Epistemology of causal inference in pharmacology
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Philosophical discussions on causal inference in medicine are stuck in dyadic camps, each defending one kind of evidence or method rather than another as best support for causal hypotheses. Whereas Evidence Based Medicine advocates the use of Randomised Controlled Trials and systematic reviews of RCTs as gold standard, philosophers of science emphasise the importance of mechanisms and their distinctive informational contribution to causal inference and assessment. Some have suggested the adoption of a pluralistic approach to causal inference, and an inductive rather than hypothetico-deductive inferential paradigm. However, these proposals deliver no clear guidelines about how such plurality of evidence sources should jointly justify hypotheses of causal associations. We here develop such guidelines by first giving a philosophical analysis of the underpinnings of Hill’s (1965) viewpoints on causality. We then put forward an evidence-amalgamation framework adopting a Bayesian net approach to model causal inference in pharmacology for the assessment of harms. Our framework accommodates a number of intuitions already expressed in the literature concerning the EBM vs. pluralist debate on causal inference, evidence hierarchies, causal holism, relevance (external validity), and reliability.
KeywordsCausation Evidence Bayesian epistemology Scientific inference Safety assessment in pharmacology Risk Bradford Hill criteria
This paper was presented at various workshops and conferences in Munich, New Brunswick, Sheffield, Helsinki, Durham, Amsterdam, and Ferrara. We greatly profited from the comments and suggestions made by the audiences; in particular we wish to thank Rani Lill Anjum, Timo Bolt, Giovanni Boniolo, Branden Fitelson, Bennett Holman, Phyllis Illari, Mike Kelly, Ulrich Mansmann, Carlo Martini, Julian Reiss, Stephen Senn, Beth Shaw, Jacob Stegenga, and Veronica Vieland. We also thank the focus group members of the ERC project “Philosophy of Pharmacology: Safety, Statistical Standards, and Evidence Amalgamation”, to whom we owe a considerable improvement of the paper’s argumentation: Jeffrey Aronson, Lorenzo Casini, Brendan Clarke, Vincenzo Crupi, Sebastian Lutz, Federica Russo, Glenn Shafer, Jan Sprenger, David Teira, and Jon Williamson. We are extremely grateful to our colleagues at the Munich Center for Mathematical Philosophy, who helped us clarify the objectives and scope of our research, and suggested possible paths of development; in particular we wish to thank Seamus Bradley, Richard Dawid, Samuel C. Fletcher, Stephan Hartmann, Alexander Reutlinger, and Gregory Wheeler. Finally, we thank two anonymous reviewers for their comments. These significantly helped us refine some important assumptions in our theoretical framework. Of course any inaccuracies or errors in the text are, however, our own responsibility.
- Anjum, R. L., & Mumford, S. (2012). Causal dispositionalism. Properties, Powers and Structure 101–118, 7 In Bird, A., Ellis, B., & Sankey, H. (Eds.), Routledge.Google Scholar
- Bartha, P. (2013). Analogy and analogical reasoning. In Zalta, E.N. (Ed.), The Stanford encyclopedia of philosophy, fall 2013 edn.Google Scholar
- Bartha, P. F. A. (2010). By parallel reasoning: the construction and evaluation of analogical arguments. Oxford University Press.Google Scholar
- Bes-Rastrollo, M., Schulze, M. B., Ruiz-Canela, M., & Martinez-Gonzalez, M. A. (2013). Financial conflicts of interest and reporting bias regarding the association between sugar-sweetened beverages and weight gain: a systematic review of systematic reviews. PLOS Medicine, 10(12), 1–9. doi: 10.1371/journal.pmed.1001578.CrossRefGoogle Scholar
- BonJour, L. (2010). Epistemology. Classic problems and contemporary responses. Rowman & Littlefield Publishers.Google Scholar
- Bovens, L., & Hartmann, S. (2003). Bayesian epistemology. Oxford University Press.Google Scholar
- Britton, O. J., Bueno-Orovio, A., Van Ammel, K., Lu, H. R., Towart, R., Gallacher, D. J., & Rodriguez, B. (2013). Experimentally calibrated population of models predicts and explains intersubject variability in cardiac cellular electrophysiology. Proceedings of the National Academy of Sciences, 110(23), E2098–E2105. doi: 10.1073/pnas.1304382110.
- Cartwright, N. (2007a). Are RCTs the Gold Standard? Biosocieties, 2, 11–20. doi: 10.1017/S1745855207005029.
- Cartwright, N. (2007b). Causal powers: what are they? Why do we need them? What can be done with them and what cannot? Tech. Rep 04/07. http://www.lse.ac.uk/CPNSS/research/concludedResearchProjects/ContingencyDissentInScience/DP/CausalPowersMonographCartwrightPrint http://www.lse.ac.uk/CPNSS/research/concludedResearchProjects/ContingencyDissentInScience/DP/CausalPowersMonographCartwrightPrint.
