(139) Risk Prediction Models for Adverse Drug Reactions and Adverse Drug Events in Older Adults – A Systematic Review

Background: Adverse drug reactions (ADRs) and adverse drug events (ADEs) are common and result in significant morbidity, mortality and healthcare costs. As the world’s population ages, the consumption of medications and healthcare in general will increase. Models predicting ADR risks in older adults have previously been found to lack reliability and validity and a quality assessment of the studies using CHARMs or Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) were not applied.

Objectives: The aim of this systematic review and meta-analysis is to provide an updated, comprehensive quality assessment and analysis of ADR-risk prediction tools in older adults.

Methods: Standard databases (Ovid Medline and Embase) and citations were searched (2012 to 2023) to identify relevant peer-reviewed studies. Studies which developed and/or validated an ADR/ADE prediction model for use in older adults and published in English 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 and adherence form was used to evaluate each of the included studies. Random effects models were used to derive a pooled discrimination estimate (area under the receiver operation curve; AUROC) for model development studies and model validation studies. The prediction model risk of bias assessment tool (PROBAST) was also applied to evaluate bias.

Results: In total 8 studies, describing 6 ADR/ADE risk prediction models met the inclusion criteria and underwent TRIPOD evaluation). Model performance was poor to very good; AUROC ranged from 0.592 to 0.917 (median 0.675; IQR 0.17). In the meta-analysis the pooled AUROC was 0.75 (95% CI 0.57, 0.87; I-squared= 96.65%) for model development studies and 0.70 (95% CI 0.57, 0.80; I-squared= 90.53%) for model validation studies. Studies had poor adherence (range 34-50%; median 45.5%; IQR 12%) to TRIPOD guidelines with studies performing poorly in terms of candidate variables (20%), study size (10%), missing data (40%) and external validation (10%). The overall risk of bias was high for all included studies.

Conclusions: Six ADR-ADE risk prediction models from 8 studies were identified through this systematic review, exhibiting poor adherence to TRIPOD guidelines which may question the investigational rigor of the studies and the usability of the models. This underscores the urgent need for the development of a validated, robust and reliable tool worthy of implementation and testing in a real-world setting to gauge its impact and usability effectively.