Abstract
Recently a great deal of attention has been paid to conflicts of interest in medical research, and the Institute of Medicine has called for more research into this important area. One research question that has not received sufficient attention concerns the mechanisms of action by which conflicts of interest can result in biased and/or flawed research. What discretion do conflicted researchers have to sway the results one way or the other? We address this issue from the perspective of selective inertia, or an unnatural selection of research methods based on which are most likely to establish the preferred conclusions, rather than on which are most valid. In many cases it is abundantly clear that a method that is not being used in practice is superior to the one that is being used in practice, at least from the perspective of validity, and that it is only inertia, as opposed to any serious suggestion that the incumbent method is superior (or even comparable), that keeps the inferior procedure in use, to the exclusion of the superior one. By focusing on these flawed research methods we can go beyond statements of potential harm from real conflicts of interest, and can more directly assess actual (not potential) harm.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alperson, S., & Berger, V. W. (2013). Beyond Jadad: Some essential features in trial quality. Clinical Investigation, 3(12), 1119–1126.
Altman, D. G. (1994). The scandal of poor medical research. BMJ, 308(6924), 283–284.
Berger, V. W. (2000). Pros and cons of permutation tests in clinical trials. Statistics in Medicine, 19, 1319–1328.
Berger, V. W. (2002). Improving the information content of categorical clinical trial endpoints. Controlled Clinical Trials, 23(5), 502–514.
Berger, V. W. (2004). On the generation and ownership of alpha in medical studies. Controlled Clinical Trials, 25(6), 613–619.
Berger, V. W. (2005). Selection bias and covariate imbalances in randomized clinical trials. Chichester: Wiley.
Berger, V. W. (2006a). Do not use blocked randomization. Headache, 46(2), 343.
Berger, V. W. (2006b). Misguided precedent is not a reason to use permuted blocks. Headache, 46(7), 1210–1212.
Berger, V. W. (2006c). Varying block sizes does not conceal the allocation. Journal of Critical Care, 21(2), 229.
Berger, V. W. (2006d). Is the Jadad score the proper evaluation of trials. Journal of Rheumatology, 33(8), 1710.
Berger, V. W., & Alperson, S. Y. (2009). A general framework for the evaluation of clinical trial quality. Reviews on Recent Clinical Trials, 4(2), 79–88.
Berger, V. W., Grant, W. C., & Vazquez, L. F. (2010). Sensitivity designs for preventing bias replication in randomized clinical trials. Statistical Methods in Medical Research, 19(4), 415–424.
Berger, V. W., & Ivanova, A. (2002). Adaptive tests for ordinal data. JMASM, 1(2), 269–280.
Berger, V. W., Ivanova, A., & Deloria-Knoll, M. (2003a). Minimizing predictability while retaining balance through the use of less restrictive randomization procedures. Statistics in Medicine, 22(19), 3017–3028.
Berger, V. W., Permutt, T., & Ivanova, A. (1998). The convex hull test for ordered categorical data. Biometrics, 54(4), 1541–1550.
Berger, V. W., Rezvani, A., & Makarewicz, V. A. (2003b). Direct effect on validity of response run-in selection in clinical trials. Controlled Clinical Trials, 24(2), 156–166.
Berger, V. W., & Vali, B. (2011). Intent-to-randomize corrections for missing data resulting from run-in selection bias in clinical trials for chronic conditions. Journal of Biopharmaceutical Statistics, 21(2), 263–270.
Bookman, A. M., Williams, K. S. A., & Shainhouse, J. Z. (2004). Effect of a topical diclofenac solution for relieving symptoms of primary osteoarthritis of the knee: A randomized controlled trial. CMAJ, 171, 333–338.
Bridoux, V., Moutel, G., Roman, H., Kianifard, B., Michot, F., Herve, C., et al. (2012). Methodological and ethical quality of randomized controlled clinical trials in gastrointestinal surgery. Journal of Gastrointestinal Surgery 1.
