4.2 Article

Measuring effectiveness of drugs in observational databanks: promises and perils

Journal

ARTHRITIS RESEARCH & THERAPY
Volume 6, Issue 2, Pages 41-44

Publisher

BMC
DOI: 10.1186/ar1151

Keywords

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

Categories

Funding

  1. NATIONAL INSTITUTE OF ARTHRITIS AND MUSCULOSKELETAL AND SKIN DISEASES [P01AR043584] Funding Source: NIH RePORTER
  2. NIAMS NIH HHS [AR43584, P01 AR043584] Funding Source: Medline

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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.

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