A Latent-Variable Causal Model of Faculty Reputational Ratings.

ERIC Educational Resources Information Center

King, Suzanne; Wolfle, Lee M.

A reanalysis was conducted of Saunier's research (1985) on sources of variation in the National Research Council (NRC) reputational ratings of university faculty. Saunier conducted a stepwise regression analysis using 12 predictor variables. Due to problems with multicollinearity and because of the atheoretical nature of stepwise regression,…

A stepwise regression tree for nonlinear approximation: applications to estimating subpixel land cover

USGS Publications Warehouse

Huang, C.; Townshend, J.R.G.

2003-01-01

A stepwise regression tree (SRT) algorithm was developed for approximating complex nonlinear relationships. Based on the regression tree of Breiman et al . (BRT) and a stepwise linear regression (SLR) method, this algorithm represents an improvement over SLR in that it can approximate nonlinear relationships and over BRT in that it gives more realistic predictions. The applicability of this method to estimating subpixel forest was demonstrated using three test data sets, on all of which it gave more accurate predictions than SLR and BRT. SRT also generated more compact trees and performed better than or at least as well as BRT at all 10 equal forest proportion interval ranging from 0 to 100%. This method is appealing to estimating subpixel land cover over large areas.

Repetition of attempted suicide among teenagers in Europe: frequency, timing and risk factors.

PubMed

Hultén, A; Jiang, G X; Wasserman, D; Hawton, K; Hjelmeland, H; De Leo, D; Ostamo, A; Salander-Renberg, E; Schmidtke, A

2001-09-01

Adolescents in many countries show high rates of suicide attempts and repetitions of attempts as a common feature. Attempted suicide is the best predictor of future suicide. Repetition of attempts further increases the risk of suicide. The present study sought to identify patterns and risk factors for repetition of attempts in older teenagers. Data were collected by uniform procedures in a longitudinal follow-up study in seven European centres participating in the WHO/EURO Multicentre Study on Suicidal Behaviour. Information on attempted suicide in the 15-19-year age group during the period 1989-1995 was analysed. A total of 1,720 attempts by 1,264 individuals over a mean follow-up period of 204 weeks (SD 108.9) were recorded. When life-table analysis was performed, 24% of the individuals who had previously attempted suicide made another attempt within one year after the index attempt, compared with 6.8% of the "first-evers", with no major gender difference. Cox regression analysis revealed that previous attempted suicide (OR 3.3, 95% CI 2.4-4.4) and use of "hard" methods (OR 1.5, 95% CI 1.1-2.1) were both significantly associated with repetition of attempted suicide. Stepwise Cox regression analysis showed that a history of previous attempted suicide was the most important independent predictor of repetition (OR 3.2, 95% CI 2.4-4.4). For young suicide attempters, follow-up and adequate aftercare are very important if repetition and risk of suicide are to be reduced. This applies particularly to those who have already made more than one attempt.

Ethnic differences in colon cancer care in the Netherlands: a nationwide registry-based study.

PubMed

Lamkaddem, M; Elferink, M A G; Seeleman, M C; Dekker, E; Punt, C J A; Visser, O; Essink-Bot, M L

2017-05-04

Ethnic differences in colon cancer (CC) care were shown in the United States, but results are not directly applicable to European countries due to fundamental healthcare system differences. This is the first study addressing ethnic differences in treatment and survival for CC in the Netherlands. Data of 101,882 patients diagnosed with CC in 1996-2011 were selected from the Netherlands Cancer Registry and linked to databases from Statistics Netherlands. Ethnic differences in lymph node (LN) evaluation, anastomotic leakage and adjuvant chemotherapy were analysed using stepwise logistic regression models. Stepwise Cox regression was used to examine the influence of ethnic differences in adjuvant chemotherapy on 5-year all-cause and colorectal cancer-specific survival. Adequate LN evaluation was significantly more likely for patients from 'other Western' countries than for the Dutch (OR 1.09; 95% CI 1.01-1.16). 'Other Western' patients had a significantly higher risk of anastomotic leakage after resection (OR 1.24; 95% CI 1.05-1.47). Patients of Moroccan origin were significantly less likely to receive adjuvant chemotherapy (OR 0.27; 95% CI 0.13-0.59). Ethnic differences were not fully explained by differences in socioeconomic and hospital-related characteristics. The higher 5-year all-cause mortality of Moroccan patients (HR 1.64; 95% CI 1.03-2.61) was statistically explained by differences in adjuvant chemotherapy receipt. These results suggest the presence of ethnic inequalities in CC care in the Netherlands. We recommend further analysis of the role of comorbidity, communication in patient-provider interaction and patients' health literacy when looking at ethnic differences in treatment for CC.

Variable selection with stepwise and best subset approaches

PubMed Central

2016-01-01

While purposeful selection is performed partly by software and partly by hand, the stepwise and best subset approaches are automatically performed by software. Two R functions stepAIC() and bestglm() are well designed for stepwise and best subset regression, respectively. The stepAIC() function begins with a full or null model, and methods for stepwise regression can be specified in the direction argument with character values “forward”, “backward” and “both”. The bestglm() function begins with a data frame containing explanatory variables and response variables. The response variable should be in the last column. Varieties of goodness-of-fit criteria can be specified in the IC argument. The Bayesian information criterion (BIC) usually results in more parsimonious model than the Akaike information criterion. PMID:27162786

Improved model of the retardance in citric acid coated ferrofluids using stepwise regression

NASA Astrophysics Data System (ADS)

Lin, J. F.; Qiu, X. R.

2017-06-01

Citric acid (CA) coated Fe3O4 ferrofluids (FFs) have been conducted for biomedical application. The magneto-optical retardance of CA coated FFs was measured by a Stokes polarimeter. Optimization and multiple regression of retardance in FFs were executed by Taguchi method and Microsoft Excel previously, and the F value of regression model was large enough. However, the model executed by Excel was not systematic. Instead we adopted the stepwise regression to model the retardance of CA coated FFs. From the results of stepwise regression by MATLAB, the developed model had highly predictable ability owing to F of 2.55897e+7 and correlation coefficient of one. The average absolute error of predicted retardances to measured retardances was just 0.0044%. Using the genetic algorithm (GA) in MATLAB, the optimized parametric combination was determined as [4.709 0.12 39.998 70.006] corresponding to the pH of suspension, molar ratio of CA to Fe3O4, CA volume, and coating temperature. The maximum retardance was found as 31.712°, close to that obtained by evolutionary solver in Excel and a relative error of -0.013%. Above all, the stepwise regression method was successfully used to model the retardance of CA coated FFs, and the maximum global retardance was determined by the use of GA.

A method for the selection of a functional form for a thermodynamic equation of state using weighted linear least squares stepwise regression

NASA Technical Reports Server (NTRS)

Jacobsen, R. T.; Stewart, R. B.; Crain, R. W., Jr.; Rose, G. L.; Myers, A. F.

1976-01-01

A method was developed for establishing a rational choice of the terms to be included in an equation of state with a large number of adjustable coefficients. The methods presented were developed for use in the determination of an equation of state for oxygen and nitrogen. However, a general application of the methods is possible in studies involving the determination of an optimum polynomial equation for fitting a large number of data points. The data considered in the least squares problem are experimental thermodynamic pressure-density-temperature data. Attention is given to a description of stepwise multiple regression and the use of stepwise regression in the determination of an equation of state for oxygen and nitrogen.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging as a Predictor of Outcome in Head-and-Neck Squamous Cell Carcinoma Patients With Nodal Metastases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shukla-Dave, Amita, E-mail: davea@mskcc.org; Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY; Lee, Nancy Y.

2012-04-01

Purpose: Dynamic contrast-enhanced MRI (DCE-MRI) can provide information regarding tumor perfusion and permeability and has shown prognostic value in certain tumors types. The goal of this study was to assess the prognostic value of pretreatment DCE-MRI in head and neck squamous cell carcinoma (HNSCC) patients with nodal disease undergoing chemoradiation therapy or surgery. Methods and Materials: Seventy-four patients with histologically proven squamous cell carcinoma and neck nodal metastases were eligible for the study. Pretreatment DCE-MRI was performed on a 1.5T MRI. Clinical follow-up was a minimum of 12 months. DCE-MRI data were analyzed using the Tofts model. DCE-MRI parameters weremore » related to treatment outcome (progression-free survival [PFS] and overall survival [OS]). Patients were grouped as no evidence of disease (NED), alive with disease (AWD), dead with disease (DOD), or dead of other causes (DOC). Prognostic significance was assessed using the log-rank test for single variables and Cox proportional hazards regression for combinations of variables. Results: At last clinical follow-up, for Stage III, all 12 patients were NED. For Stage IV, 43 patients were NED, 4 were AWD, 11 were DOD, and 4 were DOC. K{sup trans} is volume transfer constant. In a stepwise Cox regression, skewness of K{sup trans} (volume transfer constant) was the strongest predictor for Stage IV patients (PFS and OS: p <0.001). Conclusion: Our study shows that skewness of K{sup trans} was the strongest predictor of PFS and OS in Stage IV HNSCC patients with nodal disease. This study suggests an important role for pretreatment DCE-MRI parameter K{sup trans} as a predictor of outcome in these patients.« less

Severe chronic heart failure in patients considered for heart transplantation in Poland.

PubMed

Korewicki, Jerzy; Leszek, Przemysław; Zieliński, Tomasz; Rywik, Tomasz; Piotrowski, Walerian; Kurjata, Paweł; Kozar-Kamińska, Katarzyna; Kodziszewska, Katarzyna

2012-01-01

Based on the results of clinical trials, the prognosis for patients with severe heart failure (HF) has improved over the last 20 years. However, clinical trials do not reflect 'real life' due to patient selection. Thus, the aim of the POLKARD-HF registry was the analysis of survival of patients with refractory HF referred for orthotopic heart transplantation (OHT). Between 1 November 2003 and 31 October 2007, 983 patients with severe HF, referred for OHT in Poland, were included into the registry. All patients underwent routine clinical and hemodynamic evaluation, with NT-proBNP and hsCRP assessment. Death or an emergency OHT were assumed as the endpoints. The average observation period was 601 days. Kaplan-Meier curves with log-rank and univariate together with multifactor Cox regression model the stepwise variable selection method were used to determine the predictive value of analyzed variables. Among the 983 patients, the probability of surviving for one year was approximately 80%, for two years 70%, and for three years 67%. Etiology of the HF did not significantly influence the prognosis. The patients in NYHA class IV had a three-fold higher risk of death or emergency OHT. The univariate/multifactor Cox regression analysis revealed that NYHA IV class (HR 2.578, p < 0.0001), HFSS score (HR 2.572, p < 0.0001) and NT-proBNP plasma level (HR 1.600, p = 0.0200), proved to influence survival without death or emergency OHT. Despite optimal treatment, the prognosis for patients with refractory HF is still not good. NYHA class IV, NT-proBNP and HFSS score can help define the highest risk group. The results are consistent with the prognosis of patients enrolled into the randomized trials.

Predicting the duration of sickness absence for patients with common mental disorders in occupational health care.

PubMed

Nieuwenhuijsen, Karen; Verbeek, Jos H A M; de Boer, Angela G E M; Blonk, Roland W B; van Dijk, Frank J H

2006-02-01

This study attempted to determine the factors that best predict the duration of absence from work among employees with common mental disorders. A cohort of 188 employees, of whom 102 were teachers, on sick leave with common mental disorders was followed for 1 year. Only information potentially available to the occupational physician during a first consultation was included in the predictive model. The predictive power of the variables was tested using Cox's regression analysis with a stepwise backward selection procedure. The hazard ratios (HR) from the final model were used to deduce a simple prediction rule. The resulting prognostic scores were then used to predict the probability of not returning to work after 3, 6, and 12 months. Calculating the area under the curve from the ROC (receiver operating characteristic) curve tested the discriminative ability of the prediction rule. The final Cox's regression model produced the following four predictors of a longer time until return to work: age older than 50 years [HR 0.5, 95% confidence interval (95% CI) 0.3-0.8], expectation of duration absence longer than 3 months (HR 0.5, 95% CI 0.3-0.8), higher educational level (HR 0.5, 95% CI 0.3-0.8), and diagnosis depression or anxiety disorder (HR 0.7, 95% CI 0.4-0.9). The resulting prognostic score yielded areas under the curves ranging from 0.68 to 0.73, which represent acceptable discrimination of the rule. A prediction rule based on four simple variables can be used by occupational physicians to identify unfavorable cases and to predict the duration of sickness absence.

Risk stratification personalised model for prediction of life-threatening ventricular tachyarrhythmias in patients with chronic heart failure.

PubMed

Frolov, Alexander Vladimirovich; Vaikhanskaya, Tatjana Gennadjevna; Melnikova, Olga Petrovna; Vorobiev, Anatoly Pavlovich; Guel, Ludmila Michajlovna

2017-01-01

The development of prognostic factors of life-threatening ventricular tachyarrhythmias (VTA) and sudden cardiac death (SCD) continues to maintain its priority and relevance in cardiology. The development of a method of personalised prognosis based on multifactorial analysis of the risk factors associated with life-threatening heart rhythm disturbances is considered a key research and clinical task. To design a prognostic and mathematical model to define personalised risk for life-threatening VTA in patients with chronic heart failure (CHF). The study included 240 patients with CHF (mean-age of 50.5 ± 12.1 years; left ventricular ejection fraction 32.8 ± 10.9%; follow-up period 36.8 ± 5.7 months). The participants received basic therapy for heart failure. The elec-trocardiogram (ECG) markers of myocardial electrical instability were assessed including microvolt T-wave alternans, heart rate turbulence, heart rate deceleration, and QT dispersion. Additionally, echocardiography and Holter monitoring (HM) were performed. The cardiovascular events were considered as primary endpoints, including SCD, paroxysmal ventricular tachycardia/ventricular fibrillation (VT/VF) based on HM-ECG data, and data obtained from implantable device interrogation (CRT-D, ICD) as well as appropriated shocks. During the follow-up period, 66 (27.5%) subjects with CHF showed adverse arrhythmic events, including nine SCD events and 57 VTAs. Data from a stepwise discriminant analysis of cumulative ECG-markers of myocardial electrical instability were used to make a mathematical model of preliminary VTA risk stratification. Uni- and multivariate Cox logistic regression analysis were performed to define an individualised risk stratification model of SCD/VTA. A binary logistic regression model demonstrated a high prognostic significance of discriminant function with a classification sensitivity of 80.8% and specificity of 99.1% (F = 31.2; c2 = 143.2; p < 0.0001). The method of personalised risk stratification using Cox logistic regression allows correct classification of more than 93.9% of CHF cases. A robust body of evidence concerning logistic regression prognostic significance to define VTA risk allows inclusion of this method into the algorithm of subsequent control and selection of the optimal treatment modality to treat patients with CHF.

