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Tony Hillis Wing, West London Mental Health NHS Trust, Uxbridge Road, Southall, Middlesex UB1 3EU, e-mail: ahmer{at}doctors.org.uk
St Mary’s Higher Training Scheme in Psychiatry, St Charles Hospital
Three Bridges Medium Secure Unit, West London Mental Health NHS Trust
West London Mental Health NHS Trust and Honorary Research Fellow, Imperial College London
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Abstract |
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 Top Abstract IntroductionMethodResultsDiscussionConclusionReferences |
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To study the association between study support and outcome in randomised controlled trials (RCTs) of psychotropic drugs, we reviewed all RCTs published in four psychiatry journals over a 5-year period. Chi-squared tests were used to analyse the association between RCT support and outcome, and logistic regression to determine which variable best predicted outcome.
RESULTS
A significantly higher proportion of manufacturer-supported RCTs (125/138, 91%, 95% CI 88-93) had a positive outcome than non-manufacturer-supported RCTs (39/50, 78%, 95% CI 72-84; P=0.02). Having an employee author almost guaranteed a positive outcome (56/58, 97%, 95%CI94 -99).
CLINICAL IMPLICATIONS
Outcomes of drug RCTs have a significant association with support by the manufacturer of the experimental drug. Systematic reviews and meta-analyses based on these RCTs may be biased in favour of newer drugs.
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Introduction |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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To our knowledge, our study is the first of its kind looking directly at the association between the support and outcome of RCTs published in mainstream psychiatry journals.
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Method |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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We included only original clinical trials that compared the efficacy and/or the side-effects of a drug with any treatment including placebo, which had a control group and which assigned patients randomly to groups. Studies comparing non-pharmacological treatments only, analysing pooled, subgroup or follow-up data from previously published RCTs, appearing in journal supplements, and comparing different doses or durations of the same drug were all excluded.
Study support
Data were extracted on details of (1) financial support, (2) whether the
manufacturer of the experimental drug had provided the study medications and
(3) whether one or more of the authors was an employee of the manufacturer,
while being masked to the study outcome.
Study outcomes
Study outcomes were independently assigned as positive or negative
depending on whether the outcome would promote the prescribing of the
experimental drug or not. The following specific criteria were used.
Statistical analysis
We used chi-squared tests to compare the difference in proportion of
negative and positive outcomes between manufacturer-supported and
non-manufacturer-supported trials, and to analyse the association of different
types of support with study outcome. We used logistic regression to determine
which variable among all types of support and different journals was the best
predictor of outcome. All the analyses were performed with the Statistical
Package for the Social Sciences (SPSS) version 12.0 for
Windows.
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Results |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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There was disagreement on outcomes of 3 studies (2%). After discussion the differences were resolved in each case; 164 studies (87%) were classified as having a positive outcome and 24 (13%) as having a negative outcome.
There were 138 studies (73%) which declared receiving support from the manufacturer of the experimental drug. Of these, 107 (57%) had received financial support, 58 (31%) had an employee author and 34 (18%) mentioned receiving medications; 93 studies (50%) declared receiving funding from non-industry sources and 6 (3%) did not declare any support.
Chi-squared tests showed a significant difference in proportion of
manufacturer-supported (125/138, 91%, 95% CI 88-93) and
non-manufacturer-supported (39/50, 78%, 95% CI 72-84) trials having a positive
outcome (
2=5.21, d.f.=1, P=0.02, odds ratio=0.37, 95%
CI=0.15-0.89).
Among the subtypes of support, a significantly higher proportion of trials
with an employee author had a positive outcome than trials without (97%, 95%
CI 94-99 v. 83%, 95% CI 80-86) (2=6.53, d.f.=1,
P=0.01, odds ratio=0.12, 95% CI=0.02-0.77). The proportion of trials
with a positive outcome was also higher in trials with manufacturer-supplied
medications and financial support than without, but the difference was not
statistically significant (medications, 94%, 95% CI 90-98 v. 86%, 95%
CI 83-89, P=0.18; financial support, 90%, 95% CI 87-93 v.
84%, 95% CI 80-88, P=0.24).
The results of the full logistic regression model, in which we entered all the six variables at the same time, are presented in Table 2. Having an employee author was the best predictor of a positive outcome.
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Discussion |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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In psychiatry, Wahlbeck & Adams (1999) reported that in a Cochrane review of trials comparing clozapine with typical antipsychotics, studies sponsored by the manufacturer of clozapine were associated with more favourable outcomes for clozapine. In a meta-regression analysis, Moncrieff (2003) reported that trials which declared receiving some financial support from the manufacturer of clozapine showed a greater benefit of clozapine over conventional antipsychotics. In another meta-regression analysis, Freemantle et al (2000) found that the most important structural predictor of RCT outcome was trial sponsorship, although this finding was not statistically significant.
Multiple hypotheses have been put forward to explain the association between trial support and outcome. These include: publication bias (Kjaergard & Als-Nielsen, 2002); pharmaceutical companies selecting for study drugs that have been previously shown to be efficacious (Davidson, 1986); selective release and publication of data by pharmaceutical companies (Rochon et al, 1994; Blumenthal et al, 1997; Rennie, 1997; Nathan & Weatherall, 1999); multiple publications from the same trial (Gøtzsche, 1989; Huston & Moher, 1996), biased interpretation of results (Rochon et al, 1994; Friedberg et al, 1999); and pharmaceutical companies influencing study designs or reporting ensuring that the results favour their drug (Bero & Rennie, 1996; Johansen & Gøtzsche, 1999; Safer, 2002).
There are some limitations to the conclusions that can be drawn from our study. First, studies of this kind can only demonstrate association, and not causation. Second, authors may not be disclosing conflicts of interests completely, thus resulting in any study similar to this one being based on incorrect or incomplete information. There is some evidence to support this assertion (Lewison et al, 1995; Smith, 2001; Henderson et al, 2003). Third, there is the need to make subjective judgements in a study of this kind. We tried to deal with this by one reviewer making a masked assessment of support, two reviewers separately assigning outcomes based on explicit criteria, one of them being masked to data on support, and estimating level of agreement between these two reviewers.
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Conclusion |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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References |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
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