An introduction to survival analysis: Statistical methods for analysis of clinical trial data.

The randomized controlled clinical trial (RCT) is a prospective study using random assignment of subjects to treatment groups to compare the effect and value of a therapeutic intervention against a control. The RCT is the most definitive clinical research tool for evaluating the efficacy of a new therapy in human subjects. Often the outcome of interest in an RCT is the length of time until an event occurs after treatment or intervention. In this article we introduce statistical methods for evaluating differences in the patterns of time to response between two groups of subjects to determine whether one therapy is better than another. The collection of methods for analyzing such data, known as survival data, is called survival analysis. Using data from a hypothetical clinical trial for the prevention of the recurrence of depression, we illustrate two elementary methods for analyzing survival data. We also discuss generalizations of these methods to incorporate covariates and conclude with a general discussion of clinical trials of psychiatric therapies. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Statistical analysis for dependent dichotomous data

The analysis of means for attributes data (ANOMAD) is used--when normal approximation applies to binomial distribution--by extending the analysis of means (ANOM) introduced by Ott and Schilling. ANOMAD compares the individual proportions or dependent percentages or set of frequencies of subjects responding to different stimuli, with the grand average of the proportions. It is interesting to see if all temporal values of some risk factors in cardiovascular diseases (CD)--acting as "stimuli"--can provide the same effect on a group of subjects by emphasizing the most important ones.     

Statistical methods in factor analysis.

"A recent investigation of the efficiency of the centroid method of analysis is noted, and a recommendation is made regarding a valid test of the significance of residual matrices when this method is employed. The 'simple structure' concept is criticized and an alternative approach in the search for psychologically meaningful factors is recommended." 44 refs. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The contribution of image cytometry and artificial intelligence-related methods of numerical data analysis for adipose tumor histopathologic classification

Thirty-five lipomatous tumors were quantitatively described using 47 variables generated by means of computer-assisted microscope analysis. Of these 47 quantitative variables, 27 were computed on Feulgen-stained specimens (25 on cytologic and 2 on histologic samples) and, of the remaining 20, 8 related to vimentin and S-100 protein immunostaining patterns and the other 12 to the glycohistochemical staining patterns of peanut agglutinin, succinylated wheat germ agglutinin, and concavalin A agglutinin. The 35 lipomatous tumors included 6 atypical lipomas and 8 well differentiated, 5 dedifferentiated, 6 myxoid, and 10 pleomorphic liposarcomas. The actual diagnostic value contributed by each of the 47 variables with respect to the 5 lipomatous tumor groups was determined by means of the decision tree technique, an artificial intelligence-related algorithm that forms part of the supervised learning algorithms. Of the 47 quantitative variables, the decision tree technique retained 8: i.e., 2 tissue architecture-, 2 DNA ploidy level-, 2 morphonuclear-, 1 lectin histochemical-, and 1 vimentin immunostain-related variables. The decision tree technique made use of these 8 variables to set up logical rules that make it possible to identify atypical lipomas from well differentiated liposarcomas, on the one hand, and dedifferentiated liposarcomas from those that are well differentiated and pleomorphic, on the other. Thus, the combination of an artificial intelligence algorithm analyzing quantitative variables generated by means of the computer-assisted microscope analysis of cytologic and histologic samples from lipomatous tumors can be considered an expert system contributing significant diagnostic information to conventional diagnosis.     

Statistical analysis of repeated measures data using SAS procedures

Mixed linear models were developed by animal breeders to evaluate genetic potential of bulls. Application of mixed models has recently spread to all areas of research, spurred by availability of advanced computer software. Previously, mixed model analyses were implemented by adapting fixed-effect methods to models with random effects. This imposed limitations on applicability because the covariance structure was not modeled. This is the case with PROC GLM in the SAS System. Recent versions of the SAS System include PROC MIXED. This procedure implements random effects in the statistical model and permits modeling the covariance structure of the data. Thereby, PROC MIXED can compute efficient estimates of fixed effects and valid standard errors of the estimates. Modeling the covariance structure is especially important for analysis of repeated measures data because measurements taken close in time are potentially more highly correlated than those taken far apart in time.     

Statistical methods for dependent competing risks

In this study, the kinetics of glomerular endothelial cells during the repair process following glomerular injury was investigated in a model of mesangial proliferative glomerulonephritis induced by Habu-snake venom (HSV) in rats. Intravenous injection of HSV led to a cystic ballooning type lesion at day 1. Subsequently a marked segmental proliferative lesion was observed in the cystic areas at day 5. Thereafter cellularity decreased and reconstruction of the glomerular tuft was gradually observed with time. The histological structure of the glomeruli had almost returned to normal 21 days following HSV injection. After prominent depletion at day 1, the number of endothelial cells increased rapidly and reached a plateau at day 7, not significantly different from that of the control group. Morphologically endothelial cell elongation from the vascular pole into the cystic lesion was seen together with premature capillary formation in the proliferative lesion. Accompanying the reduction of mesangial expansion, the endothelial cells gradually formed definite capillary lumens. We conclude that the mesangial proliferative glomerulonephritis induced by HSV recovers to its original structural state and that the migration and proliferation of endothelial cells with accompanying capillary formation are essential for the repair process, in addition to mesangial cell proliferation.     

