The analysis of competing risks data with a focus on estimation of cause-specific and subdistribution hazard ratios from a mixture model

Treatment efficacy in clinical trials is often assessed by time from treatment initiation to occurrence of a certain critical or beneficial event. In most cases the event of interest cannot be observed for all patients, as patients are only followed for a limited time or contact to patients is lost during their follow-up time. Therefore, certain methods were developed in the framework of the so called time-to-event or survival analysis, in order to obtain valid and consistent estimates in the presence of these "censored observations", using all available information. In classical event time analysis only one endpoint exists, as the death of a patient. As patients can die from different causes, in some clinical trials time to one out of two or more mutually exclusive types of event may be of interest. In many oncological studies, for example, time to cancer-specific death is considered as primary endpoint with deaths from other causes acting as so called competing risks. Different methods for data analysis in the competing risks framework were developed in recent years, which either focus on modelling the cause-specific or the subdistribution hazard rate or split the joint distribution of event times and event types into quantities, that can be estimated from observable data. In this work the analysis of event time data in the presence of competing risks is described, including the presentation and discussion of different regression approaches. A major topic of this work is the estimation of cause-specific and subdistribution hazard rates from a mixture model and a new approach using penalized B-splines (P-splines) for estimation of conditional hazard rates in a mixture model is proposed. In order to evaluate the behaviour of the new approach, a simulation study was conducted, using simulation techniques for competing risks data, which are described in detail in this work. The presented regression models were applied to data from a clinical cohort study investigating a risk stratification for cardiac mortality in patients, that survived a myocardial infarction. Finally, the use of the presented methods for event time analysis in the presence of competing risks and results obtained from the simulation study and the data analysis are discussed.Zur Beurteilung der Wirksamkeit von Behandlungen in klinischen Studien wird häufig die Zeit vom Beginn einer Behandlung bis zum Eintreten eines bestimmten kritischen oder erwünschten Ereignisses als Zielgröße verwendet. Da in vielen Fällen das entsprechende Ereignis nicht bei allen Patienten beobachtet werden kann, da z.B. Patienten nur für einen gewissen Zeitraum nachverfolgt werden können oder der Patientenkontakt in der Nachbeobachtungszeit abbricht, wurden im Rahmen der so genannten Ereigniszeit- bzw. Überlebenszeitanalyse Verfahren entwickelt, die bei Vorliegen dieser "zensierten Beobachtungen" konsistente Schätzer liefern und dabei die gesamte verfügbare Information verwenden. In der klassischen Ereigniszeitanalyse existiert nur ein möglicher Endpunkt, wie der Tod eines Patienten. Da Patienten jedoch an verschiedenen Ursachen versterben können, ist in manchen klinischen Studien die Zeit bis zu einem von zwei oder mehreren sich gegenseitig ausschließenden Ereignistypen von Interesse. So fungiert z.B. in vielen onkologischen Studien die Zeit bis zum tumor-bedingten Tod als primärer Endpunkt, wobei andere Todesursachen sogenannte konkurrierende Risiken ("Competing Risks") darstellen. In den letzten Jahren wurden mehrere Verfahren zur Datenanalyse bei Vorliegen konkurrierender Risiken entwickelt, bei denen entweder die ereignis-spezifische oder die Subdistribution-Hazardrate modelliert wird, oder bei denen die gemeinsame Verteilung von Ereigniszeiten und Ereignistypen als Produkt von Größen abgebildet wird, die aus den beobachtbaren Daten geschätzt werden können. In dieser Arbeit werden Methoden zur Analyse von Competing-Risks-Daten, einschließlich verschiedener Regressionsansätze, vorgestellt. Besonderes Augenmerk liegt auf der Schätzung der ereignis-spezifischen und Subdistribution-Hazardraten aus einem sogenannten Mixture Model. Diesbezüglich wird auch ein neuer Ansatz zur Schätzung der konditionalen Hazardraten in einem Mixture Model unter Verwendung penalisierter B-Spline-Funktionen (P-Splines) vorgestellt. Um die Eigenschaften des neuen Ansatzes zu untersuchen, wurde eine Simulationsstudie unter Einsatz verschiedener Simulationsstrategien für Competing-Risks-Daten, die in dieser Arbeit im Detail beschrieben werden, durchgeführt. Die Regressionsmodelle wurden auf Daten einer klinischen Kohortenstudie zur Evaluation einer Risikostratifizierung für Patienten, die einen Myokardinfarkt überlebt haben, angewandt. Abschließend werden die vorgestellten Methoden zur Analyse von Ereigniszeitdaten bei Vorliegen konkurrierender Risiken sowie die Ergebnisse der Simulationsstudie und der Datenanalyse diskutiert

