Incentives for Research Effort: An Evolutionary Model of Publication Markets with Double-Blind and Open Review.

Contemporary debates about scientific institutions and practice feature many proposed reforms. Most of these require increased efforts from scientists. But how do scientists' incentives for effort interact? How can scientific institutions encourage scientists to invest effort in research? We explore these questions using a game-theoretic model of publication markets. We employ a base game between authors and reviewers, before assessing some of its tendencies by means of analysis and simulations. We compare how the effort expenditures of these groups interact in our model under a variety of settings, such as double-blind and open review systems. We make a number of findings, including that open review can increase the effort of authors in a range of circumstances and that these effects can manifest in a policy-relevant period of time. However, we find that open review's impact on authors' efforts is sensitive to the strength of several other influences.

Mass versus personalized medicine against COVID-19 in the "system sciences" era.

The importance of personalized/precision medicine for targeted therapies and improved outcomes both in terms of efficacy and safety in health care is by now grounded. We here discuss the current landscape of personalized medicine approaches against SARS-CoV-2. A schematic of the approach is illustrated in the figure in the text.

When Characteristics of Clinical Trials Require Per-Protocol as Well as Intention-to-Treat Outcomes to Draw Reliable Conclusions: Three Examples.

Under exceptional circumstances, including high rates of protocol non-compliance, per-protocol (PP) analysis can better indicate the real-world benefits of a medical intervention than intention-to-treat (ITT) analysis. Exemplifying this, the first randomized clinical trial (RCT) considered found that colonoscopy screenings were marginally beneficial, based upon ITT analysis, with only 42% of the intervention group actually undergoing the procedure. However, the study authors themselves concluded that the medical efficacy of that screening was a 50% reduction in colorectal cancer deaths among that 42% PP group. The second RCT found a ten-fold reduction in mortality for a COVID-19 treatment drug vs. placebo by PP analysis, but only a minor benefit by ITT analysis. The third RCT, conducted as an arm of the same platform trial as the second RCT, tested another COVID-19 treatment drug and reported no significant benefit by ITT analysis. Inconsistencies and irregularities in the reporting of protocol compliance for this study required consideration of PP outcomes for deaths and hospitalizations, yet the study coauthors refused to disclose them, instead directing inquiring scientists to a data repository which never held the study's data. These three RCTs illustrate conditions under which PP outcomes may differ significantly from ITT outcomes and the need for data transparency when these reported or indicated discrepancies arise.

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

Today's surge of big data coming from multiple sources is raising the stakes that pharmacovigilance has to win, making evidence synthesis a more and more robust approach in the field. In this scenario, many scholars believe that new computational methods derived from data mining will effectively enhance the detection of early warning signals for adverse drug reactions, solving the gauntlets that post-marketing surveillance requires. This article highlights the need for a philosophical approach in order to fully realize a pharmacovigilance 2.0 revolution. A state of the art on evidence synthesis is presented, followed by the illustration of E-Synthesis, a Bayesian framework for causal assessment. Computational results regarding dose-response evidence are shown at the end of this article.

E-Synthesis: A Bayesian Framework for Causal Assessment in Pharmacosurveillance.

Background: Evidence suggesting adverse drug reactions often emerges unsystematically and unpredictably in form of anecdotal reports, case series and survey data. Safety trials and observational studies also provide crucial information regarding the (un-)safety of drugs. Hence, integrating multiple types of pharmacovigilance evidence is key to minimising the risks of harm. Methods: In previous work, we began the development of a Bayesian framework for aggregating multiple types of evidence to assess the probability of a putative causal link between drugs and side effects. This framework arose out of a philosophical analysis of the Bradford Hill Guidelines. In this article, we expand the Bayesian framework and add "evidential modulators," which bear on the assessment of the reliability of incoming study results. The overall framework for evidence synthesis, "E-Synthesis", is then applied to a case study. Results: Theoretically and computationally, E-Synthesis exploits coherence of partly or fully independent evidence converging towards the hypothesis of interest (or of conflicting evidence with respect to it), in order to update its posterior probability. With respect to other frameworks for evidence synthesis, our Bayesian model has the unique feature of grounding its inferential machinery on a consolidated theory of hypothesis confirmation (Bayesian epistemology), and in allowing any data from heterogeneous sources (cell-data, clinical trials, epidemiological studies), and methods (e.g., frequentist hypothesis testing, Bayesian adaptive trials, etc.) to be quantitatively integrated into the same inferential framework. Conclusions: E-Synthesis is highly flexible concerning the allowed input, while at the same time relying on a consistent computational system, that is philosophically and statistically grounded. Furthermore, by introducing evidential modulators, and thereby breaking up the different dimensions of evidence (strength, relevance, reliability), E-Synthesis allows them to be explicitly tracked in updating causal hypotheses.

