Risk prediction models for adverse drug reactions and adverse drug events in older adults-a systematic review and meta-analysis.

Abstract

Background: Adverse drug reactions (ADRs) are common and result in significant morbidity, mortality, and associated hospital costs. Models predicting ADRs in older adults were previously found to lack reliability and validity. This systematic review and meta-analysis aim to provide an updated, comprehensive quality assessment and analysis of ADR-risk prediction tools in older adults.

Methods: Standard databases and citations were searched (2012 to 2023) and studies which developed and/or validated an ADR prediction model for use in older adults were included. Four studies from a previous systematic review were also included. The TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) checklist was used to evaluate each study. Random effects models were used to derive a pooled discrimination estimate (area-under-the-receiver-operation curve; AUROC) for model development and validation studies.

Results: Eight studies, describing 6 ADR-risk prediction models met the inclusion criteria). In the meta-analysis, the pooled AUROC was 0.75 (95% CI 0.57, 0.87; I-squared = 96.88%) for model development studies and 0.73 (95% CI 0.52, 0.87; Isquared = 90.19%) for externally validated studies. Studies had poor adherence (range 34-50%; median 46.5%; IQR 12%) to TRIPOD guidelines.

Conclusion: The studies identified through this systematic review exhibit poor adherence to TRIPOD guidelines which may question the investigational rigor and the usability of the models. This underscores the urgent need to develop a validated, robust, and reliable tool worthy of implementation and testing in a real-world setting to gauge its impact and usability effectively.