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Abstract Background 16S rDNA-PCR for the identification of a bacterial species is an established method. However, the DNA extraction reagents as well as the PCR reagents may contain residual bacterial DNA, which consequently generates false-positive PCR results. Additionally, previously used methods are frequently time-consuming. Here, we describe the results obtained with a new technology that uses DNA-free reagents for automated DNA extraction and subsequent real time PCR using sterile clinical specimens. Results In total, we compared 803 clinical specimens using real time PCR and culturing. The clinical specimens were mainly of orthopedic origin received at our diagnostic laboratory. In 595 (74.1%) samples, the results were concordant negative, and in 102 (12.7%) the results were concordant positive. A total of 170 (21.2%) clinical specimens were PCR-positive, of which 62 (36.5% from PCR positive, 7.7% in total) gave an additional benefit to the patient since only the PCR result was positive. Many of these 62 positive specimens were strongly positive based on crossingpoint values (54%

Background: 16S rDNA-PCR for the identification of a bacterial species is an established method. However, the DNA extraction reagents as well as the PCR reagents may contain residual bacterial DNA, which consequently generates false-positive PCR results. Additionally, previously used methods are frequently time-consuming. Here, we describe the results obtained with a new technology that uses DNA-free reagents for automated DNA extraction and subsequent real time PCR using sterile clinical specimens. Results: In total, we compared 803 clinical specimens using real time PCR and culturing. The clinical specimens were mainly of orthopedic origin received at our diagnostic laboratory. In 595 (74.1%) samples, the results were concordant negative, and in 102 (12.7%) the results were concordant positive. A total of 170 (21.2%) clinical specimens were PCR-positive, of which 62 (36.5% from PCR positive, 7.7% in total) gave an additional benefit to the patient since only the PCR result was positive. Many of these 62 positive specimens were strongly positive based on crossingpoint values (54% < Cp 30), and these 62 positive clinical specimens were diagnosed as medically relevant as well. Thirty-eight (4.2%) clinical specimens were culture-positive (25 of them were only enrichment culture positive) but PCR-negative, mainly for S. epidermidis, S. aureus and C. acnes. The turnaround times for negative specimens were 4 hours (automated DNA extraction and real time PCR) and 1 working day for positive specimens (including Sanger sequencing). Melting-curve analysis of SYBR Green-PCR enables the differentiation of specific and unspecific PCR products. Using Ripseq, even mixed infections of 2 bacterial species could be resolved. Conclusions: For endocarditis cases, the added benefit of PCR is obvious. The crucial innovations of the technology enable timely reporting of explicit reliable results for adequate treatment of patients. Clinical specimens with truly PCR-positive but culture-negative results represent an additional benefit for patients. Very few results at the detection limit still have to be critically examined. [ABSTRACT FROM AUTHOR]

Optimal placement of Distributed Generation (DG) is a crucial challenge for Distribution Companies (DISCO's) to run the distribution network in good operating conditions. Optimal positioning of DG units is an optimization issue where maximization of DISCO's additional benefit due to the installation of DG units in the network is considered to be an objective function. In this article, the self adaptive levy flight based black widow optimization algorithm is used as an optimization strategy to find the optimum position and size of the DG units. The proposed algorithm is implemented in the IEEE 15 and PG & E 69 bus management systems in the MATLAB environment. Based on the simulation performance, it has been found that with the correct location and size of the DG modules, the distribution network can be run with maximum DISCO's additional benefit. [ABSTRACT FROM AUTHOR]

Objective: : This study tried to observe clinical benefit of aripiprazole augmentation (ARPA) treatment for major depressive disorder with anxious distress (MDDA) in routine practice., Methods: : Retrospective chart review (n = 41) was conducted for clinical benefit of ARPA in patients with MDDA in routine practice. The primary endpoint was the mean change of Hamilton Anxiety Rating scale (HAMA) total scores from baseline to the endpoint. Additional secondary endpoints were also retrieved., Results: : The changes of primary endpoint HAMA (t = 5.731, -4.6, p = 0.001), and secondary endpoints including Hamilton Depression Rating scale (HAMD, t = 4.284, -3.4, p ＜ 0.001), Clinical Global Impression-Clinical Benefit (CGI-CB, -0.9, t = 1.821, p = 0.026), and Clinical Global Impression Score-Severity (CGI-S, t = 3.556, -0.4, p ＜ 0.001) scores were also significantly improved during the study. No significant adverse events were observed., Conclusion: : This study has shown additional benefit of ARPA treatment for MDDA patients in routine practice. However, adequately-powered and well-controlled studies are necessary for generalization of the present findings.