A simple approach to power and sample size calculations in logistic regression and Cox regression models.

PubMed

Vaeth, Michael; Skovlund, Eva

2004-06-15

For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

Causal correlation of foliar biochemical concentrations with AVIRIS spectra using forced entry linear regression

NASA Technical Reports Server (NTRS)

Dawson, Terence P.; Curran, Paul J.; Kupiec, John A.

1995-01-01

A major goal of airborne imaging spectrometry is to estimate the biochemical composition of vegetation canopies from reflectance spectra. Remotely-sensed estimates of foliar biochemical concentrations of forests would provide valuable indicators of ecosystem function at regional and eventually global scales. Empirical research has shown a relationship exists between the amount of radiation reflected from absorption features and the concentration of given biochemicals in leaves and canopies (Matson et al., 1994, Johnson et al., 1994). A technique commonly used to determine which wavelengths have the strongest correlation with the biochemical of interest is unguided (stepwise) multiple regression. Wavelengths are entered into a multivariate regression equation, in their order of importance, each contributing to the reduction of the variance in the measured biochemical concentration. A significant problem with the use of stepwise regression for determining the correlation between biochemical concentration and spectra is that of 'overfitting' as there are significantly more wavebands than biochemical measurements. This could result in the selection of wavebands which may be more accurately attributable to noise or canopy effects. In addition, there is a real problem of collinearity in that the individual biochemical concentrations may covary. A strong correlation between the reflectance at a given wavelength and the concentration of a biochemical of interest, therefore, may be due to the effect of another biochemical which is closely related. Furthermore, it is not always possible to account for potentially suitable waveband omissions in the stepwise selection procedure. This concern about the suitability of stepwise regression has been identified and acknowledged in a number of recent studies (Wessman et al., 1988, Curran, 1989, Curran et al., 1992, Peterson and Hubbard, 1992, Martine and Aber, 1994, Kupiec, 1994). These studies have pointed to the lack of a physical link between wavelengths chosen by stepwise regression and the biochemical of interest, and this in turn has cast doubts on the use of imaging spectrometry for the estimation of foliar biochemical concentrations at sites distant from the training sites. To investigate this problem, an analysis was conducted on the variation in canopy biochemical concentrations and reflectance spectra using forced entry linear regression.

Monitoring heavy metal Cr in soil based on hyperspectral data using regression analysis

NASA Astrophysics Data System (ADS)

Zhang, Ningyu; Xu, Fuyun; Zhuang, Shidong; He, Changwei

2016-10-01

Heavy metal pollution in soils is one of the most critical problems in the global ecology and environment safety nowadays. Hyperspectral remote sensing and its application is capable of high speed, low cost, less risk and less damage, and provides a good method for detecting heavy metals in soil. This paper proposed a new idea of applying regression analysis of stepwise multiple regression between the spectral data and monitoring the amount of heavy metal Cr by sample points in soil for environmental protection. In the measurement, a FieldSpec HandHeld spectroradiometer is used to collect reflectance spectra of sample points over the wavelength range of 325-1075 nm. Then the spectral data measured by the spectroradiometer is preprocessed to reduced the influence of the external factors, and the preprocessed methods include first-order differential equation, second-order differential equation and continuum removal method. The algorithms of stepwise multiple regression are established accordingly, and the accuracy of each equation is tested. The results showed that the accuracy of first-order differential equation works best, which makes it feasible to predict the content of heavy metal Cr by using stepwise multiple regression.

Simultaneous confidence bands for Cox regression from semiparametric random censorship.

PubMed

Mondal, Shoubhik; Subramanian, Sundarraman

2016-01-01

Cox regression is combined with semiparametric random censorship models to construct simultaneous confidence bands (SCBs) for subject-specific survival curves. Simulation results are presented to compare the performance of the proposed SCBs with the SCBs that are based only on standard Cox. The new SCBs provide correct empirical coverage and are more informative. The proposed SCBs are illustrated with two real examples. An extension to handle missing censoring indicators is also outlined.

Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

NASA Astrophysics Data System (ADS)

Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

2017-04-01

The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

Scoring and staging systems using cox linear regression modeling and recursive partitioning.

PubMed

Lee, J W; Um, S H; Lee, J B; Mun, J; Cho, H

2006-01-01

Scoring and staging systems are used to determine the order and class of data according to predictors. Systems used for medical data, such as the Child-Turcotte-Pugh scoring and staging systems for ordering and classifying patients with liver disease, are often derived strictly from physicians' experience and intuition. We construct objective and data-based scoring/staging systems using statistical methods. We consider Cox linear regression modeling and recursive partitioning techniques for censored survival data. In particular, to obtain a target number of stages we propose cross-validation and amalgamation algorithms. We also propose an algorithm for constructing scoring and staging systems by integrating local Cox linear regression models into recursive partitioning, so that we can retain the merits of both methods such as superior predictive accuracy, ease of use, and detection of interactions between predictors. The staging system construction algorithms are compared by cross-validation evaluation of real data. The data-based cross-validation comparison shows that Cox linear regression modeling is somewhat better than recursive partitioning when there are only continuous predictors, while recursive partitioning is better when there are significant categorical predictors. The proposed local Cox linear recursive partitioning has better predictive accuracy than Cox linear modeling and simple recursive partitioning. This study indicates that integrating local linear modeling into recursive partitioning can significantly improve prediction accuracy in constructing scoring and staging systems.

Analysis of occlusal variables, dental attrition, and age for distinguishing healthy controls from female patients with intracapsular temporomandibular disorders.

PubMed

Seligman, D A; Pullinger, A G

2000-01-01

Confusion about the relationship of occlusion to temporomandibular disorders (TMD) persists. This study attempted to identify occlusal and attrition factors plus age that would characterize asymptomatic normal female subjects. A total of 124 female patients with intracapsular TMD were compared with 47 asymptomatic female controls for associations to 9 occlusal factors, 3 attrition severity measures, and age using classification tree, multiple stepwise logistic regression, and univariate analyses. Models were tested for accuracy (sensitivity and specificity) and total contribution to the variance. The classification tree model had 4 terminal nodes that used only anterior attrition and age. "Normals" were mainly characterized by low attrition levels, whereas patients had higher attrition and tended to be younger. The tree model was only moderately useful (sensitivity 63%, specificity 94%) in predicting normals. The logistic regression model incorporated unilateral posterior crossbite and mediotrusive attrition severity in addition to the 2 factors in the tree, but was slightly less accurate than the tree (sensitivity 51%, specificity 90%). When only occlusal factors were considered in the analysis, normals were additionally characterized by a lack of anterior open bite, smaller overjet, and smaller RCP-ICP slides. The log likelihood accounted for was similar for both the tree (pseudo R(2) = 29.38%; mean deviance = 0.95) and the multiple logistic regression (Cox Snell R(2) = 30.3%, mean deviance = 0.84) models. The occlusal and attrition factors studied were only moderately useful in differentiating normals from TMD patients.

Non-Asymptotic Oracle Inequalities for the High-Dimensional Cox Regression via Lasso.

PubMed

Kong, Shengchun; Nan, Bin

2014-01-01

We consider finite sample properties of the regularized high-dimensional Cox regression via lasso. Existing literature focuses on linear models or generalized linear models with Lipschitz loss functions, where the empirical risk functions are the summations of independent and identically distributed (iid) losses. The summands in the negative log partial likelihood function for censored survival data, however, are neither iid nor Lipschitz.We first approximate the negative log partial likelihood function by a sum of iid non-Lipschitz terms, then derive the non-asymptotic oracle inequalities for the lasso penalized Cox regression using pointwise arguments to tackle the difficulties caused by lacking iid Lipschitz losses.

Non-Asymptotic Oracle Inequalities for the High-Dimensional Cox Regression via Lasso

PubMed Central

Kong, Shengchun; Nan, Bin

2013-01-01

We consider finite sample properties of the regularized high-dimensional Cox regression via lasso. Existing literature focuses on linear models or generalized linear models with Lipschitz loss functions, where the empirical risk functions are the summations of independent and identically distributed (iid) losses. The summands in the negative log partial likelihood function for censored survival data, however, are neither iid nor Lipschitz.We first approximate the negative log partial likelihood function by a sum of iid non-Lipschitz terms, then derive the non-asymptotic oracle inequalities for the lasso penalized Cox regression using pointwise arguments to tackle the difficulties caused by lacking iid Lipschitz losses. PMID:24516328

Practical application of cure mixture model for long-term censored survivor data from a withdrawal clinical trial of patients with major depressive disorder.

PubMed

Arano, Ichiro; Sugimoto, Tomoyuki; Hamasaki, Toshimitsu; Ohno, Yuko

2010-04-23

Survival analysis methods such as the Kaplan-Meier method, log-rank test, and Cox proportional hazards regression (Cox regression) are commonly used to analyze data from randomized withdrawal studies in patients with major depressive disorder. However, unfortunately, such common methods may be inappropriate when a long-term censored relapse-free time appears in data as the methods assume that if complete follow-up were possible for all individuals, each would eventually experience the event of interest. In this paper, to analyse data including such a long-term censored relapse-free time, we discuss a semi-parametric cure regression (Cox cure regression), which combines a logistic formulation for the probability of occurrence of an event with a Cox proportional hazards specification for the time of occurrence of the event. In specifying the treatment's effect on disease-free survival, we consider the fraction of long-term survivors and the risks associated with a relapse of the disease. In addition, we develop a tree-based method for the time to event data to identify groups of patients with differing prognoses (cure survival CART). Although analysis methods typically adapt the log-rank statistic for recursive partitioning procedures, the method applied here used a likelihood ratio (LR) test statistic from a fitting of cure survival regression assuming exponential and Weibull distributions for the latency time of relapse. The method is illustrated using data from a sertraline randomized withdrawal study in patients with major depressive disorder. We concluded that Cox cure regression reveals facts on who may be cured, and how the treatment and other factors effect on the cured incidence and on the relapse time of uncured patients, and that cure survival CART output provides easily understandable and interpretable information, useful both in identifying groups of patients with differing prognoses and in utilizing Cox cure regression models leading to meaningful interpretations.

A comparison between the use of Cox regression and the use of partial least squares-Cox regression to predict the survival of kidney-transplant patients

NASA Astrophysics Data System (ADS)

Solimun

2017-05-01

The aim of this research is to model survival data from kidney-transplant patients using the partial least squares (PLS)-Cox regression, which can both meet and not meet the no-multicollinearity assumption. The secondary data were obtained from research entitled "Factors affecting the survival of kidney-transplant patients". The research subjects comprised 250 patients. The predictor variables consisted of: age (X1), sex (X2); two categories, prior hemodialysis duration (X3), diabetes (X4); two categories, prior transplantation number (X5), number of blood transfusions (X6), discrepancy score (X7), use of antilymphocyte globulin(ALG) (X8); two categories, while the response variable was patient survival time (in months). Partial least squares regression is a model that connects the predictor variables X and the response variable y and it initially aims to determine the relationship between them. Results of the above analyses suggest that the survival of kidney transplant recipients ranged from 0 to 55 months, with 62% of the patients surviving until they received treatment that lasted for 55 months. The PLS-Cox regression analysis results revealed that patients' age and the use of ALG significantly affected the survival time of patients. The factor of patients' age (X1) in the PLS-Cox regression model merely affected the failure probability by 1.201. This indicates that the probability of dying for elderly patients with a kidney transplant is 1.152 times higher than that for younger patients.

A comparison of the effects of C2-cyclosporine and C0-tacrolimus on renal function and cardiovascular risk factors in kidney transplant recipients.

PubMed

Kim, S Joseph; Prasad, G V Ramesh; Huang, Michael; Nash, Michelle M; Famure, Olusegun; Park, Joseph; Thenganatt, Mary Ann; Chowdhury, Nizamuddin; Cole, Edward H; Fenton, Stanley S A; Cattran, Daniel C; Zaltzman, Jeffrey S; Cardella, Carl J

2006-10-15

There are few data directly comparing the effects of two-hour postingestion monitored cyclosporine (C2-CsA) vs. trough-monitored tacrolimus (C0-Tac) on renal function and cardiovascular risk factors. We studied 378 (202 C2-CsA vs. 176 C0-Tac) incident kidney transplant recipients in Toronto, Canada, from August 1, 2000 and December 31, 2003. Outcomes included changes in estimated glomerular filtration rate (eGFR at 1 and 6 months by modification of diet in renal disease four-variable equation), mean arterial pressure (MAP), total cholesterol (TC), and new-onset diabetes mellitus (NODM) at six months posttransplant. The independent effect of treatment/monitoring strategies on continuous outcomes and time-to-NODM was modeled using linear and Cox regression, respectively. Mean eGFR was 59.5 vs. 62.9 ml/min at one month and 50.6 vs. 61.2 ml/min at six months for C2-CsA vs. C0-Tac, respectively. Multiple linear regression revealed the slope of eGFR to be 0.93 ml/min/month lower in C2-CsA patients. This was equivalent to an adjusted average eGFR difference of 4.64 ml/min between months one and six posttransplant. There was no significant difference in average MAP and TC. In a stepwise multivariable Cox model and a propensity score analysis, there was no significant association between the type of treatment/monitoring strategy and time-to-NODM. There was a greater decline in eGFR for patients on C2-CsA (vs. C0-Tac) between one and six months posttransplant. However, MAP, TC, and the risk of NODM were comparable in both treatment/monitoring groups. The long-term impact of short-term reductions in eGFR as a function of the type of treatment/monitoring strategy requires further study.

