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.
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