Spatial mapping of hepatitis C prevalence in recent injecting drug users in contact with services.

In developed countries the majority of hepatitis C virus (HCV) infections occur in injecting drug users (IDUs) with prevalence in IDUs often high, but with wide geographical differences within countries. Estimates of local prevalence are needed for planning services for IDUs, but it is not practical to conduct HCV seroprevalence surveys in all areas. In this study survey data from IDUs attending specialist services were collected in 52/149 sites in England between 2006 and 2008. Spatially correlated random-effects models were used to estimate HCV prevalence for all sites, using auxiliary data to aid prediction. Estimates ranged from 14% to 82%, with larger cities, London and the North West having the highest HCV prevalence. The methods used generated robust estimates for each area, with a well-identified spatial pattern that improved predictions. Such models may be of use in other areas of study where surveillance data are sparse

Patient reactions to a web-based cardiovascular risk calculator in type 2 diabetes: a qualitative study in primary care.

Use of risk calculators for specific diseases is increasing, with an underlying assumption that they promote risk reduction as users become better informed and motivated to take preventive action. Empirical data to support this are, however, sparse and contradictory

A sensitivity analysis approach for informative dropout using shared parameter models.

Shared parameter models (SPMs) are a useful approach to addressing bias from informative dropout in longitudinal studies. In SPMs it is typically assumed that the longitudinal outcome process and the dropout time are independent, given random effects and observed covariates. However, this conditional independence assumption is unverifiable. Currently, sensitivity analysis strategies for this unverifiable assumption of SPMs are underdeveloped. In principle, parameters that can and cannot be identified by the observed data should be clearly separated in sensitivity analyses, and sensitivity parameters should not influence the model fit to the observed data. For SPMs this is difficult because it is not clear how to separate the observed data likelihood from the distribution of the missing data given the observed data (i.e., 'extrapolation distribution'). In this article, we propose a new approach for transparent sensitivity analyses for informative dropout that separates the observed data likelihood and the extrapolation distribution, using a typical SPM as a working model for the complete data generating mechanism. For this model, the default extrapolation distribution is a skew-normal distribution (i.e., it is available in a closed form). We propose anchoring the sensitivity analysis on the default extrapolation distribution under the specified SPM and calibrate the sensitivity parameters using the observed data for subjects who drop out. The proposed approach is used to address informative dropout in the HIV Epidemiology Research Study

Redevelopment of the Predict: Breast Cancer website and recommendations for developing interfaces to support decision-making.

OBJECTIVES: To develop a new interface for the widely used prognostic breast cancer tool: Predict: Breast Cancer. To facilitate decision-making around post-surgery breast cancer treatments. To derive recommendations for communicating the outputs of prognostic models to patients and their clinicians. METHOD: We employed a user-centred design process comprised of background research and iterative testing of prototypes with clinicians and patients. Methods included surveys, focus groups and usability testing. RESULTS: The updated interface now caters to the needs of a wider audience through the addition of new visualisations, instantaneous updating of results, enhanced explanatory information and the addition of new predictors and outputs. A programme of future research was identified and is now underway, including the provision of quantitative data on the adverse effects of adjuvant breast cancer treatments. Based on our user-centred design process, we identify six recommendations for communicating the outputs of prognostic models including the need to contextualise statistics, identify and address gaps in knowledge, and the critical importance of engaging with prospective users when designing communications. CONCLUSIONS: For prognostic algorithms to fulfil their potential to assist with decision-making they need carefully designed interfaces. User-centred design puts patients and clinicians needs at the forefront, allowing them to derive the maximum benefit from prognostic models

Accommodating informative dropout and death: a joint modelling approach for longitudinal and semi-competing risks data.

Both dropout and death can truncate observation of a longitudinal outcome. Since extrapolation beyond death is often not appropriate, it is desirable to obtain the longitudinal outcome profile of a population given being alive. We propose a new likelihood-based approach to accommodating informative dropout and death by jointly modelling the longitudinal outcome and semi-competing event times of dropout and death, with an important feature that the conditional longitudinal profile of being alive can be conveniently obtained in a closed form. We use proposed methods to estimate different longitudinal profiles of CD4 count for patients from the HIV Epidemiology Research Study

Conflict diagnostics in directed acyclic graphs, with applications in bayesian evidence synthesis

