gsbDesign: An R Package for Evaluating the Operating Characteristics of a Group Sequential Bayesian Design

The R package gsbDesign provides functions to evaluate the operating characteristics of Bayesian group sequential clinical trial designs. More specifically, we consider clinical trials with interim analyses, which compare a treatment with a control, and where the endpoint is normally distributed. Prior information can either be specified for the difference of treatment and control, or separately for the effects in the treatment and the control groups. At each interim analysis, the decision to stop or continue the trial is based on the posterior distribution of the difference between treatment and control. The decision at the final analysis is also based on this posterior distribution. Multiple success and/or futility criteria can be specified to reflect adequately medical decision-making. We describe methods to evaluate the operating characteristics of such designs for scenarios corresponding to different true treatment and control effects. The characteristics of main interest are the probabilities of success and futility at each interim analysis, and the expected sample size. We illustrate the use of gsbDesign with a detailed case study

Measurement of the electron-hole pair creation energy in a 4H-SiC p-n diode

For 4H silicon carbide (4H-SiC), the values for the electron-hole pair creation energy $\epsilon_{\text{i}}$ published in the literature vary significantly. This work presents an experimental determination of $\epsilon_{\text{i}}$ using $50$ $\mu$m 4H-SiC p-n diodes designed for particle detection in high-energy physics. The detector response was measured for $\alpha$ particles between 4.2 MeV and 5.6 MeV for 4H-SiC and a silicon reference device. Different $\alpha$ energies were obtained by using multiple nuclides and varying the effective air gap between the $\alpha$ source and the detector. The energy deposited in the detectors was determined using a Monte Carlo simulation, taking into account the device cross-sections. A linear fit of the detector response to the deposited energy yields $\epsilon_{\text{i}} = (7.83 \pm 0.02)\;\text{eV}$, which agrees well with the most recent literature. For the 4H-SiC detectors, a linewidth of 28 keV FWHM was achieved, corresponding to an energy resolution of 0.5\%.Comment: Revision prepared for submission to NIM

SiC Based Beam Monitoring System for Particle Rates from kHz to GHz

The extremely low dark current of silicon carbide (SiC) detectors, even after high-fluence irradiation, was utilized to develop a beam monitoring system for a wide range of particle rates, i.e., from the kHz to the GHz regime. The system is completely built from off-the-shelve components and is focused on compactness and simple deployment. Beam tests using a 50 um thick SiC detector reveal, that for low fluences, single particles can be detected and counted. For higher fluences, beam properties were extracted from beam cross sections using a silicon strip detector. Overall accurate results were achieved up to a particle rate of 109 particles per second

Performance of neutron-irradiated 4H-Silicon Carbide diodes subjected to Alpha radiation

The unique electrical and material properties of 4H-silicon-carbide (4H-SiC) make it a promising candidate material for high rate particle detectors. In contrast to the ubiquitously used silicon (Si), 4H-SiC offers a higher carrier saturation velocity and larger breakdown voltage, enabling a high intrinsic time resolution and mitigating pile-up effects. Additionally, as radiation hardness requirements grow more demanding, wide-bandgap materials such as 4H-SiC could offer better performance. In this work, the detector performance of 50 micron thick 4H-SiC p-in-n planar pad sensors was investigated at room temperature, using an 241Am alpha source at reverse biases of up to 1100 V. Samples subjected to neutron irradiation with fluences of up to 1e16/cm^2 were included in the study in order to quantify the radiation hardness properties of 4H-SiC. The obtained results are compared to previously performed UV-TCT studies. Samples exhibit a drop in charge collection efficiency (CCE) with increasing irradiation fluence, partially compensated at high reverse bias voltages far above full depletion voltage. A plateau of the collected charges is observed in accordance with the depletion of the volume the alpha particles penetrate for an unirradiated reference detector. For the neutron-irradiated samples, such a plateau only becomes apparent at higher reverse bias. For the highest investigated fluence, CCE behaves almost linearly with increasing reverse bias. Compared to UV-TCT measurements, the reverse bias required to deplete a sensitive volume covering full energy deposition is lower, due to the small penetration depth of the alpha particles. At the highest reverse bias, the measured CCE values agree well with earlier UV-TCT studies, with discrepancies between 1% and 5%.Comment: 10 pages (8 without references), 6 figures, 1 table, to be published in the Proceedings Section of Journal of Instrumentation (JINST) as a proceeding of iWoRiD202

gems: An R Package for Simulating from Disease Progression Models

Mathematical models of disease progression predict disease outcomes and are useful epidemiological tools for planners and evaluators of health interventions. The R package gems is a tool that simulates disease progression in patients and predicts the effect of different interventions on patient outcome. Disease progression is represented by a series of events (e.g., diagnosis, treatment and death), displayed in a directed acyclic graph. The vertices correspond to disease states and the directed edges represent events. The package gems allows simulations based on a generalized multistate model that can be described by a directed acyclic graph with continuous transition-specific hazard functions. The user can specify an arbitrary hazard function and its parameters. The model includes parameter uncertainty, does not need to be a Markov model, and may take the history of previous events into account. Applications are not limited to the medical field and extend to other areas where multistate simulation is of interest. We provide a technical explanation of the multistate models used by gems, explain the functions of gems and their arguments, and show a sample application

