 1921–26 cohort of the nationally representative, population-based Australian Longitudinal Study on Women's Health (ALSWH) and linked national and state-based administrative health records. Candidate predictors were identified through a systematic review and expert consultation, then refined using a data-driven statistical approach. A multivariable binary logistic regression model was developed and validated to predict one-year all-cause mortality.
Results
The analysis included 1576 older women with dementia (mean age, 72.6 ± 1.5 years). The model demonstrated good discrimination (AUC: 75.1 %, 95 % CI: 72.7 %–77.5 %) and excellent calibration (slope = 1.00, 95 % CI: 0.87–1.13; intercept = 0.00, 95 % CI: 0.11 – 0.11). Model validation using both 10-fold cross-validation and 1000 bootstrap iterations showed minimal optimism in its predictive performance, with AUC optimism of 0.0047 and 0.0042, respectively. Decision curve analysis indicated a net benefit across probability thresholds from 0.24 to 0.88, supporting the model's clinical utility for guiding palliative care decisions.
Conclusion
This prediction model, incorporating readily available predictors, demonstrated compelling performance and clinical utility for identifying older women with dementia at high risk of one-year mortality. The model has the potential to facilitate timely palliative care interventions and is publicly accessible via a web-based calculator. Further external validation in diverse populations and healthcare settings is warranted to confirm its generalisability.
期刊介绍:
Archives of Gerontology and Geriatrics provides a medium for the publication of papers from the fields of experimental gerontology and clinical and social geriatrics. The principal aim of the journal is to facilitate the exchange of information between specialists in these three fields of gerontological research. Experimental papers dealing with the basic mechanisms of aging at molecular, cellular, tissue or organ levels will be published.
Clinical papers will be accepted if they provide sufficiently new information or are of fundamental importance for the knowledge of human aging. Purely descriptive clinical papers will be accepted only if the results permit further interpretation. Papers dealing with anti-aging pharmacological preparations in humans are welcome. Papers on the social aspects of geriatrics will be accepted if they are of general interest regarding the epidemiology of aging and the efficiency and working methods of the social organizations for the health care of the elderly.