- Cartwright, N., & Stegenga, J. (2011). A theory of evidence for Evidence-Based policy. In Dawid, P., & Twinning William Vasilaki, M. (Eds.), Evidence, Inference and Enquiry, chap. 11, OUP (pp. 291–322).Google Scholar
- Darwiche, A. (2009). Modeling and reasoning with Bayesian networks. Cambridge University Press.Google Scholar
- Doll, R., & Peto, R. (1980). Randomised controlled trials and retrospective controls. British Medical Journal, 280, 44. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1600504/.CrossRefGoogle Scholar
- Food Drug Administration (2009). Drug induced liver injury: premarketing clinical evaluation - guidance for industry. http://www.fda.gov/downloads/Drugs/Guidance/UCM174090.pdf.
- Hempel, C. G. (1968). Maximal specificity and lawlikeness in probabilistic explanation. Philosophy of Science, 35(2), 116–133. http://www.journals.uchicago.edu/doi/abs/10.1086/288197.CrossRefGoogle Scholar
- Hill, A. B. (1965). The environment and disease: association or causation? Proceedings of the Royal Society of Medicine, 58(5), 295–300.Google Scholar
- Howson, C., & Urbach, P. (2006). Scientific Reasoning, 3 edn. Open Court.Google Scholar
- Hume, D. (1748). An enquiry concerning human understanding. The University of Adelaide Library 2004 (derived from the Harvard Classics Volume 37, 1910 P.F Collier & Son.) http://ebooks.adelaide.edu.au/h/hume/david/h92e/.
- Johnson, S. R., Tomlinson, G. A., Hawker, G. A., Granton, J. T., & Feldman, B. M. (2010). Methods to elicit beliefs for Bayesian priors: a systematic review. Journal of Clinical Epidemiology, 63(4), 355–369. doi: 10.1016/j.jclinepi.2009.06.003.
- Jüni, P., Nartey, L., Reichenbach, S., Sterchi, R., Dieppe, P. A., & Egger, M. (2004). Risk of cardiovascular events and rofecoxib: cumulative meta-analysis. The Lancet, 364(9450), 2021–2029. doi: 10.1016/S0140-6736(04)17514-4.
- Kerry, R., Eriksen, T. E., Lie, S. A. N., Mumford, S. D., & Anjum, R. L. (2012). Causation and evidence-based practice: an ontological review. Journal of Evaluation in Clinical Practice, 18(5), 1006–1012. doi: 10.1111/j.1365-2753.2012.01908.x.
- Kment, B. (2010). Causation: determination and difference-making. Noûs, 44 (1), 80–111. doi: 10.1111/j.1468-0068.2009.00732.x. Wiley Online Library.
- Krumholz, H. M., Ross, J. S., Presler, A. H., & Egilman, D. S. (2007). What have we learnt from Vioxx? British Medical Journal, 334(7585), 120–123. doi: 10.1136/bmj.39070.527986.68.
- Lamal, P. (1990). On the importance of replication. Journal of Social Behavior and Personality, 5(4), 31–35.Google Scholar
- Lewis, D. (1986). Causal explanation, Philosophical papers, chap. 3. OUP, (Vol. II pp. 214–240).Google Scholar
- Lipton, P. (2003). Inference to the best explanation. Routledge.Google Scholar
- McGrew, T. (2003). Confirmation, heuristics, and explanatory reasoning, 54 (4), 553–567. doi: 10.1093/bjps/54.4.553.
- Mill, J. S. (1884). A system of logic, ratiocinative and inductive: being a connected view of the principles of evidence and the methods of scientific investigation. Longmans, Green and Company.Google Scholar
- Neapolitan, R. E. (2003). Learning Bayesian networks. Pearson.Google Scholar
- Osimani, B. (2007). Probabilistic information and decision making in the health context: the package leaflet as basis for informed consent. Doctoral Thesis, 1 edn Università della Svizzera Italiana.Google Scholar
- Osimani, B. (2014a). Causing something to be one way rather than another. Genetic information, causal specificity and the relevance of linear order. Kybernetes, 43(6), 865–881. doi: 10.1108/K-07-2013-0149.
- Osimani, B. (2014b). Hunting side effects and explaining them: should we reverse evidence hierarchies upside down? Topoi, 33 (2), 295–312. doi: 10.1007/s11245-013-9194-7.
- Osimani, B., & Landes, J. (Forthcoming). Exact replication or varied evidence? The varied of evidence thesis and its methodological implication in medical research.Google Scholar
- Osimani, B., Russo, F., & Williamson, J. (2011). Scientific evidence and the law: an objective bayesian formalisation of the precautionary principle in pharmaceutical regulation. Journal of Philosophy, Science and Law, 11. http://jpsl.org/files/9913/6816/1730/Bayesian-Formalization.pdf.
