Epistemology of causal inference in pharmacology

Abstract

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 invoke 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. In this paper, we develop the pluralistic approach along Hill's (1965) famous criteria for discerning causal associations by employing Bovens' and Hartmann's general Bayes net reconstruction of scientific inference to model the assessment of harms in an evidenceamalgamation framework.

New Insights in Computational Methods for Pharmacovigilance: E-Synthesis, a Bayesian Framework for Causal Assessment

“…E-Synthesis emerges as a theoretical framework for causal assessment based on [20,21], aimed to support estimates of causal associations between drugs and adverse events. E-Synthesis practically consists in a “scaffold” where all the available evidence may probabilistically increase or decrease causal hypotheses.…”

“…When utilities of harms and benefits, as well as estimation of benefits are provided by further means, a drug regulatory agency can perform an expected utility calculation to determine whether the expected advantages of a drug exceed the expected dis-advantages. The agency will withdraw the drug (or not approve it), if the expected disadvantages outweigh the expected benefits, see ([20], Section 2.2)).…”

“…This article presents a new theoretical framework to support decisions in pharmacovigilance, defined “ E-Synthesis ”, a tool encoded through a Bayesian network able to robustly screen and amalgamate evidence of different types (such as epidemiological studies, molecular biology research findings, case reports) that are combined together in order to form the “critical mass” needed to make decisions about the approval/withdrawal of a particular drug for/from the market [20,21].…”

Does medicine need philosophy?

“…More specifically, many philosophers have claimed that mechanistic evidence is essential for understanding causal relationships, as, for example, the one between a drug and its effects (Russo & Williamson, ). In this regard, a philosophical movement (EBM+) is emerging providing guidelines on how to evaluate and integrate mechanistic evidence alongside statistical correlations (Parkkinen et al, ), while some other, pushing this argument even further, is trying to elaborate computational methods to amalgamate all the available evidence with respect to specific problems such as adverse drug reactions (Landes, Osimani, & Poellinger, ). This appeal for a broader approach to evidence is also important to patients.…”

Medical scientists and philosophers worldwide appeal toEBMto expand the notion of ‘evidence’

“…Our research has developed out of a conviction that philosophical analysis ought to have a direct impact on the practice of medicine. In particular, if we are to understand what is meant by ‘evidence’, what is the ‘best available evidence’ and how to apply it in the context of medicine, we need to tackle the problem of causation head on 1 8–12. In practice, this means understanding the context in which evidence is obtained, as well as how the evidence might be interpreted and applied when making practical clinical decisions 7 13.…”