Screening for Down's syndrome: effects, safety, and cost effectiveness of first and second trimester strategies commentary: rasults may not be widely applicable authors' response

Objective: To compare the effects, safety, and cost effectiveness of antenatal screening strategies for Down's syndrome. Design: Analysis of incremental cost effectiveness. Setting: United Kingdom. Main outcome measures: Number of liveborn babies with Down's syndrome, miscarriages due to chorionic villus sampling or amniocentesis, healthcare costs of screening programme, and additional costs and additional miscarriages per additional affected live birth prevented by adopting a more effective strategy. Results: Compared with no screening, the additional cost per additional liveborn baby with Down's syndrome prevented was £22 000 for measurement of nuchal translucency. The cost of the integrated test was £51 000 compared with measurement of nuchal translucency. All other strategies were more costly and less effective, or cost more per additional affected baby prevented. Depending on the cost of the screening test, the first trimester combined test and the quadruple test would also be cost effective options. Conclusions: The choice of screening strategy should be between the integrated test, first trimester combined test, quadruple test, or nuchal translucency measurement depending on how much service providers are willing to pay, the total budget available, and values on safety. Screening based on maternal age, the second trimester double test, and the first trimester serum test was less effective, less safe, and more costly than these four options

Estimation of HIV burden through Bayesian evidence synthesis

Planning, implementation and evaluation of public health policies to control the human immunodeficiency virus (HIV) epidemic require regular monitoring of disease burden. This includes the proportion living with HIV, whether diagnosed or not, and the rate of new infections in the general population and in specific risk groups and regions. Estimation of these quantities is not straightforward: data informing them directly are not typically available, but a wealth of indirect information from surveillance systems and ad hoc studies can inform functions of these quantities. In this paper we show how the estimation problem can be successfully solved through a Bayesian evidence synthesis approach, relaxing the focus on "best available" data to which classical methods are typically restricted. This more comprehensive and flexible use of evidence has led to the adoption of our proposed approach as the official method to estimate HIV prevalence in the United Kingdom since 2005

Doped and non-doped organic light-emitting diodes based on a yellow carbazole emitter into a blue-emitting matrix

A new carbazole derivative with a 3,3'-bicarbazyl core 6,6'-substituted by dicyanovinylene groups (6,6'-bis(1-(2,2'-dicyano)vinyl)-N,N'-dioctyl-3,3'-bicarbazyl; named (OcCz2CN)2, was synthesized by carbonyl-methylene Knovenagel condensation, characterized and used as a component of multilayer organic light-emitting diodes (OLEDs). Due to its -donor-acceptor type structure, (OcCz2CN)2 was found to emit a yellow light at max=590 nm (with the CIE coordinates x=0.51; y = 0.47) and was used either as a dopant or as an ultra-thin layer in a blue-emitting matrix of 4,4'-bis(2,2'-diphenylvinyl)-1,1'-biphenyl (DPVBi). DPVBi (OcCz2CN)2-doped structure exhibited, at doping ratio of 1.5 weight %, a yellowish-green light with the CIE coordinates (x = 0.31; y = 0.51), an electroluminescence efficiency EL=1.3 cd/A, an external quantum efficiency ext= 0.4 % and a luminance L= 127 cd/m2 (at 10 mA/cm2) whereas for non-doped devices utilizing the carbazolic fluorophore as a thin neat layer, a warm white with CIE coordinates (x = 0.40; y= 0.43), EL= 2.0 cd/A, ext= 0.7 %, L = 197 cd/m2 (at 10 mA/cm2) and a color rendering index (CRI) of 74, were obtained. Electroluminescence performances of both the doped and non-doped devices were compared with those obtained with 5,6,11,12-tetraphenylnaphtacene (rubrene) taken as a reference of highly efficient yellow emitter

Adhesion of tumour-infiltrating lymphocytes to endothelium: a phenotypic and functional analysis.

