Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

CiteULike is a free service for managing and discovering scholarly references - click here to get started.

Sign In to gain access to subscriptions and/or personal tools.
Medical Decision Making
This Article
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
0272989X08327332v1
29/3/343    most recent
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Kramar, A.
Right arrow Articles by Bascoul-Mollevi, C.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kramar, A.
Right arrow Articles by Bascoul-Mollevi, C.
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Early Stopping Rules in Clinical Trials Based on Sequential Monitoring of Serious Adverse Events

A. Kramar, PhD

Unité de Biostatistique, CRLC Val d'Aurelle-Paul Lamarque, Montpellier, France, andrew.kramar{at}valdorel.fnclcc.fr

C. Bascoul-Mollevi, PhD

Unité de Biostatistique, CRLC Val d'Aurelle-Paul Lamarque, Montpellier, France

Several multistage or group sequential statistical methods have been developed for defining stopping rules in terms of efficacy in phase II and III clinical trials, but they rely on interim analyses after the inclusion of a fixed number of patients. These methods, however, need to be adapted for the evaluation of serious adverse events (SAEs), which can occur relatively early in the trial. A high frequency of their occurrence may require the trial to close early. The methods developed here define stopping rules after the occurrence of each SAE by comparing the number of patients included to the number of patients satisfying maximum SAE criteria. The nominal type I error, power, and average sample number (ASN) under specific hypotheses are obtained through simulations. Data from a clinical trial are presented as an example.

Key Words: early stopping rules • serious adverse event • clinical trials.

This version was published on May 1, 2009

Medical Decision Making, Vol. 29, No. 3, 343-350 (2009)
DOI: 10.1177/0272989X08327332
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?