Introduction
Evidence-based medicine is the cornerstone of clinical practice, but it
is dependent on the quality of evidence upon which it is based.
Unfortunately, up to half of all randomized controlled trials (RCTs)
have never been published, and trials with statistically significant
findings are more likely to be published than those without (Dwan et al., 2013).
Importantly, negative trials face additional hurdles beyond study
publication bias that can result in the disappearance of non-significant
results (Boutron et al., 2010; Dwan et al., 2013; Duyx et al., 2017).
Here, we analyze the cumulative impact of biases on apparent efficacy,
and discuss possible remedies, using the evidence base for two effective
treatments for depression: antidepressants and psychotherapy.
Reporting and citation biases
We distinguish among four major biases, although others exist: study
publication bias, outcome reporting bias, spin, and citation bias. While
study publication bias involves non-publication of an entire study,
outcome reporting bias refers to non-publication of negative outcomes
within a published article or to switching the status of
(non-significant) primary and (significant) secondary outcomes (Dwan et al., 2013). Both biases pose an important threat to the validity of meta-analyses (Kicinski, 2014).
Trials that faithfully report non-significant results will yield
accurate effect size estimates, but results interpretation can still be
positively biased, which may affect apparent
efficacy. Reporting strategies that could distort the interpretation of
results and mislead readers are defined as spin (Boutron et al., 2010).
Spin occurs when authors conclude that the treatment is effective
despite non-significant results on the primary outcome, for instance by
focusing on statistically significant, but secondary, analyses (e.g.
instead of concluding that treatment X was not more effective than placebo, concluding that treatment X was well tolerated and was effective in patients who had not received prior therapy). If an article has been spun, treatments are perceived as more beneficial (Boutron et al., 2014).
Finally, citation bias is an obstacle to ensuring that negative
findings are discoverable. Studies with positive results receive more
citations than negative studies (Duyx et al., 2017), leading to a heightened visibility of positive results.
The evidence base for antidepressants
We assembled a cohort of 105 depression trials, of which 74 were also included in a previous study on publication bias (Turner et al., 2008);
we added 31 trials of novel antidepressants (approved after 2008) from
the Food and Drug Administration (FDA) database (see online
Supplementary materials). Pharmaceutical companies must preregister all
trials they intend to use to obtain FDA approval; hence, trials with
non-significant results, even if unpublished, are still accessible.
Figure 1
demonstrates the cumulative impact of reporting and citation biases. Of
105 antidepressant trials, 53 (50%) trials were considered positive by
the FDA and 52 (50%) were considered negative or questionable (Fig. 1a).
While all but one of the positive trials (98%) were published, only 25
(48%) of the negative trials were published. Hence, 77 trials were
published, of which 25 (32%) were negative (Fig. 1b).
Ten negative trials, however, became ‘positive’ in the published
literature, by omitting unfavorable outcomes or switching the status of
the primary and secondary outcomes (Fig. 1c).
Without access to the FDA reviews, it would not have been possible to
conclude that these trials, when analyzed according to protocol, were not
positive. Among the remaining 15 (19%) negative trials, five were
published with spin in the abstract (i.e. concluding that the treatment
was effective). For instance, one article reported non-significant
results for the primary outcome (p = 0.10), yet
concluded that the trial ‘demonstrates an antidepressant effect for
fluoxetine that is significantly more marked than the effect produced by
placebo’ (Rickels et al., 1986).
Five additional articles contained mild spin (e.g. suggesting the
treatment is at least numerically better than placebo). One article
lacked an abstract, but the discussion section concluded that there was a
‘trend for efficacy’. Hence, only four (5%) of 77 published trials
unambiguously reported that the treatment was not more effective than
placebo in that particular trial (Fig. 1d). Compounding the problem, positive trials were cited three times as frequently as negative trials (92 v. 32 citations in Web of Science, January 2016, p < 0.001, see online Supplementary material for further details) (Fig. 1e).
Among negative trials, those with (mild) spin in the abstract received
an average of 36 citations, while those with a clearly negative abstract
received 25 citations. While this might suggest a synergistic effect
between spin and citation biases, where negatively presented negative
studies receive especially few citations (de Vries et al., 2016), this difference was not statistically significant (p = 0.50),
likely due to the small sample size. Altogether, these results show
that the effects of different biases accumulate to hide non-significant
results from view.
Fig. 1. The cumulative impact of reporting and citation biases on the evidence base for antidepressants. (a) displays the initial, complete cohort of trials, while (b) through (e)
show the cumulative effect of biases. Each circle indicates a trial,
while the color indicates the results or the presence of spin. Circles
connected by a grey line indicate trials that were published together in
a pooled publication. In (e), the size of the circle indicates the (relative) number of citations received by that category of studies.
