Using Simulated Data to Assess Case-Crossover Designs for Studying Less Transient Effects of Drugs

Using Simulated Data to Assess Case-Crossover Designs for Studying Less Transient Effects of Drugs Drug Saf (2017) 40:757–760 DOI 10.1007/s40264-017-0549-7 COMMENTARY Using Simulated Data to Assess Case-Crossover Designs for Studying Less Transient Effects of Drugs Malcolm Maclure Published online: 3 June 2017 Springer International Publishing Switzerland 2017 Decades after the case-crossover (CCO) design was first between-person confounding in creating the simulated data described [1], recent studies of potential biases and alter- for realistic methodologic studies of traditional cohort and native applications of CCO analyses using pharmaceutical case–control designs [7]. However, much, if not all, of that and healthcare utilization databases are still yielding new between-person confounding would be automatically insights [2, 3]. In this issue of Drug Safety, Burningham eliminated from CCO analyses because cases serve as their et al. [4] report their assessments of the performance of own controls. Ironically, the main strength of OSIM2 as a CCO methods for studying more chronic effects of drugs, creator of simulation data might thus be negated by the similar to the work of Schuemie et al. [5] on studying long- main strength of the CCO design. term effects of accumulated exposures using the self-con- OSIM2 was not explicitly designed to produce realistic trolled case-series (SCCS) method. within-person confounding in the simulated data. Murray Based http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Drug Safety Springer Journals

Using Simulated Data to Assess Case-Crossover Designs for Studying Less Transient Effects of Drugs

Loading next page...
 
/lp/springer_journal/using-simulated-data-to-assess-case-crossover-designs-for-studying-kZ5nnV2mty
Publisher
Springer International Publishing
Copyright
Copyright © 2017 by Springer International Publishing Switzerland
Subject
Medicine & Public Health; Drug Safety and Pharmacovigilance; Pharmacology/Toxicology
ISSN
0114-5916
eISSN
1179-1942
D.O.I.
10.1007/s40264-017-0549-7
Publisher site
See Article on Publisher Site

Abstract

Drug Saf (2017) 40:757–760 DOI 10.1007/s40264-017-0549-7 COMMENTARY Using Simulated Data to Assess Case-Crossover Designs for Studying Less Transient Effects of Drugs Malcolm Maclure Published online: 3 June 2017 Springer International Publishing Switzerland 2017 Decades after the case-crossover (CCO) design was first between-person confounding in creating the simulated data described [1], recent studies of potential biases and alter- for realistic methodologic studies of traditional cohort and native applications of CCO analyses using pharmaceutical case–control designs [7]. However, much, if not all, of that and healthcare utilization databases are still yielding new between-person confounding would be automatically insights [2, 3]. In this issue of Drug Safety, Burningham eliminated from CCO analyses because cases serve as their et al. [4] report their assessments of the performance of own controls. Ironically, the main strength of OSIM2 as a CCO methods for studying more chronic effects of drugs, creator of simulation data might thus be negated by the similar to the work of Schuemie et al. [5] on studying long- main strength of the CCO design. term effects of accumulated exposures using the self-con- OSIM2 was not explicitly designed to produce realistic trolled case-series (SCCS) method. within-person confounding in the simulated data. Murray Based

Journal

Drug SafetySpringer Journals

Published: Jun 3, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off