Susy QCD and High Energy Cosmic Rays 1. Fragmentation functions of Susy QCD

The supersymmetric evolution of the fragmentation functions (or timelike evolution) within N=1 $QCD$ is discussed and predictions for the fragmentation functions of the theory (into final protons) are given. We use a backward running of the supersymmetric DGLAP equations, using a method developed in previous works. We start from the usual QCD parameterizations at low energy and run the DGLAP back, up to an intermediate scale -assumed to be supersymmetric- where we switch-on supersymmetry. From there on we assume the applicability of an N=1 supersymmetric evolution (ESAP). We elaborate on possible application of these results to High Energy Cosmic Rays near the GZK cutoff.Comment: 36 pages, 12 fig

The analysis of competing risks data with a focus on estimation of cause-specific and subdistribution hazard ratios from a mixture model

Treatment efficacy in clinical trials is often assessed by time from treatment initiation to occurrence of a certain critical or beneficial event. In most cases the event of interest cannot be observed for all patients, as patients are only followed for a limited time or contact to patients is lost during their follow-up time. Therefore, certain methods were developed in the framework of the so called time-to-event or survival analysis, in order to obtain valid and consistent estimates in the presence of these "censored observations", using all available information. In classical event time analysis only one endpoint exists, as the death of a patient. As patients can die from different causes, in some clinical trials time to one out of two or more mutually exclusive types of event may be of interest. In many oncological studies, for example, time to cancer-specific death is considered as primary endpoint with deaths from other causes acting as so called competing risks. Different methods for data analysis in the competing risks framework were developed in recent years, which either focus on modelling the cause-specific or the subdistribution hazard rate or split the joint distribution of event times and event types into quantities, that can be estimated from observable data. In this work the analysis of event time data in the presence of competing risks is described, including the presentation and discussion of different regression approaches. A major topic of this work is the estimation of cause-specific and subdistribution hazard rates from a mixture model and a new approach using penalized B-splines (P-splines) for estimation of conditional hazard rates in a mixture model is proposed. In order to evaluate the behaviour of the new approach, a simulation study was conducted, using simulation techniques for competing risks data, which are described in detail in this work. The presented regression models were applied to data from a clinical cohort study investigating a risk stratification for cardiac mortality in patients, that survived a myocardial infarction. Finally, the use of the presented methods for event time analysis in the presence of competing risks and results obtained from the simulation study and the data analysis are discussed.Zur Beurteilung der Wirksamkeit von Behandlungen in klinischen Studien wird häufig die Zeit vom Beginn einer Behandlung bis zum Eintreten eines bestimmten kritischen oder erwünschten Ereignisses als Zielgröße verwendet. Da in vielen Fällen das entsprechende Ereignis nicht bei allen Patienten beobachtet werden kann, da z.B. Patienten nur für einen gewissen Zeitraum nachverfolgt werden können oder der Patientenkontakt in der Nachbeobachtungszeit abbricht, wurden im Rahmen der so genannten Ereigniszeit- bzw. Überlebenszeitanalyse Verfahren entwickelt, die bei Vorliegen dieser "zensierten Beobachtungen" konsistente Schätzer liefern und dabei die gesamte verfügbare Information verwenden. In der klassischen Ereigniszeitanalyse existiert nur ein möglicher Endpunkt, wie der Tod eines Patienten. Da Patienten jedoch an verschiedenen Ursachen versterben können, ist in manchen klinischen Studien die Zeit bis zu einem von zwei oder mehreren sich gegenseitig ausschließenden Ereignistypen von Interesse. So fungiert z.B. in vielen onkologischen Studien die Zeit bis zum tumor-bedingten Tod als primärer Endpunkt, wobei andere Todesursachen sogenannte konkurrierende Risiken ("Competing Risks") darstellen. In den letzten Jahren wurden mehrere Verfahren zur Datenanalyse bei Vorliegen konkurrierender Risiken entwickelt, bei denen entweder die ereignis-spezifische oder die Subdistribution-Hazardrate modelliert wird, oder bei denen die gemeinsame Verteilung von Ereigniszeiten und Ereignistypen als Produkt von Größen abgebildet wird, die aus den beobachtbaren Daten geschätzt werden können. In dieser Arbeit werden Methoden zur Analyse von Competing-Risks-Daten, einschließlich verschiedener Regressionsansätze, vorgestellt. Besonderes Augenmerk liegt auf der Schätzung der ereignis-spezifischen und Subdistribution-Hazardraten aus einem sogenannten Mixture Model. Diesbezüglich wird auch ein neuer Ansatz zur Schätzung der konditionalen Hazardraten in einem Mixture Model unter Verwendung penalisierter B-Spline-Funktionen (P-Splines) vorgestellt. Um die Eigenschaften des neuen Ansatzes zu untersuchen, wurde eine Simulationsstudie unter Einsatz verschiedener Simulationsstrategien für Competing-Risks-Daten, die in dieser Arbeit im Detail beschrieben werden, durchgeführt. Die Regressionsmodelle wurden auf Daten einer klinischen Kohortenstudie zur Evaluation einer Risikostratifizierung für Patienten, die einen Myokardinfarkt überlebt haben, angewandt. Abschließend werden die vorgestellten Methoden zur Analyse von Ereigniszeitdaten bei Vorliegen konkurrierender Risiken sowie die Ergebnisse der Simulationsstudie und der Datenanalyse diskutiert

