Fifteen-Year Population Attributable Fractions and Causal Pies of Risk Factors for Newly Developed Hepatocellular Carcinomas in 11,801 Men in Taiwan

Development of hepatocellular carcinoma (HCC) is a multi-factorial process. Chronic infections with hepatitis B virus (HBV) and hepatitis C virus (HCV) are important risk factors of HCC. Host factors, such as alcohol drinking, may also play a role. This study aims to provide a synthesis view on the development of HCC by examining multiple risk factors jointly and collectively. Causal-pie modeling technique was applied to analyze a cohort of 11,801 male residents (followed up for 15 years) in Taiwan, during which a total of 298 incident HCC cases were ascertained. The rate ratios adjusted by age were further modeled by an additive Poisson regression. Population attributable fractions (PAFs) and causal-pie weights (CPWs) were calculated. A PAF indicates the magnitude of case-load reduction under a particular intervention scenario, whereas a CPW for a particular class of causal pies represents the proportion of HCC cases attributable to that class. Using PAF we observed a chance to reduce around 60% HCC risk moving from no HBV-related intervention to the total elimination of the virus. An additional ∼15% (or ∼5%) reduction can be expected, if the HBV-related intervention is coupled with an HCV-related intervention (or an anti-drinking campaign). Eight classes of causal pies were found to be significant, including four dose-response classes of HBV (total CPW=52.7%), one independent-effect class of HCV (CPW=14.4%), one HBV-alcohol interaction class (CPW=4.2%), one HBV-HCV interaction class (CPW=1.7%), and one all-unknown class (CPW=27.0%). Causal-pie modeling for HCC helps clarify the relative importance of each viral and host factor, as well as their interactions

Identification of animal movement patterns using tri-axial magnetometry

BackgroundAccelerometers are powerful sensors in many bio-logging devices, and are increasingly allowing researchers to investigate the performance, behaviour, energy expenditure and even state, of free-living animals. Another sensor commonly used in animal-attached loggers is the magnetometer, which has been primarily used in dead-reckoning or inertial measurement tags, but little outside that. We examine the potential of magnetometers for helping elucidate the behaviour of animals in a manner analogous to, but very different from, accelerometers. The particular responses of magnetometers to movement means that there are instances when they can resolve behaviours that are not easily perceived using accelerometers.MethodsWe calibrated the tri-axial magnetometer to rotations in each axis of movement and constructed 3-dimensional plots to inspect these stylised movements. Using the tri-axial data of Daily Diary tags, attached to individuals of number of animal species as they perform different behaviours, we used these 3-d plots to develop a framework with which tri-axial magnetometry data can be examined and introduce metrics that should help quantify movement and behaviour.ResultsTri-axial magnetometry data reveal patterns in movement at various scales of rotation that are not always evident in acceleration data. Some of these patterns may be obscure until visualised in 3D space as tri-axial spherical plots (m-spheres). A tag-fitted animal that rotates in heading while adopting a constant body attitude produces a ring of data around the pole of the m-sphere that we define as its Normal Operational Plane (NOP). Data that do not lie on this ring are created by postural rotations of the animal as it pitches and/or rolls. Consequently, stereotyped behaviours appear as specific trajectories on the sphere (m-prints), reflecting conserved sequences of postural changes (and/or angular velocities), which result from the precise relationship between body attitude and heading. This novel approach shows promise for helping researchers to identify and quantify behaviours in terms of animal body posture, including heading.ConclusionMagnetometer-based techniques and metrics can enhance our capacity to identify and examine animal behaviour, either as a technique used alone, or one that is complementary to tri-axial accelerometry

Activity Increase Despite Arthritis (AÏDA): design of a Phase II randomised controlled trial evaluating an active management booklet for hip and knee osteoarthritis [ISRCTN24554946]

<p>Abstract</p> <p>Background</p> <p>Hip and knee osteoarthritis is a common cause of pain and disability, which can be improved by exercise interventions. However, regular exercise is uncommon in this group because the low physical activity level in the general population is probably reduced even further by pain related fear of movement. The best method of encouraging increased activity in this patient group is not known. A booklet has been developed for patients with hip or knee osteoarthritis. It focuses on changing disadvantageous beliefs and encouraging increased physical activity.</p> <p>Methods/Design</p> <p>This paper describes the design of a Phase II randomised controlled trial (RCT) to test the effectiveness of this new booklet for patients with hip and knee osteoarthritis in influencing illness and treatment beliefs, and to assess the feasibility of conducting a larger definitive RCT in terms of health status and exercise behaviour. A computerised search of four general medical practice patients' record databases will identify patients older than 50 years of age who have consulted with hip or knee pain in the previous twelve months. A random sample of 120 will be invited to participate in the RCT comparing the new booklet with a control booklet, and we expect 100 to return final questionnaires. This trial will assess the feasibility of recruitment and randomisation, the suitability of the control intervention and outcome measurement tools, and will provide an estimate of effect size. Outcomes will include beliefs about hip and knee pain, beliefs about exercise, fear avoidance, level of physical activity, health status and health service costs. They will be measured at baseline, one month and three months.</p> <p>Discussion</p> <p>We discuss the merits of testing effectiveness in a phase II trial, in terms of intermediate outcome measures, whilst testing the processes for a larger definitive trial. We also discuss the advantages and disadvantages of testing the psychometric properties of the primary outcome measures concurrently with the trial.</p> <p>Trial registration</p> <p>Current Controlled Trials ISRCTN24554946</p