Concordance Between Anticholinergic Burden Scales.
OBJECTIVE
To evaluate concordance of five commonly used anticholinergic scales.


METHODS
Cross-sectional secondary analysis.


METHODS
Pittsburgh, Pennsylvania, and Memphis, Tennessee.


METHODS
Community-dwelling adults aged 70 to 79 with baseline medication data from the Health, Aging, and Body Composition Study (N = 3,055).


METHODS
Any anticholinergic use, weighted scores, and total standardized daily dosage were calculated using five anticholinergic measures (Anticholinergic Cognitive Burden (ACB) Scale, Anticholinergic Drug Scale (ADS), Anticholinergic Risk Scale (ARS), Drug Burden Index anticholinergic component (DBI-ACh), and Summated Anticholinergic Medications Scale (SAMS)). Concordance was evaluated using kappa statistics and Spearman rank correlations.


RESULTS
Any anticholinergic use in rank order was 51% for the ACB, 43% for the ADS, 29% for the DBI-ACh, 23% for the ARS, and 16% for the SAMS. Kappa statistics for all pairwise use comparisons ranged from 0.33 to 0.68. Similarly, concordance as measured using weighted kappa statistics ranged from 0.54 to 0.70 for the three scales not incorporating dosage (ADS, ARS, ACB). Spearman rank correlation between the DBI-ACh and SAMS was 0.50.


CONCLUSIONS
Only low to moderate concordance was found between the five anticholinergic scales. Future research is needed to examine how these differences in measurement affect their predictive validity with respect to clinically relevant outcomes, such as cognitive impairment.
Division of Geriatrics, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.|Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania.|Center for Health Equity Research and Geriatric Research Education and Clinical Center, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania.
Jennifer G
JG
Naples
School of Pharmacy, University of Washington, Seattle, Washington.
Zachary A
ZA
Marcum
Division of Geriatrics, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.|Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
Subashan
S
Perera
School of Pharmacy, University of Washington, Seattle, Washington.
Shelly L
SL
Gray
Division of Geriatrics, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.|Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
Anne B
AB
Newman
Intramural Research Program, National Institute on Aging, Baltimore, Maryland.
Eleanor M
EM
Simonsick
Department of Psychiatry, University of California at San Francisco, San Francisco, California.|Department of Neurology, University of California at San Francisco, San Francisco, California.|Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, California.|San Francisco Veterans Affairs Medical Center, San Francisco, California.
Kristine
K
Yaffe
Geriatric Research, Education and Clinical Center, Malcolm Randall Veterans Affairs Medical Center, Gainesville, Florida.
Ronald I
RI
Shorr
Division of Geriatrics, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.|Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania.|Center for Health Equity Research and Geriatric Research Education and Clinical Center, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania.|Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
Joseph T
JT
Hanlon
D000368:Aged; D018680:Cholinergic Antagonists / Q000009:adverse effects*; D003430:Cross-Sectional Studies; D005260:Female; D006306:Health Surveys; D006801:Humans; D008297:Male; D018570:Risk Assessment
D018680:Cholinergic Antagonists
aged; cholinergic antagonists; drug use