Risk and prognostic factors for pneumonia and choking amongst Parkinson's disease patients with dysphagia.

PubMed

Goh, Kwang-Hwee; Acharyya, Sanchalika; Ng, Samuel Yong-Ern; Boo, Jasmine Pei-Ling; Kooi, Amanda Hui-Juan; Ng, Hwee-Lan; Li, Wei; Tay, Kay-Yaw; Au, Wing-Lok; Tan, Louis Chew-Seng

2016-08-01

To evaluate the time to hospitalisation and baseline factors associated with pneumonia/choking in Parkinson's Disease (PD) patients. Although dysphagia and pneumonia are common problems in PD, scarce research has been performed. A total of 194 PD patients who underwent a VFS evaluation were retrospectively selected. The mode of feeding and admissions for pneumonia/choking were analyzed. Baseline clinical and demographic variables were compared between feeding groups. Kaplan-Meier survival analysis was performed to estimate time to pneumonia/choking. Clinical variables significantly associated with pneumonia/choking free survival were identified using Cox regression. Hospitalisation for pneumonia/choking occurred in 89 out of 194 patients, with the highest admission rate in rejected enteral feeding group (66.7%), followed by enteral feeding (61.8%) and oral feeding (38.8%) groups. The estimates of median time to event were 11, 14, and 47 months for rejected enteral feeding, enteral and oral feeding groups respectively (log-rank test p < 0.001). The rejected enteral feeding group had the highest risk of pneumonia/choking (HR 4.61, 95%CI:2.33-9.08, p < 0.001), followed by enteral feeding group (HR 2.29, 95%CI:1.25-4.19, p = 0.007), when compared to oral feeding group after adjusting for possible confounders. A stepwise Cox regression showed that the rejected enteral feeding (HR 4.89, 95%CI:2.19-10.88, p < 0.001), enteral mode of feeding (HR 2.43, 95%CI:1.11-5.32, p = 0.026), and Charlson weighted index of co-morbidity (HR 1.27, 95%CI:1.03-1.58, p = 0.028) were independently associated with higher hazard of pneumonia/choking. Compliance to feeding recommendations is important to reduce the risk of hospitalisation for pneumonia/choking. The recommended mode of feeding and comorbidity index was significantly associated with pneumonia/choking risk. Copyright © 2016 Elsevier Ltd. All rights reserved.

Extract from Nandina domestica inhibits lipopolysaccharide-induced cyclooxygenase-2 expression in human pulmonary epithelial A549 cells.

PubMed

Ueki, Takuro; Akaishi, Tatsuhiro; Okumura, Hidenobu; Abe, Kazuho

2012-01-01

Extract from fruits of Nandina domestica THUNBERG (NDE) has been used to improve cough and breathing difficulty in Japan for many years. To explore whether NDE may alleviate respiratory inflammation, we investigated its effect on expression of cyclooxygenase-2 (COX-2) and production of prostaglandin E₂ (PGE₂) in human pulmonary epithelial A549 cells in culture. Treatment with lipopolysaccharide (LPS; 6 µg/mL) resulted in an increase of COX-2 expression and PGE₂ production in A549 cells. Both the LPS-induced COX-2 expression and PGE₂ production were significantly inhibited by NDE (1-10 µg/mL) in a concentration-dependent manner. NDE did not affect COX-1 expression nor COX activity. These results suggest that NDE downregulates LPS-induced COX-2 expression and inhibits PGE₂ production in pulmonary epithelial cells. Furthermore, higenamine and nantenine, two major constituents responsible for tracheal relaxing effect of NDE, did not mimic the inhibitory effect of NDE on LPS-induced COX-2 expression in A549 cells. To identify active constituent(s) of NDE responsible for the anti-inflammatory effect, NDE was introduced in a polyaromatic absorbent resin column and stepwise eluted to yield water fraction, 20% methanol fraction, 40% methanol fraction, 99.8% methanol fraction, and 99.5% acetone fraction. However, none of these five fractions alone inhibited LPS-induced COX-2 expression. On the other hand, exclusion of water fraction from NDE abolished the inhibitory effect of NDE on LPS-induced COX-2 expression. These results suggest that constituent(s) present in water fraction is required but not sufficient for the anti-inflammatory activity of NDE, which may result from interactions among multiple constituents.

Immortal time bias in observational studies of time-to-event outcomes.

PubMed

Jones, Mark; Fowler, Robert

2016-12-01

The purpose of the study is to show, through simulation and example, the magnitude and direction of immortal time bias when an inappropriate analysis is used. We compare 4 methods of analysis for observational studies of time-to-event outcomes: logistic regression, standard Cox model, landmark analysis, and time-dependent Cox model using an example data set of patients critically ill with influenza and a simulation study. For the example data set, logistic regression, standard Cox model, and landmark analysis all showed some evidence that treatment with oseltamivir provides protection from mortality in patients critically ill with influenza. However, when the time-dependent nature of treatment exposure is taken account of using a time-dependent Cox model, there is no longer evidence of a protective effect of treatment. The simulation study showed that, under various scenarios, the time-dependent Cox model consistently provides unbiased treatment effect estimates, whereas standard Cox model leads to bias in favor of treatment. Logistic regression and landmark analysis may also lead to bias. To minimize the risk of immortal time bias in observational studies of survival outcomes, we strongly suggest time-dependent exposures be included as time-dependent variables in hazard-based analyses. Copyright © 2016 Elsevier Inc. All rights reserved.

Adjusted variable plots for Cox's proportional hazards regression model.

PubMed

Hall, C B; Zeger, S L; Bandeen-Roche, K J

1996-01-01

Adjusted variable plots are useful in linear regression for outlier detection and for qualitative evaluation of the fit of a model. In this paper, we extend adjusted variable plots to Cox's proportional hazards model for possibly censored survival data. We propose three different plots: a risk level adjusted variable (RLAV) plot in which each observation in each risk set appears, a subject level adjusted variable (SLAV) plot in which each subject is represented by one point, and an event level adjusted variable (ELAV) plot in which the entire risk set at each failure event is represented by a single point. The latter two plots are derived from the RLAV by combining multiple points. In each point, the regression coefficient and standard error from a Cox proportional hazards regression is obtained by a simple linear regression through the origin fit to the coordinates of the pictured points. The plots are illustrated with a reanalysis of a dataset of 65 patients with multiple myeloma.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Comparison of Survival Models for Analyzing Prognostic Factors in Gastric Cancer Patients

PubMed

Habibi, Danial; Rafiei, Mohammad; Chehrei, Ali; Shayan, Zahra; Tafaqodi, Soheil

2018-03-27

Objective: There are a number of models for determining risk factors for survival of patients with gastric cancer. This study was conducted to select the model showing the best fit with available data. Methods: Cox regression and parametric models (Exponential, Weibull, Gompertz, Log normal, Log logistic and Generalized Gamma) were utilized in unadjusted and adjusted forms to detect factors influencing mortality of patients. Comparisons were made with Akaike Information Criterion (AIC) by using STATA 13 and R 3.1.3 softwares. Results: The results of this study indicated that all parametric models outperform the Cox regression model. The Log normal, Log logistic and Generalized Gamma provided the best performance in terms of AIC values (179.2, 179.4 and 181.1, respectively). On unadjusted analysis, the results of the Cox regression and parametric models indicated stage, grade, largest diameter of metastatic nest, largest diameter of LM, number of involved lymph nodes and the largest ratio of metastatic nests to lymph nodes, to be variables influencing the survival of patients with gastric cancer. On adjusted analysis, according to the best model (log normal), grade was found as the significant variable. Conclusion: The results suggested that all parametric models outperform the Cox model. The log normal model provides the best fit and is a good substitute for Cox regression. Creative Commons Attribution License

Retro-regression--another important multivariate regression improvement.

PubMed

Randić, M

2001-01-01

We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

COX-2 and PPAR-γ confer cannabidiol-induced apoptosis of human lung cancer cells.

PubMed

Ramer, Robert; Heinemann, Katharina; Merkord, Jutta; Rohde, Helga; Salamon, Achim; Linnebacher, Michael; Hinz, Burkhard

2013-01-01

The antitumorigenic mechanism of cannabidiol is still controversial. This study investigates the role of COX-2 and PPAR-γ in cannabidiol's proapoptotic and tumor-regressive action. In lung cancer cell lines (A549, H460) and primary cells from a patient with lung cancer, cannabidiol elicited decreased viability associated with apoptosis. Apoptotic cell death by cannabidiol was suppressed by NS-398 (COX-2 inhibitor), GW9662 (PPAR-γ antagonist), and siRNA targeting COX-2 and PPAR-γ. Cannabidiol-induced apoptosis was paralleled by upregulation of COX-2 and PPAR-γ mRNA and protein expression with a maximum induction of COX-2 mRNA after 8 hours and continuous increases of PPAR-γ mRNA when compared with vehicle. In response to cannabidiol, tumor cell lines exhibited increased levels of COX-2-dependent prostaglandins (PG) among which PGD(2) and 15-deoxy-Δ(12,14)-PGJ(2) (15d-PGJ(2)) caused a translocation of PPAR-γ to the nucleus and induced a PPAR-γ-dependent apoptotic cell death. Moreover, in A549-xenografted nude mice, cannabidiol caused upregulation of COX-2 and PPAR-γ in tumor tissue and tumor regression that was reversible by GW9662. Together, our data show a novel proapoptotic mechanism of cannabidiol involving initial upregulation of COX-2 and PPAR-γ and a subsequent nuclear translocation of PPAR-γ by COX-2-dependent PGs.

Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.

PubMed

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei

2016-02-01

Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.

Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions

PubMed Central

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei

2015-01-01

Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979

Estimation of variance in Cox's regression model with shared gamma frailties.

PubMed

Andersen, P K; Klein, J P; Knudsen, K M; Tabanera y Palacios, R

1997-12-01

The Cox regression model with a shared frailty factor allows for unobserved heterogeneity or for statistical dependence between the observed survival times. Estimation in this model when the frailties are assumed to follow a gamma distribution is reviewed, and we address the problem of obtaining variance estimates for regression coefficients, frailty parameter, and cumulative baseline hazards using the observed nonparametric information matrix. A number of examples are given comparing this approach with fully parametric inference in models with piecewise constant baseline hazards.

Properties of added variable plots in Cox's regression model.

PubMed

Lindkvist, M

2000-03-01

The added variable plot is useful for examining the effect of a covariate in regression models. The plot provides information regarding the inclusion of a covariate, and is useful in identifying influential observations on the parameter estimates. Hall et al. (1996) proposed a plot for Cox's proportional hazards model derived by regarding the Cox model as a generalized linear model. This paper proves and discusses properties of this plot. These properties make the plot a valuable tool in model evaluation. Quantities considered include parameter estimates, residuals, leverage, case influence measures and correspondence to previously proposed residuals and diagnostics.

Stepwise versus Hierarchical Regression: Pros and Cons

ERIC Educational Resources Information Center

Lewis, Mitzi

2007-01-01

Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

A Hybrid Approach of Stepwise Regression, Logistic Regression, Support Vector Machine, and Decision Tree for Forecasting Fraudulent Financial Statements

PubMed Central

Goo, Yeong-Jia James; Shen, Zone-De

2014-01-01

As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%. PMID:25302338

A hybrid approach of stepwise regression, logistic regression, support vector machine, and decision tree for forecasting fraudulent financial statements.

PubMed

Chen, Suduan; Goo, Yeong-Jia James; Shen, Zone-De

2014-01-01

As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.

Cox regression analysis with missing covariates via nonparametric multiple imputation.

PubMed

Hsu, Chiu-Hsieh; Yu, Mandi

2018-01-01

We consider the situation of estimating Cox regression in which some covariates are subject to missing, and there exists additional information (including observed event time, censoring indicator and fully observed covariates) which may be predictive of the missing covariates. We propose to use two working regression models: one for predicting the missing covariates and the other for predicting the missing probabilities. For each missing covariate observation, these two working models are used to define a nearest neighbor imputing set. This set is then used to non-parametrically impute covariate values for the missing observation. Upon the completion of imputation, Cox regression is performed on the multiply imputed datasets to estimate the regression coefficients. In a simulation study, we compare the nonparametric multiple imputation approach with the augmented inverse probability weighted (AIPW) method, which directly incorporates the two working models into estimation of Cox regression, and the predictive mean matching imputation (PMM) method. We show that all approaches can reduce bias due to non-ignorable missing mechanism. The proposed nonparametric imputation method is robust to mis-specification of either one of the two working models and robust to mis-specification of the link function of the two working models. In contrast, the PMM method is sensitive to misspecification of the covariates included in imputation. The AIPW method is sensitive to the selection probability. We apply the approaches to a breast cancer dataset from Surveillance, Epidemiology and End Results (SEER) Program.

A stepwise model to predict monthly streamflow

NASA Astrophysics Data System (ADS)

Mahmood Al-Juboori, Anas; Guven, Aytac

2016-12-01

In this study, a stepwise model empowered with genetic programming is developed to predict the monthly flows of Hurman River in Turkey and Diyalah and Lesser Zab Rivers in Iraq. The model divides the monthly flow data to twelve intervals representing the number of months in a year. The flow of a month, t is considered as a function of the antecedent month's flow (t - 1) and it is predicted by multiplying the antecedent monthly flow by a constant value called K. The optimum value of K is obtained by a stepwise procedure which employs Gene Expression Programming (GEP) and Nonlinear Generalized Reduced Gradient Optimization (NGRGO) as alternative to traditional nonlinear regression technique. The degree of determination and root mean squared error are used to evaluate the performance of the proposed models. The results of the proposed model are compared with the conventional Markovian and Auto Regressive Integrated Moving Average (ARIMA) models based on observed monthly flow data. The comparison results based on five different statistic measures show that the proposed stepwise model performed better than Markovian model and ARIMA model. The R2 values of the proposed model range between 0.81 and 0.92 for the three rivers in this study.

