Those Who Have the Gold Make the Evidence: How the Pharmaceutical Industry Biases the Outcomes of Clinical Trials of Medications

School of Health Policy and Management, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada.
Science and Engineering Ethics (Impact Factor: 0.96). 02/2011; 18(2):247-61. DOI: 10.1007/s11948-011-9265-3
Source: PubMed


Pharmaceutical companies fund the bulk of clinical research that is carried out on medications. Poor outcomes from these studies can have negative effects on sales of medicines. Previous research has shown that company funded research is much more likely to yield positive outcomes than research with any other sponsorship. The aim of this article is to investigate the possible ways in which bias can be introduced into research outcomes by drawing on concrete examples from the published literature. Poorer methodology in industry-funded research is not likely to account for the biases seen. Biases are introduced through a variety of measures including the choice of comparator agents, multiple publication of positive trials and non-publication of negative trials, reinterpreting data submitted to regulatory agencies, discordance between results and conclusions, conflict-of-interest leading to more positive conclusions, ghostwriting and the use of "seeding" trials. Thus far, efforts to contain bias have largely focused on more stringent rules regarding conflict-of-interest (COI) and clinical trial registries. There is no evidence that any measures that have been taken so far have stopped the biasing of clinical research and it's not clear that they have even slowed down the process. Economic theory predicts that firms will try to bias the evidence base wherever its benefits exceed its costs. The examples given here confirm what theory predicts. What will be needed to curb and ultimately stop the bias that we have seen is a paradigm change in the way that we treat the relationship between pharmaceutical companies and the conduct and reporting of clinical trials.

Download full-text


Available from: Joel Lexchin, Jul 21, 2014
  • Source
    • "Investigators can bias research by using a study design that is more likely to support their hypothesis than other designs or by analyzing or interpreting data in a way that favors their interests or the interests of the sponsor (Michaels 2008). Companies may decide not to publish data that are unfavorable to their products (Lexchin 2012). In extreme cases, investigators or companies may fabricate or falsify data in order to produce results favorable to their interests (Krimsky 2007). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Financial relationships in academic research can create institutional conflicts of interest (COIs) because the financial interests of the institution or institutional officials may inappropriately influence decision-making. Strategies for dealing with institutional COIs include establishing institutional COI committees that involve the board of trustees in conflict review and management, developing policies that shield institutional decisions from inappropriate influences, and establishing private foundations that are independent of the institution to own stock and intellectual property and to provide capital to start-up companies.
    Science and Engineering Ethics 10/2015; DOI:10.1007/s11948-015-9702-9 · 0.96 Impact Factor
  • Source
    • "4; Elliott 2011, ch. 4; Lexchin 2012; Intemann and de Melo-Martín 2014, among many others.) However, following Hicks 2014, §5, I suggest that taking this approach to analyzing the controversy is more difficult than it appears. "
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper examines the scientific controversy over the yields of genetically modified [GM] crops as a case study in epistemologically deep disagreements. Appeals to "the evidence" are inadequate to resolve such disagreements; not because the interlocutors have radically different metaphysical views (as in cases of incommensurability), but instead because they assume rival epistemological frameworks and so have incompatible views about what kinds of research methods and claims count as evidence. Specifically, I show that, in the yield debate, proponents and opponents of GM crops cite two different sets of claims as evidence, which correspond to two rival epistemological frameworks, classical experimental epistemology and Nancy Cartwright's evidence for use. I go on to argue that, even if both sides of the debate accepted Cartwright's view, they might still disagree over what counts as evidence, because evidence for use ties standards of evidence to what is sometimes called the "context of application." Copyright © 2015 Elsevier Ltd. All rights reserved.
    Studies in History and Philosophy of Science Part C Studies in History and Philosophy of Biological and Biomedical Sciences 03/2015; 50:1-12. DOI:10.1016/j.shpsc.2015.02.002
  • Source
    • "For example, the majority of the studies evaluating the safety and efficacy of Gardasil Õ were conducted directly by or funded by the vaccine manufacturer, Merck Frosst (Lippman et al., 2007). Manufacturer bias in the reporting of clinical trial data is widely recognized as a serious problem with respect to pharmaceutical drugs (Lexchin, 2012). Merck Frosst exerting pressure on the Ontario Government to frame the HPV vaccine as an anti-cancer vaccine rather than a vaccine against a sexually transmitted infection (STI) illustrates the reality of conflicting interests (Lippman et al., 2007; Erdman, 2008; Polzer and Knabe, 2009). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Health regulators must carefully monitor the real-world safety and effectiveness of marketed vaccines through post-market monitoring in order to protect the public's health and promote those vaccines that best achieve public health goals. Yet, despite the fact that vaccines used in collective immunization programmes should be assessed in the context of a public health response, post-market effectiveness monitoring is often limited to assessing immunogenicity or limited programmatic features, rather than assessing effectiveness across popu-lations. We argue that post-market monitoring ought to be expanded in two ways to reflect a 'public health notion of post-market effectiveness', which incorporates normative public health considerations: (i) effectiveness monitoring should yield higher quality data and grant special attention to underrepresented and vulnerable populations; and (ii) the scope of effectiveness should be expanded to include a consideration of the various social factors that maximize (and minimize) a vaccine's effectiveness at the population level, paying particular attention to how immunization programmes impact related health gradients. We use the case of the human papillomavirus vaccine in Canada to elucidate how expanding post-market effectiveness monitoring is necessary to close the gap between clinical practice and public health, and to ensure that vaccines are effective in a morally relevant sense.
    Public Health Ethics 01/2015; DOI:10.1093/phe/phu049 · 1.18 Impact Factor
Show more