1,721,139 research outputs found
Design and Conduct of research and clinical trials
No full textKey points:* The clinical impact of research evidence relies on confidence in its quality.* Palliative care is characterized by complex clinical situations, but clinical trials require simple clinical questions.* The designs of explanatory and pragmatic trials depend on the clinical research question.* Choices of study populations and standard comparators influence the generalizability of the results (i.e., external validity).* An adequate sample size and low attrition rate influence the reliability of the study result (i.e., internal validity).* Randomization reduces the risk of bias by overcoming confounding factors.* Choices of clinically relevant outcome measures and patient populations are crucial for the relevance of palliative care clinical trials.* Qualitative and other important clinical information can be included in the design of quantitative clinical trails.* Infrastructural support is essential for adequate recruitment, data management, and research governance.<br/
Interim safety data on the FRAGMATIC trial: a randomised phase III clinical trial investigating the effect of FRAGMin (R) added to standard therapy in patients with lung cancer
No full textBackground: Venous thromboembolism (VTE) is common in lungcancer patients and the incidence is increased by treatments. Lungcancer patients often have advanced disease at presentation, as wellas co-morbidities, such as heart failure and chronic lung disease allof which increase the risk of VTE. Low molecular weight heparin(LMWH) has been used in the prophylaxis of VTE but there arelimited data on the use of LMWH as primary thromboprophylaxisin cancer patients. Because of this and interesting animal data suggestingthat LMWH may be anti-metastatic, the effect of long termLMWH on overall survival should be investigated
FRAGMATIC: A randomised phase III clinical trial investigating the effect of <b>fragm</b>in<sup>® </sup><b>a</b>dded to standard <b>t</b>herapy <b>i</b>n patients with lung <b>c</b>ancer
Full text linkAbstract Background Venous thromboembolism (VTE) occurs when blood clots in the leg, pelvic or other deep vein (deep vein thrombosis) with or without transport of the thrombus into the pulmonary arterial circulation (pulmonary embolus). VTE is common in patients with cancer and is increased by surgery, chemotherapy, radiotherapy and disease progression. Low molecular weight heparin (LMWH) is routinely used to treat VTE and some evidence suggests that LMWH may also have an anticancer effect, by reduction in the incidence of metastases. The FRAGMATIC trial will assess the effect of adding dalteparin (FRAGMIN), a type of LMWH, to standard treatment for patients with lung cancer. Methods/Design The study design is a randomised multicentre phase III trial comparing standard treatment and standard treatment plus daily LMWH for 24 weeks in patients with lung cancer. Patients eligible for this study must have histopathological or cytological diagnosis of primary bronchial carcinoma (small cell or non-small cell) within 6 weeks of randomisation, be 18 or older, and must be willing and able to self-administer 5000 IU dalteparin by daily subcutaneous injection or have it administered to themselves or by a carer for 24 weeks. A total of 2200 patients will be recruited from all over the UK over a 3 year period and followed up for a minimum of 1 year after randomisation. Patients will be randomised to one of the two treatment groups in a 1:1 ratio, standard treatment or standard treatment plus dalteparin. The primary outcome measure of the trial is overall survival. The secondary outcome measures include venous thrombotic event (VTE) free survival, serious adverse events (SAEs), metastasis-free survival, toxicity, quality of life (QoL), levels of breathlessness, anxiety and depression, cost effectiveness and cost utility. Trial registration Current Controlled Trials ISRCTN80812769</p
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
Using deep learning on histology to inform colorectal cancer patient treatment
Full text linkColorectal cancer is a serious health problem in the UK, with 11,500 patients diagnosed with rectal cancer each year. Neoadjuvant chemoradiotherapy treatment can be given to a patient prior to surgery to shrink the tumour, but roughly one third of patients will have a poor response to this treatment. In this work we develop deep learning approaches to predict how rectal cancer patients will respond to radiotherapy treatment, based off the routinely taken histology slides of pre-operative biopsies, in order to help clinicians make better personalised treatment decisions. We integrate the context of the imaging modality and the nature of the cancer into our approaches, first by including morphological and positional information into a Vision Transformer network. Secondly, we use tissue graph neural networks and multi-task learning with spatial and molecular endpoints to improve interpretability of our prediction model. Finally, we develop a domain adaptation method to help our proposed approach generalise to different cohorts of patients
- …
