elaborator: A Novel App for Insights into Laboratory Data of Clinical Trials.

In clinical studies there are huge numbers of laboratory parameters available that are measured at several visits for several treatment groups. The status quo for presenting laboratory data in clinical trials consists in generating large numbers of tables and data listings. Such tables and listings are required for submissions to health authorities. However, reviewing laboratory data presented in the form of tables and listings is a lengthy and tedious process. Thus, to enable efficient exploration of laboratory data we developed elaborator, a comprehensive and easy-to-use interactive browser-based application. The elaborator app comprises three analyses types for addressing different questions, for example about changes in laboratory values that frequently occur, treatment-related changes and changes beyond the normal ranges. In this way, the app can be used by study teams for identifying safety signals in a clinical trial as well as for generating hypotheses that are further inspected with detailed analyses and possibly data from other sources. The elaborator app is implemented in the statistical software R. The R package elaborator can be obtained from https://cran.r-project.org/package=elaborator . Patients' laboratory data need to be extracted from the clinical database and pre-processed locally for feeding into the app. For exploring data by means of the elaborator, the user needs some familiarity with R but no programming knowledge is required.

Reestablishment of individual sleep structure during a single 14-h recovery sleep episode after 58 h of wakefulness.

Sleep structure is highly stable within individuals but different between individuals. The present study investigated robustness of the individual sleep structure to extended total sleep deprivation. Seventeen healthy men spent a baseline night (23:00-07:00 hours), 58 h of sleep deprivation and a 14-h recovery night (17:00-07:00 hours) in the laboratory. Intraclass correlation coefficients showed that the agreement between baseline and recovery with respect to the proportion of the different sleep stages increased as a function of recovery sleep duration. High values were reached for most of the sleep stages at the end of 14 h of recovery sleep (intraclass correlation coefficients between 0.38 and 0.76). If sleep duration of the recovery night is extended to 14 h, sleep stage distribution resembles that of a baseline night underlining the robustness of the individual sleep structure.

Short-term annoyance from nocturnal aircraft noise exposure: results of the NORAH and STRAIN sleep studies.

PURPOSE: The German Aerospace Center (DLR) investigated in the NORAH sleep study the association between a distinct change in nocturnal aircraft noise exposure due to the introduction of a night curfew (11:00 p.m.-5:00 a.m.) at Frankfurt Airport and short-term annoyance reactions of residents in the surrounding community. Exposure-response curves were calculated by random effects logistic regression to evaluate the aircraft noise-related parameters (1) number of overflights and (2) energy equivalent noise level LASeq for the prediction of short-term annoyance. Data of the NORAH sleep study were compared with the STRAIN sleep study which was conducted by DLR near Cologne-Bonn Airport in 2001/2002 (N = 64), representing a steady-state/low-rate change. METHODS: The NORAH sleep study was based on questionnaire surveys with 187 residents living in the vicinity of Frankfurt Airport. Noise-induced short-term annoyance and related non-acoustical variables were assessed. Nocturnal aircraft noise exposure was measured inside the residents' home. RESULTS: A statistically significant rise in the portion of annoyed residents with increasing number of overflights was found. Similarly, the portion of annoyed subjects increased with rising LASeq. Importance of the frequency of fly-overs for the prediction of annoyance reactions was emphasized. The annoyance probability was significantly higher in the NORAH than in the STRAIN sleep study. CONCLUSIONS: Results confirm the importance of both acoustical parameters for the prediction of short-term annoyance due to nocturnal aircraft noise. Quantitative annoyance models that were derived at steady-state/low-rate change airports cannot be directly applied to airports that underwent a distinct change in operational and noise exposure patterns.

Noise exposure-response relationships established from repeated binary observations: Modeling approaches and applications.

Noise exposure-response relationships are used to estimate the effects of noise on individuals or a population. Such relationships may be derived from independent or repeated binary observations, and modeled by different statistical methods. Depending on the method by which they were established, their application in population risk assessment or estimation of individual responses may yield different results, i.e., predict "weaker" or "stronger" effects. As far as the present body of literature on noise effect studies is concerned, however, the underlying statistical methodology to establish exposure-response relationships has not always been paid sufficient attention. This paper gives an overview on two statistical approaches (subject-specific and population-averaged logistic regression analysis) to establish noise exposure-response relationships from repeated binary observations, and their appropriate applications. The considerations are illustrated with data from three noise effect studies, estimating also the magnitude of differences in results when applying exposure-response relationships derived from the two statistical approaches. Depending on the underlying data set and the probability range of the binary variable it covers, the two approaches yield similar to very different results. The adequate choice of a specific statistical approach and its application in subsequent studies, both depending on the research question, are therefore crucial.

Passenger comfort on high-speed trains: effect of tunnel noise on the subjective assessment of pressure variations.

When passing through a tunnel, aerodynamic effects on high-speed trains may impair passenger comfort. These variations in atmospheric pressure are accompanied by transient increases in sound pressure level. To date, it is unclear whether the latter influences the perceived discomfort associated with the variations in atmospheric pressure. In a pressure chamber of the DLR-Institute of Aerospace Medicine, 71 participants (M = 28.3 years ± 8.1 SD) rated randomised pressure changes during two conditions according to a crossover design. The pressure changes were presented together with tunnel noise such that the sound pressure level was transiently elevated by either +6 dB (low noise condition) or +12 dB (high noise condition) above background noise level (65 dB(A)). Data were combined with those of a recent study, in which identical pressure changes were presented without tunnel noise (Schwanitz et al., 2013, 'Pressure Variations on a Train - Where is the Threshold to Railway Passenger Discomfort?' Applied Ergonomics 44 (2): 200-209). Exposure-response relationships for the combined data set comprising all three noise conditions show that pressure discomfort increases with the magnitude and speed of the pressure changes but decreases with increasing tunnel noise. Practitioner Summary: In a pressure chamber, we systematically examined how pressure discomfort, as it may be experienced by railway passengers, is affected by the presence of tunnel noise during pressure changes. It is shown that across three conditions (no noise, low noise (+6 dB), high noise (+12 dB)) pressure discomfort decreases with increasing tunnel noise.

Pseudo-value approach for comparing survival medians for dependent data.

Survival median is commonly used to compare treatment groups in cancer-related research. The current literature focuses on developing tests for independent survival data. However, researchers often encounter dependent survival data such as matched pair data or clustered data. We propose a pseudo-value approach to test the equality of survival medians for both independent and dependent survival data. We investigate the type I error and power of the proposed method by a simulation study, in which we examine independent and dependent data. The simulation study shows that the proposed method performs equivalently to the existing methods for independent survival data and performs better for dependent survival data. A study comparing survival median times for bone marrow transplants illustrates the proposed method.

Comparison of statistics in association tests of genetic markers for survival outcomes.

Computationally efficient statistical tests are needed in association testing of large scale genetic markers for survival outcomes. In this study, we explore several test statistics based on the Cox proportional hazards model for survival data. First, we consider the classical partial likelihood-based Wald and score tests. A revised way to compute the score statistics is explored to improve the computational efficiency. Next, we propose a Cox-Snell residual-based score test, which allows us to handle the controlling variables more conveniently. We also illustrated the incorporation of these three tests into a permutation procedure to adjust for the multiple testing. In addition, we examine a simulation-based approach proposed by Lin (2005) to adjust for multiple testing. We presented the comparison of these four statistics in terms of type I error, power, family-wise error rate, and computational efficiency under various scenarios via extensive simulation.