285 research outputs found

    Applying Matching Procedures in the Generation and Synthesis of Evidence

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    The gold standard for clinical studies are blinded randomized trials, but such a design is not always feasible due to ethical or practical reasons. Using an external historical control group out of an earlier conducted trial or registry might be an option. When using historical controls, one often faces the situation of non-comparable study populations. Matching procedures may help to build balanced samples for comparison. In this thesis an adaptive matched case-control trial design is established, which allows for a sample size recalculation at a planned interim analysis with the goal to enhance the matching rate at final analysis. The recalculation is based on the lower confidence interval limit of the matching rate observed at interim analysis. The newly developed resampling CI method estimates the 1:1 matching rate using a bootstrap like procedure (without replacement) and equal-sized groups for matching at interim. A naĂŻve approach would be to use all patients for estimating the matching rate and directly reflect this value for recalculating the sample size. The new approach shows good performance in terms of power and type I error rate but needs more newly recruited patients than the naĂŻve approach. Additionally, investigations for the time point of interim analysis are done. Simulations result in a number of 1/2 to 2/3 of the control patients, however, it seems that the time point is more depending on the actual number of patients used for matching than on the proportion. However, if the historical control group is large and for example only a small phase II trial is feasible the before described method might not be a good choice. Rather, each intervention patient may find more than one matching partner. Therefore, an iterative procedure to determining the number of matching partners is developed. The idea is an interim analysis, which includes an iterative increase in the number of matching partners and a parallel calculation of the matching rate. The number will be increased as long as the 1:M matching rate is higher than the 1:1 matching rate including a potential tolerance. The 1:M matching rate at interim analysis can then be used for recalculating the sample size. This procedure is easy to implement and can be combined with many study designs, such as two-stage designs. One has to note that the number of matching partners highly depends on the overlap of patient populations, meaning a small overlap leads to a low number of matching partners and vice versa. To conclude, by involving the trial-specific matching rate in the sample size recalculation one is able to enhance power in a matched case-control trial. Not only in the generation of evidence unbalanced patient cohorts arise, but also in evidence synthesis this poses a problem. A common situation in evidence synthesis is an indirect comparison, where the comparison of interest, assume treatment A versus C, is not examined in a direct comparison. But there are trials comparing A with treatment B and another trial comparing C and B. using those trials to calculate a treatment effect for A versus C is called indirect comparison. It is likely that the independent trials AB and CB do not have the same underlying population. A special case, where individual patient data is available for one of the trials is assumed. Then a matching-like procedure can help to balance the cohorts, this method is called matching adjusted indirect comparison which is not sufficiently examined, yet. Another widely used method for indirect comparisons is the method of Bucher. A method comparison between those two methods is conducted for clinically relevant scenarios where assumptions of the methods are violated. Simulations lead to the conjecture that indirect comparisons are considerably underpowered. The method of Bucher and the matching adjusted indirect comparison show similar performance in scenarios without cross-trial differences. The matching approach leads to higher coverage and power when populations differ, effect modifiers are present, and regression models are not sufficiently adjusted. But matching confounders which do not modify the effect leads to increased bias. Until now, indirect comparisons are applied using one study per treatment comparison because the matching adjusted indirect comparison is designed for this setting. Nevertheless, it is likely that there are two or even more studies comparing the same treatments. When synthesizing evidence, one should always aim to include all appropriate evidence. Therefore, approaches to include multiple studies in indirect comparisons are introduced and compared. All include a step for combining treatment effects and one for calculating indirect treatment effects. The main difference between the approaches is the order of those two steps. An increasing number of studies can enhance power to desired regions above 80%, but it was not possible to identify one best performing method over all considered scenarios. In conclusion, when applying matching procedures in evidence synthesis the underlying situation needs to be checked carefully, and matching variables need to be chosen carefully because adjusting for confounders influences the precision of the indirect comparison

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    Adaptive propensity score procedure improves matching in prospective observational trials

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    Background: Randomized controlled trials are the gold-standard for clinical trials. However, randomization is not always feasible. In this article we propose a prospective and adaptive matched case-control trial design assuming that a control group already exists. Methods: We propose and discuss an interim analysis step to estimate the matching rate using a resampling step followed by a sample size recalculation. The sample size recalculation is based on the observed mean resampling matching rate. We applied our approach in a simulation study and to a real data set to evaluate the characteristics of the proposed design and to compare the results to a naive approach. Results: The proposed design achieves at least 10% higher matching rate than the naive approach at final analysis, thus providing a better estimation of the true matching rate. A good choice for the interim analysis seems to be a fraction of around 1/2 to 2/3 of the control patients. Conclusion: The proposed resampling step in a prospective matched case-control trial design leads to an improved estimate of the final matching rate and, thus, to a gain in power of the approach due to sensible sample size recalculation