Breakfast Frequency and Development of Metabolic Risk

PubMed Central

Odegaard, Andrew O.; Jacobs, David R.; Steffen, Lyn M.; Van Horn, Linda; Ludwig, David S.; Pereira, Mark A.

2013-01-01

OBJECTIVE The relation of breakfast intake frequency to metabolic health is not well studied. The aim of this study was to examine breakfast intake frequency with incidence of metabolic conditions. RESEARCH DESIGN AND METHODS We performed an analysis of 3,598 participants from the community-based Coronary Artery Risk Development in Young Adults (CARDIA) study who were free of diabetes in the year 7 examination when breakfast and dietary habits were assessed (1992–1993) and participated in at least one of the five subsequent follow-up examinations over 18 years. RESULTS Relative to those with infrequent breakfast consumption (0–3 days/week), participants who reported eating breakfast daily gained 1.9 kg less weight over 18 years (P = 0.001). In a Cox regression analysis, there was a stepwise decrease in risk across conditions in frequent breakfast consumers (4–6 days/week) and daily consumers. The results for incidence of abdominal obesity, obesity, metabolic syndrome, and hypertension remained significant after adjustment for baseline measures of adiposity (waist circumference or BMI) in daily breakfast consumers. Hazard ratios (HRs) and 95% CIs for daily breakfast consumption were as follows: abdominal obesity HR 0.78 (95% CI 0.66–0.91), obesity 0.80 (0.67–0.96), metabolic syndrome 0.82 (0.69–0.98), and hypertension 0.84 (0.72–0.99). For type 2 diabetes, the corresponding estimate was 0.81 (0.63–1.05), with a significant stepwise inverse association in black men and white men and women but no association in black women. There was no evidence of differential results for high versus low overall dietary quality. CONCLUSIONS Daily breakfast intake is strongly associated with reduced risk of a spectrum of metabolic conditions. PMID:23775814

A nomogram to predict the survival of stage IIIA-N2 non-small cell lung cancer after surgery.

PubMed

Mao, Qixing; Xia, Wenjie; Dong, Gaochao; Chen, Shuqi; Wang, Anpeng; Jin, Guangfu; Jiang, Feng; Xu, Lin

2018-04-01

Postoperative survival of patients with stage IIIA-N2 non-small cell lung cancer (NSCLC) is highly heterogeneous. Here, we aimed to identify variables associated with postoperative survival and develop a tool for survival prediction. A retrospective review was performed in the Surveillance, Epidemiology, and End Results database from January 2004 to December 2009. Significant variables were selected by use of the backward stepwise method. The nomogram was constructed with multivariable Cox regression. The model's performance was evaluated by concordance index and calibration curve. The model was validated via an independent cohort from the Jiangsu Cancer Hospital Lung Cancer Center. A total of 1809 patients with stage IIIA-N2 NSCLC who underwent surgery were included in the training cohort. Age, sex, grade, histology, tumor size, visceral pleural invasion, positive lymph nodes, lymph nodes examined, and surgery type (lobectomy vs pneumonectomy) were identified as significant prognostic variables using backward stepwise method. A nomogram was developed from the training cohort and validated using an independent Chinese cohort. The concordance index of the model was 0.673 (95% confidence interval, 0.654-0.692) in training cohort and 0.664 in validation cohort (95% confidence interval, 0.614-0.714). The calibration plot showed optimal consistency between nomogram predicted survival and observed survival. Survival analyses demonstrated significant differences between different subgroups stratified by prognostic scores. This nomogram provided the individual survival prediction for patients with stage IIIA-N2 NSCLC after surgery, which might benefit survival counseling for patients and clinicians, clinical trial design and follow-up, as well as postoperative strategy-making. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

An investigation of correlation between pilot scanning behavior and workload using stepwise regression analysis

NASA Technical Reports Server (NTRS)

Waller, M. C.

1976-01-01

An electro-optical device called an oculometer which tracks a subject's lookpoint as a time function has been used to collect data in a real-time simulation study of instrument landing system (ILS) approaches. The data describing the scanning behavior of a pilot during the instrument approaches have been analyzed by use of a stepwise regression analysis technique. A statistically significant correlation between pilot workload, as indicated by pilot ratings, and scanning behavior has been established. In addition, it was demonstrated that parameters derived from the scanning behavior data can be combined in a mathematical equation to provide a good representation of pilot workload.

Preoperative galactose elimination capacity predicts complications and survival after hepatic resection.

PubMed

Redaelli, Claudio A; Dufour, Jean-François; Wagner, Markus; Schilling, Martin; Hüsler, Jürg; Krähenbühl, Lukas; Büchler, Markus W; Reichen, Jürg

2002-01-01

To analyze a single center's 6-year experience with 258 consecutive patients undergoing major hepatic resection for primary or secondary malignancy of the liver, and to examine the predictive value of preoperative liver function assessment. Despite the substantial improvements in diagnostic and surgical techniques that have made liver surgery a safer procedure, careful patient selection remains mandatory to achieve good results in patients with hepatic tumors. In this prospective study, 258 patients undergoing hepatic resection were enrolled: 111 for metastases, 78 for hepatocellular carcinoma (HCC), 21 for cholangiocellular carcinoma, and 48 for other primary hepatic tumors. One hundred fifty-eight patients underwent segment-oriented liver resection, including hemihepatectomies, and 100 had subsegmental resections. Thirty-two clinical and biochemical parameters were analyzed, including liver function assessment by the galactose elimination capacity (GEC) test, a measure of hepatic functional reserve, to predict postoperative (60-day) rates of death and complications and long-term survival. All variables were determined within 5 days before surgery. Data were subjected to univariate and multivariate analysis for two patient subgroups (HCC and non-HCC). The cutoffs for GEC in both groups were predefined. Long-term survival (>60 days) was subjected to Kaplan-Meier analysis and the Cox proportional hazard model. In the entire group of 258 patients, a GEC less than 6 mg/min/kg was the only preoperative biochemical parameter that predicted postoperative complications and death by univariate and stepwise regression analysis. A GEC of more than 6 mg/min/kg was also significantly associated with longer survival. This predictive value could also be shown in the subgroup of 180 patients with tumors other than HCC. In the subgroup of 78 patients with HCC, a GEC less than 4 mg/min/kg predicted postoperative complications and death by univariate and stepwise regression analysis. Further, a GEC of more than 4 mg/min/kg was also associated with longer survival. This prospective study establishes the preoperative determination of the hepatic reserve by GEC as a strong independent and valuable predictor for short- and long-term outcome in patients with primary and secondary hepatic tumors undergoing resection.

Preoperative Galactose Elimination Capacity Predicts Complications and Survival After Hepatic Resection

PubMed Central

Redaelli, Claudio A.; Dufour, Jean-François; Wagner, Markus; Schilling, Martin; Hüsler, Jürg; Krähenbühl, Lukas; Büchler, Markus W.; Reichen, Jürg

2002-01-01

Objective To analyze a single center’s 6-year experience with 258 consecutive patients undergoing major hepatic resection for primary or secondary malignancy of the liver, and to examine the predictive value of preoperative liver function assessment. Summary Background Data Despite the substantial improvements in diagnostic and surgical techniques that have made liver surgery a safer procedure, careful patient selection remains mandatory to achieve good results in patients with hepatic tumors. Methods In this prospective study, 258 patients undergoing hepatic resection were enrolled: 111 for metastases, 78 for hepatocellular carcinoma (HCC), 21 for cholangiocellular carcinoma, and 48 for other primary hepatic tumors. One hundred fifty-eight patients underwent segment-oriented liver resection, including hemihepatectomies, and 100 had subsegmental resections. Thirty-two clinical and biochemical parameters were analyzed, including liver function assessment by the galactose elimination capacity (GEC) test, a measure of hepatic functional reserve, to predict postoperative (60-day) rates of death and complications and long-term survival. All variables were determined within 5 days before surgery. Data were subjected to univariate and multivariate analysis for two patient subgroups (HCC and non-HCC). The cutoffs for GEC in both groups were predefined. Long-term survival (>60 days) was subjected to Kaplan-Meier analysis and the Cox proportional hazard model. Results In the entire group of 258 patients, a GEC less than 6 mg/min/kg was the only preoperative biochemical parameter that predicted postoperative complications and death by univariate and stepwise regression analysis. A GEC of more than 6 mg/min/kg was also significantly associated with longer survival. This predictive value could also be shown in the subgroup of 180 patients with tumors other than HCC. In the subgroup of 78 patients with HCC, a GEC less than 4 mg/min/kg predicted postoperative complications and death by univariate and stepwise regression analysis. Further, a GEC of more than 4 mg/min/kg was also associated with longer survival. Conclusions This prospective study establishes the preoperative determination of the hepatic reserve by GEC as a strong independent and valuable predictor for short- and long-term outcome in patients with primary and secondary hepatic tumors undergoing resection. PMID:11753045

Analysis of model development strategies: predicting ventral hernia recurrence.

PubMed

Holihan, Julie L; Li, Linda T; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K

2016-11-01

There have been many attempts to identify variables associated with ventral hernia recurrence; however, it is unclear which statistical modeling approach results in models with greatest internal and external validity. We aim to assess the predictive accuracy of models developed using five common variable selection strategies to determine variables associated with hernia recurrence. Two multicenter ventral hernia databases were used. Database 1 was randomly split into "development" and "internal validation" cohorts. Database 2 was designated "external validation". The dependent variable for model development was hernia recurrence. Five variable selection strategies were used: (1) "clinical"-variables considered clinically relevant, (2) "selective stepwise"-all variables with a P value <0.20 were assessed in a step-backward model, (3) "liberal stepwise"-all variables were included and step-backward regression was performed, (4) "restrictive internal resampling," and (5) "liberal internal resampling." Variables were included with P < 0.05 for the Restrictive model and P < 0.10 for the Liberal model. A time-to-event analysis using Cox regression was performed using these strategies. The predictive accuracy of the developed models was tested on the internal and external validation cohorts using Harrell's C-statistic where C > 0.70 was considered "reasonable". The recurrence rate was 32.9% (n = 173/526; median/range follow-up, 20/1-58 mo) for the development cohort, 36.0% (n = 95/264, median/range follow-up 20/1-61 mo) for the internal validation cohort, and 12.7% (n = 155/1224, median/range follow-up 9/1-50 mo) for the external validation cohort. Internal validation demonstrated reasonable predictive accuracy (C-statistics = 0.772, 0.760, 0.767, 0.757, 0.763), while on external validation, predictive accuracy dipped precipitously (C-statistic = 0.561, 0.557, 0.562, 0.553, 0.560). Predictive accuracy was equally adequate on internal validation among models; however, on external validation, all five models failed to demonstrate utility. Future studies should report multiple variable selection techniques and demonstrate predictive accuracy on external data sets for model validation. Copyright © 2016 Elsevier Inc. All rights reserved.

A fast identification algorithm for Box-Cox transformation based radial basis function neural network.

PubMed

Hong, Xia

2006-07-01

In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

Associations between dietary and lifestyle risk factors and colorectal cancer in the Scottish population.

PubMed

Theodoratou, Evropi; Farrington, Susan M; Tenesa, Albert; McNeill, Geraldine; Cetnarskyj, Roseanne; Korakakis, Emmanouil; Din, Farhat V N; Porteous, Mary E; Dunlop, Malcolm G; Campbell, Harry

2014-01-01

Colorectal cancer (CRC) accounts for 9.7% of all cancer cases and for 8% of all cancer-related deaths. Established risk factors include personal or family history of CRC as well as lifestyle and dietary factors. We investigated the relationship between CRC and demographic, lifestyle, food and nutrient risk factors through a case-control study that included 2062 patients and 2776 controls from Scotland. Forward and backward stepwise regression was applied and the stability of the models was assessed in 1000 bootstrap samples. The variables that were automatically selected to be included by the forward or backward stepwise regression and whose selection was verified by bootstrap sampling in the current study were family history, dietary energy, 'high-energy snack foods', eggs, juice, sugar-sweetened beverages and white fish (associated with an increased CRC risk) and NSAIDs, coffee and magnesium (associated with a decreased CRC risk). Application of forward and backward stepwise regression in this CRC study identified some already established as well as some novel potential risk factors. Bootstrap findings suggest that examination of the stability of regression models by bootstrap sampling is useful in the interpretation of study findings. 'High-energy snack foods' and high-energy drinks (including sugar-sweetened beverages and fruit juices) as risk factors for CRC have not been reported previously and merit further investigation as such snacks and beverages are important contributors in European and North American diets.

Order Selection for General Expression of Nonlinear Autoregressive Model Based on Multivariate Stepwise Regression

NASA Astrophysics Data System (ADS)

Shi, Jinfei; Zhu, Songqing; Chen, Ruwen

2017-12-01

An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.

Self-Concept and Participation in School Activities Reanalyzed.

ERIC Educational Resources Information Center

Winne, Philip H.; Walsh, John

1980-01-01

Yarworth and Gauthier (EJ 189 606) examined whether self-concept variables enhanced predictions about students' participation in school activities, using unstructured stepwise regression techniques. A reanalysis of their data using hierarchial regression models tested their hypothesis more appropriately, and uncovered multicollinearity and…

Breast-feeding in South Korea: factors influencing its initiation and duration.

PubMed

Chung, Woojin; Kim, Hanjoong; Nam, Chung-Mo

2008-03-01

To investigate factors influencing the practices of partial breast-feeding (PBF) and exclusive breast-feeding (EBF). A national, cross-sectional survey was conducted among married women aged 15-49 years from May to August 2003. South Korea. A total of 865 mothers answered questions regarding the feeding practices of their youngest baby, born between January 2001 and May 2003. The initiation rates of PBF and EBF were 81% and 63%, respectively. However, the median durations of PBF and EBF were very short: 12 and 8 weeks, respectively. According to stepwise logistic and Cox regression analyses, the more prenatal care women received, the more likely they were to initiate PBF and EBF but the less likely to continue EBF. Delivery by Caesarean section decreased the initiation of PBF and EBF. The mother's education level and employment status before marriage, the amount of prenatal care, delivery method and baby's status at birth affected breast-feeding initiation, whereas the amount of prenatal care influenced breast-feeding duration. To promote breast-feeding, education and campaigning on the importance of continued breast-feeding should be provided to the general public, particularly to health workers in maternity units.

