Interpreting big-data analysis of retrospective observational data

The Lancet Rheumatology, vol. 2, pp. e652–e653

Abstract

Current data technology offers fantastic new opportunities to generate data that can inform us about the safety of drugs. These data will affect the way we use drugs by balancing benefits of specific agents with better and more information on their associated risks. Nowadays, possibilities to use big data to deal with safety concerns are enormous, and it is difficult not to get enthusiastic reading papers that take this approach. An outstanding example is the use of claims data of 160 000 patients with rheumatoid arthritis to assess the risk for lower-tract gastrointestinal perforation associated with tocilizumab and tofacitinib in comparison with other biological drugs.

Authors 2

1. Tom W. J. Huizinga corresponding Aachen Department or Rheumatology

   Leiden University Medical Center

   Affiliation as printed

   Department or Rheumatology, Leiden University Medical Center, Leiden, Netherlands

2. Rachel Knevel Aachen Department or Rheumatology

   Brigham and Women's Hospital · Leiden University Medical Center

   Affiliation as printed

   Brigham And Women's Hospital, Department of Medicine, Division of Rheumatology, Boston, MA, USA

   Department or Rheumatology, Leiden University Medical Center, Leiden, Netherlands