- Pearl, J. (2000). Causality: models, reasoning, and inference, 1st edn. Cambridge University Press.Google Scholar
- Platt, J. R. (1964). Strong inference. Science, 146(3642), 347–353. http://science.sciencemag.org/content/146/3642/347.CrossRefGoogle Scholar
- Poellinger, R. (2017). Analogy-based inference patterns in pharmacological research, Forthcoming.Google Scholar
- Poellinger, R., & Beebe, C. (2017). Bayesian confirmation from analog models, Forthcoming.Google Scholar
- Roush, S. (2005). Tracking truth: knowledge, evidence, and science. Oxford University Press.Google Scholar
- Russell, B. (1912). On the notion of cause, Proceedings of the aristotelian society, (Vol. 13 pp. 1–26). http://www.jstor.org/stable/4543833.
- Russo, F., & Williamson, J. (2007). Interpreting causality in the health sciences. International Studies in the Philosophy of Science, 21(2), 157–170. doi: 10.1080/02698590701498084.
- Salmon, W. (1984). Scientific explanation and the causal structure of the world. Princeton: Princeton University Press.Google Scholar
- Schum, D. (2011). Classifying forms and combinations of evidence: Necessary in a science of evidence. In Dawid, P., Twinning, W., & Vasilaki, M. (Eds.), Evidence, inference and enquiry, chap. 2. OUP (pp. 11–36).Google Scholar
- Senn, S. (2007). Statistical Issues in Drug Development. Wiley.Google Scholar
- Shaheen, S., Potts, J., Gnatiuc, L., Makowska, J., Kowalski, M. L., Joos, G., van Zele, T., van Durme, Y., De Rudder, I., Wöhrl, S., Godnic-Cvar, J., Skadhauge, L., Thomsen, G., Zuberbier, T., Bergmann, K. C., Heinzerling, L., Gjomarkaj, M., Bruno, A., Pace, E., Bonini, S., Fokkens, W., Weersink, E. J. M., Loureiro, C., Todo-Bom, A., Villanueva, C. M., Sanjuas, C., Zock, J. P., Janson, C., & Burney, P. (2008). The relation between paracetamol use and asthma: a ga2len european case-control study. European Respiratory Journal, 32(5), 1231–1236. doi: 10.1183/09031936.00039208.
- Spirtes, P., Glymour, C., & Scheines, R. (2000). Causation, prediction, and search. Adaptive computation and machine learning. MIT Press.Google Scholar
- Steel, D. (2008). Across the boundaries. Extrapolation in biology and social sciences. Oxford University Press.Google Scholar
- Straus, S. E., & McAlister, F. A. (2000). Evidence-based medicine: a commentary on common criticisms. Canadian Medical Association Journal, 163(7), 837–841.Google Scholar
- Suppes, P. (Ed.) (1970). A Probabilistic Theory of causality. North-Holland Pub. Co. Google Scholar
- Teira, D. (2011). Frequentist versus bayesian clinical trials. In Gifford, F. (Ed.) Handbook of Philosophy of Medicine (pp. 255–298). Wiley.Google Scholar
- Teira, D., & Reiss, J. (2013). Causality, impartiality and evidence-based policy, Mechanism and causality in biology and economics, (pp. 207–224). Springer.Google Scholar
- Wimsatt, W. C. (1981). Robustness, reliability and overdetermination. In Brewer, M., & Colllins, B. (Eds.), Scientific inquiry and the social sciences: festschrift for Donald Campbell, (pp. 125–163). Jossey-Bass Publishers.Google Scholar
- Wimsatt, W.C. (2012). Robustness, reliability, and overdetermination (1981). In Soler, L., Trizio, E., Nickles, T., & Wimsatt, W. (Eds.), Characterizing the robustness of science, boston studies in the philosophy of science, (Vol. 292 pp. 61–87): Springer, DOI doi: 10.1007/978-94-007-2759-5_2.
- Woodward, J. (2003). Making things happen: a theory of causal explanation (Oxford Studies in the Philosophy of Science). Oxford University Press.Google Scholar
- Woodward, J. (2010). Causation in biology: stability, specificity and the choice of levels of explanation. Biology and Philosophy, 44, 267–318. doi: 10.1007/s10539-010-9200-z.
- Worrall, J. (2007a). Evidence in medicine and evidence-based medicine. Philosophy Compass, 2(6), 981–1022. doi: 10.1111/j.1747-9991.2007.00106.x.
- Worrall, J. (2007b). Why there’s no cause to randomize. British Journal for the Philosophy of Science, 58(3), 451–488. doi: 10.1093/bjps/axm024.