[Duration of breastfeeding and its relevant influencing factors on under 2-years-old in rural areas of 10 provinces in China].

PubMed

Wang, Jian-min; Li, Neng; Xie, Sheng-nan; Yang, Sen-bei; Zheng, Xiao-xuan; Zhang, Jing

2013-07-01

To understand the current status and relevant factors influencing the duration of breastfeeding in rural areas in China. Children under two years old were selected as subjects from the study on "Physical growth among the under 7-years-old children from the rural areas of ten provinces in China in 2006". Kaplan-Meier method was used to estimate the survival curves and Cox multivariate stepwise regression was used to identify the relevant factors on the duration of breastfeeding. Median of the duration for breastfeeding was 12 months in rural areas of 10 provinces in China. Results of this study suggested that factors as sex, birth order, areas of residency, nationality, initiation of formula, parents' education levels, maternal services and family income were correlated with the duration of breastfeeding. Duration of breastfeeding among rural children under 2-years of age was short in the 10 provinces of China. Factors as level of education, residential areas and family income of the parents as well as sex of the children were correlated with the duration of breastfeeding. Intervention program should be implemented to improve the current status on breastfeeding.

Predicting risk of nonmelanoma skin cancer and premalignant skin lesions in renal transplant recipients.

PubMed

Urwin, Helen R; Jones, Peter W; Harden, Paul N; Ramsay, Helen M; Hawley, Carmel M; Nicol, David L; Fryer, Anthony A

2009-06-15

Nonmelanoma skin cancer (NMSC) and associated premalignant lesions represent a major complication after transplantation, particularly in areas with high ultraviolet radiation (UVR) exposure. The American Society of Transplantation has proposed annual NMSC screening for all renal transplant recipients. The aim of this study was to develop a predictive index (PI) that could be used in targeted screening. Data on patient demographics, UVR exposure, and other clinical parameters were collected on 398 adult recipients recruited from the Princess Alexandra Hospital, Brisbane. Structured interview, skin examination, biopsy of lesions, and review of medical/pathologic records were performed. Time to presentation with the first NMSC was assessed using Cox's regression models and Kaplan-Meier estimates used to assess detection of NMSC during screening. Stepwise selection identified age, outdoor UVR exposure, living in a hot climate, pretransplant NMSC, childhood sunburning, and skin type as predictors. The PI generated was used to allocate patients into three screening groups (6 months, 2 years, and 5 years). The survival curves of these groups were significantly different (P<0.0001). Jack-knife validation correctly allocated all patients into the appropriate group. We have developed a simple PI to enable development of targeted NMSC surveillance strategies.

BFLCRM: A BAYESIAN FUNCTIONAL LINEAR COX REGRESSION MODEL FOR PREDICTING TIME TO CONVERSION TO ALZHEIMER’S DISEASE*

PubMed Central

Lee, Eunjee; Zhu, Hongtu; Kong, Dehan; Wang, Yalin; Giovanello, Kelly Sullivan; Ibrahim, Joseph G

2015-01-01

The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer’s disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer’s Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM. PMID:26900412

Evaluation of interpolation techniques for the creation of gridded daily precipitation (1 × 1 km2); Cyprus, 1980-2010

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Pashiardis, Stelios; Lange, Manfred A.

2014-01-01

High-resolution gridded daily data sets are essential for natural resource management and the analyses of climate changes and their effects. This study aims to evaluate the performance of 15 simple or complex interpolation techniques in reproducing daily precipitation at a resolution of 1 km2 over topographically complex areas. Methods are tested considering two different sets of observation densities and different rainfall amounts. We used rainfall data that were recorded at 74 and 145 observational stations, respectively, spread over the 5760 km2 of the Republic of Cyprus, in the Eastern Mediterranean. Regression analyses utilizing geographical copredictors and neighboring interpolation techniques were evaluated both in isolation and combined. Linear multiple regression (LMR) and geographically weighted regression methods (GWR) were tested. These included a step-wise selection of covariables, as well as inverse distance weighting (IDW), kriging, and 3D-thin plate splines (TPS). The relative rank of the different techniques changes with different station density and rainfall amounts. Our results indicate that TPS performs well for low station density and large-scale events and also when coupled with regression models. It performs poorly for high station density. The opposite is observed when using IDW. Simple IDW performs best for local events, while a combination of step-wise GWR and IDW proves to be the best method for large-scale events and high station density. This study indicates that the use of step-wise regression with a variable set of geographic parameters can improve the interpolation of large-scale events because it facilitates the representation of local climate dynamics.

[Associated factors in newborns with intrauterine growth retardation].

PubMed

Thompson-Chagoyán, Oscar C; Vega-Franco, Leopoldo

2008-01-01

To identify the risk factors implicated in the intrauterine growth retardation (IUGR) of neonates born in a social security institution. Case controls design study in 376 neonates: 188 with IUGR (weight < 10 percentile) and 188 without IUGR. When they born, information about 30 variables of risk for IUGR were obtained from mothers. Risk analysis and logistical regression (stepwise) were used. Odds ratios were significant for 12 of the variables. The model obtains by stepwise regression included: weight gain at pregnancy, prenatal care attendance, toxemia, chocolate ingestion, father's weight, and the environmental house. Must of the variables included in the model are related to socioeconomic disadvantages related to the risk of RCIU in the population.

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

USGS Publications Warehouse

Brown, C. Erwin

1993-01-01

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

Risk model for estimating the 1-year risk of deferred lesion intervention following deferred revascularization after fractional flow reserve assessment.

PubMed

Depta, Jeremiah P; Patel, Jayendrakumar S; Novak, Eric; Gage, Brian F; Masrani, Shriti K; Raymer, David; Facey, Gabrielle; Patel, Yogesh; Zajarias, Alan; Lasala, John M; Amin, Amit P; Kurz, Howard I; Singh, Jasvindar; Bach, Richard G

2015-02-21

Although lesions deferred revascularization following fractional flow reserve (FFR) assessment have a low risk of adverse cardiac events, variability in risk for deferred lesion intervention (DLI) has not been previously evaluated. The aim of this study was to develop a prediction model to estimate 1-year risk of DLI for coronary lesions where revascularization was not performed following FFR assessment. A prediction model for DLI was developed from a cohort of 721 patients with 882 coronary lesions where revascularization was deferred based on FFR between 10/2002 and 7/2010. Deferred lesion intervention was defined as any revascularization of a lesion previously deferred following FFR. The final DLI model was developed using stepwise Cox regression and validated using bootstrapping techniques. An algorithm was constructed to predict the 1-year risk of DLI. During a mean (±SD) follow-up period of 4.0 ± 2.3 years, 18% of lesions deferred after FFR underwent DLI; the 1-year incidence of DLI was 5.3%, while the predicted risk of DLI varied from 1 to 40%. The final Cox model included the FFR value, age, current or former smoking, history of coronary artery disease (CAD) or prior percutaneous coronary intervention, multi-vessel CAD, and serum creatinine. The c statistic for the DLI prediction model was 0.66 (95% confidence interval, CI: 0.61-0.70). Patients deferred revascularization based on FFR have variation in their risk for DLI. A clinical prediction model consisting of five clinical variables and the FFR value can help predict the risk of DLI in the first year following FFR assessment. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.

Leigh syndrome associated with a novel mutation in the COX15 gene.

PubMed

Miryounesi, Mohammad; Fardaei, Majid; Tabei, Seyed Mohammadbagher; Ghafouri-Fard, Soudeh

2016-06-01

Leigh syndrome (LS) is a subacute necrotizing encephalomyelopathy with a diverse range of symptoms, such as psychomotor delay or regression, weakness, hypotonia, truncal ataxia, intention tremor as well as lactic acidosis in the blood, cerebrospinal fluid or urine. Both nuclear gene defects and mutations of the mitochondrial genome have been detected in these patients. Here we report a 7-year-old girl with hypotonia, tremor, developmental delay and psychomotor regression. However, serum lactate level as well as brain magnetic resonance imaging were normal. Mutational analysis has revealed a novel mutation in exon 4 of COX15 gene (c.415C>G) which results in p.Leu139Val. Previous studies have demonstrated that COX15 mutations are associated with typical LS as well as fatal infantile hypertrophic cardiomyopathy. Consequently, clinical manifestations of COX15 mutations may be significantly different in patients. Such information is of practical importance in genetic counseling.

Quantitative laser-induced breakdown spectroscopy data using peak area step-wise regression analysis: an alternative method for interpretation of Mars science laboratory results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clegg, Samuel M; Barefield, James E; Wiens, Roger C

2008-01-01

The ChemCam instrument on the Mars Science Laboratory (MSL) will include a laser-induced breakdown spectrometer (LIBS) to quantify major and minor elemental compositions. The traditional analytical chemistry approach to calibration curves for these data regresses a single diagnostic peak area against concentration for each element. This approach contrasts with a new multivariate method in which elemental concentrations are predicted by step-wise multiple regression analysis based on areas of a specific set of diagnostic peaks for each element. The method is tested on LIBS data from igneous and metamorphosed rocks. Between 4 and 13 partial regression coefficients are needed to describemore » each elemental abundance accurately (i.e., with a regression line of R{sup 2} > 0.9995 for the relationship between predicted and measured elemental concentration) for all major and minor elements studied. Validation plots suggest that the method is limited at present by the small data set, and will work best for prediction of concentration when a wide variety of compositions and rock types has been analyzed.« less

Identification of molecular markers associated with mite resistance in coconut (Cocos nucifera L.).

PubMed

Shalini, K V; Manjunatha, S; Lebrun, P; Berger, A; Baudouin, L; Pirany, N; Ranganath, R M; Prasad, D Theertha

2007-01-01

Coconut mite (Aceria guerreronis 'Keifer') has become a major threat to Indian coconut (Coçcos nucifera L.) cultivators and the processing industry. Chemical and biological control measures have proved to be costly, ineffective, and ecologically undesirable. Planting mite-resistant coconut cultivars is the most effective method of preventing yield loss and should form a major component of any integrated pest management stratagem. Coconut genotypes, and mite-resistant and -susceptible accessions were collected from different parts of South India. Thirty-two simple sequence repeat (SSR) and 7 RAPD primers were used for molecular analyses. In single-marker analysis, 9 SSR and 4 RAPD markers associated with mite resistance were identified. In stepwise multiple regression analysis of SSRs, a combination of 6 markers showed 100% association with mite infestation. Stepwise multiple regression analysis for RAPD data revealed that a combination of 3 markers accounted for 83.86% of mite resistance in the selected materials. Combined stepwise multiple regression analysis of RAPD and SSR data showed that a combination of 5 markers explained 100% of the association with mite resistance in coconut. Markers associated with mite resistance are important in coconut breeding programs and will facilitate the selection of mite-resistant plants at an early stage as well as mother plants for breeding programs.

Hypnotism as a Function of Trance State Effects, Expectancy, and Suggestibility: An Italian Replication.

PubMed

Pekala, Ronald J; Baglio, Francesca; Cabinio, Monia; Lipari, Susanna; Baglio, Gisella; Mendozzi, Laura; Cecconi, Pietro; Pugnetti, Luigi; Sciaky, Riccardo

2017-01-01

Previous research using stepwise regression analyses found self-reported hypnotic depth (srHD) to be a function of suggestibility, trance state effects, and expectancy. This study sought to replicate and expand that research using a general state measure of hypnotic responsivity, the Phenomenology of Consciousness Inventory: Hypnotic Assessment Procedure (PCI-HAP). Ninety-five participants completed an Italian translation of the PCI-HAP, with srHD scores predicted from the PCI-HAP assessment items. The regression analysis replicated the previous research results. Additionally, stepwise regression analyses were able to predict the srHD score equally well using only the PCI dimension scores. These results not only replicated prior research but suggest how this methodology to assess hypnotic responsivity, when combined with more traditional neurophysiological and cognitive-behavioral methodologies, may allow for a more comprehensive understanding of that enigma called hypnosis.

Temperature and cell-type dependency of sulfide effects on mitochondrial respiration.

PubMed

Groeger, Michael; Matallo, Jose; McCook, Oscar; Wagner, Florian; Wachter, Ulrich; Bastian, Olga; Gierer, Saskia; Reich, Vera; Stahl, Bettina; Huber-Lang, Markus; Szabó, Csaba; Georgieff, Michael; Radermacher, Peter; Calzia, Enrico; Wagner, Katja

2012-10-01

Previous studies suggest that sulfide-induced inhibition of cytochrome c oxidase (cCox) and, consequently, the metabolic and toxic effects of sulfide are less pronounced at low body temperature. Because the temperature-dependent effects of sulfide on the inflammatory response are still a matter of debate, we investigated the impact of varying temperature on the cCox excess capacity and the mitochondrial sulfide oxidation by the sulfide-ubiquinone oxidoreductase in macrophage-derived cell lines (AMJ2-C11 and RAW 264.7). Using an oxygraph chamber, the inhibition of mitochondrial respiration was measured by stepwise titrations with sulfide and the nonmetabolizable cCox inhibitor sodium azide at 25°C and 37°C. Using the latter of the two inhibitors, the excess capacity of the cCox was obtained. Furthermore, we quantified the capacity of these cells to withstand sulfide inhibition by measuring the amount required to inhibit respiration by 50% and 90% and the viability of the cells after 24-h exposure to 100 ppm of hydrogen sulfide. At low titration rates, the AMJ2-C11 cells, but not the RAW 264.7 cells, increased their capacity to withstand exogenously added sulfide. This effect was even greater at 25°C than at 37°C. Furthermore, only the AMJ2-C11 cells remained viable after sulfide exposure for 24 h. In contrast, only in the RAW 264.7 cells that an increase in cCox excess capacity was found at low temperatures. In macrophage-derived cell lines, both the excess capacity of cCox and the efficiency of sulfide elimination may increase at low temperatures. These properties may modify the effects of sulfide in immune cells and, potentially, the inflammatory response during sulfide exposure at different body temperatures.

