Citation

Dormosh N, van de Loo B, Heymans MW, Schut MC, Medlock S, van Schoor NM, van der Velde N, Abu-Hanna A. Age Ageing 2024; 53(7).

Copyright

(Copyright © 2024, Oxford University Press)

DOI

10.1093/ageing/afae131

PMID

38979796

PMCID

PMC11231951

Abstract

BACKGROUND: Prediction models can identify fall-prone individuals. Prediction models can be based on either data from research cohorts (cohort-based) or routinely collected data (RCD-based). We review and compare cohort-based and RCD-based studies describing the development and/or validation of fall prediction models for community-dwelling older adults.

METHODS: Medline and Embase were searched via Ovid until January 2023. We included studies describing the development or validation of multivariable prediction models of falls in older adults (60+). Both risk of bias and reporting quality were assessed using the PROBAST and TRIPOD, respectively.

RESULTS: We included and reviewed 28 relevant studies, describing 30 prediction models (23 cohort-based and 7 RCD-based), and external validation of two existing models (one cohort-based and one RCD-based). The median sample sizes for cohort-based and RCD-based studies were 1365 [interquartile range (IQR) 426-2766] versus 90 441 (IQR 56 442-128 157), and the ranges of fall rates were 5.4% to 60.4% versus 1.6% to 13.1%, respectively. Discrimination performance was comparable between cohort-based and RCD-based models, with the respective area under the receiver operating characteristic curves ranging from 0.65 to 0.88 versus 0.71 to 0.81. The median number of predictors in cohort-based final models was 6 (IQR 5-11); for RCD-based models, it was 16 (IQR 11-26). All but one cohort-based model had high bias risks, primarily due to deficiencies in statistical analysis and outcome determination.

CONCLUSIONS: Cohort-based models to predict falls in older adults in the community are plentiful. RCD-based models are yet in their infancy but provide comparable predictive performance with no additional data collection efforts. Future studies should focus on methodological and reporting quality.

Language: en

Keywords

Humans; Risk Factors; Aged; Female; Male; accidental falls; systematic review; Age Factors; Risk Assessment; Aged, 80 and over; Reproducibility of Results; older people; Predictive Value of Tests; Models, Statistical; electronic health records; prediction models; *Accidental Falls/statistics & numerical data; Geriatric Assessment/methods; *Independent Living/statistics & numerical data; geriatric medicine; prospective cohorts; risk stratification tools; routinely collected data