Reviewing the Mechanistic Evidence Assessors E-Synthesis and EBM+: A Case Study of Amoxicillin and Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS).

BACKGROUND: Basic science has delivered unprecedented insights into intricate relationships on the smallest scales within well-controlled environments. Addressing pressing societal decision problems requires an understanding of systems on larger scales in real-world situations. OBJECTIVE: To assess how well the evidence assessors E-Synthesis and EBM+ assess basic science findings to support medical decision making. METHODS: We demonstrate the workings of E-Synthesis and EBM+ on a case study: the suspected causal connection between the widely-used drug amoxicillin (AMX) and the putative adverse drug reaction: Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS). RESULTS: We determine an increase in the probability that AMX can cause DRESS within the E-Synthesis approach and using the EBM+ standards assess the basic science findings as supporting the existence of a mechanism linking AMX and DRESS. CONCLUSIONS: While progress is made towards developing methodologies which allow the incorporation of basic science research in the decision making process for pressing societal questions, there is still considerable need for further developments. A continued dialogue between basic science researchers and methodologists, philosophers and statisticians seems to offer the best prospects for developing and evaluating continuously evolving methodologies.

For Whom Does Determinism Undermine Moral Responsibility? Surveying the Conditions for Free Will Across Cultures.

Philosophers have long debated whether, if determinism is true, we should hold people morally responsible for their actions since in a deterministic universe, people are arguably not the ultimate source of their actions nor could they have done otherwise if initial conditions and the laws of nature are held fixed. To reveal how non-philosophers ordinarily reason about the conditions for free will, we conducted a cross-cultural and cross-linguistic survey (N = 5,268) spanning twenty countries and sixteen languages. Overall, participants tended to ascribe moral responsibility whether the perpetrator lacked sourcehood or alternate possibilities. However, for American, European, and Middle Eastern participants, being the ultimate source of one's actions promoted perceptions of free will and control as well as ascriptions of blame and punishment. By contrast, being the source of one's actions was not particularly salient to Asian participants. Finally, across cultures, participants exhibiting greater cognitive reflection were more likely to view free will as incompatible with causal determinism. We discuss these findings in light of documented cultural differences in the tendency toward dispositional versus situational attributions.

Causal assessment of pharmaceutical treatments: why standards of evidence should not be the same for benefits and harms?

It is increasingly acknowledged both among epidemiologists and regulators that the assessment of pharmaceutical harm requires specific methodological approaches that cannot simply duplicate those developed for testing efficacy. However, this intuition lacks sound epistemic bases and delivers ad hoc advice. This paper explains why the same methods of scientific inference do not fare equally well for efficacy and safety assessment by tracing them back to their epistemic foundations. To illustrate this, Cartwright's distinction into clinching and vouching methods is adopted and a series of reasons is provided for preferring the latter to the former: (1) the need to take into account all available knowledge and integrate it with incoming data; (2) the awareness that a latent unknown risk may always change the safety profile of a given drug (precautionary principle); (3) cumulative learning over time; (4) requirement of probabilistic causal assessment to allow decision under uncertainty; (5) impartiality; and (6) limited and local information provided by randomised controlled trials. Subsequently, the clinchers/vouchers distinction is applied to a case study concerning the debated causal association between paracetamol and asthma. This study illustrates the tension between implicit epistemologies adopted in evaluating evidence and causality; furthermore, it also shows that discounting causal evidence may be a result of unacknowledged low priors or lack of valid alternative options. We conclude with a presentation of the changing landscape in pharmacology and the trend towards an increased use of Bayesian tools for assessment of harms.

Safety vs. efficacy assessment of pharmaceuticals: Epistemological rationales and methods.

In their comparative analysis of Randomised Clinical Trials and observational studies, Papanikoloau et al. (2006) assert that "it may be unfair to invoke bias and confounding to discredit observational studies as a source of evidence on harms". There are two kinds of answers to the question why this is so. One is based on metaphysical assumptions, such as the problem of causal sufficiency, modularity and other statistical assumptions. The other is epistemological and relates to foundational issues and how they determine the constraints we put on evidence. I will address here the latter dimension and present recent proposals to amend evidence hierarchies for the purpose of safety assessment of pharmaceuticals; I then relate these suggestions to a case study: the recent debate on the causal association between paracetamol and asthma. The upshot of this analysis is that different epistemologies impose different constraints on the methods we adopt to collect and evaluate evidence; thus they grant "lower level" evidence on distinct grounds and at different conditions. Appreciating this state of affairs illuminates the debate on the epistemic asymmetry concerning benefits and harms and sets the basis for a foundational, as opposed to heuristic, justification of safety assessment based on heterogeneous evidence.

