1,720,994 research outputs found
On the conditional probability for assessing time dependence of association in shared frailty models with bivariate current status data
No full textShared frailty models are frequently used for inducing dependence between survival times. In this paper, we consider bivariate current status data that are reasonable to model by shared frailty models. A time-dependent association measure that has a conditional probability interpretation is revisited for its potential application to such data. We propose a method of estimation and derive asymptotic standard errors for this measure. Its small sample performance and its performance in assessing the temporal variation in the strength of association in realistic scenarios is investigated by means of experiments. We show that the measure based on the conditional probability can vary with time even in the absence of any time-dependent effects. Furthermore, we give evidence that it lacks interpretability in suggesting appropriate frailty models. We provide an illustration with multivariate current status data arising from a community-based study of cardiovascular diseases in Taiwan. We compare the observed patterns of association with the ones obtained by employing a fairly new time-varying association measure that is relevant for shared frailty models, owing to its connection to the cross-ratio function, and which serves as a diagnostic tool for suggesting classes of frailty distributions with constant, increasing or decreasing association over time. (C) 2016 Elsevier B.V. All rights reserved
On the shape of the cross-ratio function in bivariate survival models induced by truncated and folded normal frailty distributions
No full textIn shared frailty models for bivariate survival data the frailty is identifiable through the cross-ratio function (CRF), which provides a convenient measure of association for correlated survival variables. The CRF may be used to compare patterns of dependence across models and data sets. We explore the shape of the CRF for the families of one-sided truncated normal and folded normal frailty distributions
On the Addams family of discrete frailty distributions for modeling multivariate case I interval-censored data
No full textAbstract Random effect models for time-to-event data, also known as frailty models, provide a conceptually appealing way of quantifying association between survival times and of representing heterogeneities resulting from factors which may be difficult or impossible to measure. In the literature, the random effect is usually assumed to have a continuous distribution. However, in some areas of application, discrete frailty distributions may be more appropriate. The present paper is about the implementation and interpretation of the Addams family of discrete frailty distributions. We propose methods of estimation for this family of densities in the context of shared frailty models for the hazard rates for case I interval-censored data. Our optimization framework allows for stratification of random effect distributions by covariates. We highlight interpretational advantages of the Addams family of discrete frailty distributions and theK-point distribution as compared to other frailty distributions. A unique feature of the Addams family and the K-point distribution is that the support of the frailty distribution depends on its parameters. This feature is best exploited by imposing a model on the distributional parameters, resulting in a model with non-homogeneous covariate effects that can be analyzed using standard measures such as the hazard ratio. Our methods are illustrated with applications to multivariate case I interval-censored infection data
On the analysis of clonogenic survival data: Statistical alternatives to the linear-quadratic model
Full text linkBackground: The most frequently used method to quantitatively describe the response to ionizing irradiation in terms of clonogenic survival is the linear-quadratic (LQ) model. In the LQ model, the logarithm of the surviving fraction is regressed linearly on the radiation dose by means of a second-degree polynomial. The ratio of the estimated parameters for the linear and quadratic term, respectively, represents the dose at which both terms have the same weight in the abrogation of clonogenic survival. This ratio is known as the alpha/beta ratio. However, there are plausible scenarios in which the alpha/beta ratio fails to sufficiently reflect differences between dose-response curves, for example when curves with similar alpha/beta ratio but different overall steepness are being compared. In such situations, the interpretation of the LQ model is severely limited. Methods: Colony formation assays were performed in order to measure the clonogenic survival of nine human pancreatic cancer cell lines and immortalized human pancreatic ductal epithelial cells upon irradiation at 0-10 Gy. The resulting dataset was subjected to LQ regression and non-linear log-logistic regression. Dimensionality reduction of the data was performed by cluster analysis and principal component analysis. Results: Both the LQ model and the non-linear log-logistic regression model resulted in accurate approximations of the observed dose-response relationships in the dataset of clonogenic survival. However, in contrast to the LQ model the non-linear regression model allowed the discrimination of curves with different overall steepness but similar alpha/beta ratio and revealed an improved goodness-of-fit. Additionally, the estimated parameters in the non-linear model exhibit a more direct interpretation than the alpha/beta ratio. Dimensionality reduction of clonogenic survival data by means of cluster analysis was shown to be a useful tool for classifying radioresistant and sensitive cell lines. More quantitatively, principal component analysis allowed the extraction of scores of radioresistance, which displayed significant correlations with the estimated parameters of the regression models. Conclusions: Undoubtedly, LQ regression is a robust method for the analysis of clonogenic survival data. Nevertheless, alternative approaches including non-linear regression and multivariate techniques such as cluster analysis and principal component analysis represent versatile tools for the extraction of parameters and/or scores of the cellular response towards ionizing irradiation with a more intuitive biological interpretation. The latter are highly informative for correlation analyses with other types of data, including functional genomics data that are increasingly being generated
