Mindfulness-based supportive therapy on reducing suffering in patients with advanced cancer: randomised controlled trial

Objectives Suffering is common among patients with advanced cancer. The practice of mindfulness during patient care can potentially reduce suffering. We aimed to examine the efficacy of mindfulness-based supportive therapy (MBST) on reducing suffering in patients with advanced cancer. Methods We conducted a parallel-group, single-blinded, randomised controlled trial at the University of Malaya Medical Centre, Malaysia. Seventy-three patients with advanced cancer with an overall suffering score ≥4/10 based on the Suffering Pictogram were recruited and randomly assigned into either the MBST group (n=34) or the control group (n=39). Results There was a statistically significant reduction in the overall suffering score in the MBST group compared with the control group (U=432.5, median1 =−2.0, median2 =−1.0, z=−2.645, p=0.008). There was also significant improvement in the total Hospital Anxiety and Depression Scale score (U=483.5, median1 =−4.0, median2 =−3.0, z=−1.994, p=0.046), and the total Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being score (U=252.0, median1 =+14.5, median2 =+5.0, z=−4.549, p=0.000) in the MBST group compared with the control group. Conclusions The results provided evidence that the practice of MBST during patient care could promote positive psychosocial outcome

STAT3 can be activated through paracrine signaling in breast epithelial cells

<p>Abstract</p> <p>Background</p> <p>Many cancers, including breast cancer, have been identified with increased levels of phosphorylated or the active form of Signal Transducers and Activators of Transcription 3 (STAT3) protein. However, whether the tumor microenvironment plays a role in this activation is still poorly understood.</p> <p>Methods</p> <p>Conditioned media, which contains soluble factors from MDA-MB-231 and MDA-MB-468 breast cancer cells and breast cancer associated fibroblasts, was added to MCF-10A breast epithelial and MDA-MB-453 breast cancer cells. The stimulation of phosphorylated STAT3 (p-STAT3) levels by conditioned media was assayed by Western blot in the presence or absence of neutralized IL-6 antibody, or a JAK/STAT3 inhibitor, JSI-124. The stimulation of cell proliferation in MCF-10A cells by conditioned media in the presence or absence of JSI-124 was subjected to MTT analysis. IL-6, IL-10, and VEGF levels were determined by ELISA analysis.</p> <p>Results</p> <p>Our results demonstrated that conditioned media from cell lines with constitutively active STAT3 are sufficient to induce p-STAT3 levels in various recipients that do not possess elevated p-STAT3 levels. This signaling occurs through the JAK/STAT3 pathway, leading to STAT3 phosphorylation as early as 30 minutes and is persistent for at least 24 hours. ELISA analysis confirmed a correlation between elevated levels of IL-6 production and p-STAT3. Neutralization of the IL-6 ligand or gp130 was sufficient to block increased levels of p-STAT3 (Y705) in treated cells. Furthermore, soluble factors within the MDA-MB-231 conditioned media were also sufficient to stimulate an increase in IL-6 production from MCF-10A cells.</p> <p>Conclusion</p> <p>These results demonstrate STAT3 phosphorylation in breast epithelial cells can be stimulated by paracrine signaling through soluble factors from both breast cancer cells and breast cancer associated fibroblasts with elevated STAT3 phosphorylation. The induction of STAT3 phosphorylation is through the IL-6/JAK pathway and appears to be associated with cell proliferation. Understanding how IL-6 and other soluble factors may lead to STAT3 activation via the tumor microenvironment will provide new therapeutic regimens for breast carcinomas and other cancers with elevated p-STAT3 levels.</p

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

How Willing Are Patients or Their Caregivers to Deprescribe:a Systematic Review and Meta-analysis

BACKGROUND: Polypharmacy is associated with the increased use of potentially inappropriate medications, where the risks of medicine use outweigh its benefits. Stopping medicines (deprescribing) that are no longer needed can be beneficial to reduce the risk of adverse events. We summarized the willingness of patients and their caregivers towards deprescribing. METHODS: A systematic search was conducted in four databases from inception until April 30, 2021 as well as search of citation of included articles. Studies that reported patients’ and/or their caregivers’ attitude towards deprescribing quantitatively were included. All studies were independently screened, reviewed, and data extracted in duplicates. Patients and caregivers willingness to deprescribe their regular medication was pooled using random effects meta-analysis of proportions. RESULTS: Twenty-nine unique studies involving 11,049 participants were included. All studies focused on the attitude of the patients towards deprescribing, and 7 studies included caregivers’ perspective. Overall, 87.6% (95% CI: 83.3 to 91.4%) patients were willing to deprescribe their medication, based upon the doctors’ suggestions. This was lower among caregivers, with only 74.8% (49.8% to 93.8%) willing to deprescribe their care recipients’ medications. Patients’ or caregivers’ willingness to deprescribe were not influenced by study location, study population, or the number of medications they took. DISCUSSION: Most patients and their caregivers were willing to deprescribe their medications, whenever possible and thus should be offered a trial of deprescribing. Nevertheless, as these tools have a poor predictive ability, patients and their caregivers should be engaged during the deprescribing process to ensure that the values and opinions are heard, which would ultimately improve patient safety. In terms of limitation, as not all studies may published the methods and results of measurement they used, this may impact the methodological quality and thus our findings. OPEN SCIENCE FRAMEWORK REGISTRATION: https://osf.io/fhg94 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-021-06965-5

Comparison of Graphical Passwords Using ISO 9126

This article is to learn the characteristics of graphical passwords by comparing different categories of graphical passwords with the ISO 9126 model. The ISO 9126 model is divided into six parts, which are usability, reliability, functionality, maintainability, efficiency, and portability. Each part listed is sub-categorised by the standard and is used to evaluate the quality of a product. Multiple graphical passwords are chosen from different classification of graphical passwords for thirty users to test and fill in the survey. Then a survey was conducted to compare each of these five categories of graphical passwords based on the ISO 9126 model. Thirty users of different ages and gender were invited to the booth to test the graphical password systems and fill in survey. The survey results as described in the article show us which category of graphical passwords contains more of the ISO 9126 characteristics

Intervention for Diabetes with Education, Advancement and Support (IDEAS) study: Protocol for a cluster randomised controlled trial

Background: The high market penetration of mobile phones has triggered an opportunity to combine mobile technology with health care to overcome challenges in today’s health care setting. Although Malaysia has a high Internet and mobile penetration rate, evaluations of the efficacy of incorporating this technology in diabetes care is not common. We report the development of a telemonitoring coaching system, using the United Kingdom (UK) Medical Research Council (MRC) framework, for patients with type 2 diabetes mellitus. Methods” The Intervention for Diabetes with Education, Technological Advancement and Support (IDEAS) study is a telemonitoring programme based on an empowerment philosophy to enable participants to be responsible for their own health decision and behaviour. An iterative cycle of development, piloting, and collating qualitative and quantitative data will be used to inform and refine the intervention. To increase compliance, the intervention will be designed to encourage self-management using simple, non-technical knowledge. The primary outcomes will be HbA1c, blood pressure, total cholesterol, and quality of life and diabetes self-efficacy. In addition, an economic analysis on health service utilisation will be collected. Discussion: The mixed-method approach in this study will allow for a holistic overview of using telemonitoring in diabetes care. This design enables researchers to understand the effectiveness of telemonitoring as well as provide insights towards the receptiveness of incorporating information technology amongst type 2 diabetes patients in a community setting. Trial registration: ClinicalTrials.gov NCT02466880 Registered 2 June 2015