Incidence of Kaposi Sarcoma in HIV-infected patients – a prospective multi-cohort study from Southern Africa

Oral presentation presented at the 13th International Conference on Malignancies in AIDS and Other Acquired Immunodeficiencies (ICMAOI) Bethesda, MD, USA. 7-8 November 2011The original publication is available at http://www.infectagentscancer.com/content/7/S1/O20Background: The incidence of Kaposi Sarcoma (KS) is high in sub-Saharan Africa. Data on KS among HIV-infected patients receiving and not yet receiving antiretroviral therapy (ART) are, however, scarce in Africa. Within the framework of a large multi-cohort project, the International epidemiologic Database to Evaluate AIDS (IeDEA), we estimate the incidence and risk factors for the development of KS in HIV-infected patients in Southern Africa.Publishers' Versio

Hepatitis C Virus Infections in the Swiss HIV Cohort Study: A Rapidly Evolving Epidemic

In the Swiss HIV Cohort Study, a nationwide cohort with systematic hepatitis C virus (HCV) infection screening since 1998, HCV incidence decreased in injection drug users, remained low in heterosexuals, and dramatically increased in men who have sex with me

Impact of Single Nucleotide Polymorphisms and of Clinical Risk Factors on New-Onset Diabetes Mellitus in HIV-Infected Individuals

Background.Metabolic complications, including cardiovascular events and diabetes mellitus (DM), are a major long-term concern in human immunodeficienc virus (HIV)-infected individuals. Recent genome-wide association studies have reliably associated multiple single nucleotide polymorphisms (SNPs) to DM in the general population. Methods.We evaluated the contribution of 22 SNPs identifie in genome-wide association studies and of longitudinally measured clinical factors to DM. We genotyped all 94 white participants in the Swiss HIV Cohort Study who developed DM from 1 January 1999 through 31 August 2009 and 550 participants without DM. Analyses were based on 6054 person-years of follow-up and 13,922 measurements of plasma glucose. Results.The contribution to DM risk explained by SNPs (14% of DM variability) was larger than the contribution to DM risk explained by current or cumulative exposure to different antiretroviral therapy combinations (3% of DM variability). Participants with the most unfavorable genetic score (representing 12% and 19% of the study population, respectively, when applying 2 different genetic scores) had incidence rate ratios for DM of 3.80 (95% confidenc interval [CI], 2.05-7.06) and 2.74 (95% CI, 1.53-4.88), respectively, compared with participants with a favorable genetic score. However, addition of genetic data to clinical risk factors that included body mass index only slightly improved DM prediction. Conclusions.In white HIV-infected persons treated with antiretroviral therapy, the DM effect of genetic variants was larger than the potential toxic effects of antiretroviral therapy. SNPs contributed significantl to DM risk, but their addition to a clinical model improved DM prediction only slightly, similar to studies in the general populatio

Estimated mortality of adult HIV-infected patients starting treatment with combination antiretroviral therapy

To provide estimates of mortality among HIV-infected patients starting combination antiretroviral therapy

Maximum tumor diameter adjusted to the risk profile predicts biochemical recurrence after radical prostatectomy

Currently, no consensus exists on the best method for tumor quantification in prostate cancer (PCA), and its prognostic value remains controversial. We evaluated how a newly defined maximum tumor diameter (MTD) might contribute to the prediction of biochemical recurrence (BCR) in a consecutive series of PCA patients treated with radical prostatectomy (RP). Patients with PCA who underwent RP without neoadjuvant therapy at a single center were included for analysis. MTD was defined as the largest diameter of all identified tumors in all three dimensions (i.e., length, width, or depth) of the prostate ("Basel technique”). Cox regression models addressed the association of MTD with BCR in three risk groups (low risk—prostate-specific antigen (PSA)  20ng/ml or pT3 or GS ≥ 8) and whole cohort. Within a median follow-up of 44months (interquartile range (IQR) 23-66), 48 patients (9.4%) in the intermediate-risk and high-risk groups experienced BCR. In multivariate Cox regression analysis, PSA, pathological stage (pT stage), GS, positive surgical margins (PSMs), and MTD > 19.5mm were independent predictors for BCR (p 24.5mm) was the only independent predictor of BCR in the intermediate-risk group (hazard ratio (HR) 9.933, 95% confidence interval (CI) 2.070-47.665; p < 0.05). MTD is an independent risk factor of BCR in PC patients after RP. The combination of the MTD with other well-known prognostic factors after RP may improve decision-making concerning follow-up intensity or adjuvant treatment