La autora presenta algunas criticas generales al proyecto de reducir las leyes causales a probabilidades. Además, muestra que las leyes causales son imprescindibles para poder diferenciar las strategias efectivas de las que no lo son y da un criterio para considerar cuando podemos deducir causalidad a través de datos estadísticos.

The claims of randomized controlled trials to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This article describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. (...) It argues that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The article reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

Evidence-Based Medicine is a relatively new movement that seeks to put clinical med- icine on a firmer scientific footing. I take it as uncontroversial that medical practice should be based on best evidence-the interesting questions concern the details. This paper tries to move towards a coherent and unified account of best evidence in medicine, by exploring in particular the EBM position on RCTs (randomized controlled trials).

Evidence-Based Medicine is a relatively new movement that seeks to put clinical medicine on a firmer scientific footing. I take it as uncontroversial that medical practice should be based on best evidence—the interesting questions concern the details. This paper tries to move towards a coherent and unified account of best evidence in medicine, by exploring in particular the EBM position on RCTs.

An astonishing volume and diversity of evidence is available for many hypotheses in the biomedical and social sciences. Some of this evidence—usually from randomized controlled trials (RCTs)—is amalgamated by meta-analysis. Despite the ongoing debate regarding whether or not RCTs are the ‘gold-standard’ of evidence, it is usually meta-analysis which is considered the best source of evidence: meta-analysis is thought by many to be the platinum standard of evidence. However, I argue that meta-analysis falls far short of that standard. Different meta-analyses (...) of the same evidence can reach contradictory conclusions. Meta-analysis fails to provide objective grounds for intersubjective assessments of hypotheses because numerous decisions must be made when performing a meta-analysis which allow wide latitude for subjective idiosyncrasies to influence its outcome. I end by suggesting that an older tradition of evidence in medicine—the plurality of reasoning strategies appealed to by the epidemiologist Sir Bradford Hill—is a superior strategy for assessing a large volume and diversity of evidence. (shrink)

Evidence-Based Medicine (EBM) developed from the work of clinical epidemiologists at McMaster University and Oxford University in the 1970s and 1980s and self-consciously presented itself as a "new paradigm" called "evidence-based medicine" in the early 1990s. The techniques of the randomized controlled trial, systematic review and meta-analysis have produced an extensive and powerful body of research. They have also generated a critical literature that raises general concerns about its methods. This paper is a systematic review of the critical literature. It (...) finds the description of EBM as a Kuhnian paradigm helpful and worth taking further. Three kinds of criticism are evaluated in detail: criticisms of procedural aspects of EBM (especially from Cartwright, Worrall and Howick), data showing the greater than expected fallibility of EBM (Ioaanidis and others), and concerns that EBM is incomplete as a philosophy of science (Ashcroft and others). The paper recommends a more instrumental or pragmatic approach to EBM, in which any ranking of evidence is done by reference to the actual, rather than the theoretically expected, reliability of results. Emphasis on EBM has eclipsed other necessary research methods in medicine. With the recent emphasis on translational medicine, we are seeing a restoration of the recognition that clinical research requires an engagement with basic theory (e.g. physiological, genetic, biochemical) and a range of empirical techniques such as bedside observation, laboratory and animal studies. EBM works best when used in this context. (shrink)

We argue that the health sciences make causal claims on the basis of evidence both of physical mechanisms, and of probabilistic dependencies. Consequently, an analysis of causality solely in terms of physical mechanisms or solely in terms of probabilistic relationships, does not do justice to the causal claims of these sciences. Yet there seems to be a single relation of cause in these sciences - pluralism about causality will not do either. Instead, we maintain, the health sciences require a theory (...) of causality that unifies its mechanistic and probabilistic aspects. We argue that the epistemic theory of causality provides the required unification. (shrink)

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. © 2010 Springer Science+Business Media B.V. (shrink)

Published research findings are sometimes refuted by subsequent evidence, says Ioannidis, with ensuing confusion and disappointment.