Ectopic c-kit Expression Affects the Fate of Melanocyte Precursors inPatchMutant Embryos

AbstractThePatch(Ph) mutation in the mouse, a deletion that includes the gene for PDGFRα, is a recessive lethal that exhibits a dominant pigment phenotype in heterozygotes. To assess whether thePhmutation acts cell-autonomously or non-autonomously on melanocyte development, we have examined the melanogenic potential of neural crest populations from normal and mutant crest cellsin vitroand the pattern of dispersal and survival of melanocyte precursors (MPs)in vivo.We report that trunk neural crest cells from homozygousPhembryos give rise to pigmented melanocytesin vitroin response to Steel factor (SlF).In vivo,homozygousPhembryos contain a subpopulation of crest-derived cells that express c-kit and tyrosinase-related protein-2 characteristic of MPs. These cells begin to migrate normally on the lateral crest migration pathway, but then fail to disperse in the dermal mesenchyme and subsequently disappear. Although dermal mesenchyme is adversely affected inPhhomozygotes, SlF mRNA expression by the cells of the dermatome is normal inPhembryos when neural crest-derived MPs start to migrate on the lateral pathway. In contrast, mRNA for the SlF receptor, c-kit, was observed to be ectopically expressed in somites and lateral mesenchyme in embryos carrying thePhmutation. Based on this ectopic expression of c-kit inPhmutant embryos, and the observed distribution of SlF protein in normal and mutant embryos, we suggest that competition for limited amounts of SlF localized on the lateral neural crest migration pathway alters melanocyte dispersal and survival

Marching at the front and dragging behind: differential αVβ3-integrin turnover regulates focal adhesion behavior

Integrins are cell–substrate adhesion molecules that provide the essential link between the actin cytoskeleton and the extracellular matrix during cell migration. We have analyzed αVβ3-integrin dynamics in migrating cells using a green fluorescent protein–tagged β3-integrin chain. At the cell front, adhesion sites containing αVβ3-integrin remain stationary, whereas at the rear of the cell they slide inward. The integrin fluorescence intensity within these different focal adhesions, and hence the relative integrin density, is directly related to their mobility. Integrin density is as much as threefold higher in sliding compared with stationary focal adhesions. High intracellular tension under the control of RhoA induced the formation of high-density contacts. Low-density adhesion sites were induced by Rac1 and low intracellular tension. Photobleaching experiments demonstrated a slow turnover of β3-integrins in low-density contacts, which may account for their stationary nature. In contrast, the fast β3-integrin turnover observed in high-density contacts suggests that their apparent sliding may be caused by a polarized renewal of focal contacts. Therefore, differential acto-myosin–dependent integrin turnover and focal adhesion densities may explain the mechanical and behavioral differences between cell adhesion sites formed at the front, and those that move in the retracting rear of migrating cells

A cluster randomised school-based lifestyle intervention programme for the prevention of childhood obesity and related early cardiovascular disease (JuvenTUM 3)

<p>Abstract</p> <p>Background</p> <p>Childhood obesity is not only associated with adult obesity but also with increased risk of adult onset of type 2 diabetes and subsequent coronary heart disease. The potential effects of school-based health intervention programmes on cardiovascular risk and surrogate markers are unclear, as only few studies have attempted to investigate a complete risk profile including a detailed laboratory analysis or micro- and macrovascular function. In this study a comprehensive school-based randomized intervention programme will be investigated in 10-14-year old children addressing the influence of lifestyle intervention on inactivity, cardiometabolic risk factors and early signs of vascular disease.</p> <p>Methods/Design</p> <p>15 secondary schools in Southern Germany are randomly assigned to intervention or control schools. Children in the fifth grade (10-11 years) will be observed over four years. The study combines a school-based with a home-based approach, aiming at children, teachers and parents. The main components are weekly lifestyle-lessons for children, taught by regular classroom teachers to increase physical activity in- and outside of school, to improve eating patterns at school and at home, to reduce media consumption and to amplify well-being. In 4-6 annual meetings, teachers receive information about health-related topics with worksheets for children and supporting equipment, accounting for school-specific needs and strategies. Parents' trainings are provided on a regular basis.</p> <p>All examinations are performed at the beginning and at the end of every school year. Anthropometry includes measurements of BMI, waist and upper arm circumferences, skinfold thickness as well as peripheral blood pressure. Blood sampling includes lipid parameters, insulin, glucose, hsCRP, adiponectin, and IL-6 as well as testosteron and estrogen to determine maturation status. Vascular function is non-invasively assessed by measuring arterial stiffness in large arteries using a sphygmograph and by analysing arteriolar and venular diameters in the retinal microcirculation using a non-mydriatric vessel analyser. A questionnaire is filled out to determine daily physical activity, motivational factors, dietary habits, quality of life (KINDL-R) and socio-economic data. Physical fitness is assessed by a six-item test battery.</p> <p>Discussion</p> <p>Our study aims to provide a feasible long-term intervention strategy to re-establish childhood health and to prevent obesity-related cardiovascular dysfunction in children.</p> <p>Trial Registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT00988754">NCT00988754</a></p

