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We introduce a new modelling for long-term survival models, assuming that the number of competing causes follows a mixture of Poisson and the Birnbaum-Saunders distribution. In this context, we present some statistical properties of our model and demonstrate that the promotion time model emerges as a limiting case. We delve into detailed discussions of specific models within this class. Notably, we examine the expected number of competing causes, which depends on covariates. This allows for direct modeling of the cure rate as a function of covariates. We present an Expectation-Maximization (EM) algorithm for parameter estimation, to discuss the estimation via maximum likelihood (ML) and provide insights into parameter inference for this model. Additionally, we outline sufficient conditions for ensuring the consistency and asymptotic normal distribution of ML estimators. To evaluate the performance of our estimation method, we conduct a Monte Carlo simulation to provide asymptotic properties and a power study of LR test by contrasting our methodology against the promotion time model. To demonstrate the practical applicability of our model, we apply it to a real medical dataset from a population-based study of incidence of breast cancer in São Paulo, Brazil. Our results illustrate that the proposed model can outperform traditional approaches in terms of model fitting, highlighting its potential utility in real-world scenarios.
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Biometria , Neoplasias da Mama , Modelos Estatísticos , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/terapia , Humanos , Biometria/métodos , Feminino , Método de Monte Carlo , Funções Verossimilhança , Análise de Sobrevida , AlgoritmosRESUMO
This paper introduces a new family of quantile regression models whose response variable follows a reparameterized Marshall-Olkin distribution indexed by quantile, scale, and asymmetry parameters. The family has arisen by applying the Marshall-Olkin approach to distributions belonging to the location-scale family. Models of higher flexibility and whose structure is similar to generalized linear models were generated by quantile reparameterization. The maximum likelihood (ML) method is presented for the estimation of the model parameters, and simulation studies evaluated the performance of the ML estimators. The advantages of the family are illustrated through an application to a set of nutritional data, whose results indicate it is a good alternative for modeling slightly asymmetric response variables with support on the real line.
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Cure rate models have been widely studied to analyze time-to-event data with a cured fraction of patients. In this type of model, the number of concurrent causes is assumed to be a random variable. However, in practice, it is natural to admit that the distribution of the number of competing causes is different from individual to individual. Our proposal is to assume that the number of competing causes belongs to a class of a finite mixture of competing causes distributions. We assume the number of malignant cells follow a mixture of two power series distributions and suppose that the time to the event of interest follows a Weibull distribution. We consider the proportion of the cured number of competing causes depending on covariates, allowing direct modeling of the cure rate. The proposed model includes several well-known models as special cases and defines many new special models. An expectation-maximization algorithm is proposed for parameter estimation, where the expectation step involves the computation of the expected number of concurrent causes for each individual. A Monte Carlo simulation is performed to assess the behavior of the estimation method. In order to show the potential for the practice of our model, we apply it to the real medical data set from a population-based study of incident cases of cutaneous melanoma diagnosed in the state of São Paulo, Brazil, illustrating that the model proposed can outperform traditional models in terms of model fitting.
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Melanoma , Neoplasias Cutâneas , Humanos , Modelos Estatísticos , Funções Verossimilhança , Análise de Sobrevida , Melanoma/diagnóstico , Brasil , Simulação por Computador , AlgoritmosRESUMO
The Multiple Comparison Procedures with Modeling Techniques (MCP-Mod) framework has been recently approved by the U.S. Food, Administration, and European Medicines Agency as fit-for-purpose for phase II studies. Nonetheless, this approach relies on the asymptotic properties of Maximum Likelihood (ML) estimators, which might not be reasonable for small sample sizes. In this paper, we derived improved ML estimators and correction for their covariance matrices in the censored Weibull regression model based on the corrective and preventive approaches. We performed two simulation studies to evaluate ML and improved ML estimators with their covariance matrices in (i) a regression framework (ii) the Multiple Comparison Procedures with Modeling Techniques framework. We have shown that improved ML estimators are less biased than ML estimators yielding Wald-type statistics that controls type I error without loss of power in both frameworks. Therefore, we recommend the use of improved ML estimators in the MCP-Mod approach to control type I error at nominal value for sample sizes ranging from 5 to 25 subjects per dose.
