Table 2.

Summary of quality assessment of included studies

Standard criteria		McElnay et al12	Tangiisuran13	Onder et al14	Trivalle et al15
Study design		Prospective cohort (development and validation)	Prospective cohort (development and validation)	Retrospective cohort (development) Prospective (validation)	Prospective cohort (development) Retrospective cohort (validation)
Participant recruitment	Clear inclusion criteria	Yes Development – Nonelective admissions – Medical, surgical, cardiac and geriatric, wards in a single hospital – >65 years old – Taking medicines Validation as above	Yes Development – Admitted to one of four care of the elderly wards in a teaching hospital – >80 years old Validation – Admitted to one of four European hospitals – ≥65 years old – Taking medicines	Yes Development – Selected community-and university-based hospital admissions – ≥65 years old – Taking medicines Validation as above except admitted to one of four European hospitals	Yes Development – Consecutive admissions to 16 geriatric rehabilitation centers Validation as above
	Evidence that patient selection was not biased	Unsure Data only collected from 50% of development-phase and 42% of validation-phase patients recruited who underwent interview	Yes All patient exclusions were for appropriately assessed reasons	Unsure An unknown number of patients were excluded due to incomplete data 61 cancer patients excluded	Unsure Data from 71 patients were excluded (these patients were either part of an intervention arm or not present for the whole 4 weeks of the study)
	Acceptably low rates of loss to follow-up	Yes Data from all patients who underwent interview were used in development and validation of model	Yes No patients lost to follow-up	Yes No patients lost to follow-up	Yes No patients lost to follow-up
Candidate predictor variablesa	Clear methods used to measure predictors	Partly 2/7 identified variables were not easily quantifiable (ie, “GI problems” and “patient thinks drugs are responsible for hospital admission”)	Mostly Data on 17 potential variables assessed Not clear how comorbidity, liver disease, previous history of ADR, or known allergy to medication were defined	Partly A trained physician completed a questionnaire for each patient, but unclear how key variables (comorbid conditions, liver disease, previous ADR) were defined or consistently applied between assessors	Partly Where candidate predictors were reported, they could be clearly described Potential candidate predictors that were not included in the model are unknown
	Blinding to outcome	Yes Data collected prospectively	Yes Data collected prospectively	Partly Blinding is not reported for the development phase Physicians collecting data for the validation phase were blinded	Yes Data collected prospectively
	Conformity with linear gradient	Not reported	Not reported	Not reported	Yes Linearity was checked where possible
	Test for colinearity	Partly Outlined in method but not mentioned in results	Partly Outlined in method but not mentioned in results	Not reported	Yes High-correlation risk factors were identified and examined in separate models
Outcomeb	Appropriate methods used to measure outcomes	Partly Data sourced from patient records and interviews ADE as defined by: – ADR (measured using modified Naranjo scale) – Adherence (self-reported)	Partly Medical information and health care staff reviewed daily using standardized checklist Suspected ADRs assessed for causality, preventability, and severity using Naranjo algorithm, Hallas criteria, and a confidence in causality Likert scale	Partly Wards visited daily, and nursing and medical records examined daily Causality was assessed based on Naranjo algorithm	Partly A combination of approaches used to identify ADEs: a self-generated standardized 32-item checklist was completed by nursing staff. Incident reporting and weekly chart review were also conducted. Four criteria were used to assign likelihood of causality
Statistical power	Sufficient events per variable (ie, > 10)	No Unable to determine exact number, but < 10	No 86 ADRs/34 candidate predictor variables =2.5	Yes Unable to determine exact number but > 10	Not possible to determine
Selection of predictor variables	Method of selection reported for independent variables	Partly Screened in univariate analysis and entered into model if P<0.25 Applicable to >5% of population	Yes Screened in univariate analysis and entered into model if P<0.05 Variables identified from other studies entered into model if P<0.25 Applicable to >5% of population	Yes Screened in univariate analysis and entered into model if P≤0.10	Yes Screened in univariate analysis and entered into model if P<0.05 Applicable to >5% of population
	Fitting procedure reported	Yes Stepwise backward-elimination procedures (using maximum likelihood method) Preliminary removal of variables at P=0.15 then P=0.05	Yes Multivariate logistic regression using backward-elimination procedure and forward selection Removal criteria P=0.10	Partly Stepwise logistic regression Added and retained variables if P≤0.1 Methods of variable elimination and retention were unclear	Partly Stepwise logistic regression Retained variables if P<0.05 Methods of variable elimination and retention were unclear
Model performance	Development phase reported	No	Yes Discrimination as AUROC reported with CI Calibration as Hosmer-Lemeshow and Nagelkerke R2 Sensitivity and specificity reported	Partly Discrimination as AUROC reported with CI Sensitivity and specificity reported	No
	Validation phase reported	Partly Only overall accuracy, sensitivity, and specificity reported	Yes Discrimination as AUROC reported with CI Sensitivity and specificity reported	Partly Discrimination as AUROC reported with CI	Partly Discrimination as AUROC reported with CI

Notes:

^aInteractions and coding were not dealt with in any of the studies.

^bAll studies collapsed continuous categorical data into binary outcomes.

Abbreviations: ADE, adverse drug event; ADR, adverse drug reaction; AUROC, area under the receiver operator curve; CI, confidence interval; GI, gastrointestinal