[Use of multiple regression models in observational studies (1970-2013) and requirements of the STROBE guidelines in Spanish scientific journals].

PubMed

Real, J; Cleries, R; Forné, C; Roso-Llorach, A; Martínez-Sánchez, J M

In medicine and biomedical research, statistical techniques like logistic, linear, Cox and Poisson regression are widely known. The main objective is to describe the evolution of multivariate techniques used in observational studies indexed in PubMed (1970-2013), and to check the requirements of the STROBE guidelines in the author guidelines in Spanish journals indexed in PubMed. A targeted PubMed search was performed to identify papers that used logistic linear Cox and Poisson models. Furthermore, a review was also made of the author guidelines of journals published in Spain and indexed in PubMed and Web of Science. Only 6.1% of the indexed manuscripts included a term related to multivariate analysis, increasing from 0.14% in 1980 to 12.3% in 2013. In 2013, 6.7, 2.5, 3.5, and 0.31% of the manuscripts contained terms related to logistic, linear, Cox and Poisson regression, respectively. On the other hand, 12.8% of journals author guidelines explicitly recommend to follow the STROBE guidelines, and 35.9% recommend the CONSORT guideline. A low percentage of Spanish scientific journals indexed in PubMed include the STROBE statement requirement in the author guidelines. Multivariate regression models in published observational studies such as logistic regression, linear, Cox and Poisson are increasingly used both at international level, as well as in journals published in Spanish. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Multi-omics facilitated variable selection in Cox-regression model for cancer prognosis prediction.

PubMed

Liu, Cong; Wang, Xujun; Genchev, Georgi Z; Lu, Hui

2017-07-15

New developments in high-throughput genomic technologies have enabled the measurement of diverse types of omics biomarkers in a cost-efficient and clinically-feasible manner. Developing computational methods and tools for analysis and translation of such genomic data into clinically-relevant information is an ongoing and active area of investigation. For example, several studies have utilized an unsupervised learning framework to cluster patients by integrating omics data. Despite such recent advances, predicting cancer prognosis using integrated omics biomarkers remains a challenge. There is also a shortage of computational tools for predicting cancer prognosis by using supervised learning methods. The current standard approach is to fit a Cox regression model by concatenating the different types of omics data in a linear manner, while penalty could be added for feature selection. A more powerful approach, however, would be to incorporate data by considering relationships among omics datatypes. Here we developed two methods: a SKI-Cox method and a wLASSO-Cox method to incorporate the association among different types of omics data. Both methods fit the Cox proportional hazards model and predict a risk score based on mRNA expression profiles. SKI-Cox borrows the information generated by these additional types of omics data to guide variable selection, while wLASSO-Cox incorporates this information as a penalty factor during model fitting. We show that SKI-Cox and wLASSO-Cox models select more true variables than a LASSO-Cox model in simulation studies. We assess the performance of SKI-Cox and wLASSO-Cox using TCGA glioblastoma multiforme and lung adenocarcinoma data. In each case, mRNA expression, methylation, and copy number variation data are integrated to predict the overall survival time of cancer patients. Our methods achieve better performance in predicting patients' survival in glioblastoma and lung adenocarcinoma. Copyright © 2017. Published by Elsevier Inc.

The Breslow estimator of the nonparametric baseline survivor function in Cox's regression model: some heuristics.

PubMed

Hanley, James A

2008-01-01

Most survival analysis textbooks explain how the hazard ratio parameters in Cox's life table regression model are estimated. Fewer explain how the components of the nonparametric baseline survivor function are derived. Those that do often relegate the explanation to an "advanced" section and merely present the components as algebraic or iterative solutions to estimating equations. None comment on the structure of these estimators. This note brings out a heuristic representation that may help to de-mystify the structure.

A statistical model for Windstorm Variability over the British Isles based on Large-scale Atmospheric and Oceanic Mechanisms

NASA Astrophysics Data System (ADS)

Kirchner-Bossi, Nicolas; Befort, Daniel J.; Wild, Simon B.; Ulbrich, Uwe; Leckebusch, Gregor C.

2016-04-01

Time-clustered winter storms are responsible for a majority of the wind-induced losses in Europe. Over last years, different atmospheric and oceanic large-scale mechanisms as the North Atlantic Oscillation (NAO) or the Meridional Overturning Circulation (MOC) have been proven to drive some significant portion of the windstorm variability over Europe. In this work we systematically investigate the influence of different large-scale natural variability modes: more than 20 indices related to those mechanisms with proven or potential influence on the windstorm frequency variability over Europe - mostly SST- or pressure-based - are derived by means of ECMWF ERA-20C reanalysis during the last century (1902-2009), and compared to the windstorm variability for the European winter (DJF). Windstorms are defined and tracked as in Leckebusch et al. (2008). The derived indices are then employed to develop a statistical procedure including a stepwise Multiple Linear Regression (MLR) and an Artificial Neural Network (ANN), aiming to hindcast the inter-annual (DJF) regional windstorm frequency variability in a case study for the British Isles. This case study reveals 13 indices with a statistically significant coupling with seasonal windstorm counts. The Scandinavian Pattern (SCA) showed the strongest correlation (0.61), followed by the NAO (0.48) and the Polar/Eurasia Pattern (0.46). The obtained indices (standard-normalised) are selected as predictors for a windstorm variability hindcast model applied for the British Isles. First, a stepwise linear regression is performed, to identify which mechanisms can explain windstorm variability best. Finally, the indices retained by the stepwise regression are used to develop a multlayer perceptron-based ANN that hindcasted seasonal windstorm frequency and clustering. Eight indices (SCA, NAO, EA, PDO, W.NAtl.SST, AMO (unsmoothed), EA/WR and Trop.N.Atl SST) are retained by the stepwise regression. Among them, SCA showed the highest linear coefficient, followed by SST in western Atlantic, AMO and NAO. The explanatory regression model (considering all time steps) provided a Coefficient of Determination (R^2) of 0.75. A predictive version of the linear model applying a leave-one-out cross-validation (LOOCV) shows an R2 of 0.56 and a relative RMSE of 4.67 counts/season. An ANN-based nonlinear hindcast model for the seasonal windstorm frequency is developed with the aim to improve the stepwise hindcast ability and thus better predict a time-clustered season over the case study. A 7 node-hidden layer perceptron is set, and the LOOCV procedure reveals a R2 of 0.71. In comparison to the stepwise MLR the RMSE is reduced a 20%. This work shows that for the British Isles case study, most of the interannual variability can be explained by certain large-scale mechanisms, considering also nonlinear effects (ANN). This allows to discern a time-clustered season from a non-clustered one - a key issue for applications e.g., in the (re)insurance industry.

Estimating extent of mortality associated with the Douglas-fir beetle in the Central and Northern Rockies

Treesearch

Jose F. Negron; Willis C. Schaupp; Kenneth E. Gibson; John Anhold; Dawn Hansen; Ralph Thier; Phil Mocettini

1999-01-01

Data collected from Douglas-fir stands infected by the Douglas-fir beetle in Wyoming, Montana, Idaho, and Utah, were used to develop models to estimate amount of mortality in terms of basal area killed. Models were built using stepwise linear regression and regression tree approaches. Linear regression models using initial Douglas-fir basal area were built for all...

Use of Cox's Cure Model to Establish Clinical Determinants of Long-Term Disease-Free Survival in Neoadjuvant-Chemotherapy-Treated Breast Cancer Patients without Pathologic Complete Response.

PubMed

Asano, Junichi; Hirakawa, Akihiro; Hamada, Chikuma; Yonemori, Kan; Hirata, Taizo; Shimizu, Chikako; Tamura, Kenji; Fujiwara, Yasuhiro

2013-01-01

In prognostic studies for breast cancer patients treated with neoadjuvant chemotherapy (NAC), the ordinary Cox proportional-hazards (PH) model has been often used to identify prognostic factors for disease-free survival (DFS). This model assumes that all patients eventually experience relapse or death. However, a subset of NAC-treated breast cancer patients never experience these events during long-term follow-up (>10 years) and may be considered clinically "cured." Clinical factors associated with cure have not been studied adequately. Because the ordinary Cox PH model cannot be used to identify such clinical factors, we used the Cox PH cure model, a recently developed statistical method. This model includes both a logistic regression component for the cure rate and a Cox regression component for the hazard for uncured patients. The purpose of this study was to identify the clinical factors associated with cure and the variables associated with the time to recurrence or death in NAC-treated breast cancer patients without a pathologic complete response, by using the Cox PH cure model. We found that hormone receptor status, clinical response, human epidermal growth factor receptor 2 status, histological grade, and the number of lymph node metastases were associated with cure.

Modeling time-to-event (survival) data using classification tree analysis.

PubMed

Linden, Ariel; Yarnold, Paul R

2017-12-01

Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

Semi-parametric regression model for survival data: graphical visualization with R

PubMed Central

2016-01-01

Cox proportional hazards model is a semi-parametric model that leaves its baseline hazard function unspecified. The rationale to use Cox proportional hazards model is that (I) the underlying form of hazard function is stringent and unrealistic, and (II) researchers are only interested in estimation of how the hazard changes with covariate (relative hazard). Cox regression model can be easily fit with coxph() function in survival package. Stratified Cox model may be used for covariate that violates the proportional hazards assumption. The relative importance of covariates in population can be examined with the rankhazard package in R. Hazard ratio curves for continuous covariates can be visualized using smoothHR package. This curve helps to better understand the effects that each continuous covariate has on the outcome. Population attributable fraction is a classic quantity in epidemiology to evaluate the impact of risk factor on the occurrence of event in the population. In survival analysis, the adjusted/unadjusted attributable fraction can be plotted against survival time to obtain attributable fraction function. PMID:28090517

A global goodness-of-fit statistic for Cox regression models.

PubMed

Parzen, M; Lipsitz, S R

1999-06-01

In this paper, a global goodness-of-fit test statistic for a Cox regression model, which has an approximate chi-squared distribution when the model has been correctly specified, is proposed. Our goodness-of-fit statistic is global and has power to detect if interactions or higher order powers of covariates in the model are needed. The proposed statistic is similar to the Hosmer and Lemeshow (1980, Communications in Statistics A10, 1043-1069) goodness-of-fit statistic for binary data as well as Schoenfeld's (1980, Biometrika 67, 145-153) statistic for the Cox model. The methods are illustrated using data from a Mayo Clinic trial in primary billiary cirrhosis of the liver (Fleming and Harrington, 1991, Counting Processes and Survival Analysis), in which the outcome is the time until liver transplantation or death. The are 17 possible covariates. Two Cox proportional hazards models are fit to the data, and the proposed goodness-of-fit statistic is applied to the fitted models.

Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…

Cox proportional hazards model of myopic regression for laser in situ keratomileusis flap creation with a femtosecond laser and with a mechanical microkeratome.

PubMed

Lin, Meng-Yin; Chang, David C K; Hsu, Wen-Ming; Wang, I-Jong

2012-06-01

To compare predictive factors for postoperative myopic regression between laser in situ keratomileusis (LASIK) with a femtosecond laser and LASIK with a mechanical microkeratome. Nobel Eye Clinic, Taipei, Taiwan. Retrospective comparative study. Refractive outcomes were recorded 1 day, 1 week, and 1, 3, 6, 9, and 12 months after LASIK. A Cox proportional hazards model was used to evaluate the impact of the 2 flap-creating methods and other covariates on postoperative myopic regression. The femtosecond group comprised 409 eyes and the mechanical microkeratome group, 377 eyes. For both methods, significant predictors for myopic regression after LASIK included preoperative manifest spherical equivalent (P=.0001) and central corneal thickness (P=.027). Laser in situ keratomileusis with a mechanical microkeratome had a higher probability of postoperative myopic regression than LASIK with a femtosecond laser (P=.0002). After adjusting for other covariates in the Cox proportional hazards model, the cumulative risk for myopic regression with a mechanical microkeratome was higher than with a femtosecond laser 12 months postoperatively (P=.0002). With the definition of myopic regression as a myopic shift of 0.50 diopter (D) or more and residual myopia of -0.50 D or less, the risk estimate based on the mean covariates in all eyes in the femtosecond group and mechanical microkeratome group at 12 months was 43.6% and 66.9%, respectively. Laser in situ keratomileusis with a mechanical microkeratome had a higher risk for myopic regression than LASIK with a femtosecond laser through 12 months postoperatively. Copyright © 2012. Published by Elsevier Inc.

ORACLE INEQUALITIES FOR THE LASSO IN THE COX MODEL

PubMed Central

Huang, Jian; Sun, Tingni; Ying, Zhiliang; Yu, Yi; Zhang, Cun-Hui

2013-01-01

We study the absolute penalized maximum partial likelihood estimator in sparse, high-dimensional Cox proportional hazards regression models where the number of time-dependent covariates can be larger than the sample size. We establish oracle inequalities based on natural extensions of the compatibility and cone invertibility factors of the Hessian matrix at the true regression coefficients. Similar results based on an extension of the restricted eigenvalue can be also proved by our method. However, the presented oracle inequalities are sharper since the compatibility and cone invertibility factors are always greater than the corresponding restricted eigenvalue. In the Cox regression model, the Hessian matrix is based on time-dependent covariates in censored risk sets, so that the compatibility and cone invertibility factors, and the restricted eigenvalue as well, are random variables even when they are evaluated for the Hessian at the true regression coefficients. Under mild conditions, we prove that these quantities are bounded from below by positive constants for time-dependent covariates, including cases where the number of covariates is of greater order than the sample size. Consequently, the compatibility and cone invertibility factors can be treated as positive constants in our oracle inequalities. PMID:24086091

ORACLE INEQUALITIES FOR THE LASSO IN THE COX MODEL.