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Tamanho da Amostra , Humanos , Simulação por ComputadorRESUMO
Roux-en-Y gastric bypass (RYGB) is considered the gold standard procedure in patients with obesity and gastroesophageal reflux (GERD), but in patients with preoperative hiatal hernia (HH) or GERD, who are unfit for RYGB, there are no clear guidelines. Ligamentum teres cardiopexy (LTC) has been proposed as an effective alternative. The purpose of this study was to analyze medium-term results of LTC procedure associated with laparoscopic sleeve gastrectomy (LSG) in patients with GERD or HH, according to the absence of pathologic acid reflux in esophageal 24 h pH monitoring test, symptom release, or PPI reduction. Five patients underwent LSG-LTC between March 2018 and October 2019. In one patient, the effectiveness of LTC as an anti-reflux procedure could not be assessed because of conversion to RYGB was required. After a follow-up period of 30 [24-42] months and excessive BMI loss of 62.74 ± 18.18%, GERD recurrence was observed in 75% of patients. The study was discontinued due to unsatisfactory preliminary results with LTC. Our results suggest that LTC might not prevent GERD after LSG in patients with preoperative GERD or HH.
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Derivação Gástrica , Refluxo Gastroesofágico , Hérnia Hiatal , Laparoscopia , Obesidade Mórbida , Ligamentos Redondos , Humanos , Obesidade Mórbida/cirurgia , Refluxo Gastroesofágico/prevenção & controle , Refluxo Gastroesofágico/cirurgia , Refluxo Gastroesofágico/complicações , Hérnia Hiatal/complicações , Derivação Gástrica/métodos , Gastrectomia/métodos , Ligamentos Redondos/cirurgia , Laparoscopia/efeitos adversos , Estudos Retrospectivos , Resultado do TratamentoRESUMO
Over the last decades, the challenges in survival models have been changing considerably and full probabilistic modeling is crucial in many medical applications. Motivated from a new biological interpretation of cancer metastasis, we introduce a general method for obtaining more flexible cure rate models. The proposal model extended the promotion time cure rate model. Furthermore, it includes several well-known models as special cases and defines many new special models. We derive several properties of the hazard function for the proposed model and establish mathematical relationships with the promotion time cure rate model. We consider a frequentist approach to perform inferences, and the maximum likelihood method is employed to estimate the model parameters. Simulation studies are conducted to evaluate its performance with a discussion of the obtained results. A real dataset from population-based study of incident cases of melanoma diagnosed in the state of São Paulo, Brazil, is discussed in detail.
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Melanoma , Modelos Estatísticos , Humanos , Funções Verossimilhança , Análise de Sobrevida , Distribuição de Poisson , Brasil , Melanoma/terapiaRESUMO
Considering that the prevalence of overweight and obesity in Southeast of Spain is high, the aim of this work was to analyze the relation between the adherence to a personalized diet and the effectiveness of changes in the body composition in overweight and obese adults in this region. This quasi-experimental study presents the following selection criteria: attendance at the consultation between 2006 and 2012, subjects ≥ 19 years of age with overweight or obesity. In total, 591 overweight or obese individuals were involved in this study, attending 4091 clinic consultations in total. Most of the sample consisted of subjects who attended >3 consultations (>1.5 months), and were females aged 19-64 years who obtained clinically significant changes in fat mass (FM, ≥5%) and recommended changes in fat-free mass (FFM, ≥0%). Based on the results obtained and the experience gained from this research, the following recommendations are established: (i) record fat mass and fat-free mass index as a complement to body mass index; (ii) use FM and FFM to evaluate effectiveness of interventions with the aim of obtaining body composition changes; (iii) use personalized diet to achieve significant changes in FM and avoid non-recommended changes in FFM.
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In this article, we discuss an extension of the classical negative binomial cure rate model with piecewise exponential distribution of the time to event for concurrent causes, which enables the modeling of monotonic and non-monotonic hazard functions (ie, the shape of the hazard function is not assumed as in traditional parametric models). This approach produces a flexible cure rate model, depending on the choice of time partition. We discuss local influence on this negative binomial power piecewise exponential model. We report on Monte Carlo simulation studies and application of the model to real melanoma and leukemia datasets.
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Melanoma , Modelos Estatísticos , Simulação por Computador , Humanos , Melanoma/diagnóstico , Melanoma/terapia , Método de Monte Carlo , Análise de SobrevidaRESUMO
In this article, we introduce a long-term survival model in which the number of competing causes of the event of interest follows the zero-modified geometric (ZMG) distribution. Such distribution accommodates equidispersion, underdispersion, and overdispersion and captures deflation or inflation of zeros in the number of lesions or initiated cells after the treatment. The ZMG distribution is also an appropriate alternative for modeling clustered samples when the number of competing causes of the event of interest consists of two subpopulations, one containing only zeros (cure proportion), while in the other (noncure proportion) the number of competing causes of the event of interest follows a geometric distribution. The advantage of this assumption is that we can measure the cure proportion in the initiated cells. Furthermore, the proposed model can yield greater or lower cure proportion than that of the geometric distribution when modeling the number of competing causes. In this article, we present some statistical properties of the proposed model and use the maximum likelihood method to estimate the model parameters. We also conduct a Monte Carlo simulation study to evaluate the performance of the estimators. We present and discuss two applications using real-world medical data to assess the practical usefulness of the proposed model.