关于生存分析中的统计方法及其应用

设计了4组实验,通过对老鼠注射某种药物,观测老鼠的生存时间,收集科学数据,然后利用对数(log-rank)检验理论,对观测到的数据进行生存分析,最终确定药物的疗效.     

Statistical models for PET and SPECT data

This article outlines the statistical developments that have taken place in emission tomography during the past decade or so. We discuss the statistical aspects of the modelling of the projection data and define the additive Poisson regression model. This leads to the use of the method of maximum likelihood as a means of estimating the underlying isotope concentration within a given region of a patient's body, and to the use of the EM algorithm to compute the reconstruction. The need for the regulation of the maximum likelihood solution is tackled using Bayesian techniques. A number of algorithms for the computation of regularized solutions are outlined. The issue of parameter estimation is discussed and some open issues are mentioned.     

Statistical methods for analyses of incomplete clinical service records: Concurrent use of longitudinal and cross-sectional data.

Statistical procedures that have become routine in other social sciences were used to analyze data from clinical service records. Despite the absence of control groups, nonrandom assignment of clients to treatment conditions, and incomplete records, effective analyses of psychotherapeutic processes were possible. Multivariate regression models, with variables that were transformed to significantly improve skewness and regression linearity, were controlled for heteroskedasticity and for end-point censoring of dependent variables. They were also used to measure the effects of a categorical variable (gender) and a scalable variable (intake distress) on a reactive outcome measure (of acute distress) and on an unreactive one (of long-term satisfaction). Graphical methods for summarizing large data sets helped identify intake variables that could control for attrition-related sampling biases. These longitudinal covariates and corrections to adjust degrees of freedom for cases with repeated measures were then used to construct statistical models that were equivalents of pure cross-sectional designs. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Statistical methods for the Ames Salmonella assay: a review

Exposure of Clone 9 cells, a rat liver cell line, to hydrogen peroxide (H2O2) resulted in a striking and rapid stimulation of glucose transport (8- to 10-fold in 1 h). A comparable response was found in 3T3-L1 preadipocytes, C2C12 myoblasts, and NIH 3T3 fibroblasts, which, similar to Clone 9 cells, express only the Glut 1 glucose transporter isoform. The enhancement of glucose transport in Clone 9 cells in response to H2O2 was significantly attenuated by genistein and the phospholipase C (PLC) inhibitor, U73122. Exposure to H2O2 resulted in a rise in cell sn-1,2-diacylglycerol content, and the rise was significantly inhibited by U73122. Moreover, the H2O2-induced stimulation of glucose transport was significantly blocked by thapsigargin. Neither staurosporine nor a 24-h preincubation in the presence of phorbol-12-myristate-13-acetate (TPA) affected the stimulatory effect of hydrogen peroxide on glucose transport. The activity of big mitogen-activated kinase (BMK1) and of stress-activated protein kinase (SAPK), both members of mitogen-activated protein kinases, were enhanced in response to exposure to H2O2; however, neither protein kinase appeared to be linked to the enhancement of glucose transport by H2O2. It is concluded that the stimulation of glucose transport in response to H2O2 is independent of changes in PKC, BMK1, and SAPK activity, and is mediated, at least in part, through H2O2-induced stimulation of protein tyrosine kinase and PLC pathways.     

Parametric analysis of fMRI data using linear systems methods

In Colombia, violence seems uncontrollable. Along with massacres and group killings of astonishing cruelty, there are also kidnappings and disappearances, abuse of children and the elderly, and rape of young adolescents. Every day, without respite, Columbians are witnesses or victims of street crimes as well as racial, sexual, and socioeconomic discrimination. Unwillingly, they become agents of aggression in public transport, at home, at school, and at work. Colombia has the highest rates of mortality from homicide in the world. Apart from the enormous institutional burden that violence imposes on the health services and forensic medicine, it now constitutes the principal public health problem in the country. To confront it, the health sector must develop policies and finance actions, develop innovative ways to train personnel, implement public education processes, and devote more effort and greater creativity to research, which up to now has provided some, but not enough, important answers. Violence, which is the substitution of force for any type of dialogue, must be considered within the context of life and health. This it not merely an attempt to rationalize violence, much less to substitute words or reflection for action, but rather an attempt to understand it in depth in order to search for alternatives. With that goal, this article analyzes the subject of violence in Colombia, principally from the perspective of its effect on the health of the citizens and its implications for the health sector. The author fully recognizes the subjectivity and limitations of the views he expresses herein.     

