Abstract
Proponents of Evidence-based medicine (EBM) do not provide a clear role for basic science in therapeutic decision making. Of what they do say about basic science, most of it is negative. Basic science resides on the lower tiers of EBM’s hierarchy of evidence. Therapeutic decisions, according to proponents of EBM, should be informed by evidence from randomised studies (and systematic reviews of randomised studies) rather than basic science. A framework of models explicates the links between the mechanisms of basic science, experimental inquiry, and observed data. Relying on the framework of models I show that basic science often plays a role not only in specifying experiments, but also analysing and interpreting the data that is provided. Further, and contradicting what is implied in EBM’s hierarchy of evidence, appeals to basic science are often required to apply clinical research to therapeutic questions.
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Notes
A different ‘expedience’ argument could be mounted without interpreting the hierarchy of evidence categorically. If, on occasion, evidence from lower down the hierarchy could be more important to a decision about a specific patient (despite the availability of evidence obtained from a method listed higher), it might be argued that the cost of finding this evidence outweighs the benefits, either in terms of the individual patient, or over the course of the many decisions clinicians need to make. This argument, however, is not provided in the key EBM texts or articles.
La Caze (2009) provides further discussion.
While the step from basic science to the mechanisms of basic science is rarely stated explicitly in the EBM literature, the move is continuously implied. Mechanism is suggested in the use of the term ‘pathophysiologic rationale’ in the original statement of EBM quoted above. Mechanism is also implied in the notions of ‘biological plausibility’ suggested in the following quote from statistician Douglas Altman:
My view is that biological plausibility is the weakest reason [for thinking a difference observed in a subgroup of patients is genuine], as doctors seem able to find a biologically plausible explanation for any finding. (Altman 1998, p. 301)
Quotes such as these can be multiplied.
Conversely, the findings of randomised trials can provide leads for biological research, and possibly help flesh out the mechanism sketch.
Hormone replacement therapy and flecainide, as discussed earlier, provide striking examples of instances in which reasonably well supported putative mechanisms do not necessarily lead to benefits in patients. Note, that examples such as these don’t necessarily mean that the mechanism is not instantiated; there could, for instance, be unexpected harms which swamp the postulated benefits.
There is, of course, much debate surrounding different approaches to statistical inference. But the framework of models, and their role in statistical analysis, is orthogonal to debates over preferred methods of statistical inference.
As Mayo (1996, pp. 139–141) observes, should a ceteris paribus condition come under question, a decision can be made to include it in the formal analysis of the trial.
Notably, this use of basic science is not seen as contentious by proponents of EBM; it is the use of basic science in therapeutic decision making that is questioned.
References
Altman DG (1998) Within trial variation—a false trail? J Clin Epidemiol 51(4):301–303
Bechtel W, Richardson RC (1993) Discovering complexity: decomposition and localization as strategies in scientific research. Cambridge Univeristy Press, Cambridge
Bresalier RS, Sandler RS, Quan H, Bolognese JA, Oxenius B, Horgan K, Lines C, Riddell R, Morton D, Lanas A, Konstam MA, Baron JA (2005) Cardiovascular events associated with rofecoxib in a colorectal andenoma chemoprevention trial. N Engl J Med 352(11):1092–1102
Brookes S, Whitely E, Peters T, Mulheran PA, Egger M, Davey Smith G (2001) Subgroup analyses in randomised controlled trials: quantifying the risks of false-positives and false-negatives. Health Technol Assess 5(33):1–58