Chalmers, T. C., Smith, H. J., Blackburn, B., et al. (1981). A method for assessing the quality of a randomized control trial. Controlled Clinical Trials, 2, 31–49.
Chaudhry, S., Schroter, S., Smith, R., & Morris, J. (2002). Does declaration of competing interests affect readers’ perceptions? A randomized trial. BMJ, 325, 1391–1392.
Dwan, K., Gamble, C., Williamson, P. R., Kirkham, J. J., & The Reporting Bias Group. (2013). Systematic review of the empirical evidence of study publication bias and outcome reporting bias—an updated review. PLoS ONE, 8(7), e66844. doi:10.1371/journal.pone.0066844.
Fayers, P. M., & King, M. (2008). A highly significant difference in baseline characteristics: The play of chance of evidence of a more selective game? Quality of Life Research, 17, 1121–1123.
Geary, R. C. (1947). Testing for normality. Biometrika, 34, 209–242.
Harrington, A. (1997). The placebo effect. Cambridge: Harvard University Press.
Institute of Medicine. (2009). Conflict of interest in medical research, education, and practice. Washington, DC: The National Academies Press.
Ioannidis, J. P. A. (2005). Why most published research findings are false. PLOS Medicine, 2(8), e124.
Jacobs, A. (2003). Clarification needed about possible bias and statistical testing. BMJ USA, 3, 93.
Jadad, A. R., Moore, R. A., Carroll, D., et al. (1996). Assessing the quality of reports of randomized clinical trials: Is blinding necessary? Controlled Clinical Trials, 17, 1–12.
La Torre, G., Chiaradia, G., Gianfanga, F., De Laurentis, A., Boocia, S., & Ricciardi, W. (2006). Quality assessment in meta- analysis. Italian Journal of Public Health, 3, 44–50.
Lexchin, J. (2012a). Those who have the gold make the evidence: How the pharmaceutical industry biases the outcomes of clinical trials of medications. Science and Engineering Ethics, 18, 247–261.
Lexchin, J. (2012b). Sponsorship bias in clinical research. The International Journal of Risk and Safety in Medicine, 24(4), 233–242.
Lundh, A., Sismondo, S., Lexchin, J., Busuioc, O. A., & Bero, L. (2012). Industry sponsorship and research outcome. The Cochrane Library 12.
Matts, J. P., & McHugh, R. B. (1983). Conditional markov chain designs for accrual clinical trials. Biometrical Journal, 25, 563–577.
Palys, K. E., & Berger, V. W. (2013). A note on the jadad score as an efficient tool for measuring trial quality. Journal of Gastrointestinal Surgery, 17(6), 1170–1171. doi:10.1007/s11605-012-2106-0. (Epub 2012 Dec 12. PubMed PMID: 23233271).
Panati, C. (1989). Panati’s extraordinary endings of practically everything and everybody. New York: Harper & Row.
Perlman, P., Possen, B. H., Legat, V. D., Rubenacker, A. S., Bockiger, U., & Stieben-Emmerling, L. (2013). When will we see people of negative height. Significance, 10(1), 46–48.
Soares, J. F., & Wu, C. F. J. (1982). Some restricted randomization rules in sequential designs. Communications in Statistics Theory and Methods, 12, 2017–2034.
Cytel (1995). StatXact-3 for Windows: Statistical software for exact nonparametric inference. Cytel Software Corporation, Cambridge.
Towheed, T. E. (2006). Pennsaid therapy for osteoarthritis of the knee: A systematic review and metaanalysis of randomized controlled trials. Journal of Rheumatology, 33, 567–573.
Acknowledgments
The review team offered insightful comments that resulted in a vastly improved revision.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Berger, V.W. Conflicts of Interest, Selective Inertia, and Research Malpractice in Randomized Clinical Trials: An Unholy Trinity. Sci Eng Ethics 21, 857–874 (2015). https://doi.org/10.1007/s11948-014-9576-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11948-014-9576-2