Statistical analysis of data derived from clinical variables of plaque and gingivitis

BACKGROUND: Historical cohort studies in England have found that impaired fetal growth and lower respiratory tract infections in early childhood are associated with lower levels of lung function in late adult life. These relations are investigated in a similar study in Scotland. METHODS: In 1985-86 a follow up study was carried out of 1070 children who had been born in St Andrew's from 1921 to 1935 and followed from birth to 14 years of age by the Mackenzie Institute for Medical Research. Recorded information included birth weight and respiratory illnesses. The lung function of 239 of these individuals was measured. RESULTS: There was no association between birth weight and lung function. Pneumonia before two years of age was associated with a difference in mean forced expiratory volume in one second (FEV1) of -0.39 litres (95% confidence interval (CI) -0.67, -0.11; p = 0.007) and in mean forced vital capacity (FVC) of -0.60 litres (95% CI -0.92, -0.28; p < 0.001), after controlling for age, sex, height, smoking, type of spirometer, and other illnesses before two years. Similar reductions were seen in men and women. Bronchitis before two years was associated with smaller deficits in FEV1 and FVC. Asthma or wheeze at two years and older and cough after five years were also associated with a reduction in FEV1. CONCLUSIONS: The relation between impaired fetal growth and lower lung function in late adult life seen in previous studies was not confirmed in this cohort. The deficits in FEV1 and FVC associated with pneumonia and bronchitis in the first two years of life are consistent with a causal relation.     

四分位法和迭代法对数据分散的能力验证检测数据统计分析结果的比较

能力验证是指利用实验室间比对,按照预先制定的准则评价参加者能力的活动。四分位法和迭代法均是分析能力验证数据的稳健统计分析方法,可以用来计算数据目标标准偏差,评价实验室上报数据是否合格。通过分析多项检测能力验证数据,比较了两种稳健统计分析方法的计算结果。分析数据的结果表明,当上报数据的标准化四分位距与基于经验模型的再现性标准差之比(H值)大于2或稳健变异系数CV大于0.05时,各实验室间检测能力相差较大,能力验证数据分布较分散,迭代计算次数大于1次,标准化四分位距与迭代法计算的稳健标准差比值大于1,四分位法放宽了能力验证的评价标准。     

Statistical methods for detecting activated regions in functional MRI of the brain

Two statistical tests for detecting activated pixels in functional MRI (fMRI) data are presented. The first test (t-test) is the optimal solution to the problem of detecting a known activation signal in Gaussian white noise. The results of this test are shown to be equivalent to the cross-correlation method that is widely used for activation detection in fMRI. The second test (F test) is the optimal solution when the measured data are modeled to consist of an unknown activation signal that lies in a known lower dimensional subspace of the measurement space with added Gaussian white noise. A model for the signal subspace based on a truncated trigonometric Fourier series is proposed for periodic activation-baseline imaging paradigms. The advantage of the second method is that it does not assume any information about the shape or delay of the activation signal, except that it is periodic with the same period as the activation-baseline pattern. The two models are applied to experimental echo-planar fMRI data sets and the results are compared.     

Statistical methods in computational anatomy

This paper reviews recent developments by the Washington/Brown groups for the study of anatomical shape in the emerging new discipline of computational anatomy. Parametric representations of anatomical variation for computational anatomy are reviewed, restricted to the assumption of small deformations. The generation of covariance operators for probabilistic measures of anatomical variation on coordinatized submanifolds is formulated as an empirical procedure. Populations of brains are mapped to common coordinate systems, from which template coordinate systems are constructed which are closest to the population of anatomies in a minimum distance sense. Variation of several one-, two- and three-dimensional manifolds, i.e. sulci, surfaces and brain volumes are examined via Gaussian measures with mean and covariances estimated directly from maps of templates to targets. Methods are presented for estimating the covariances of vector fields from a family of empirically generated maps, posed as generalized spectrum estimation indexed over the submanifolds. Covariance estimation is made parametric, analogous to autoregressive modelling, by introducing small deformation linear operators for constraining the spectrum of the fields.     

Statistical methods in psychiatric genetics

Most psychiatric disorders are determined by the complex interplay between genetic and environmental factors. Aetiological research into these complex disorders raises many different questions which require a variety of statistical methods. These include survival analysis for the estimation of morbid risk, structural equation models for the partitioning of phenotypic variances and covariances into genetic and other components, complex segregation analysis to detect loci of major effect, and linkage and association analysis for the localisation and identification of susceptibility genes. Future developments in psychiatric genetics will involve the integration of genetic and epidemiological statistics in order to study the interplay between genetic and environmental factors in the complex pathways which lead to mental disorders.