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C. Röver

Publications and source records attributed to C. Röver.

3 recordsLinked to original sources

Present criteria for prophylactic ICD implantation: Insights from the EU-CERT-ICD (Comparative Effectiveness Research to Assess the Use of Primary ProphylacTic Implantable Cardioverter Defibrillators in EUrope) project

BACKGROUND. The clinical effectiveness of primary prevention implantable cardioverter defibrillator (ICD) therapy is under debate. It is urgently needed to better identify patients who benefit from prophylactic ICD therapy. The EUropean Comparative Effectiveness Research to Assess the Use of Primary ProphylacTic Implantable Cardioverter Defibrillators (EU-CERT-ICD) completed in 2019 will assess this issue. SUMMARY. The EU-CERT-ICD is a prospective investigator-initiated non-randomized, controlled, multicenter observational cohort study done in 44 centers across 15 European countries. A total of 2327 patients with heart failure due to ischemic heart disease or dilated cardiomyopathy indicated for primary prophylactic ICD implantation were recruited between 2014 and 2018 (>1500 patients at first ICD implantation, >750 patients non-randomized non-ICD control group). The primary endpoint was all-cause mortality, first appropriate shock was co-primary endpoint. At baseline, all patients underwent 12-lead ECG and Holter-ECG analysis using multiple advanced methods for risk stratification as well as documentation of clinical characteristics and laboratory values. The EU-CERT-ICD data will provide much needed information on the survival benefit of preventive ICD therapy and expand on previous prospective risk stratification studies which showed very good applicability of clinical parameters and advanced risk stratifiers in order to define patient subgroups with above or below average ICD benefit. CONCLUSION. The EU-CERT-ICD study will provide new and current data about effectiveness of primary prophylactic ICD implantation. The study also aims for improved risk stratification and patient selection using clinical risk markers in general, and advanced ECG risk markers in particular.

stat.AP

Recent advances in methodology for clinical trials in small populations: the InSPiRe project

Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This led to an EU FP7 call for proposals in 2013. One of the three projects funded was the Innovative Methodology for Small Populations Research (InSPiRe) project. This paper summarizes the main results of the project, which was completed in 2017. The InSPiRe project has led to development of novel statistical methodology for clinical trials in small populations in four areas. We have explored new decision-making methods for small population clinical trials using a Bayesian decision-theoretic framework to compare costs with potential benefits, developed approaches for targeted treatment trials, enabling simultaneous identification of subgroups and confirmation of treatment effect for these patients, worked on early phase clinical trial design and on extrapolation from adult to pediatric studies, developing methods to enable use of pharmacokinetics and pharmacodynamics data, and also developed improved robust meta-analysis methods for a small number of trials to support the planning, analysis and interpretation of a trial as well as enabling extrapolation between patient groups. In addition to scientific publications, we have contributed to regulatory guidance and produced free software in order to facilitate implementation of the novel methods.

stat.AP

Bayesian parameter estimation in the second LISA Pathfinder Mock Data Challenge

A main scientific output of the LISA Pathfinder mission is to provide a noise model that can be extended to the future gravitational wave observatory, LISA. The success of the mission depends thus upon a deep understanding of the instrument, especially the ability to correctly determine the parameters of the underlying noise model. In this work we estimate the parameters of a simplified model of the LISA Technology Package (LTP) instrument. We describe the LTP by means of a closed-loop model that is used to generate the data, both injected signals and noise. Then, parameters are estimated using a Bayesian framework and it is shown that this method reaches the optimal attainable error, the Cramer-Rao bound. We also address an important issue for the mission: how to efficiently combine the results of different experiments to obtain a unique set of parameters describing the instrument.

gr-qc