Highly Efficient Design-of-Experiments Methods for Combining CFD Analysis and Experimental Data

It is the purpose of this study to examine the impact of "highly efficient" Design-of-Experiments (DOE) methods for combining sets of CFD generated analysis data with smaller sets of Experimental test data in order to accurately predict performance results where experimental test data were not obtained. The study examines the impact of micro-ramp flow control on the shock wave boundary layer (SWBL) interaction where a complete paired set of data exist from both CFD analysis and Experimental measurements By combining the complete set of CFD analysis data composed of fifteen (15) cases with a smaller subset of experimental test data containing four/five (4/5) cases, compound data sets (CFD/EXP) were generated which allows the prediction of the complete set of Experimental results No statistical difference were found to exist between the combined (CFD/EXP) generated data sets and the complete Experimental data set composed of fifteen (15) cases. The same optimal micro-ramp configuration was obtained using the (CFD/EXP) generated data as obtained with the complete set of Experimental data, and the DOE response surfaces generated by the two data sets were also not statistically different

ICD Shock, Not Ventricular Fibrillation, Causes Elevation of High Sensitive Troponin T after Defibrillation Threshold Testing-The Prospective, Randomized, Multicentre TropShock-Trial

Background The placement of an implantable cardioverter defibrillator (ICD) has become routine practice to protect high risk patients from sudden cardiac death. However, implantation-related myocardial micro-damage and its relation to different implantation strategies are poorly characterized. Methods A total of 194 ICD recipients (64 +/- 12 years, 83% male, 95% primary prevention of sudden cardiac death, 35% cardiac resynchronization therapy) were randomly assigned to one of three implantation strategies: (1) ICD implantation without any defibrillation threshold (DFT) testing,(2) estimation of the DFT without arrhythmia induction (modified "upper limit of vulnerability (ULV) testing") or (3) traditional safety margin testing including ventricular arrhythmia induction. High-sensitive Troponin T (hsTnT) levels were determined prior to the implantation and 6 hours after. Results All three groups showed a postoperative increase of hsTnT. The mean delta was 0.031 +/- 0.032 ng/ml for patients without DFT testing, 0.080 +/- 0.067 ng/ml for the modified ULV-testing and 0.064 +/- 0.056 ng/ml for patients with traditional safety margin testing. Delta hsTnT was significantly larger in both of the groups with intraoperative ICD testing compared to the non-testing strategy (p<0.001 each). There was no statistical difference in delta hsTnT between the two groups with intraoperative ICD testing (p = 0.179). Conclusion High-sensitive Troponin T release during ICD implantation is significantly higher in patients with intraoperative ICD testing using shock applications compared to those without testing. Shock applications, with or without arrhythmia induction, did not result in a significantly different delta hsTnT. Hence, the ICD shock itself and not ventricular fibrillation seems to cause myocardial micro-damage

The mechanisms and dynamics of αvβ3 integrin clustering in living cells

During cell migration, the physical link between the extracellular substrate and the actin cytoskeleton mediated by receptors of the integrin family is constantly modified. We analyzed the mechanisms that regulate the clustering and incorporation of activated αvβ3 integrins into focal adhesions. Manganese (Mn2+) or mutational activation of integrins induced the formation of de novo F-actin–independent integrin clusters. These clusters recruited talin, but not other focal adhesion adapters, and overexpression of the integrin-binding head domain of talin increased clustering. Integrin clustering required immobilized ligand and was prevented by the sequestration of phosphoinositole-4,5-bisphosphate (PI(4,5)P2). Fluorescence recovery after photobleaching analysis of Mn2+-induced integrin clusters revealed increased integrin turnover compared with mature focal contacts, whereas stabilization of the open conformation of the integrin ectodomain by mutagenesis reduced integrin turnover in focal contacts. Thus, integrin clustering requires the formation of the ternary complex consisting of activated integrins, immobilized ligands, talin, and PI(4,5)P2. The dynamic remodeling of this ternary complex controls cell motility