Randomised controlled trial of fish oil supplement to treat cancer cachexia

This is the protocol for a review and there is no abstract. The objectives are as follows: Our overall aim is to provide an overview of interventions for preventing falls in older people by summarising the evidence from multiple Cochrane intervention reviews that evaluate the effects (primarily, rate of falls and number of fallers) of these interventions in different populations of older people, such as those defined by setting or by specific medical conditions. Fall prevention interventions will include those in the following categories: supervised or unsupervised exercises; medication; surgery; management of urinary incontinence; fluid or nutrition therapy; psychological; environment and assistive technologies; social environment; knowledge/education interventions and any other interventions that do not fall into one of these categories (Lamb 2007). Interventions tested may belong to one category ('single' intervention), or more than one category ('multiple' and 'multifactorial' interventions)

General practice performance in referral for suspected cancer: influence of number of cases and case-mix on publicly reported data

Background:Publicly available data show variation in GPs’ use of urgent suspected cancer (USC) referral pathways. We investigated whether this could be due to small numbers of cancer cases and random case-mix, rather than due to true variation in performance. Methods:We analysed individual GP practice USC referral detection rates (proportion of the practice's cancer cases that are detected via USC) and conversion rates (proportion of the practice's USC referrals that prove to be cancer) in routinely collected data from GP practices in all of England (over 4 years) and northeast Scotland (over 7 years). We explored the effect of pooling data. We then modelled the effects of adding random case-mix to practice variation. Results:Correlations between practice detection rate and conversion rate became less positive when data were aggregated over several years. Adding random case-mix to between-practice variation indicated that the median proportion of poorly performing practices correctly identified after 25 cancer cases were examined was 20% (IQR 17 to 24) and after 100 cases was 44% (IQR 40 to 47). Conclusions:Much apparent variation in GPs’ use of suspected cancer referral pathways can be attributed to random case-mix. The methods currently used to assess the quality of GP-suspected cancer referral performance, and to compare individual practices, are misleading. These should no longer be used, and more appropriate and robust methods should be develope

Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons

Purpose: The Medical Imaging and Data Resource Center (MIDRC) open data commons was launched to accelerate the development of artificial intelligence (AI) algorithms to help address the COVID-19 pandemic. The purpose of this study was to quantify longitudinal representativeness of the demographic characteristics of the primary MIDRC dataset compared to the United States general population (US Census) and COVID-19 positive case counts from the Centers for Disease Control and Prevention (CDC). Approach: The Jensen-Shannon distance (JSD), a measure of similarity of two distributions, was used to longitudinally measure the representativeness of the distribution of (1) all unique patients in the MIDRC data to the 2020 US Census and (2) all unique COVID-19 positive patients in the MIDRC data to the case counts reported by the CDC. The distributions were evaluated in the demographic categories of age at index, sex, race, ethnicity, and the combination of race and ethnicity. Results: Representativeness of the MIDRC data by ethnicity and the combination of race and ethnicity was impacted by the percentage of CDC case counts for which this was not reported. The distributions by sex and race have retained their level of representativeness over time. Conclusion: The representativeness of the open medical imaging datasets in the curated public data commons at MIDRC has evolved over time as the number of contributing institutions and overall number of subjects have grown. The use of metrics, such as the JSD support measurement of representativeness, is one step needed for fair and generalizable AI algorithm development.</p

Supporting the role of universities in leading individual and societal transformation through education for sustainable development

There is growing recognition of the value of Education for Sustainable Development (ESD) for all learners, and of the unique role that universities play in the transformation of individuals, institutions and societies towards more sustainable futures. Universities engage and even lead in several areas: education, research and community engagement, all of which are essential in this transformation. Further, given their focus and influence, universities are pivotal to action needed to realise the UN Sustainable Development Goals (SDGs) but, to date, UK university integration of ESD and engagement with the SDGs is relatively limited. In recognition that a more urgent and meaningful response is needed to deliver the 2030 targeted socio-economic transformation outlined by the SDGs, the UK ESD Guidance has been comprehensively revised to support universities to deliver education which enables students to acquire sustainability competencies, equipping them to play leadership roles in an increasingly uncertain world. In this case study, we critically analyse the role of universities and explore why ESD needs to be more urgently integrated in teaching and learning. We review the barriers to achieving ESD in UK universities at political and institutional levels. Finally, we explore the policy-practice interface and outline how the new UK ESD Guidance can support universities in leading individual and societal transformation through ESD and act as a stimulus for embedding ESD in university curricula in both UK and international contexts. We conclude that universities have as yet unfulfilled potential to explore and facilitate ESD for sustainability leadership