Russo and Williamson claim that establishing causal claims requires mechanistic and difference-making evidence. In this article, I will argue that Russo and Williamson's formulation of their thesis is multiply ambiguous. I will make three distinctions: mechanistic evidence as type vs object of evidence; what mechanism or mechanisms we want evidence of; and how much evidence of a mechanism we require. I will feed these more precise meanings back into the Russo–Williamson thesis and argue that it is both true and false: (...) two weaker versions of the thesis are worth supporting, while the stronger versions are not. Further, my distinctions are of wider concern because they allow us to make more precise claims about what kinds of evidence are required in particular cases. (shrink)

Philosophers of science have insisted that evidence of underlying mechanisms is required to support claims about the effects of medical interventions. Yet evidence about mechanisms does not feature on dominant evidence-based medicine “hierarchies.” After arguing that only inferences from mechanisms (“mechanistic reasoning”)—not mechanisms themselves—count as evidence, I argue for a middle ground. Mechanistic reasoning is not required to establish causation when we have high-quality controlled studies; moreover, mechanistic reasoning is more problematic than has been assumed. Yet where the problems can (...) be overcome, mechanistic reasoning can and should be used as evidence. (shrink)

Because “evidence” is at issue in evidence-based medicine (EBM), the critical responses to the movement have taken up themes from post-positivist philosophy of science to demonstrate the untenability of the objectivist account of evidence. While these post-positivist critiques seem largely correct, I propose that when they focus their analyses on what counts as evidence, the critics miss important and desirable pragmatic features of the evidence-based approach. This article redirects critical attention toward EBM’s rigid hierarchy of evidence as the culprit of (...) its objectionable epistemic practices. It reframes the EBM discourse in light of a distinction between objectivist and pragmatic epistemology, which allows for a more nuanced analysis of EBM than previously offered: one that is not either/or in its evaluation of the decision-making technology as either iconoclastic or creedal. -/- . (shrink)

Weighing complex sets of evidence (i.e., from multiple disciplines and often divergent in implications) is increasingly central to properly informed decision-making. Determining “where the weight of evidence lies” is essential both for making maximal use of available evidence and figuring out what to make of such evidence. Weighing evidence in this sense requires an approach that can handle a wide range of evidential sources (completeness), that can combine the evidence with rigor, and that can do so in a way other (...) experts can assess and critique (transparency). But the democratic context in need of weight-of-evidence analysis also places additional constraints on the process, including communicability of the process to the general public, the need for an approach that can be used across a broad range of contexts (scope), and timeliness of process (practicality). I will compare qualitative and quantitative approaches with respect to both traditional epistemic criteria and criteria that arise from the democratic context, and argue that a qualitative explanatory approach can best meet the criteria and elucidate how to utilize the other approaches. This should not be surprising, as the approach I argue for is the one that most closely tracks general scientific reasoning. (shrink)

The philosophy of evidence-based medicine -- What is EBM? -- What is good evidence for a clinical decision? -- Ruling out plausible rival hypotheses and confounding factors : a method -- Resolving the paradox of effectiveness : when do observational studies offer the same degree of evidential support as randomized trials? -- Questioning double blinding as a universal methodological virtue of clinical trials : resolving the Philip's paradox -- Placebo controls : problematic and misleading baseline measures of effectiveness -- Questioning (...) the methodological superiority of "placebo" over "active" controlled trials -- Examining the paradox that traditional roles for mechanistic reasoning and expert -- Judgment have been up-ended by EBM -- A qualified defence of the EBM stance on mechanistic reasoning -- Knowledge that versus knowledge how : situating the EBM position on expert clinical judgment -- Moving EBM forward. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

The International Agency for Research on Cancer (IARC) is an organization which seeks to identify the causes of human cancer. Per agent, such as betel quid or Human Papillomaviruses, they review the available evidence deriving from epidemiological studies, animal experiments and information about mechanisms (and other data). The evidence of the different groups is combined such that an overall assessment of the carcinogenicity of the agent in question is obtained. In this paper, we critically review the IARC’s carcinogenicity evaluations. First (...) we show that serious objections can be raised against their criteria and procedures – more specifically regarding the role of mechanistic knowledge in establishing causal claims. Our arguments are based on the problem of confounders, of the assessment of the temporal stability of carcinogenic relations, and of the extrapolation from animal experiments. Then we address a very important question, viz. how we should treat the carcinogenicity evaluations that were based on the current procedures. After showing that this question is important, we argue that an overall dismissal of the current evaluations would be too radical. Instead, we argue in favour of a stepwise re-evaluation of the current findings. (shrink)