Efficacy of cancer immunotherapy with cultured tumour-infiltrating lymphocytes (TILs) depends upon infused TILs migrating into tumour-bearing tissue, in which they mediate an anti-tumour response. For TILs to enter a tumour, they must first bind to tumour endothelium, and this process depends on TILs expressing and regulating the function of relevant cell-surface receptors. We analysed the cell-surface phenotype and endothelial binding of TILs cultured from human melanoma and compared them with peripheral blood T cells and with allostimulated T cells cultured under similar conditions. Compared with peripheral blood T cells, TILs expressed high levels of five integrins, two other adhesion molecules, including the skin homing molecule CLA, and several activation markers and showed markedly enhanced integrin-mediated adhesion to a dermal microvascular endothelial cell line in vitro. Compared with the allostimulated T cells, TILs expressed higher levels of the cutaneous lymphocyte antigen (CLA), the adhesion molecule CD31 and the activation markers CD30 and CD69, but lower levels of several other adhesion and activation molecules. These phenotypic and functional properties of TILs should have complex effects on their migration in vivo. Expression of CLA, the skin homing receptor, may increase migration to melanoma (a skin cancer), whereas integrin activation may cause non-specific binding of TILs to other endothelium. Manipulation of the culture conditions in which TILs are expanded might result in a phenotype that is more conducive to selective tumour homing in vivo

Immunizations with pneumococcal surface protein A and pneumolysin are protective against pneumonia in a murine model of pulmonary infection with Streptococcus pneumoniae

Intranasal infection of mice with certain strains of capsular group 19 Streptococcus pneumoniae can result in focal pneumonia in the absence of bacteremia. Using this model of murine pneumonia, we demonstrated that immunization with recombinant forms of either pneumococcal surface protein A (PspA) or PdB (a genetically detoxified derivative of pneumolysin) elicited significant protection against focal pulmonary infection. This may be the first demonstration that a proposed vaccine antigen can protect against pneumococcal pneumonia. The best protection was obtained by immunizing mice with a mixture of PspA and PdB, indicating that the protection elicited by these antigens can complement each other. This result is in agreement with previous studies that used pneumococcal sepsis and nasal colonization models and demonstrate that the best protein vaccines for prevention of infection may be those that include more than one protection-eliciting pneumococcal protein.David E. Briles, Susan K. Hollingshead, James C. Paton, Edwin W. Ades, Lea Novak, Frederik W. van Ginkel, and William H. Benjamin, Jr

Immunizations with pneumococcal surface protein A and pneumolysin are protective against pneumonia in a murine model of pulmonary infection with Streptococcus pneumoniae

Intranasal infection of mice with certain strains of capsular group 19 Streptococcus pneumoniae can result in focal pneumonia in the absence of bacteremia. Using this model of murine pneumonia, we demonstrated that immunization with recombinant forms of either pneumococcal surface protein A (PspA) or PdB (a genetically detoxified derivative of pneumolysin) elicited significant protection against focal pulmonary infection. This may be the first demonstration that a proposed vaccine antigen can protect against pneumococcal pneumonia. The best protection was obtained by immunizing mice with a mixture of PspA and PdB, indicating that the protection elicited by these antigens can complement each other. This result is in agreement with previous studies that used pneumococcal sepsis and nasal colonization models and demonstrate that the best protein vaccines for prevention of infection may be those that include more than one protection-eliciting pneumococcal protein.David E. Briles, Susan K. Hollingshead, James C. Paton, Edwin W. Ades, Lea Novak, Frederik W. van Ginkel, and William H. Benjamin, Jr

Multinma: A comprehensive R package for network meta-analysis of survival outcomes with aggregate data, individual patient data, or a mixture of both