    Amplification of bacteria-induced platelet activation is triggered by FcγRIIA, integrin αiIbβ3, and platelet factor 4

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    Bacterial adhesion to platelets is mediated via a range of strain-specific bacterial surface proteins that bind to a variety of platelet receptors. It is unclear how these interactions lead to platelet activation. We demonstrate a critical role for the immune receptor FcγRIIA, αIIbβ3, and Src and Syk tyrosine kinases in platelet activation by Staphylococcus aureus, Streptococcus sanguinis, Streptococcus gordonii, Streptococcus oralis, and Streptococcus pneumoniae. FcγRIIA activation is dependent on immunoglobulin G (IgG) and αIIbβ3 engagement. Moreover, feedback agonists adenosine 59-diphosphate and thromboxane A2 aremandatory for platelet aggregation. Additionally, platelet factor 4 (PF4) binds to bacteria and reduces the lag time for aggregation, and gray platelet syndromea-granule-deficient platelets do not aggregate to 4 of 5 bacterial strains. We propose that FcγRIIA-mediated activation is a common response mechanism used against a wide range of bacteria, and that release of secondary mediators and PF4 serve as a positive feedback mechanism for activation through an IgG-dependent pathway. © 2014 by The American Society of Hematology

    Primary care physicians’ satisfaction after health care reform: a cross-sectional study from two cities in Central Java, Indonesia

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    Background: In 2014, Indonesia launched a mandatory national health insurance system called Jaminan Kesehatan Nasional (JKN). The reform introduced new conditions for primary care physicians (PCPs) that could influence their job satisfaction. This study assessed PCPs’ satisfaction and its predictors in two cities in Central Java, Indonesia, following the reform. Methods: In this exploratory, cross-sectional study, we recruited 276 PCPs from the selected area. The data were all collected in 2016 using self-report questionnaires and interviews. PCPs’ satisfaction was measured using a modified version of the Warr-Cook-Wall Job Satisfaction Scale which contains 19 items and uses a Likert-type response scale. Analysis of variance, the Kruskal-Wallis H test, both with Bonferroni corrections for post hoc testing, and Cochran–Mantel–Haenszel tests were used to compare overall job satisfaction between participant groups. We used simple and multiple linear regression analyses to identify the predictors of PCP satisfaction. Furthermore, a logistic regression analysis for binary outcome was applied to model the PCPs intention to leave practice. Results: PCPs’ mean overall satisfaction level was 3.19 out of 5. They tended to be very satisfied with their relationship with colleagues, working hours, and physical working conditions. However, the PCPs were dissatisfied with the new referral system, the JKN health services standards, and JKN policy. The factors significantly associated with job satisfaction (p <  0.001) included type of practice, performance of managerial tasks, and PCPs’ perceptions of and experiences with patients. PCP satisfaction was negatively associated (p = 0.004) with PCPs’ intention to leave their practice. Conclusions: The PCPs investigated in these two cities in Central Java had moderate satisfaction after the Indonesian health care reform. PCPs who worked in solo practices, performed managerial tasks, and had good experiences with patients tended to have higher satisfaction scores, which in turn prevented them from developing an intention to leave their practice. The three aspects that PCPs with which most dissatisfied were related with the JKN reform. Because of that, the government and BPJS for Health should aim to improve the JKN system in order to increase PCPs’ satisfaction

    DIW's 2009 Fall Forecast: Key Economic Trends

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    Following an unprecedented contraction in GDP, the German economy returns to expansion. Growth will be modest in 2010, however, as the forces of the recovery are not yet stable. This is the key result of the Autumn outlook of the German Institute for Economic Research (DIW). DIW expects Germany's GDP to grow by 1.3% in 2010. While this figure is higher than the forecast for the entire euro zone (+0.8%), it is not cause for celebration: Next year's growth is too low to compensate for the decline in output since the start of the crisis. By the end of 2010, Germany's GDP will have returned to its level at the beginning of 2006

    Herbstgrundlinien 2009: leichte Erholung im nächsten Jahr

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    Weltwirtschaft: Erholung auf wackeligem Fundament / Deutschland: Nur langsam aus der Talsohle / Geldpolitik und Finanzmärkte: Kreditklemme vorbeugen / Finanzpolitik: Einnahmen steigern und Ausgaben kürzen / Die wichtigsten Daten der Volkswirtschaftlichen Gesamtrechnung für Deutschlan
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