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Melanoma , Modelos Estatísticos , Humanos , Funções Verossimilhança , Melanoma/tratamento farmacológico , Método de Monte Carlo , Análise de SobrevidaRESUMO
Background and purpose: SWI MRI, a T2*-dominant MRI sequence with T1 shine-through effect, uses intrinsic structural susceptibility to create enhancement among brain structures. We evaluated whether gadolinium-enhanced SWI (SWI-Gd) improves brain metastasis detection in combination with other MRI sequences. Materials and methods: MRI images of 24 patients (46 studies) were prospectively acquired using a 1.5-T scanner. T1-weighted, unenhanced SWI (SWI-U) and SWI-Gd were evaluated blindly to clinical features by two board-certified radiologists. Results: SWI-Gd revealed more significant metastatic lesions than either T1-Gd or SWI-U (p = 0.0004 for either comparator sequence). Moreover, SWI-Gd revealed more lesions only for those patients with ≤5 lesions on T1-Gd (n = 30 studies from 16 patients; p = 0.046). Performing SWI-Gd added <5 min of scanning time with no further additional risk. Conclusions: Our findings suggest that, when added to T1-Gd and other common sequences, SWI-Gd may improve the diagnostic yield of brain metastases with only a few extra minutes of scanning time and no further risk than that of a regular gadolinium-enhanced MRI.
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In this paper, we propose a generalization of the power series cure rate model for the number of competing causes related to the occurrence of the event of interest. The model includes distributions not yet used in the cure rate models context, such as the Borel, Haight and Restricted Generalized Poisson distributions. The model is conveniently parameterized in terms of the cure rate. Maximum likelihood estimation based on the Expectation Maximization algorithm is discussed. A simulation study designed to assess some properties of the estimators is carried out, showing the good performance of the proposed estimation procedure in finite samples. Finally, an application to a bone marrow transplant data set is presented.
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Algoritmos , Modelos Estatísticos , Funções Verossimilhança , Distribuição de Poisson , Análise de SobrevidaRESUMO
In this paper, we propose a simple parametric modal linear regression model where the response variable is gamma distributed using a new parameterization of this distribution that is indexed by mode and precision parameters, that is, in this new regression model, the modal and precision responses are related to a linear predictor through a link function and the linear predictor involves covariates and unknown regression parameters. The main advantage of our new parameterization is the straightforward interpretation of the regression coefficients in terms of the mode of the positive response variable, as is usual in the context of generalized linear models, and direct inference in parametric mode regression based on the likelihood paradigm. Furthermore, we discuss residuals and influence diagnostic tools. A Monte Carlo experiment is conducted to evaluate the performances of these estimators in finite samples with a discussion of the results. Finally, we illustrate the usefulness of the new model by two applications, to biology and demography.
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Biometria/métodos , Diagnóstico , Modelos LinearesRESUMO
This paper focuses on studying a truncated positive version of the power-normal (PN) model considered in Durrans (1992). The truncation point is considered to be zero so that the resulting model is an extension of the half normal distribution. Some probabilistic properties are studied for the proposed model along with maximum likelihood and moments estimation. The model is fitted to two real datasets and compared with alternative models for positive data. Results indicate good performance of the proposed model.
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Copula models have become increasingly popular for modelling the dependence structure in multivariate survival data. The two-parameter Archimedean family of Power Variance Function (PVF) copulas includes the Clayton, Positive Stable (Gumbel) and Inverse Gaussian copulas as special or limiting cases, thus offers a unified approach to fitting these important copulas. Two-stage frequentist procedures for estimating the marginal distributions and the PVF copula have been suggested by Andersen (Lifetime Data Anal 11:333-350, 2005), Massonnet et al. (J Stat Plann Inference 139(11):3865-3877, 2009) and Prenen et al. (J R Stat Soc Ser B 79(2):483-505, 2017) which first estimate the marginal distributions and conditional on these in a second step to estimate the PVF copula parameters. Here we explore an one-stage Bayesian approach that simultaneously estimates the marginal and the PVF copula parameters. For the marginal distributions, we consider both parametric as well as semiparametric models. We propose a new method to simulate uniform pairs with PVF dependence structure based on conditional sampling for copulas and on numerical approximation to solve a target equation. In a simulation study, small sample properties of the Bayesian estimators are explored. We illustrate the usefulness of the methodology using data on times to appendectomy for adult twins in the Australian NH&MRC Twin registry. Parameters of the marginal distributions and the PVF copula are simultaneously estimated in a parametric as well as a semiparametric approach where the marginal distributions are modelled using Weibull and piecewise exponential distributions, respectively.
