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Commentary

Measuring effectiveness of drugs in observational databanks: promises and perils

Eswar Krishnan* and James F Fries

Author Affiliations

Division of Immunology, Department of Medicine, Stanford University, Palo Alto, CA, USA

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Arthritis Res Ther 2004, 6:41-44  doi:10.1186/ar1151

Published: 5 February 2004

Abstract

Observational databanks have inherent strengths and shortcomings. As in randomized controlled trials, poor design of these databanks can either exaggerate or reduce estimates of drug effectiveness and can limit generalizability. This commentary highlights selected aspects of study design, data collection and statistical analysis that can help overcome many of these inadequacies. An international metaRegister and a formal mechanism for standardizing and sharing drug data could help improve the utility of databanks. Medical journals have a vital role in enforcing a quality checklist that improves reporting.

Keywords:
bias; cohort study; confounding; data banks; randomized controlled trial; rheumatoid arthritis