Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting

<p>Abstract</p> <p>Background</p> <p>The World Health Organisation estimates that by 2030 there will be approximately 350 million people with type 2 diabetes. Associated with renal complications, heart disease, stroke and peripheral vascular disease, early identification of patients with undiagnosed type 2 diabetes or those at an increased risk of developing type 2 diabetes is an important challenge. We sought to systematically review and critically assess the conduct and reporting of methods used to develop risk prediction models for predicting the risk of having undiagnosed (prevalent) or future risk of developing (incident) type 2 diabetes in adults.</p> <p>Methods</p> <p>We conducted a systematic search of PubMed and EMBASE databases to identify studies published before May 2011 that describe the development of models combining two or more variables to predict the risk of prevalent or incident type 2 diabetes. We extracted key information that describes aspects of developing a prediction model including study design, sample size and number of events, outcome definition, risk predictor selection and coding, missing data, model-building strategies and aspects of performance.</p> <p>Results</p> <p>Thirty-nine studies comprising 43 risk prediction models were included. Seventeen studies (44%) reported the development of models to predict incident type 2 diabetes, whilst 15 studies (38%) described the derivation of models to predict prevalent type 2 diabetes. In nine studies (23%), the number of events per variable was less than ten, whilst in fourteen studies there was insufficient information reported for this measure to be calculated. The number of candidate risk predictors ranged from four to sixty-four, and in seven studies it was unclear how many risk predictors were considered. A method, not recommended to select risk predictors for inclusion in the multivariate model, using statistical significance from univariate screening was carried out in eight studies (21%), whilst the selection procedure was unclear in ten studies (26%). Twenty-one risk prediction models (49%) were developed by categorising all continuous risk predictors. The treatment and handling of missing data were not reported in 16 studies (41%).</p> <p>Conclusions</p> <p>We found widespread use of poor methods that could jeopardise model development, including univariate pre-screening of variables, categorisation of continuous risk predictors and poor handling of missing data. The use of poor methods affects the reliability of the prediction model and ultimately compromises the accuracy of the probability estimates of having undiagnosed type 2 diabetes or the predicted risk of developing type 2 diabetes. In addition, many studies were characterised by a generally poor level of reporting, with many key details to objectively judge the usefulness of the models often omitted.</p

Age-associated mitochondrial DNA mutations cause metabolic remodelling that contributes to accelerated intestinal tumorigenesis.

Oxidative phosphorylation (OXPHOS) defects caused by somatic mitochondrial DNA (mtDNA) mutations increase with age in human colorectal epithelium and are prevalent in colorectal tumours, but whether they actively contribute to tumorigenesis remains unknown. Here we demonstrate that mtDNA mutations causing OXPHOS defects are enriched during the human adenoma/carcinoma sequence, suggesting they may confer a metabolic advantage. To test this we deleted the tumour suppressor Apc in OXPHOS deficient intestinal stem cells in mice. The resulting tumours were larger than in control mice due to accelerated cell proliferation and reduced apoptosis. We show that both normal crypts and tumours undergo metabolic remodelling in response to OXPHOS deficiency by upregulating the de novo serine synthesis pathway (SSP). Moreover, normal human colonic crypts upregulate the SSP in response to OXPHOS deficiency prior to tumorigenesis. Our data show that age-associated OXPHOS deficiency causes metabolic remodelling that can functionally contribute to accelerated intestinal cancer development

Overview of data-synthesis in systematic reviews of studies on outcome prediction models

Background: Many prognostic models have been developed. Different types of models, i.e. prognostic factor and outcome prediction studies, serve different purposes, which should be reflected in how the results are summarized in reviews. Therefore we set out to investigate how authors of reviews synthesize and report the results of primary outcome prediction studies. Methods: Outcome prediction reviews published in MEDLINE between October 2005 and March 2011 were eligible and 127 Systematic reviews with the aim to summarize outcome prediction studies written in English were identified for inclusion. Characteristics of the reviews and the primary studies that were included were independently assessed by 2 review authors, using standardized forms. Results: After consensus meetings a total of 50 systematic reviews that met the inclusion criteria were included. The type of primary studies included (prognostic factor or outcome prediction) was unclear in two-thirds of the reviews. A minority of the reviews reported univariable or multivariable point estimates and measures of dispersion from the primary studies. Moreover, the variables considered for outcome prediction model development were often not reported, or were unclear. In most reviews there was no information about model performance. Quantitative analysis was performed in 10 reviews, and 49 reviews assessed the primary studies qualitatively. In both analyses types a range of different methods was used to present the results of the outcome prediction studies. Conclusions: Different methods are applied to synthesize primary study results but quantitative analysis is rarely performed. The description of its objectives and of the primary studies is suboptimal and performance parameters of the outcome prediction models are rarely mentioned. The poor reporting and the wide variety of data synthesis strategies are prone to influence the conclusions of outcome prediction reviews. Therefore, there is much room for improvement in reviews of outcome prediction studies. (aut.ref.