This paper analyzes the dynamics of entry and adjustment that underlies the process leading to the tragedy of the commons under two scenarios, one in which the users only react ex post to the entry of other users and the other in which the users anticipate and proact to such entry. The key to our analysis is the logic of entry based on the devaluation cost, which explains (1) why entry takes place when the incumbent users are in temporary equilibrium, (2) how this equilibrium shifts sequentially with the entry of new users, (3) why such equilibria resemble either the Cournot-Nash equilibrium of a static game or the Stackelberg type equilibrium of a dynamic game depending on the reactive or the proactive nature of the users, (4) why the stocks owned by the users in the proactive case depend on the order of entry and remain unchanged once determined at the point of entry. The speed of depletion, cumulative profits of the users, and the distribution pattern of the ownership differ significantly between the two scenarios. Our theory also explains why and how duopoly and oligopoly emerge through the process of entry and adjustment and acquire different equilibrium features. [ABSTRACT FROM AUTHOR]

In 2010, the Federal Parliament (Bundestag) of Germany passed a new law (Arzneimittelmarktneuordnungsgesetz, AMNOG) on the regulation of medicinal products that applies to all pharmaceutical products with active ingredients that are launched beginning January 1, 2011. The law describes the process to determine the price at which an approved new product will be reimbursed by the statutory health insurance system. The process consists of two phases. The first phase assesses the additional benefit of the new product versus an appropriate comparator (zweckmäßige Vergleichstherapie, zVT). The second phase involves price negotiation. Focusing on the first phase, this paper investigates requirements of benefit assessment of a new product under this law with special attention on the methods applied by the German authorities on issues such as the choice of the comparator, patient relevant endpoints, subgroup analyses, extent of benefit, determination of net benefit, primary and secondary endpoints, and uncertainty of the additional benefit. We propose alternative approaches to address the requirements in some cases and invite other researchers to help develop solutions in other cases. [ABSTRACT FROM AUTHOR]

A method for simultaneously assessing noninferiority with respect to efficacy and superiority with respect to another endpoint in two-arm noninferiority trials is presented. The procedure controls both the average type I error rate for the intersection-union test problem and the frequentist type I error rate for the noninferiority test by α while allowing an increased level for the superiority test. For normally distributed outcomes, two methods are presented to deal with the uncertainty about the correlation between the endpoints which defines the adjusted levels. The operating characteristics of these procedures are investigated. Furthermore, the sample size required when applying the proposed method is compared with that of alternative procedures. Application of the method in the situation of binary endpoints and mixed normal and binary endpoints, respectively, is sketched. An illustrative example is provided demonstrating implementation of the proposed approach in a clinical trial. [ABSTRACT FROM AUTHOR]

Background: Non-inferiority (NI) trials in drug research are used to demonstrate that a new treatment is not less effective than an active comparator. Since phase IV trials typically aim at informing a clinical decision, the value of a phase IV non-inferiority trial hinges also on its clinical relevance. In such trials, clinical relevance would refer to the added benefit claims of a specific drug, apart from efficacy, relative to its comparator drug in the trial. Methods: In this study, we reviewed 41 phase IV trials and extracted information on whether the authors mentioned any additional benefit beyond the NI (efficacy) claim of the drug and whether the additional benefit was proven in the trial. We checked whether the additional claim was based on descriptions only or on formal statistical analyses. Results: Our results showed that 22 out of the 41 NI trials mentioned additional benefit of the test drug and most of these claims were related to the safety profile. Of all the post-authorization NI trials that claimed additional benefit, 10 out of 22 NI trials used formal statistical analyses to show additional benefit, and only one included a sample size calculation for the additional benefit prior to the trial. Conclusion: We conclude that there is room for improvement in terms of designing phase IV NI trials with added benefit claims and in proving these additional claims. [ABSTRACT FROM AUTHOR]

Background: Pharmaceutical companies design clinical development programs to generate the data that they believe will support reimbursement for the experimental compound., Objective: The objective of the study was to present a process for using multicriteria decision analysis (MCDA) by a pharmaceutical company to estimate the probability of a positive recommendation for reimbursement for a new drug given drug and environmental attributes., Methods: The MCDA process included 1) selection of decisions makers who were representative of those making reimbursement decisions in a specific country; 2) two pre-workshop questionnaires to identify the most important attributes and their relative importance for a positive recommendation for a new drug; 3) a 1-day workshop during which participants undertook three tasks: i) they agreed on a final list of decision attributes and their importance weights, ii) they developed level descriptions for these attributes and mapped each attribute level to a value function, and iii) they developed profiles for hypothetical products 'just likely to be reimbursed'; and 4) use of the data from the workshop to develop a prediction algorithm based on a logistic regression analysis. The MCDA process is illustrated using case studies for three countries, the United Kingdom, Germany, and Spain. The extent to which the prediction algorithms for each country captured the decision processes for the workshop participants in our case studies was tested using a post-meeting questionnaire that asked the participants to make recommendations for a set of hypothetical products., Results: The data collected in the case study workshops resulted in a prediction algorithm: 1) for the United Kingdom, the probability of a positive recommendation for different ranges of cost-effectiveness ratios; 2) for Spain, the probability of a positive recommendation at the national and regional levels; and 3) for Germany, the probability of a determination of clinical benefit. The results from the post-meeting questionnaire revealed a high predictive value for the algorithm developed using MCDA., Conclusions: Prediction algorithms developed using MCDA could be used by pharmaceutical companies when designing their clinical development programs to estimate the likelihood of a favourable reimbursement recommendation for different product profiles and for different positions in the treatment pathway.