The evidence base for psychotherapy
While the pharmaceutical industry has a financial motive for
suppressing unfavorable results, these biases are also present in the
other areas of research, such as psychotherapy. Without a standardized
trial registry, however, they are more difficult to detect and
disentangle. Statistical tests suggest an excess of positive findings in
the psychotherapy literature, due to either study publication bias or
outcome reporting bias (Flint et al., 2015). Of 55 National Institutes of Health-funded psychotherapy trials, 13 (24%) remained unpublished (Driessen et al., 2015), and these had a markedly lower effect size than the published trials.
Regarding spin, 49 (35%) of 142 papers were considered negative in a recent meta-analysis (Flint et al., 2015),
but we found that only 12 (8%) abstracts concluded that psychotherapy
was not more effective than a control condition. The remaining abstracts
were either positive (73%) or mixed (19%) (e.g. concluding that the
treatment was effective for one outcome but not another). Although we
could not establish the pre-specified primary outcome for these trials,
and therefore cannot determine whether a specific abstract is biased,
published psychotherapy trials, as a whole, clearly provide a more
positive impression of the effectiveness of psychotherapy than is
justified by available evidence. Positive psychotherapy trials were also
cited nearly twice as frequently as negative trials (111 citations v. 58, p = 0.003).
Negative trials with a positive or mixed abstract were cited more often
than those with a negative abstract (59 and 87 citations, respectively v. 26, p = 0.05); however, the small sample size precludes definitive conclusions on the effects of spin on citation rates.
Preventing bias
Mandatory prospective registration has long been advocated as a
solution for study publication and outcome reporting bias. The
International Committee of Medical Journal Editors (ICMJE) began
requiring prospective registration of clinical trials as a precondition
for publication in 2005, but many journals do not require registration
(Knüppel et al., 2013) and others allow retrospective registration (Harriman and Patel, 2016).
Since 2007, the FDA also requires prospective registration of most drug
trials. This increasing pressure may explain why recently completed,
negative antidepressant trials are more frequently published than older
negative trials: all negative trials that remained unpublished were
completed before 2004, while the 25 trials completed in 2004 or later
(including 14 for which registration was legally required) were all
published, even though nine were negative. A regulatory requirement is
likely to be one of the most effective measures to ensure universal
registration; unfortunately, the 2007 law excludes trials of behavioral
interventions (e.g. psychotherapy) and phase 1 (healthy volunteer)
trials.
Nevertheless, registration seems insufficient
to ensure complete and accurate reporting of a trial. Only around half
of all trials registered at ClinicalTrials.gov were published within two
years of completion (Ross et al., 2009), and non-reporting of protocol-specified outcomes or the silent addition of new outcomes is also common (Jones et al., 2015, http://www.compare-trials.org).
Close examination of registries by independent researchers may be
necessary for registration to be a truly effective deterrent to study
publication and outcome reporting bias. An alternative (or addition) to
registration could be publication of study protocols or ‘registered
reports’, in which journals accept a study for publication based on the
introduction and methods, before the results are known. Widespread
adoption of this format might also help to prevent spin, by reducing the
pressure that researchers might feel to ‘oversell’ their results to get
published. Furthermore, in our analysis, positive studies were
published in journals with a higher median impact factor (and thus
higher visibility) than negative studies (3.5 v. 2.4 for antidepressant trials and 3.1 v.
2.6 for psychotherapy trials), which may be one driver behind the
difference in citation rates. Hence, adoption of registered reports
might also reduce citation bias by reducing the tendency for positive
studies to be published in higher impact journals. Peer reviewers could
also play a crucial role in ensuring that abstracts accurately report
trial results and that important negative studies are cited. Finally,
the prevalence of spin and citation biases also shows the importance of
assessing a study's actual results (rather than relying on the authors’
conclusions) and of conducting independent literature searches, since
reference lists may yield a disproportionate number of positive (and
positively presented) studies.
Conclusions
The problem of study publication bias is well-known. Our examination of
antidepressant trials, however, shows the pernicious cumulative effect
of additional reporting and citation biases, which together eliminated
most negative results from the antidepressant literature and left the
few published negative results difficult to discover. These biases are
unlikely to be unique to antidepressant trials. We have already shown
that similar processes, though more difficult to assess, occur within
the psychotherapy literature, and it seems likely that the effect of
these biases accumulates whenever they are present. Consequently,
researchers and clinicians across medical fields must be aware of the
potential for bias to distort apparent treatment efficacy, which poses a
threat to the practice of evidence-based medicine.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0033291718001873.
Acknowledgements
Marcus R. Munafò is a member of the United Kingdom Centre for Tobacco
and Alcohol Studies, a UKCRC Public Health Research: Centre of
Excellence. Funding from British Heart Foundation, Cancer Research UK,
Economic and Social Research Council, Medical Research Council, and the
National Institute for Health Research, under the auspices of the UK
Clinical Research Collaboration, is gratefully acknowledged.
Conflict of interest
The authors have no conflicts of interest to report.
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