TIA-1 Cytotoxic Granule-Associated RNA Binding Protein Improves the Prognostic Performance of CD8 in Mismatch Repair-Proficient Colorectal Cancer

Evidence suggests a confounding effect of mismatch repair (MMR) status on immune response in colorectal cancer. The identification of innate and adaptive immune cells, that can complement the established prognostic effect of CD8 in MMR-proficient colorectal cancers patients, representing 85% of all cases, has not been performed

Assessing health-related quality of life in patients with inflammatory bowel disease, in Crete, Greece

BACKGROUND: Health Related Quality of Life (HRQoL) is an important outcome measure in Inflammatory Bowel Disease (IBD). The aim of our study was to assess HRQoL in a population of 135 Greek patients with IBD. METHODS: A cohort of 135 patients with IBD, 81 with ulcerative colitis (UC) and 54 with Crohn's disease (CD) were enrolled in our study. Demographic and disease-related data were recorded. HRQoL was assessed by a disease-specific and a generic questionnaire, IBDQ and SF-36, respectively. Disease activity was assessed by Harvey-Bradshaw Index and the Colitis Activity Index for CD and UC patients, respectively. RESULTS: Among all variables recorded in our study, only disease activity had a significant effect on HRQoL. Patients with active disease scored significantly lower on both IBDQ and SF-36 when compared to those in remission. Only two among the four IBDQ dimensions, bowel and systemic, had significant ability in distinguishing best patients in remission from those with active disease. CONCLUSIONS: IBD has a negative impact on HRQoL. Patients with active disease are more impaired than patients in remission. In our population of patients bowel and systemic dimensions had a predominant value in patients' perception of quality of life. Patients in our study using the same instrument scored higher than previously reported

Nurse-patient interaction and communication: a systematic literature review

Aim: The purpose of this review is to describe the use and definitions of the concepts of nurse-patient interaction and nurse-patient communication in nursing literature. Furthermore, empirical findings of nurse-patient communication research will be presented, and applied theories will be shown. Method: An integrative literature search was executed. The total number of relevant citations found was 97. The search results were reviewed, and key points were extracted in a standardized form. Extracts were then qualitatively summarized according to relevant aspects and categories for the review. Results: The relation of interaction and communication is not clearly defined in nursing literature. Often the terms are used interchangeably or synonymously, and a clear theoretical definition is avoided or rather implicit. Symbolic interactionism and classic sender-receiver models were by far the most referred to models. Compared to the use of theories of adjacent sciences, the use of original nursing theories related to communication is rather infrequent. The articles that try to clarify the relation of both concepts see communication as a special or subtype of interaction. Conclusion: The included citations all conclude that communication skills can be learned to a certain degree. Involvement of patients and their role in communication often is neglected by authors. Considering the mutual nature of communication, patients’ share in conversation should be taken more into consideration than it has been until now. Nursing science has to integrate its own theories of nursing care with theories of communication and interaction from other scientific disciplines like sociology

The gut microbiota: a major player in the toxicity of environmental pollutants?

Exposure to environmental chemicals has been linked to various health disorders, including obesity, type 2 diabetes, cancer and dysregulation of the immune and reproductive systems, whereas the gastrointestinal microbiota critically contributes to a variety of host metabolic and immune functions. We aimed to evaluate the bidirectional relationship between gut bacteria and environmental pollutants and to assess the toxicological relevance of the bacteria–xenobiotic interplay for the host. We examined studies using isolated bacteria, faecal or caecal suspensions—germ-free or antibiotic-treated animals—as well as animals reassociated with a microbiota exposed to environmental chemicals. The literature indicates that gut microbes have an extensive capacity to metabolise environmental chemicals that can be classified in five core enzymatic families (azoreductases, nitroreductases, β-glucuronidases, sulfatases and β-lyases) unequivocally involved in the metabolism of >30 environmental contaminants. There is clear evidence that bacteria-dependent metabolism of pollutants modulates the toxicity for the host. Conversely, environmental contaminants from various chemical families have been shown to alter the composition and/or the metabolic activity of the gastrointestinal bacteria, which may be an important factor contributing to shape an individual’s microbiotype. The physiological consequences of these alterations have not been studied in details but pollutant-induced alterations of the gut bacteria are likely to contribute to their toxicity. In conclusion, there is a body of evidence suggesting that gut microbiota are a major, yet underestimated element that must be considered to fully evaluate the toxicity of environmental contaminants

Gut microbiota functions: metabolism of nutrients and other food components

The diverse microbial community that inhabits the human gut has an extensive metabolic repertoire that is distinct from, but complements the activity of mammalian enzymes in the liver and gut mucosa and includes functions essential for host digestion. As such, the gut microbiota is a key factor in shaping the biochemical profile of the diet and, therefore, its impact on host health and disease. The important role that the gut microbiota appears to play in human metabolism and health has stimulated research into the identification of specific microorganisms involved in different processes, and the elucidation of metabolic pathways, particularly those associated with metabolism of dietary components and some host-generated substances. In the first part of the review, we discuss the main gut microorganisms, particularly bacteria, and microbial pathways associated with the metabolism of dietary carbohydrates (to short chain fatty acids and gases), proteins, plant polyphenols, bile acids, and vitamins. The second part of the review focuses on the methodologies, existing and novel, that can be employed to explore gut microbial pathways of metabolism. These include mathematical models, omics techniques, isolated microbes, and enzyme assays

Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration

The REMARK “elaboration and explanation” guideline, by Doug Altman and colleagues, provides a detailed reference for authors on important issues to consider when designing, conducting, and analyzing tumor marker prognostic studies