title: Predicting adverse drug reactions in older adults; a systematic review of the risk prediction models.
abstract: Adverse drug reaction (ADR) risk-prediction models for use in older adults have been developed, but it is not clear if they are suitable for use in clinical practice. This systematic review aimed to identify and investigate the quality of validated ADR risk-prediction models for use in older adults. Standard computerized databases, the gray literature, bibliographies, and citations were searched (2012) to identify relevant peer-reviewed studies. Studies that developed and validated an ADR prediction model for use in patients over 65 years old, using a multivariable approach in the design and analysis, were included. Data were extracted and their quality assessed by independent reviewers using a standard approach. Of the 13,423 titles identified, only 549 were associated with adverse outcomes of medicines use. Four met the inclusion criteria. All were conducted in inpatient cohorts in Western Europe. None of the models satisfied the four key stages in the creation of a quality risk prediction model; development and validation were completed, but impact and implementation were not assessed. Model performance was modest; area under the receiver operator curve ranged from 0.623 to 0.73. Study quality was difficult to assess due to poor reporting, but inappropriate methods were apparent. Further work needs to be conducted concerning the existing models to enable the development of a robust ADR risk-prediction model that is externally validated, with practical design and good performance. Only then can implementation and impact be assessed with the aim of generating a model of high enough quality to be considered for use in clinical care to prioritize older people at high risk of suffering an ADR.
authors.affiliation: Institute of Pharmaceutical Sciences, King's College London, London, UK ; Pharmacy Department, St Thomas' Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK.
authors.forename: Jennifer M
authors.initials: JM
authors.lastname: Stevenson
authors.affiliation: Institute of Pharmaceutical Sciences, King's College London, London, UK ; Pharmacy Department, St Thomas' Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK.
authors.forename: Josceline L
authors.initials: JL
authors.lastname: Williams
authors.affiliation: Pharmacy Department, St Thomas' Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK.
authors.forename: Thomas G
authors.initials: TG
authors.lastname: Burnham
authors.affiliation: Department of Primary Care and Public Health Sciences, King's College London, London, UK.
authors.forename: A Toby
authors.initials: AT
authors.lastname: Prevost
authors.affiliation: Department of Ageing and Health, Guy's and St Thomas' NHS Foundation Trust, London, UK.
authors.forename: Rebekah
authors.initials: R
authors.lastname: Schiff
authors.affiliation: Pharmacy Department, St Thomas' Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK.
authors.forename: S David
authors.initials: SD
authors.lastname: Erskine
authors.affiliation: Institute of Pharmaceutical Sciences, King's College London, London, UK.
authors.forename: J Graham
authors.initials: JG
authors.lastname: Davies
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems; D000367:Age Factors; D000368:Aged; D019540:Area Under Curve; D015331:Cohort Studies; D005060:Europe; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis; D055553:Prescription Drugs / Q000009:adverse effects*; D018570:Risk Assessment
chemical_list: D055553:Prescription Drugs
keywords: aged; medication-related harm; prognosis; stratified care