Cox DR (2006) Principles of statistical inference. Cambridge Univeristy Press, Cambridge
Devereaux PJ, Yusuf S (2003) The evolution of the randomized controlled trial and its role in evidence-based decision making. J Intern Med 254:105–113
Echt D, Liebson P, Mitchell L, Peters R, Obias-Manno D, Barker A, Arensberg D, Baker A, Friedman L, Greene H et al (1991) Mortality and morbidity in patients receiving encainide, flecainide, or placebo. Fhe cardiac arrhythmia suppression trial. N Engl J Med 324(12):781–788
Evidence-Based Medicine Working Group (1992) Evidence-based medicine: a new approach to teaching the practice of medicine. JAMA 268(17):2420–2425
Feinstein A (1996) Two centuries of conflict-collaboration between medicine and mathematics. J Clin Epidemiol 49(12):1339–1343
Feinstein AR (1998) The problem of cogent subgroups: a clinicostatistical tragedy. J Clin Epidemiol 51(4):297–299
Glennan S (1996) Mechanisms and the nature of causation. Erkenntnis 44(1):49–71
Guyatt GH, Rennie D (eds) (2002) Users’ guide to the medical literature: Essentials of evidence-based clinical practice. American Medical Association Press, Chigaco
ISIS-2 Collaborative Group (1988) Randomised trial of intravenous streptokinase, oral aspirin, both, or neither among 17 187 cases of suspected acute myocardial infarction: Isis-2. The Lancet 332(8607):349–360
La Caze A (2008) Evidence-based medicine can’t be .... Soc Epistemol 22(4):353–370
La Caze A (2009) Evidence-based medicine must be .... J Med Philos 34:509–527
Lagakos SW (2006) Time-to-event analyses for long-term treatments—the APPROVe trial. N Engl J Med 355(2):113–117
Machamer P, Darden L, Craver C (2000) Thinking about mechanisms. Philoso Sci 67(1):1–25
Mayo DG (1996) Error and the growth of experimental knowledge. Science and its conceptual foundations. University of Chicago Press, Chigaco
Nissen SE, Furberg CD, Bresalier RS, Baron JA (2006) Adverse cardiovascular effects of rofecoxib. N Engl J Med 355(2):203–205
Peto R, Collins R, Gray R (1995) Large-scale randomized evidence: Large, simple trials and overviews of trials. J Clin Epidemiol 48(1):23–40
Phillips B, Ball C, Sackett DL, Badenoch D, Straus SE, Haynes RB, Dawes M (1998) Oxford centre for evidence-based medicine levels of evidence (May 2001). Tech. rep., http://www.cebm.net/?o=1023
Poisson SD, Dulong PL, Larrey DJ, Double FJ (2001) Statistical research on conditions caused by calculi by Doctor Civiale. Int J Epidemiol 30(6):1246–1249
Reilly B (2004) The essence of EBM. Br Med J 329:991–2
Sackett DL (2006) The principles behind the tactics of performing therapeutic trials. In: Haynes RB, Sackett DL, Guyatt GH, Tugwell P (eds) Clinical epidemiology: how to do clinical practice research, 3rd edn. Lippincott Williams and Wilkins, Philadelphia, pp 173–243
Sackett DL, Rosenberg W, Gray JAM, Haynes B, Richardson WS (1996) Evidence based medicine: what is it and what it isn’t. Br Med J 312(7023):71–72
Salmon WC (1971) Statistical explanation and statistical relevance. University of Pittsburgh Press, Pittsburgh
Schulz KF, Altman DG, Moher D (2010) Consort 2010 statement: updated guidelines for reporting parallel group randomized trials. Ann Intern Med 152(11):1–7
Straus SE, Richardson WS, Glasziou P, Haynes RB (2005) Evidence-based medicine: how to practice and teach, 3rd edn. Elsevier Churchill Livingstone, London
Suppes P (1962) Models of data. In: Nagel E, Suppes P, Tarski A (eds) Logic, Methodology and philosophy of science: Proceedings of the 1960 International Congress, Stanford University Press, Stanford, pp 252–261
Women’s Health Initiative Writing Group (2002) Risks and benefits of estrogen plus progestin in health postmenopausal women. JAMA 288:321–333
Acknowledgments
I would like to thank Mark Colyvan, Jason Grossman, Neil Thomason, Jeremy Howick, Lindley Darden and Carl Craver for helpful discussions on previous versions of this paper.
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La Caze, A. The role of basic science in evidence-based medicine. Biol Philos 26, 81–98 (2011). https://doi.org/10.1007/s10539-010-9231-5
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DOI: https://doi.org/10.1007/s10539-010-9231-5