Until RCT proven? On the asymmetry of evidence requirements for risk assessment.

The problem of collecting, analysing and evaluating evidence on adverse drug reactions is an example of the more general class of epistemological problems related to scientific inference and prediction, as well as a central problem of health care practice. Philosophical discussions have analysed critically the methodological pitfalls and epistemological implications of evidence assessment in medicine; however, they have focused predominantly on evidence of treatment efficacy. Most of this work is devoted to statistical methods of causal inference with a special focus on the privileged role assigned to randomized controlled trials (RCTs) in evidence-based medicine. Regardless of whether the RCT's privilege holds for efficacy assessment, it is nevertheless important to make a distinction between causal inference in relation to intended and unintended effects, in that the unknowns at stake are heterogeneous in the two contexts. This point has been emphasized by epidemiologists in the last decade. Their primary focus is methodological and regards the fact that bias and confounding factors do not affect studies on intended and unintended effects in the same way. However, deeper concerns ground the intuition for such a distinction; these are related to the constraints we impose on evidence and their epistemological justification. My thesis is that such constraints ought to be understood as being different in evidence for risk versus for efficacy. I present the recent debate on the causal association between acetaminophen and asthma in order to illustrate the point at issue. The upshot of my analysis is that different epistemologies confer different methodological choices, which in turn bring about relevant practical implications such as the decision to restrict or suspend drug use rather than leaving it on the market. Thus, it is worth considering the criteria underlying our evidence constraints because they may be ill suited to the purpose for which they are used.

Disability, human rights, and the International Classification of Functioning, Disability, and Health: systematic review.

This literature review focuses on the literature on disability from the ethical and human rights perspective in the light of the International Classification of Functioning, Disability, and Health in the period from January 1, 2008, to June 30, 2010. This article identifies and examines studies that deal with the subject of disability with reference to rights, ethical issues, and justice. A total of 42 articles and 33 books were selected. The subject most frequently dealt with in studies on disability is that of human rights (76% of the articles and 79% of the books examined), followed by topics relating to welfare (52% of articles and 64% of books), International Classification of Functioning, Disability, and Health (38% of articles and 45% of books), justice (24% of articles and 48% of books), education (21% of articles and 61% of books), and work (19% of articles and 39% of books). The subject of disability is dealt with in various fields of study and various disciplines. Most of the studies are based on the legal approach. It is to be hoped that there will be an increase in the philosophical and ethical study of disability, which has only recently entered the European debate.

Is genetic infommation family property? expandig on the argument of confidentiiality breach and duty to inform persons at risk / ¿la información genética es de prpiedad familiar? ampliando el argumento de la rruptura de la confidencialidad y en el deber de informar personas en situación de riegoo / A informaão genéética é de propriedade failiar? ampliando o argumento daa quebra da confidencialidade e o dever de informar pessoas em situação de risco

A current trend in bioethics considers genetic information as family property. This paper uses a logical approach to critically examine Matthew Liao's proposal on the familial nature of genetic information as grounds for the duty to share it with relatives and for breach of confidentiality by the geneticist. The authors expand on the topic by examining the relationship between the arguments of probability and the familial nature of genetic information, as well as the concept of harm in the context of genetic risk. Lastly, they examine the concept of harm in relation to the type of situations w the potential recipient of the information is not the person directly affected by the risk.

Considerar la información genética como una propiedad familiar es una tendencia actual en Bioética. El artículo examina con un método crítico, desde un enfoque lógico conceptual la propuesta de Matthew Liao, que sugiere como justificación de la obligación de compartir información entre familiares y para la ruptura de la confidencialidad, la naturaleza familiar de la información genética. Se amplía el tema mediante la relación entre los argumentos de la probabilidad y naturaleza familiar de la información genética y analiza el concepto de daño en el contexto del riesgo genético. Por último examina del concepto de daño en relación con el tipo de situaciones en que el posible receptor de la información no es la persona directamente afectada por el riesgo.

Considerar a informação genética como uma propriedade familiar é uma tendência atual em Bioética. O artigo examina com um método crítico, a partir de um enfoque lógico conceitual, a proposta de Matthew Liao, que sugere como justificativa a obrigação de compartilhar informação entre familiares e para a quebra da confidencialidade, a natureza familiar da informação genética. Amplia-se o tema mediante a relação entre os argumentos da probabilidade e a natureza familiar da informação genética, e analisa o conceito de dano no contexto do risco genético. Por último, examina o conceito de dano referente ao tipo de situações no qual o possível receptor da informação não é a pessoa diretamente afetada pelo risco.