Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users.

Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions.

The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

/pdf/the-prisma-statement-for-reporting-systematic-reviews-and-3j53e5oe33.pdf

The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Systematic reviews and meta-analyses are essential to summarise evidence relating to efficacy and safety of healthcare interventions accurately and reliably. The clarity and transparency of these reports, however, are not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (quality of reporting of meta-analysis) statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realising these issues, an international group that included experienced authors and methodologists developed PRISMA (preferred reporting items for systematic reviews and meta-analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this explanation and elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA statement, this document, and the associated website (www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

/pdf/the-prisma-statement-for-reporting-systematic-reviews-and-48ibbzju0k.pdf

The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

/pdf/genome-wide-association-study-of-14-000-cases-of-seven-5ay7q0q3vy.pdf

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

/pdf/teaching-research-methods-to-undergraduate-dental-students-3bdz33bt1z.pdf

Teaching research methods to undergraduate dental students

Meta-analysis of effect of high vs. low vitamin E on cardiovascular mortality for observational and intervention studies

consumption were 1.0 (reference), 0.66 (0.48 to 0.9 0), 0.70 (0.51 to 0.97) and 0.62 (0.43 to 0.90), p for linear trend =0.02. (4) Higher childhood intake of vegetables wa s associated with lower risk of stroke. After contr olling for age, sex, energy intake and range of socio-economic and other confounders the rate ratio between the highes t and lowest quartiles of intake was 0.40, 95% CI 0.19 to 0.83, p for trend = 0.01) (5) Higher intake of fish was a ssociated with higher risk of stroke. The fully adjusted rate rati o between the highest and lowest quartile of fish i ntake was 2.01, 95% CI 1.09 to 3.69, P for trend = 0.01) (5). There was no association between intake of any of the foo ds and constituents considered and deaths attributed to co ronary heart disease or all cause mortality (5). The reported childhood diet-cancer associations were robust to a djustment for measurement error (6). Conclusions ‐ Though these results are based on household measures on children across a range of ages measured in the 1930s they do suggest that diet in childhood influences diet in old age and cancer risk. These findings require replication but suggest that childhood diets rich i n vegetables and fruit may be beneficial.

Diet in childhood and diet and mortality in old age : findings from the Boyd Orr cohort

Clare England (  clare.england@bristol.ac.uk ) University of Bristol Kate Ingar eld-Herbert University of Bristol Matthew Beasley University Hospitals Bristol NHS Foundation Trust Laura Moss Velindre Cancer Centre Sobhan Vinjamuri Royal Liverpool and Broadgreen University Hospital NHS Trust Ingrid Haupt-Schott Velindre Cancer Centre Gail McKane Royal Liverpool and Broadgreen University Hospital NHS Trust Linda Hunt University of Bristol Georgia Herbert University of Bristol Sam Leary University of Bristol Andy Ness University of Bristol Charlotte Atkinson University of Bristol

/pdf/treatment-and-outcomes-in-differentiated-thyroid-cancer-a-4g6wzh9f2v.pdf

Treatment and Outcomes in Differentiated Thyroid Cancer: A Retrospective Exploration in Three UK Centres That Provide Different Advice on Low Iodine Diets

Accurate diet measurement is challenging and strategies to support researchers in selecting the most appropriate dietary assessment tools (DATs) are required. DIET@NET (DIETary Assessment tools NETwork) partnership aimed to create an online resource that provides guidelines for selecting tools with access to validated DATs. 

The Nutritools website(1) (www.nutritools.org), was developed using 3 approaches. 1) Creation of Best Practice Guidelines(2), enabling researchers to choose the most appropriate DAT for their work. These were generated using the Delphi method which enabled integration of expert views. 2) Creating an interactive DAT e-library, with the DATs being identified through a systematic review of systematic reviews(3). Bubble charts and summary plots are used to compare DATs. 3) Development of a Food Questionnaire Creator (FQC), an online interface between food tables and the DATs which allows users to create their own food questionnaires. This work was overseen by the DIET@NET partnership. Other useful information includes links to food composition databases and a detailed glossary of terms.

Results from the systematic review of reviews generated information for Nutritools. The website includes 127 international validated tools, of which 63 tools were validated in the UK (with 45 validated from year 2000 onwards). The majority (n = 34) of the validated tools were food frequency questionnaires, developed from 1981 to 2016. Numbers of foods included ranged from 8–692 items. Five of the 12 dietary recalls included were web-based. Tools were usually validated against another self-reported dietary assessment method, mainly weighed food diaries. More than 1500 papers with non-UK tools were identified, of these, data on 64 international tools and their validation studies were added to Nutritools.

The FQC allows for food questionnaires to be created using data from the UK National Diet and Nutrition Survey (NDNS) Year 6 and the Composition of Foods Integrated Dataset. Results from the NDNS can be used to formulate food questions that capture a large proportion of the nutrients of interest and to inform portion sizes.

In conclusion, Nutritools (www.nutritools.org), is an online platform that hosts international validated and interactive DATs. Researchers can use the interactive Best Practice Guidelines and features in the selection of the most appropriate DAT for their study, and the Food Questionnaire Creator to develop their own online food questionnaires.



This project was funded by the Medical Research Council (MRC) (ref: MR/L02019X/1).



1. Warthon-Medina M, Hooson J, Hancock N, et al. (2017) The Lancet 390, pS94.

2. Cade JE, Warthon-Medina M, Albar S, et al. (2017) BMC Medicine 15(1), p202.

3. Hooson J, Hancock N, Greenwood DC, et al. (2016) Proc Nutr Soc 75(OCE3).

/pdf/nutritools-org-an-innovative-website-including-a-food-22v8337nze.pdf

Andy R Ness

Papers

Teaching research methods to undergraduate dental students

Meta-analysis of effect of high vs. low vitamin E on cardiovascular mortality for observational and intervention studies

Diet in childhood and diet and mortality in old age : findings from the Boyd Orr cohort

Treatment and Outcomes in Differentiated Thyroid Cancer: A Retrospective Exploration in Three UK Centres That Provide Different Advice on Low Iodine Diets

Nutritools.org an innovative website including a Food Questionnaire Creator for dietary assessment in health research