Complex stochastic models represented by directed acyclic graphs (DAGs) are increasingly employed to synthesise multiple, imperfect and disparate sources of evidence, to estimate quantities that are difficult to measure directly. The various data sources are dependent on shared parameters and hence have the potential to conflict with each other, as well as with the model. In a Bayesian framework, the model consists of three components: the prior distribution, the assumed form of the likelihood and structural assumptions. Any of these components may be incompatible with the observed data. The detection and quantification of such conflict and of data sources that are inconsistent with each other is therefore a crucial component of the model criticism process. We first review Bayesian model criticism, with a focus on conflict detection, before describing a general diagnostic for detecting and quantifying conflict between the evidence in different partitions of a DAG. The diagnostic is a p-value based on splitting the information contributing to inference about a "separator" node or group of nodes into two independent groups and testing whether the two groups result in the same inference about the separator node(s). We illustrate the method with three comprehensive examples: an evidence synthesis to estimate HIV prevalence; an evidence synthesis to estimate influenza case-severity; and a hierarchical growth model for rat weights.This work was supported by the Medical Research Council [Unit Programme Numbers U105260566 and U105260557

Exploring variations in childhood stunting in Nigeria using league table, control chart and spatial analysis

Background: Stunting, linear growth retardation is the best measure of child health inequalities as it captures multiple dimensions of children’s health, development and environment where they live. The developmental priorities and socially acceptable health norms and practices in various regions and states within Nigeria remains disaggregated and with this, comes the challenge of being able to ascertain which of the regions and states identifies with either high or low childhood stunting to further investigate the risk factors and make recommendations for action oriented policy decisions. Methods: We used data from the birth histories included in the 2008 Nigeria Demographic and Health Survey (DHS) to estimate childhood stunting. Stunting was defined as height for age below minus two standard deviations from the median height for age of the standard World Health Organization reference population. We plotted control charts of the proportion of childhood stunting for the 37 states (including federal capital, Abuja) in Nigeria. The Local Indicators of Spatial Association (LISA) were used as a measure of the overall clustering and is assessed by a test of a null hypothesis. Results: Childhood stunting is high in Nigeria with an average of about 39%. The percentage of children with stunting ranged from 11.5% in Anambra state to as high as 60% in Kebbi State. Ranking of states with respect to childhood stunting is as follows: Anambra and Lagos states had the least numbers with 11.5% and 16.8% respectively while Yobe, Zamfara, Katsina, Plateau and Kebbi had the highest (with more than 50% of their underfives having stunted growth). Conclusions: Childhood stunting is high in Nigeria and varied significantly across the states. The northern states have a higher proportion than the southern states. There is an urgent need for studies to explore factors that may be responsible for these special cause variations in childhood stunting in Nigeria

The effectiveness of brief personalized normative feedback in reducing alcohol-related problems amongst University students: protocol for a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Studies have shown that university/college students tend to have an exaggerated view of the quantities of alcohol being consumed by their peers. Making students aware of this misperception may help change behaviour and reduce problem drinking.</p> <p>Methods/Design</p> <p>A Solomon Three Group Design will be used. There is one intervention group and two control groups, controlling separately for measurement and for intervention effects. Recruitment, consent, randomisation and data collection are all on-line. The primary outcomes are AUDIT Score, weekly consumption, perceived social norms, and alcohol related problems; secondary outcomes include alcohol expectancies and other health behaviours.</p> <p>Discussion</p> <p>This trial will provide information on the effectiveness of an on-line personalized normative feedback intervention for alcohol misuse in university students.</p> <p>Trial registration</p> <p>International Standard Randomised Controlled Trial Number: ISRCTN30784467</p

Outcome in neonates with Ebstein's anomaly

AbstractThe presentation and outcome of 50 patients with neonatal Ebstein's anomaly seen from 1961 to 1990 were reviewed. The majority (88%) presented in the 1st 3 days of life; cyanosis (80%) was the most common presenting feature. Associated defects, present in 27 infants (54%), included pulmonary stenosis in 11 and atresia in 7. Nine patients (18%) died in the neonatal period; there were 15 late deaths (due to hemodynamic deterioration in 9, sudden death in 5 and a noncardiac cause in 1) at a mean age of 4.5 years (range 4 months to 19 years). Actuarial survival at 10 years was 61%.A new echocardiographic grade (1 to 4 in order of increasing severity of the defect) was devised with use of the ratio of the area of the right atrium and atrialized right ventricle to the area of the functional right ventricle and left heart chambers. Cardiac death occured in 0 of 4 infants with grade 1, 1 (10%) of 16 with grade 2, 4 (44%) of 9 with grade 3 and 5 (100%) of 5 with grade 4. In a multivariate analysis of clinical and investigational features at presentation, echocardiographic grade of severity was the best independent predictor of death.Neonates with Ebstein's anomaly have a high early mortality rate and those surviving the 1st month of life remain at high risk of late hemodynamic deterioration or sudden death. Echocardiographic grading of severity of the defect permits prognostic stratification