PubMed

Huang, Jian; Sun, Tingni; Ying, Zhiliang; Yu, Yi; Zhang, Cun-Hui

2013-06-01

We study the absolute penalized maximum partial likelihood estimator in sparse, high-dimensional Cox proportional hazards regression models where the number of time-dependent covariates can be larger than the sample size. We establish oracle inequalities based on natural extensions of the compatibility and cone invertibility factors of the Hessian matrix at the true regression coefficients. Similar results based on an extension of the restricted eigenvalue can be also proved by our method. However, the presented oracle inequalities are sharper since the compatibility and cone invertibility factors are always greater than the corresponding restricted eigenvalue. In the Cox regression model, the Hessian matrix is based on time-dependent covariates in censored risk sets, so that the compatibility and cone invertibility factors, and the restricted eigenvalue as well, are random variables even when they are evaluated for the Hessian at the true regression coefficients. Under mild conditions, we prove that these quantities are bounded from below by positive constants for time-dependent covariates, including cases where the number of covariates is of greater order than the sample size. Consequently, the compatibility and cone invertibility factors can be treated as positive constants in our oracle inequalities.

Quantitative structure-activity relationship of the curcumin-related compounds using various regression methods

NASA Astrophysics Data System (ADS)

Khazaei, Ardeshir; Sarmasti, Negin; Seyf, Jaber Yousefi

2016-03-01

Quantitative structure activity relationship were used to study a series of curcumin-related compounds with inhibitory effect on prostate cancer PC-3 cells, pancreas cancer Panc-1 cells, and colon cancer HT-29 cells. Sphere exclusion method was used to split data set in two categories of train and test set. Multiple linear regression, principal component regression and partial least squares were used as the regression methods. In other hand, to investigate the effect of feature selection methods, stepwise, Genetic algorithm, and simulated annealing were used. In two cases (PC-3 cells and Panc-1 cells), the best models were generated by a combination of multiple linear regression and stepwise (PC-3 cells: r2 = 0.86, q2 = 0.82, pred_r2 = 0.93, and r2m (test) = 0.43, Panc-1 cells: r2 = 0.85, q2 = 0.80, pred_r2 = 0.71, and r2m (test) = 0.68). For the HT-29 cells, principal component regression with stepwise (r2 = 0.69, q2 = 0.62, pred_r2 = 0.54, and r2m (test) = 0.41) is the best method. The QSAR study reveals descriptors which have crucial role in the inhibitory property of curcumin-like compounds. 6ChainCount, T_C_C_1, and T_O_O_7 are the most important descriptors that have the greatest effect. With a specific end goal to design and optimization of novel efficient curcumin-related compounds it is useful to introduce heteroatoms such as nitrogen, oxygen, and sulfur atoms in the chemical structure (reduce the contribution of T_C_C_1 descriptor) and increase the contribution of 6ChainCount and T_O_O_7 descriptors. Models can be useful in the better design of some novel curcumin-related compounds that can be used in the treatment of prostate, pancreas, and colon cancers.

Influence of storage conditions on the stability of monomeric anthocyanins studied by reversed-phase high-performance liquid chromatography.

PubMed

Morais, Helena; Ramos, Cristina; Forgács, Esther; Cserháti, Tibor; Oliviera, José

2002-04-25

The effect of light, storage time and temperature on the decomposition rate of monomeric anthocyanin pigments extracted from skins of grape (Vitis vinifera var. Red globe) was determined by reversed-phase high-performance liquid chromatography (RP-HPLC). The impact of various storage conditions on the pigment stability was assessed by stepwise regression analysis. RP-HPLC separated well the five anthocyanins identified and proved the presence of other unidentified pigments at lower concentrations. Stepwise regression analysis confirmed that the overall decomposition rate of monomeric anthocyanins, peonidin-3-glucoside and malvidin-3-glucoside significantly depended on the time and temperature of storage, the effect of storage time being the most important. The presence or absence of light exerted a negligible impact on the decomposition rate.

Estimation of longitudinal stability and control derivatives for an icing research aircraft from flight data

NASA Technical Reports Server (NTRS)

Batterson, James G.; Omara, Thomas M.

1989-01-01

The results of applying a modified stepwise regression algorithm and a maximum likelihood algorithm to flight data from a twin-engine commuter-class icing research aircraft are presented. The results are in the form of body-axis stability and control derivatives related to the short-period, longitudinal motion of the aircraft. Data were analyzed for the baseline (uniced) and for the airplane with an artificial glaze ice shape attached to the leading edge of the horizontal tail. The results are discussed as to the accuracy of the derivative estimates and the difference between the derivative values found for the baseline and the iced airplane. Additional comparisons were made between the maximum likelihood results and the modified stepwise regression results with causes for any discrepancies postulated.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

PubMed

Ching, Travers; Zhu, Xun; Garmire, Lana X

2018-04-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

Box-Cox transformation of left-censored data with application to the analysis of coronary artery calcification and pharmacokinetic data.

PubMed

Han, Cong; Kronmal, Richard

2004-12-15

Box-Cox transformation is investigated for regression models for left-censored data. Examples are provided using coronary calcification data from the Multi-Ethnic Study of Atherosclerosis and pharmacokinetic data of a nicotine nasal spray. Copyright 2004 John Wiley & Sons, Ltd.

Predictors of course in obsessive-compulsive disorder: logistic regression versus Cox regression for recurrent events.

PubMed

Kempe, P T; van Oppen, P; de Haan, E; Twisk, J W R; Sluis, A; Smit, J H; van Dyck, R; van Balkom, A J L M

2007-09-01

Two methods for predicting remissions in obsessive-compulsive disorder (OCD) treatment are evaluated. Y-BOCS measurements of 88 patients with a primary OCD (DSM-III-R) diagnosis were performed over a 16-week treatment period, and during three follow-ups. Remission at any measurement was defined as a Y-BOCS score lower than thirteen combined with a reduction of seven points when compared with baseline. Logistic regression models were compared with a Cox regression for recurrent events model. Logistic regression yielded different models at different evaluation times. The recurrent events model remained stable when fewer measurements were used. Higher baseline levels of neuroticism and more severe OCD symptoms were associated with a lower chance of remission, early age of onset and more depressive symptoms with a higher chance. Choice of outcome time affects logistic regression prediction models. Recurrent events analysis uses all information on remissions and relapses. Short- and long-term predictors for OCD remission show overlap.

Comparison of four staging systems of lymph node metastasis in gastric cancer.

PubMed

Zhang, Ming; Zhu, Guanyu; Ma, Yan; Xue, Yingwei

2009-11-01

The classification of lymph node metastasis in patients with gastric cancer is still controversial. Our aim was to evaluate the relative merits of four staging systems of lymph node metastasis. In our study, the nodal status was classified according to the 5th edition of the tumor node metastasis (TNM) system, the Japanese Classification of Gastric Carcinoma (JCGC), the ratio of metastatic lymph nodes, and the size of the largest metastatic lymph node. Each staging system was scored as good (+2), fair (+1), or poor (0) with respect to the theoretical value (extent of the anatomical lymphatic tumor spread), convenience (simplicity), surgical applicability (extent of lymph node dissection), and prognostic value (ability to predict survival rate). In the multivariate analysis including the four staging systems and other potential prognostic factors, stepwise Cox regression revealed that the ratio of metastatic lymph nodes was the most independent prognostic factor. The TNM, ratio, and size systems were convenient because they had no consideration for the location of the tumor and lymph node. Although the JCGC system had advantages in theoretical value and surgical application, it was most optional due to the complexity of the system. Although all different staging systems are comparable, the metastatic lymph node ratio system is convenient, reproducible, and has the highest ability to predict survival.

Association of pretreatment neutrophil-lymphocyte ratio and outcome in emergency colorectal cancer care.

PubMed

Palin, R P; Devine, A T; Hicks, G; Burke, D

2018-04-01

Introduction The association between the neutrophil-lymphocyte ratio (NLR) and outcome in elective colorectal cancer surgery is well established; the relationship between NLR and the emergency colorectal cancer patient is, as yet, unexplored. This paper evaluates the predictive quality of the NLR for outcome in the emergency colorectal cancer patient. Materials and Methods A total of 187 consecutive patients who underwent emergency surgery for colorectal cancer were included in the study. NLR was calculated from the haematological tests done on admission. Receiver operating characteristic analyses were used to determine the most suitable cut-off for NLR. Outcomes were assessed by mortality at 30 and 90 days using stepwise Cox proportional hazards regression. Results An NLR cut-off of 5 was found to have the highest sensitivity and specificity. At 30 days, age and time from admission to surgery were associated with increased mortality; a high NLR was associated with an increased risk of mortality in univariate but not multivariate analysis. At 90 days, age, NLR, time from admission to surgery and nodal status were all significantly associated with increased mortality on multivariate analysis. Conclusions Pre-operative NLR is a cheap, easily performed and useful clinical tool to aid prediction of outcome in the emergency colorectal cancer patient.

A simple prognostic model for overall survival in metastatic renal cell carcinoma.

PubMed

Assi, Hazem I; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

2016-01-01

The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis.

A simple prognostic model for overall survival in metastatic renal cell carcinoma

PubMed Central

Assi, Hazem I.; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

2016-01-01

Introduction: The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. Methods: We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. Results: There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. Conclusions: In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis. PMID:27217858

Pre-Stroke Weight Loss is Associated with Post-Stroke Mortality among Men in the Honolulu-Asia Aging Study

PubMed Central

Bell, Christina L.; Rantanen, Taina; Chen, Randi; Davis, James; Petrovitch, Helen; Ross, G. Webster; Masaki, Kamal

2013-01-01

Objective To examine baseline pre-stroke weight loss and post-stroke mortality among men. Design Longitudinal study of late-life pre-stroke body mass index (BMI), weight loss and BMI change (midlife to late-life), with up to 8-year incident stroke and mortality follow-up. Setting Honolulu Heart Program/Honolulu-Asia Aging Study. Participants 3,581 Japanese-American men aged 71–93 years and stroke-free at baseline. Main Outcome Measure Post-stroke Mortality: 30-day post-stroke, analyzed with stepwise multivariable logistic regression and long-term post-stroke (up to 8-year), analyzed with stepwise multivariable Cox regression. Results Weight loss (10-pound decrements) was associated with increased 30-day post-stroke mortality (aOR=1.48, 95%CI 1.14–1.92), long-term mortality after incident stroke (all types n=225, aHR=1.25, 95%CI=1.09–1.44) and long-term mortality after incident thromboembolic stroke (n=153, aHR 1.19, 95%CI-1.01–1.40). Men with overweight/obese late-life BMI (≥25kg/m2, compared to normal/underweight BMI) had increased long-term mortality after incident hemorrhagic stroke (n=54, aHR=2.27, 95%CI=1.07–4.82). Neither desirable nor excessive BMI reductions (vs. no change/increased BMI) were associated with post-stroke mortality. In the overall sample (n=3,581), nutrition factors associated with increased long-term mortality included 1) weight loss (10-pound decrements, aHR=1.15, 1.09–1.21); 2) underweight BMI (vs. normal BMI, aHR=1.76, 1.40–2.20); and 3) both desirable and excessive BMI reductions (vs. no change or gain, separate model from weight loss and BMI, aHRs=1.36–1.97, p<0.001). Conclusions Although obesity is a risk factor for stroke incidence, pre-stroke weight loss was associated with increased post-stroke (all types and thromboembolic) mortality. Overweight/obese late-life BMI was associated with increased post-hemorrhagic stroke mortality. Desirable and excessive BMI reductions were not associated with post-stroke mortality. Weight loss, underweight late-life BMI and any BMI reduction were all associated with increased long-term mortality in the overall sample. PMID:24113337

Multiple linear regression analysis

NASA Technical Reports Server (NTRS)

Edwards, T. R.

1980-01-01

Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

Proton radius from electron scattering data

NASA Astrophysics Data System (ADS)

Higinbotham, Douglas W.; Kabir, Al Amin; Lin, Vincent; Meekins, David; Norum, Blaine; Sawatzky, Brad

2016-05-01

Background: The proton charge radius extracted from recent muonic hydrogen Lamb shift measurements is significantly smaller than that extracted from atomic hydrogen and electron scattering measurements. The discrepancy has become known as the proton radius puzzle. Purpose: In an attempt to understand the discrepancy, we review high-precision electron scattering results from Mainz, Jefferson Lab, Saskatoon, and Stanford. Methods: We make use of stepwise regression techniques using the F test as well as the Akaike information criterion to systematically determine the predictive variables to use for a given set and range of electron scattering data as well as to provide multivariate error estimates. Results: Starting with the precision, low four-momentum transfer (Q2) data from Mainz (1980) and Saskatoon (1974), we find that a stepwise regression of the Maclaurin series using the F test as well as the Akaike information criterion justify using a linear extrapolation which yields a value for the proton radius that is consistent with the result obtained from muonic hydrogen measurements. Applying the same Maclaurin series and statistical criteria to the 2014 Rosenbluth results on GE from Mainz, we again find that the stepwise regression tends to favor a radius consistent with the muonic hydrogen radius but produces results that are extremely sensitive to the range of data included in the fit. Making use of the high-Q2 data on GE to select functions which extrapolate to high Q2, we find that a Padé (N =M =1 ) statistical model works remarkably well, as does a dipole function with a 0.84 fm radius, GE(Q2) =(1+Q2/0.66 GeV2) -2 . Conclusions: Rigorous applications of stepwise regression techniques and multivariate error estimates result in the extraction of a proton charge radius that is consistent with the muonic hydrogen result of 0.84 fm; either from linear extrapolation of the extremely-low-Q2 data or by use of the Padé approximant for extrapolation using a larger range of data. Thus, based on a purely statistical analysis of electron scattering data, we conclude that the electron scattering results and the muonic hydrogen results are consistent. It is the atomic hydrogen results that are the outliers.

