1,720,997 research outputs found
STATISTICS IN CLINICAL TRIALS: OUT OF CONDITION. SOME PROBLEMS OF UNCONDITIONAL INFERENCEAT THE CROSSROADS OF METHODOLOGY AND ETHICS
Full text linkRandomized controlled trials are experiments for the evaluation of a new treatment option, currently representing the "gold standard" in health care assessment. Clinical trials fulfill a double role of evidence production and of regulatory oversight in sanctioning new drugs' approval into the drug market.
For this reason trials are large and tightly regulated enterprises that have to comply with ethical requirements while at the same time maintaining high epistemic standards, in a balance that becomes increasingly difficult to strike as research questions become more and more sophisticated.
The statistical framework adopted for designing and analysing trials represents a relevant part of this architecture. Statististical methodology influences such aspects as which inferences are licensed on the basis of data and what is the degree of support granted to an hypothesis. Thus, statistics plays a fundamental role as a gatekeeper both in warranting the ethical permissibility of a trial, and in licensing conclusions about the most effective treatment.
Certain widely-accepted statistical principles have an impact on the way results from medical studies are evaluated.
One such principle is conditioning, i.e. the possibility to incorporate an assessment of strength of evidence in inferential statements of confidence. Currently, conditioning is not part of the statistical method in use, although it is upheld by alternative statistical paradigms such as the Bayesian. In my thesis I analyze the impact of conditioning upon the ethical, epistemic and regulatory facets of trials and I suggest the possibility of incorporating conditioning within the current statistical paradigm of clinical research
Mechanistic understanding in clinical practice : complementing evidence-based medicine with personalized medicine
No full textIn the last century, medicine has undergone an unprecedented wave of radical changes. From the implementation of surgery up to the development of single gene-targeted therapies, clinical decision making has become increasingly complex to handle. Today, this complexity needs to be rethought in the light of two emerging paradigms: evidence-based medicine (EBM) and personalized medicine (P-Med). The new availability of diverse sources of scientific evidence raises significant issues concerning how clinicians will compare, evaluate and orient their decisions in front of a rapidly growing plethora of therapies, procedures, medical technologies and drugs. In this paper, we compare the background visions behind these two paradigms, evaluating their respective relevance for present and future clinical decision making. In particular, we argue that EBM and P-Med are driven by two diverse modes of reasoning about ‘evidence making’ in medicine. EBM is grounded on statistical notions and epidemiological data, generally gathered through systematic meta-reviews of randomized controlled trials; P-Med, instead, is grounded on mechanistic explanations of molecular interactions, metabolic pathways and biomarkers. While both paradigms are epistemically sound, we argue that they cannot, and should not, be hybridized into a unique model. Rather, they ought to represent two compatible, but alternative ways of informing the clinical practice. Hence, we conclude that clinicians may expect to see their responsibility increasing as they will deal with diverse, but equally compelling, ways of reasoning and deciding about which intervention will qualify as the ‘best one’ in each individual case
The ethics of non-inferiority trials : a consequentialist analysis
Full text linkDiscussions about the merits and shortcomings of non-inferiority trials are becoming increasingly common in the medical community and among regulatory agencies. However, criticisms targeting the ethical standing of non-inferiority trials have often been mistargeted. In this article we review the ethical standing of trials of non-inferiority. In the first part of the article, we outline a consequentialist position according to which clinical trials are best conceived as epistemic tools aimed at fostering the proper ends of medicine. According to this view, clinical trials are means to ends, and thus their moral status depends both on how well they perform as means to reach desired ends and on which ends they are meant to achieve. Building upon this normative framework in the next two sections we analyze the specific ethical issues raised by non-inferiority trials. By making it clear that clinical trials are just epistemic tools – i.e. means to certain ends – it is possible not only to clarify the conceptual debate over a fundamental issue in clinical research, but also to identify which ethically relevant considerations ought to be addressed in setting up a non-inferiority trial
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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