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Teorema de Bayes , Análise de Sobrevida , Algoritmos , Austrália , Interpretação Estatística de Dados , Modelos Estatísticos , Análise MultivariadaRESUMO
Reactive oxygen species (ROS) production is one of the main mechanisms used to kill microbes during innate immune response. D-lactic acid, which is augmented during acute ruminal acidosis, reduces platelet activating factor (PAF)-induced ROS production and L-selectin shedding in bovine neutrophils in vitro. This study was conducted to investigate whether acute ruminal acidosis induced by acute oligofructose overload in heifers interferes with ROS production and L-selectin shedding in blood neutrophils. Blood neutrophils and plasma were obtained by jugular venipuncture, while ruminal samples were collected using rumenocentesis. Lactic acid from plasma and ruminal samples was measured by HPLC. PAF-induced ROS production and L-selectin shedding were measured in vitro in bovine neutrophils by a luminol chemiluminescence assay and flow cytometry, respectively. A significant increase in ruminal and plasma lactic acid was recorded in these animals. Specifically, a decrease in PAF-induced ROS production was observed 8 h after oligofructose overload, and this was sustained until 48 h post oligofructose overload. A reduction in PAF-induced L-selectin shedding was observed at 16 h and 32 h post oligofructose overload. Overall, the results indicated that neutrophil PAF responses were altered in heifers with ruminal acidosis, suggesting a potential dysfunction of the innate immune response.
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Acidose/veterinária , Doenças dos Bovinos/imunologia , Imunidade Inata , Neutrófilos/efeitos dos fármacos , Oligossacarídeos/farmacologia , Fator de Ativação de Plaquetas/farmacologia , Acidose/induzido quimicamente , Acidose/imunologia , Animais , Sangue , Bovinos , Doenças dos Bovinos/induzido quimicamente , Feminino , Citometria de Fluxo/veterinária , Selectina L/metabolismo , Oligossacarídeos/toxicidade , Espécies Reativas de Oxigênio/metabolismo , RúmenRESUMO
CdTe nanoparticle-polymer composite films were deposited conformally using a layer-by-layer (LbL) process onto planar or ZnO nanorod-coated substrates. Films were annealed between 150-450 degrees C. Under air this led to oxidation of the nanoparticles while under vacuum their composition was retained. Annealing at 450 degrees C led to complete removal of the polymer with a loss of quantum confinement as shown by UV-vis spectroscopy. Annealing at 350 degrees C gave partial removal of the polymer and retained quantum confinement. Such annealed nanoparticle composite systems may have application in photovoltaics.
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ZnO nanorods are doped with Sb during the aqueous chemical synthesis by addition of Sb acetate dissolved in ethylene glycol.
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Controlled release solid oral dosage forms have been widely used for decades, enabling drugs to be administered more comfortably while at the same time providing a sustained and reproducible method of release. (Meth)acrylate copolymers are one of the options available when considering a sustained release solid form. Due to their different functionalities it is possible to achieve various different release profiles. The electrical character of these copolymers and their pH-dependent solubility can result in new and modified patterns when these polymers are combined. This review sheds light on various studies involving combinations of (meth)acrylate copolymers for use in multi-unit systems and matrix tablets, and also on several analytical methods that help to identify possible interactions between these polymers.
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Portadores de Fármacos/química , Ácidos Polimetacrílicos/química , Química Farmacêutica/métodos , Preparações de Ação Retardada , Concentração de Íons de Hidrogênio , Solubilidade , ComprimidosRESUMO
Colloidal semiconductor nanocrystals are promising luminophores for creating a new generation of electroluminescence devices. Research on semiconductor nanocrystal based light-emitting diodes (LEDs) has made remarkable advances in just one decade: the external quantum efficiency has improved by over two orders of magnitude and highly saturated color emission is now the norm. Although the device efficiencies are still more than an order of magnitude lower than those of the purely organic LEDs there are potential advantages associated with nanocrystal-based devices, such as a spectrally pure emission color, which will certainly merit future research. Further developments of nanocrystal-based LEDs will be improving material stability, understanding and controlling chemical and physical phenomena at the interfaces, and optimizing charge injection and charge transport.