Randomized controlled trial of live lactobacillus acidophilus plus bifidobacterium bifidum in prophylaxis of diarrhea during radiotherapy in cervical cancer patients

<p>Abstract</p> <p>Background</p> <p>Radiation-induced diarrhea is frequently observed during pelvic radiotherapy. This study was performed to determine the ability of a probiotic containing live lactobacillus acidophilus plus bifidobacterium bifidum to reduce the incidence of radiation-induced diarrhea in locally advanced cervical cancer patients.</p> <p>Methods</p> <p>Patients who were undergoing pelvic radiotherapy concurrent with weekly cisplatin were randomly assigned to a study drug or placebo, in a double-blind study. Diarrhea was graded weekly according the Common Toxicity Criteria (CTC) system. Stool consistency and white and red blood cell count in stool were also assessed. The primary endpoint was to reduce the incidence of diarrhea, defined by a CTC grade 2 or more, and the need for anti-diarrheal medication.</p> <p>Results</p> <p>A total of 63 patients were enrolled. Grade 2 -3 diarrhea was observed in 45% of the placebo group (n = 31) and 9% of the study drug group (n = 32) (p = 0.002). Anti-diarrheal medication use was significantly reduced in the placebo group (p = 0.03). The patients in the study drug group had a significantly improved stool consistency (p < 0.001).</p> <p>Conclusions</p> <p>Live lactobacillus acidophilus plus bifidobacterium bifidum reduced the incidence of radiation-induced diarrhea and the need for anti-diarrheal medication and had a significant benefits on stool consistency.</p

The National Awareness and Early Diagnosis Initiative in England: assembling the evidence

A National Awareness and Early Diagnosis Initiative (NAEDI) has been established in England as part of the Government's strategy to improve cancer outcomes. One of the early priorities for this initiative has been to assemble the diverse evidence linking late diagnosis with poor survival and avoidable deaths. This supplement brings together new perspectives on existing research in this area together with findings from recently commissioned research. This paper describes a provisional model, the ‘NAEDI pathway', for testing hypotheses relating to late diagnosis and its impact. Key findings from other papers in this supplement are also highlighted

Estimating the potential survival gains by eliminating socioeconomic and sex inequalities in stage at diagnosis of melanoma.

BACKGROUND: Although inequalities in cancer survival are thought to reflect inequalities in stage at diagnosis, little evidence exists about the size of potential survival gains from eliminating inequalities in stage at diagnosis. METHODS: We used data on patients diagnosed with malignant melanoma in the East of England (2006-2010) to estimate the number of deaths that could be postponed by completely eliminating socioeconomic and sex differences in stage at diagnosis after fitting a flexible parametric excess mortality model. RESULTS: Stage was a strong predictor of survival. There were pronounced socioeconomic and sex inequalities in the proportion of patients diagnosed at stages III-IV (12 and 8% for least deprived men and women and 25 and 18% for most deprived men and women, respectively). For an annual cohort of 1025 incident cases in the East of England, eliminating sex and deprivation differences in stage at diagnosis would postpone approximately 24 deaths to beyond 5 years from diagnosis. Using appropriate weighting, the equivalent estimate for England would be around 215 deaths, representing 11% of all deaths observed within 5 years from diagnosis in this population. CONCLUSIONS: Reducing socioeconomic and sex inequalities in stage at diagnosis would result in substantial reductions in deaths within 5 years of a melanoma diagnosis.This article is an independent research supported by different funding bodies, beyond the authors’ own employing organisations. MJR was partially funded by a Cancer Research UK Postdoctoral Fellowship (CRUK_A13275). GL is supported by a Postdoctoral Fellowship award by the National Institute for Health Research (NIHR PDF-2011-04-047) to end of 2014 and a Cancer Research UK Clinician Scientist Fellowship award (A18180) from January 2015. The views expressed in this publication are those of the authors and not necessarily those of the National Health Service (NHS), the National Institute for Health Research, the Department of Health, Cancer Research UK, or any other organisation. We thank all staff at the National Cancer Registration Service, Public Health England, Eastern Office, who helped collect and code data used in this study. We particularly acknowledge the help of Dr Clement H Brown and Dr Brian A Rous who were responsible for staging.This is the final published version. It first appeared at http://www.nature.com/bjc/journal/v112/n1s/full/bjc201550a.html