Search results for "BREAST"
showing 10 items of 1871 documents
Bayesian joint ordinal and survival modeling for breast cancer risk assessment
2016
We propose a joint model to analyze the structure and intensity of the association between longitudinal measurements of an ordinal marker and time to a relevant event. The longitudinal process is defined in terms of a proportional-odds cumulative logit model. Time-to-event is modeled through a left-truncated proportionalhazards model, which incorporates information of the longitudinal marker as well as baseline covariates. Both longitudinal and survival processes are connected by means of a common vector of random effects. General inferences are discussed under the Bayesian approach and include the posterior distribution of the probabilities associated to each longitudinal category and the …
dglars: An R Package to Estimate Sparse Generalized Linear Models
2014
dglars is a publicly available R package that implements the method proposed in Augugliaro, Mineo, and Wit (2013), developed to study the sparse structure of a generalized linear model. This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method proposed in Efron, Hastie, Johnstone, and Tibshirani (2004). The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve: a predictor-corrector algorithm, proposed in Augugliaro et al. (2013), and a cyclic coordinate descent algorithm, proposed in Augugliaro, Mineo, and Wit (2012). The latter algorithm, as shown here, is significan…
Bayesian assessment of times to diagnosis in breast cancer screening
2008
Breast cancer is one of the diseases with the most profound impact on health in developed countries and mammography is the most popular method for detecting breast cancer at a very early stage. This paper focuses on the waiting period from a positive mammogram until a confirmatory diagnosis is carried out in hospital. Generalized linear mixed models are used to perform the statistical analysis, always within the Bayesian reasoning. Markov chain Monte Carlo algorithms are applied for estimation by simulating the posterior distribution of the parameters and hyperparameters of the model through the free software WinBUGS.
Bayesian Mapping of Lichens Growing on Trees
2001
Suitability of trees as hosts for epiphytic lichens are studied in a forest stand of size 25 ha. Suitability is measured as occupation probabilites which are modelled using hierarchical Bayesian approach. These probabilities are useful for an ecologist. They give smoothed spatial distribution map of suitability for each of the species and can be used in detecting high- and low-probability areas. In addition, suitability is explained by tree-level covariates. Spatial dependence, which is due to unobserved spatially structured covariates, is modelled through an unobserved Markov random field. Markov chain Monte Carlo method has been applied in Bayesian computation. The extensive spatial data …
Estimating completeness in cancer registries--comparing capture-recapture methods in a simulation study.
2008
Completeness of registration is one of the quality indicators usually reported by cancer registries. This allows researchers to assess how useful and representative the data is. Several methods have been suggested to estimate completeness. In this paper a multi-state model for the process of cancer diagnosis and treatment is presented. In principle, every contact with a doctor during diagnosis, treatment, and aftercare can give rise to a cancer registry notification with a certain probability. Therefore the states included in the model are "incident tumour" and "death" but also contacts with doctors such as consultation of a general practitioner or specialised doctor, diagnostic procedures,…
Efficient change point detection in genomic sequences of continuous measurements
2010
Abstract Motivation: Knowing the exact locations of multiple change points in genomic sequences serves several biological needs, for instance when data represent aCGH profiles and it is of interest to identify possibly damaged genes involved in cancer and other diseases. Only a few of the currently available methods deal explicitly with estimation of the number and location of change points, and moreover these methods may be somewhat vulnerable to deviations of model assumptions usually employed. Results: We present a computationally efficient method to obtain estimates of the number and location of the change points. The method is based on a simple transformation of data and it provides re…
Recent applications of point process methods in forestry statistics
2000
Forestry statistics is an important field of applied statistics with a long tradition. Many forestry problems can be solved by means of point processes or marked point processes. There, the "points" are tree locations and the "marks" are tree characteristics such as diameter at breast height or degree of damage by environmental factors. Point pro- cess characteristics are valuable tools for exploratory data analysis in forestry, for describing the variability of forest stands and for under- standing and quantifying ecological relationships. Models of point pro- cesses are also an important basis of modern single-tree modeling, that gives simulation tools for the investigation of forest stru…
Cytotoxic bufadienolides from the leaves of a medicinal plant Melianthus comosus collected in South Africa.
2020
Abstract From the leaves of South African medicinal plant Melianthus comosus, four previously undescribed bufadienolides, 16β-formyloxymelianthugenin (1), 2β-acetoxymelianthusigenin (2), 2β-hydroxy-3β,5β-di-O-acetylhellebrigenin (3), and 2β-acetoxy-5β-O-acetylhellebrigenin (4) were isolated together with two known bufadienolides. The structural elucidation of the compounds was based on 1D and 2D NMR spectroscopy, high-resolution mass spectrometry, and other spectroscopic methods. The relative configurations were determined by single-crystal X-ray crystallography analysis and NOESY correlations. The isolated compounds displayed strong cytotoxicity against MCF-7 breast cancer cells, sensitive…
New complex polycyclic compounds: Synthesis, antiproliferative activity and mechanism of action
2020
Abstract Polycyclic or O-glycoconiugate polycyclic compounds 1a-g were previously tested for their in vitro antiproliferative activity. In this series of compounds, activity increases as log P decreases. Specifically, compounds 1d and 1g showed lower log P values together with the best antiproliferative profiles. With the aim of extending our understanding of the structure–activity relationship (SAR) of this class of compounds, we prepared new polycyclic derivatives 2a-c, which bear on each of the two phenyl rings hydrophilic substituents (OH, SO2NH2 or NHCOCH3). These substituents are able to form hydrogen bonds and to decrease the partition coefficient value as compared with compound 1d. …
Naphthalene Derivatives from the Roots of Pentas parvifolia and Pentas bussei
2016
The phytochemical investigation of the CH2Cl2/MeOH (1:1) extract of the roots of Pentas parvifolia led to the isolation of three new naphthalenes, parvinaphthols A (1), B (2), and C (3), two known anthraquinones, and five known naphthalene derivatives. Similar investigation of the roots of Pentas bussei afforded a new polycyclic naphthalene, busseihydroquinone E (4), a new 2,2'-binaphthralenyl-1,1'-dione, busseihydroquinone F (5), and five known naphthalenes. All purified metabolites were characterized by NMR and MS data analyses, whereas the absolute configurations of 3 and 4 were determined by single-crystal X-ray diffraction studies. The E-geometry of compound 5 was supported by DFT-base…