Pooling, meta-analysis, and the evaluation of drug safety

<p>Abstract</p> <p>Background</p> <p>The "integrated safety report" of the drug registration files submitted to health authorities usually summarizes the rates of adverse events observed for a new drug, placebo or active control drugs by pooling the safety dat...

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Main Authors: Leizorovicz Alain, Cucherat Michel, Lièvre Michel
Format: Article
Language:English
Published: BMC 2002-03-01
Series:Current Controlled Trials in Cardiovascular Medicine
Online Access:http://cvm.controlled-trials.com/content/3/1/6
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spelling doaj-0880305f93f644a9a2f2c451ab5204952020-11-24T22:13:24ZengBMCCurrent Controlled Trials in Cardiovascular Medicine1468-67082002-03-0131610.1186/1468-6708-3-6Pooling, meta-analysis, and the evaluation of drug safetyLeizorovicz AlainCucherat MichelLièvre Michel<p>Abstract</p> <p>Background</p> <p>The "integrated safety report" of the drug registration files submitted to health authorities usually summarizes the rates of adverse events observed for a new drug, placebo or active control drugs by pooling the safety data across the trials. Pooling consists of adding the numbers of events observed in a given treatment group across the trials and dividing the results by the total number of patients included in this group. Because it considers treatment groups rather than studies, pooling ignores validity of the comparisons and is subject to a particular kind of bias, termed "Simpson's paradox." In contrast, meta-analysis and other stratified analyses are less susceptible to bias.</p> <p>Methods</p> <p>We use a hypothetical, but not atypical, application to demonstrate that the results of a meta-analysis can differ greatly from those obtained by pooling the same data. In our hypothetical model, a new drug is compared to 1) a placebo in 4 relatively small trials in patients at high risk for a certain adverse event and 2) an active reference drug in 2 larger trials of patients at low risk for this event.</p> <p>Results</p> <p>Using meta-analysis, the relative risk of experiencing the adverse event with the new drug was 1.78 (95% confidence interval [1.02; 3.12]) compared to placebo and 2.20 [0.76; 6.32] compared to active control. By pooling the data, the results were, respectively, 1.00 [0.59; 1.70] and 5.20 [2.07; 13.08].</p> <p>Conclusions</p> <p>Because these findings could mislead health authorities and doctors, regulatory agencies should require meta-analyses or stratified analyses of safety data in drug registration files.</p> http://cvm.controlled-trials.com/content/3/1/6
collection DOAJ
language English
format Article
sources DOAJ
author Leizorovicz Alain
Cucherat Michel
Lièvre Michel
spellingShingle Leizorovicz Alain
Cucherat Michel
Lièvre Michel
Pooling, meta-analysis, and the evaluation of drug safety
Current Controlled Trials in Cardiovascular Medicine
author_facet Leizorovicz Alain
Cucherat Michel
Lièvre Michel
author_sort Leizorovicz Alain
title Pooling, meta-analysis, and the evaluation of drug safety
title_short Pooling, meta-analysis, and the evaluation of drug safety
title_full Pooling, meta-analysis, and the evaluation of drug safety
title_fullStr Pooling, meta-analysis, and the evaluation of drug safety
title_full_unstemmed Pooling, meta-analysis, and the evaluation of drug safety
title_sort pooling, meta-analysis, and the evaluation of drug safety
publisher BMC
series Current Controlled Trials in Cardiovascular Medicine
issn 1468-6708
publishDate 2002-03-01
description <p>Abstract</p> <p>Background</p> <p>The "integrated safety report" of the drug registration files submitted to health authorities usually summarizes the rates of adverse events observed for a new drug, placebo or active control drugs by pooling the safety data across the trials. Pooling consists of adding the numbers of events observed in a given treatment group across the trials and dividing the results by the total number of patients included in this group. Because it considers treatment groups rather than studies, pooling ignores validity of the comparisons and is subject to a particular kind of bias, termed "Simpson's paradox." In contrast, meta-analysis and other stratified analyses are less susceptible to bias.</p> <p>Methods</p> <p>We use a hypothetical, but not atypical, application to demonstrate that the results of a meta-analysis can differ greatly from those obtained by pooling the same data. In our hypothetical model, a new drug is compared to 1) a placebo in 4 relatively small trials in patients at high risk for a certain adverse event and 2) an active reference drug in 2 larger trials of patients at low risk for this event.</p> <p>Results</p> <p>Using meta-analysis, the relative risk of experiencing the adverse event with the new drug was 1.78 (95% confidence interval [1.02; 3.12]) compared to placebo and 2.20 [0.76; 6.32] compared to active control. By pooling the data, the results were, respectively, 1.00 [0.59; 1.70] and 5.20 [2.07; 13.08].</p> <p>Conclusions</p> <p>Because these findings could mislead health authorities and doctors, regulatory agencies should require meta-analyses or stratified analyses of safety data in drug registration files.</p>
url http://cvm.controlled-trials.com/content/3/1/6
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