A study of a survival data using kernel estimates of hazard rate and aging intensity functions

Metabolic evaluation of brain tumor using magnetic resonance spectroscopy

Conventional magnetic resonance imaging in the differentiation between high and low-grade brain tumours in paediatric patients

The aging intensity functions analyze the aging property quantitatively, in the sense that the larger the aging intensity, the stronger the tendency of aging. They are useful tools to describe reliability properties of distributions. In the literature, the aging intensity functions have been studied in the univariate and bivariate case but without considering the possibility of observing a dynamic history. In this paper, the concept of aging intensity function is extended to the multivariate case by the use of the multivariate conditional hazard rate functions. Some properties of those functions are studied and a focus on the bivariate case is performed. Finally, the multivariate conditional aging intensity functions are studied for the order dependent version of the time-homogeneous load-sharing model and a study on the comparison among surviving components in a system is provided.

Differentiation between high and low grade tumours in paediatric patients by using apparent diffusion coefficients

A unified form of gamma-type distributions

866 DIFFERENTIAL MIRNA EXPRESSION PROFILES IN URINES FROM BLADDER CANCER PATIENTS

The continuous development of flexible probability distributions has become essential for accurately describing complex stochastic phenomena. In this study, a new theoretical based on the New Sine Type II Generalized Topp-Leone distribution is investigated. The model is constructed by integrating the sine trigonometric transformation with the Type II Topp-Leone generator applied to an arbitrary baseline distribution. This combination introduces additional shape parameters that enhance the adaptability of the resulting family of distributions. Several mathematical properties of the proposed model are derived. These include explicit expressions for the cumulative distribution function (cdf), probability density function (pdf), survival function, and hazard rate function. In addition, analytical forms of the quantile function, moments, moment generating function, and order statistics are established. The author’s adopted two estimation techniques in this work: the maximum likelihood estimation (MLE) and the maximum product of spacing (MPLS) estimation methods. The structural characteristics of the distribution reveal that it is capable of producing a wide range of density and hazard rate shapes depending on the selected baseline model and parameter values. The theoretical results presented in this work provide a general framework for constructing new members of the family and offer a foundation for further statistical developments involving estimation techniques and practical implementations. Plots of the pdf, cdf as well as the validity check on the pdf of the new model indicate that the model is adequate capable of handling all the intricate associated with real-life datasets.

10 Background: Prostate Imaging Reporting and Data System (PIRADS) Version 2 was recently issued by The American College of Radiology. Each score, from 1 to 5, corresponds to the likelihood of clinically significant cancer. We aim to evaluate the correlation between a higher PIRADS score and the presence of high grade tumor on histopathology. Methods: 300 consecutive 3T Multiparametric Prostate MRI (MP-MRI) were identified from March 26, 2012, to June 29, 2015. We reviewed patient charts and a total of 102 patients underwent either a transrectal ultrasound guided (TRUS) biopsy or a total prostatectomy after the MP-MRI. Thirty-four patients were excluded due to prior radiation or cryoablation to the prostate, leaving 68 treatment-naive patients (44-84 years). MP-MRIs were re-interpreted utilizing the new PIRADS V.2 scoring system and correlated with pathology findings. Statistical comparisons were made using R (v.3.1.2) and Fisher’s exact test. Results: High grade (Gleason 8-10) tumors were found only in MP-MRI with a PIRADS score of 5 and a higher percentage of tumor is found in MP-MRI with PIRADS scores of 4 and 5 (80%) when compared to PIRADS scores of 2 and 3 (32%). Low grade (Gleason 6-7) tumors were also found in both PIRADS 4 and 5 categories. There was a significant relationship between a higher PIRADS score and a finding of cancer on pathology (p = 0.0003, OR=0.118, 95% CI 0.03-0.41). Conclusions: The PIRADS scoring system is a useful tool in suggesting the likelihood of clinically significant cancer, with high grade tumors found only in MP-MRI with a score of PIRADS 5. However, MP-MRI and PIRADS criteria alone are not sufficient for determining clinically significant prostate cancer since both high grade and low grade tumors were found in PIRADS 5 and 4 categories. Correlation with other clinical parameters and biopsy is required for confirmation. A larger scale study would be helpful for further delineation. [Table: see text]

Management of Pediatric Spinal Cord Astrocytomas: Outcomes With Adjuvant Radiation

Mixed High and Low Grade Bladder Tumors—Are They Clinically High or Low Grade?

There are many measures for qualitative and quantitative analysis of ageing phenomena of a system with a well defined statistical distribution, namely, hazard rate, ageing intensity (AI) function etc. The extensive usage of Weibull distributions in various fields has prompted us to explore the ageing property of these models. The present work derives the AI function of recent continuous Weibull distributions. In the process, we obtain generalizations of a few recent Weibull models. As noted, the characteristics of a distribution described by hazard rate and ageing intensity function differ altogether in many cases. Some of the results presented in this work have been analyzed through a simulation study using R software.

The presence of non-conforming components instead of, or in addition to, the usual assembly errors results in N- or W-shaped hazard rate (HR) functions rather than the usual bathtub (i.e. U-shaped) ones. Although there have been numerous models for bathtub-shaped HR functions, N- and W-shaped HR functions are usually modelled using mixtures of two or more distributions. While this approach does sometimes lead to tidy interpretation, there can be a degree of overparameterization, with consequent problems in stability and fitting. For this reason, the present paper revisits the natural approach of modelling N- and W-shaped HR functions using polynomial functions of degree three or four. Although the non-negativity of the hazard rate function becomes non-trivial, this ensures a minimal number of parameters. The polynomial approach also allows the use of a parametric model without imposing a particular shape of hazard rate function on the data, which usually requires a non-parametric approach. The possible hazard rate shapes obtainable are characterized, and detailed formulae for local minima and maxima of the functions provided. The performance of the models is compared to that of several generalizations of the Weibull distribution, with promising results.

Non-linearity in cancer dose-response: The role of exposure duration

Hazard rate function (HRF) is always applied to make preventive maintenance (PM) decisions, and it is statistically estimated from failure time data. However, the classical HRF is not appropriate for systems under online monitoring, which is stopped to be checked and repaired when the monitored data exceed a predetermined threshold level. In this paper, based on two types of failure and corresponding two types of HRFs, two level checking and maintenance policy is constructed, which incorporates online monitoring and offline inspection. Finally, numerical examples are shown to verify the ideas of this paper.

The discrete additive Weibull distribution: A bathtub-shaped hazard for discontinuous failure data