Em4 Wuppertal Modifikation Beta Download
Traful Stakelbeck
Like penicillin and other beta-lactam antibiotics, history tells us that entirely new agents that target novel, druggable, broadly conserved essential enzymes involved in the biogenesis of outer membranes of bacteria could offer a great opportunity in terms of efficacy, safety and treating otherwise resistant bacteria. This is also the basic idea behind the winning project of the US-start-up company Prokaryotics Inc., a spin-out from Merck & Co., Inc. to develop a new antibiotic that targets the fundamentally essential biochemical assembly components of the Gram-negative outer membrane, an intrinsic barrier that naturally restricts antibiotic entry and ultimate efficacy. The most promising target in this regard for drug development is is LspA. By modifying LspA (lipoprotein signal peptidase A), an essential component in outer membrane biogenesis, Prokaryotics provides an exciting opportunity to develop next generation antibiotic agents effective on their own or in combination with existing agents to provide effective mono-therapeutic or synergistic efficacy against drug-resistant bacteria.
Meta-analyses for diagnostic accuracy studies are complicated by the fact that two parameters of interest (sensitivity and specificity) are given by each study, leading to statistical models with bivariate responses. We propose a new model using beta-binomial marginal distributions and bivariate copulas to this task. The model comes with the advantage that sensitivity and specificity are modelled on their original scale while still allowing for (1) these being correlated within each study, (2) these being heterogeneous across studies, (3) accessing the individual patient data, (4) allowing extreme values of 100% sensitivity and specificity, and (5) using standard software (e.g., SAS PROC NLMIXED). Compared to the current standard model [1,2], our model has a closed-form likelihood, thus facilitating parameter estimation. Finally, by using different copulas, the model allows for different correlation patterns between sensitivity and specificity.
We illustrate the methods by the classical example of Glas et al. [3] on the diagnostic accuracy of a urinary tumor marker (telomerase) for the diagnosis of primary bladder cancer. Moreover, we report on simulation results comparing our model to the current standard model.