Introduction of Non-Vitamin K Antagonist Anticoagulants Strongly Increased the Rate of Anticoagulation in Hospitalized Geriatric Patients with Atrial Fibrillation
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A Comparison of Conventional and In-Situ Audiometry on Participants with Varying Levels of Sensorineural Hearing Loss
No full textBackground: In-situ audiometry is a hearing aid feature that enables the measurement of hearing threshold levels through the hearing instrument using the built-in sound generator and the hearing aid receiver. This feature can be used in hearing aid fittings instead of conventional pure-tone audiometry (PTA), particularly in places where no standard audiometric equipment is available. Differences between conventional and in-situ thresholds are described and discussed for some particular hearing aids. No previous investigation has measured and compared these differences for a number of current hearing aid models by various manufacturers across a wide range of hearing losses. Purpose: The purpose of this study was to perform a model-based comparison of conventionally and insitu measured hearing thresholds. Data were collected for a range of hearing aid devices to study and generalize the effects that may occur under clinical conditions. Research Design: Research design was an experimental and regression study. Study Sample: A total of 30 adults with sensorineural hearing loss served as test persons. They were assigned to three subgroups of 10 subjects with mild (M), moderate to severe (MS), and severe (S) sensorineural hearing loss. Intervention: All 30 test persons underwent both conventional PTA and in-situ audiometry with four hearing aid models by various manufacturers. Data Collection and Analysis: The differences between conventionally and in-situ measured hearing threshold levels were calculated and evaluated by an exploratory data analysis followed by a sophisticated statistical modeling process. Results: At 500 and 1500 Hz, almost all threshold differences (conventional PTA minus in-situ data) were negative, i.e., in the low to mid frequencies, hearing loss was overestimated by most devices relative to PTA. At 4000 Hz, the majority of differences (7 of 12) were positive, i.e., in the frequency range above 1500 Hz, hearing loss was frequently underestimated. As hearing loss increased (M -> MS -> S), the effect of the underestimation decreased. At 500 and 1500 Hz, Resound devices showed the smallest threshold deviations, followed by Phonak, Starkey, and Oticon instruments. At 4000 Hz, this observed pattern partly disappeared and Starkey and Oticon devices showed a reversed effect with increasing hearing loss (M -> MS -> S). Because of high standard errors for the estimates, only a few explicit rankings of the devices could be established based on significant threshold differences (5% level). Conclusions: Differences between conventional PTA and in-situ threshold levels may be attributed to (1) frequency, (2) device/hearing loss, and (3) calibration/manufacturer effects. Frequency effects primarily resulting in an overestimation of hearing loss by in-situ audiometry in the low and mid frequencies are mainly due to sound drain-off through vents and leaks. Device/hearing loss effects may be due to leakage as well as boundary effects because in-situ audiometry is confined to a limited measurement range. Finally, different calibration approaches may result in different offset levels between PTA and in-situ audiometry calibration. In some cases, the observed threshold differences of up to 10-15 dB may translate to varied hearing aid fittings for the same user depending on how hearing threshold levels were measured.GN ReSoun
Inherent radioresistance of head and neck squamous cell carcinoma cells: principal component analysis identifies cellular senescence as a crucial driver
No full textHSP90 inhibition as a means of radiosensitizing resistant, aggressive soft tissue sarcomas
No full textRadiotherapy is an essential part of multi-modal treatment for soft tissue sarcomas. Treatment failure is commonly attributed to radioresistance, but comprehensive analyses of radiosensitivity are not available, and suitable biomarkers or candidates for targeted radiosensitization are scarce. Here, we systematically analyzed the intrinsic radioresistance of a panel of soft tissue sarcoma cell lines, and extracted scores of radioresistance by principal component analysis (PCA). To identify molecular markers of radioresistance, transcriptomic profiling of DNA damage response regulators was performed. The expression levels of HSP90 and its clients ATR, ATM, and NBS1 revealed strong, positive correlations with the PCA-derived radioresistance scores. Their functional involvement was addressed by HSP90 inhibition, which preferentially sensitized radioresistant sarcoma cells and was accompanied by delayed γ-H2AX foci clearance and HSP90 client protein degradation. The induction of apoptosis and necrosis was not significantly enhanced, but increased levels of basal and irradiation-induced senescence upon HSP90 inhibition were detected. Finally, evaluation of our findings in the TCGA soft tissue sarcoma cohort revealed elevated expression levels of HSP90, ATR, ATM, and NBS1 in a relevant subset of cases with particularly poor prognosis, which might preferentially benefit from HSP90 inhibition in combination with radiotherapy in the future
Inherent radioresistance of head and neck squamous cell carcinoma cells: principal component analysis identifies cellular senescence as a crucial driver
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