IntroductionSurvival or time-to-event outcomes are commonplace in disease areas such as oncology. Healthcare decision makers require estimates of relative efficacy between different treatment options, however treatments of interest are frequently not all compared in head-to-head randomised controlled trials, and so indirect comparison and network meta-analysis (NMA) methods are required to synthesise evidence from a connected network of trials and treatments. An extension of NMA, multilevel network meta-regression (ML-NMR), is increasingly used to account for differences in effect modifiers between populations where individual patient data are available from one or more trials. However, to date there has been no user-friendly software package that can perform NMA or ML-NMR with survival outcomes; instead analysts have needed to rely on complex bespoke modelling code. MethodsA recent update to the multinma R package provides a user-friendly suite of models and tools for synthesising survival outcomes from multiple trials, with aggregate data, individual patient data, or mixtures of both. Models are fitted in a Bayesian framework using Stan. A full range of parametric proportional hazards and accelerated failure time survival distributions are implemented, along with flexible baseline hazard models via M-splines or piecewise exponential hazards with a novel random walk shrinkage prior that avoids overfitting. Shape parameters may be stratified or regressed on treatment arm and/or covariates to relax proportionality. Right, left, and interval censoring, and delayed entry are all supported.ResultsWe present analyses of two case studies using the multinma package. First, we performed a NMA of published aggregate data from a network of treatments for advanced non-small cell lung cancer using flexible M-spline baseline hazards. We introduced treatment effects onto the spline coefficients to account for non-proportional hazards, and produced estimated survival curves in a target population required for further economic modelling.Second, we performed a ML-NMR using a mixture of individual patient data and aggregate data from a network of treatments for newly-diagnosed multiple myeloma. We adjusted for effect-modifying covariates, and produced population-adjusted estimates for target populations of interest to decision-making. Covariate adjustment removed evidence for non-proportional hazards that was present in unadjusted models.ConclusionsThe multinma package makes NMA and ML-NMR methods accessible to a broad audience. The latest update to include a suite of functionality for survival analysis facilitates application of these methods to widespread settings such as oncology, where until now there was no user-friendly software available

Multinma: A comprehensive R package for network meta-analysis of survival outcomes with aggregate data, individual patient data, or a mixture of both

IntroductionSurvival or time-to-event outcomes are commonplace in disease areas such as oncology. Healthcare decision makers require estimates of relative efficacy between different treatment options, however treatments of interest are frequently not all compared in head-to-head randomised controlled trials, and so indirect comparison and network meta-analysis (NMA) methods are required to synthesise evidence from a connected network of trials and treatments. An extension of NMA, multilevel network meta-regression (ML-NMR), is increasingly used to account for differences in effect modifiers between populations where individual patient data are available from one or more trials. However, to date there has been no user-friendly software package that can perform NMA or ML-NMR with survival outcomes; instead analysts have needed to rely on complex bespoke modelling code. MethodsA recent update to the multinma R package provides a user-friendly suite of models and tools for synthesising survival outcomes from multiple trials, with aggregate data, individual patient data, or mixtures of both. Models are fitted in a Bayesian framework using Stan. A full range of parametric proportional hazards and accelerated failure time survival distributions are implemented, along with flexible baseline hazard models via M-splines or piecewise exponential hazards with a novel random walk shrinkage prior that avoids overfitting. Shape parameters may be stratified or regressed on treatment arm and/or covariates to relax proportionality. Right, left, and interval censoring, and delayed entry are all supported.ResultsWe present analyses of two case studies using the multinma package. First, we performed a NMA of published aggregate data from a network of treatments for advanced non-small cell lung cancer using flexible M-spline baseline hazards. We introduced treatment effects onto the spline coefficients to account for non-proportional hazards, and produced estimated survival curves in a target population required for further economic modelling.Second, we performed a ML-NMR using a mixture of individual patient data and aggregate data from a network of treatments for newly-diagnosed multiple myeloma. We adjusted for effect-modifying covariates, and produced population-adjusted estimates for target populations of interest to decision-making. Covariate adjustment removed evidence for non-proportional hazards that was present in unadjusted models.ConclusionsThe multinma package makes NMA and ML-NMR methods accessible to a broad audience. The latest update to include a suite of functionality for survival analysis facilitates application of these methods to widespread settings such as oncology, where until now there was no user-friendly software available

MATERNAL PREVALENCE OF TOXOPLASMA ANTIBODY BASED ON ANONYMOUS NEONATAL SEROSURVEY - A GEOGRAPHICAL ANALYSIS

A total of 12902 neonatal samples collected on absorbent paper for routine metabolic screening were tested anonymously for antibodies to toxoplasma. Seroprevalence varied from 19.5% in inner London, to 11.6% in suburban London, and 7.6% in non-metropolitan districts. Much of this variation appeared to be associated with the proportions of livebirths in each district to women born outside the UK. However, additional geographical variation remained and seroprevalence in UK-born women was estimated to be 12.7% in inner London. 7.5% in suburban London, and 5.5% in non-metropolitan areas. These estimates are considerably lower than any previously reported in antenatal sera in the UK. The wide geographical variation highlights a need for further research to determine the relative importance of different routes of transmission