Research: Treatment Study to determine the durability of glycaemic control with early treatment with a vildagliptin–metformin combination regimen vs. standard-of-care metformin monotherapy—the VERIFY trial: a randomized double-blind trial

PubMed Central

Del Prato, S; Foley, J E; Kothny, W; Kozlovski, P; Stumvoll, M; Paldánius, P M; Matthews, D R

2014-01-01

Aims Durability of good glycaemic control (HbA1c) is of importance as it can be the foundation for delaying diabetic complications. It has been hypothesized that early initiation of treatment with the combination of oral anti-diabetes agents with complementary mechanisms of action can increase the durability of glycaemic control compared with metformin monotherapy followed by a stepwise addition of oral agents. Dipeptidyl peptidase-4 inhibitors are good candidates for early use as they are efficacious in combination with metformin, show weight neutrality and a low risk of hypoglycaemia. We aimed to test the hypothesis that early combined treatment of metformin and vildagliptin slows β-cell deterioration as measured by HbA1c. Methods Approximately 2000 people with Type 2 diabetes mellitus who were drug-naive or who were treated with metformin for less than 1 month, and who have HbA1c of 48–58 mmol/mol (6.5–7.5%), will be randomized in a 1:1 ratio in VERIFY, a 5-year multinational, double-blind, parallel-group study designed to compare early initiation of a vildagliptin–metformin combination with standard-of-care initiation of metformin monotherapy, followed by the stepwise addition of vildagliptin when glycaemia deteriorates. Further deterioration will be treated with insulin. The primary analysis for treatment failure will be from a Cox proportional hazard regression model and the durability of glycaemic control will be evaluated by assessing treatment failure rate and the rate of loss in glycaemic control over time as co-primary endpoints. Summary VERIFY is the first study to investigate the long-term clinical benefits of early combination treatment vs. the standard-of-care metformin monotherapy with a second agent added by threshold criteria. PMID:24863949

Comparison of Risk Factor Profiles for Primary Open-Angle Glaucoma Subtypes Defined by Pattern of Visual Field Loss: A Prospective Study.

PubMed

Kang, Jae H; Loomis, Stephanie J; Rosner, Bernard A; Wiggs, Janey L; Pasquale, Louis R

2015-04-01

We explored whether risk factor associations differed by primary open-angle glaucoma (POAG) subtypes defined by visual field (VF) loss pattern (i.e., paracentral or peripheral). We included 77,157 women in the Nurses' Health Study (NHS) and 42,773 men in the Health Professionals Follow-up Study (HPFS 1986-2010), and incident medical record confirmed cases of paracentral (n = 440) and peripheral (n = 865) POAG subtypes. We evaluated African heritage, glaucoma family history, body mass index (BMI), mean arterial blood pressure, diabetes mellitus, physical activity, smoking, caffeine intake, and alcohol intake. We used competing risk Cox regression analyses modeling age as the metameter and stratified by age, cohort, and event type. We sequentially identified factors with the least significant differences in associations with POAG subtypes ("stepwise down" approach with P for heterogeneity [P-het] < 0.10 as threshold). Body mass index was more inversely associated with the POAG paracentral VF loss subtype than the peripheral VF loss subtype (per 10 kg/m2; hazard ratio [HR] = 0.67 [95% confidence interval (CI): 0.52, 0.86] versus HR = 0.93 [95% CI: 0.78, 1.10]; P-het = 0.03) as was smoking (per 10 pack-years; HR = 0.92 [95% CI: 0.87, 0.98] versus HR = 0.98 [95% CI: 0.94, 1.01]; P-het = 0.09). These findings were robust in sensitivity analyses using a "stepwise up" approach (identify factors that showed the most significant differences). Nonheterogeneous (P-het > 0.10) adverse associations with both POAG subtypes were observed with glaucoma family history, diabetes, African heritage, greater caffeine intake, and higher mean arterial pressure. These data indicate that POAG with early paracentral VF loss has distinct as well as common determinants compared with POAG with peripheral VF loss.

Patients started on hemodialysis with tunneled dialysis catheter have similar survival after arteriovenous fistula and arteriovenous graft creation.

PubMed

Yuo, Theodore H; Chaer, Rabih A; Dillavou, Ellen D; Leers, Steven A; Makaroun, Michel S

2015-12-01

Current guidelines suggest that arteriovenous fistula (AVF) is associated with survival advantage over arteriovenous graft (AVG). However, AVFs often require months to become functional, increasing tunneled dialysis catheter (TDC) use, which can erode the benefit of an AVF. We sought to compare survival in patients with end-stage renal disease after creation of an AVF or AVG in patients starting hemodialysis (HD) with a TDC and to identify patient populations that may benefit from preferential use of AVG over AVF. Using U.S. Renal Data System databases, we identified incident HD patients in 2005 through 2008 and observed them through 2008. Initial access type and clinical variables including albumin levels were assessed using U.S. Renal Data System data collection forms. Attempts at AVF and AVG creation in patients who started HD through a TDC were identified by Current Procedural Terminology codes. We accounted for the effect of changes in access type by truncating follow-up when an additional AVF or AVG was performed. Survival curves were then constructed, and log-rank tests were used for pairwise survival comparisons, stratified by age. Multivariate analysis was performed with Cox proportional hazards regressions; variables were chosen using stepwise elimination. An interaction of access type and albumin level was detected, and Cox models using differing thresholds for albumin level were constructed. The primary outcome was survival. Among the 138,245 patients who started with a TDC and had complete records amenable for analysis, 22.8% underwent AVF creation (mean age ± standard deviation, 68.9 ± 12.5 years; 27.8% mortality at 1 year) and 7.6% underwent AVG placement (70.2 ± 12.0 years; 28.2% mortality) within 3 months of HD initiation; 69.6% remained with a TDC (63.2 ± 15.4 years; 33.8% mortality). In adjusted Cox proportional hazards regression, AVF creation is equivalent to AVG placement in terms of survival (hazard ratio [HR], 0.98; 95% confidence interval [CI], 0.93-1.02; P = .349). AVG placement is superior to continued TDC use (HR, 1.54; 95% CI, 1.48-1.61; P < .001). In patients older than 80 years with albumin levels >4.0 g/dL, AVF creation is associated with higher mortality hazard compared with AVG creation (HR, 1.22; 95% CI, 1.04-1.43; P = .013). For patients who start HD through a TDC, placement of an AVF and AVG is associated with similar mortality hazard. Further study is necessary to determine the ideal access for patients in whom the survival advantage of an AVF over an AVG is uncertain. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Comparison of exact, efron and breslow parameter approach method on hazard ratio and stratified cox regression model

NASA Astrophysics Data System (ADS)

Fatekurohman, Mohamat; Nurmala, Nita; Anggraeni, Dian

2018-04-01

Lungs are the most important organ, in the case of respiratory system. Problems related to disorder of the lungs are various, i.e. pneumonia, emphysema, tuberculosis and lung cancer. Comparing all those problems, lung cancer is the most harmful. Considering about that, the aim of this research applies survival analysis and factors affecting the endurance of the lung cancer patient using comparison of exact, Efron and Breslow parameter approach method on hazard ratio and stratified cox regression model. The data applied are based on the medical records of lung cancer patients in Jember Paru-paru hospital on 2016, east java, Indonesia. The factors affecting the endurance of the lung cancer patients can be classified into several criteria, i.e. sex, age, hemoglobin, leukocytes, erythrocytes, sedimentation rate of blood, therapy status, general condition, body weight. The result shows that exact method of stratified cox regression model is better than other. On the other hand, the endurance of the patients is affected by their age and the general conditions.

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

PubMed

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

Cytopathologic differential diagnosis of low-grade urothelial carcinoma and reactive urothelial proliferation in bladder washings: a logistic regression analysis.

PubMed

Cakir, Ebru; Kucuk, Ulku; Pala, Emel Ebru; Sezer, Ozlem; Ekin, Rahmi Gokhan; Cakmak, Ozgur

2017-05-01

Conventional cytomorphologic assessment is the first step to establish an accurate diagnosis in urinary cytology. In cytologic preparations, the separation of low-grade urothelial carcinoma (LGUC) from reactive urothelial proliferation (RUP) can be exceedingly difficult. The bladder washing cytologies of 32 LGUC and 29 RUP were reviewed. The cytologic slides were examined for the presence or absence of the 28 cytologic features. The cytologic criteria showing statistical significance in LGUC were increased numbers of monotonous single (non-umbrella) cells, three-dimensional cellular papillary clusters without fibrovascular cores, irregular bordered clusters, atypical single cells, irregular nuclear overlap, cytoplasmic homogeneity, increased N/C ratio, pleomorphism, nuclear border irregularity, nuclear eccentricity, elongated nuclei, and hyperchromasia (p ˂ 0.05), and the cytologic criteria showing statistical significance in RUP were inflammatory background, mixture of small and large urothelial cells, loose monolayer aggregates, and vacuolated cytoplasm (p ˂ 0.05). When these variables were subjected to a stepwise logistic regression analysis, four features were selected to distinguish LGUC from RUP: increased numbers of monotonous single (non-umbrella) cells, increased nuclear cytoplasmic ratio, hyperchromasia, and presence of small and large urothelial cells (p = 0.0001). By this logistic model of the 32 cases with proven LGUC, the stepwise logistic regression analysis correctly predicted 31 (96.9%) patients with this diagnosis, and of the 29 patients with RUP, the logistic model correctly predicted 26 (89.7%) patients as having this disease. There are several cytologic features to separate LGUC from RUP. Stepwise logistic regression analysis is a valuable tool for determining the most useful cytologic criteria to distinguish these entities. © 2017 APMIS. Published by John Wiley & Sons Ltd.

Extended cox regression model: The choice of timefunction

NASA Astrophysics Data System (ADS)

Isik, Hatice; Tutkun, Nihal Ata; Karasoy, Durdu

2017-07-01

Cox regression model (CRM), which takes into account the effect of censored observations, is one the most applicative and usedmodels in survival analysis to evaluate the effects of covariates. Proportional hazard (PH), requires a constant hazard ratio over time, is the assumptionofCRM. Using extended CRM provides the test of including a time dependent covariate to assess the PH assumption or an alternative model in case of nonproportional hazards. In this study, the different types of real data sets are used to choose the time function and the differences between time functions are analyzed and discussed.

Personality predicts time to remission and clinical status in hypochondriasis during a 6-year follow-up.

PubMed

Greeven, Anja; van Balkom, Anton J L M; Spinhoven, Philip

2014-05-01

We aimed to investigate whether personality characteristics predict time to remission and psychiatric status. The follow-up was at most 6 years and was performed within the scope of a randomized controlled trial that investigated the efficacy of cognitive behavioral therapy, paroxetine, and placebo in hypochondriasis. The Life Chart Interview was administered to investigate for each year if remission had occurred. Personality was assessed at pretest by the Abbreviated Dutch Temperament and Character Inventory. Cox's regression models for recurrent events were compared with logistic regression models. Sixteen (36.4%) of 44 patients achieved remission during the follow-up period. Cox's regression yielded approximately the same results as the logistic regression. Being less harm avoidant and more cooperative were associated with a shorter time to remission and a remitted state after the follow-up period. Personality variables seem to be relevant for describing patients with a more chronic course of hypochondriacal complaints.

ELASTIC NET FOR COX'S PROPORTIONAL HAZARDS MODEL WITH A SOLUTION PATH ALGORITHM.

PubMed

Wu, Yichao

2012-01-01

For least squares regression, Efron et al. (2004) proposed an efficient solution path algorithm, the least angle regression (LAR). They showed that a slight modification of the LAR leads to the whole LASSO solution path. Both the LAR and LASSO solution paths are piecewise linear. Recently Wu (2011) extended the LAR to generalized linear models and the quasi-likelihood method. In this work we extend the LAR further to handle Cox's proportional hazards model. The goal is to develop a solution path algorithm for the elastic net penalty (Zou and Hastie (2005)) in Cox's proportional hazards model. This goal is achieved in two steps. First we extend the LAR to optimizing the log partial likelihood plus a fixed small ridge term. Then we define a path modification, which leads to the solution path of the elastic net regularized log partial likelihood. Our solution path is exact and piecewise determined by ordinary differential equation systems.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data

PubMed Central

Ching, Travers; Zhu, Xun

2018-01-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet. PMID:29634719

Effects of electroacupuncture on luteal regression and steroidogenesis in ovarian hyperstimulation syndrome model rat.

PubMed

Huang, Xuan; Chen, Li; Xia, You-Bing; Xie, Min; Sun, Qin; Yao, Bing

2018-03-15

Electroacupuncture (EA) is an effective and safe therapeutic method widely used for treating clinical diseases. Previously, we found that EA could decrease serum hormones and reduce ovarian size in ovarian hyperstimulation syndrome (OHSS) rat model. Nevertheless, the mechanisms that contribute to these improvements remain unclear. HE staining was used to count the number of corpora lutea (CL) and follicles. Immunohistochemical and ELISA were applied to examine luteal functional and structural regression. Immunoprecipitation was used for analyzing the interaction between NPY (neuropeptide Y) and COX-2; western blotting and qRT-PCR were used to evaluate the expressions of steroidogenic enzymes and PKA/CREB pathway. EA treatment significantly reduced the ovarian weight and the number of CL, also decreased ovarian and serum levels of PGE2 and COX-2 expression; increased ovarian PGF2α levels and PGF2α/PGE2 ratio; decreased PCNA expression and distribution; and increased cyclin regulatory inhibitor p27 expression to have further effect on the luteal formation, and promote luteal functional and structural regression. Moreover, expression of COX-2 in ovaries was possessed interactivity increased expression of NPY. Furthermore, EA treatment lowered the serum hormone levels, inhibited PKA/CREB pathway and decreased the expressions of steroidogenic enzymes. Hence, interaction with COX-2, NPY may affect the levels of PGF2α and PGE2 as well as impact the proliferation of granulosa cells in ovaries, thus further reducing the luteal formation, and promoting luteal structural and functional regression, as well as the ovarian steroidogenesis following EA treatment. EA treatment could be an option for preventing OHSS in ART. Copyright © 2018 Elsevier Inc. All rights reserved.

Evaluation of methodology for the analysis of 'time-to-event' data in pharmacogenomic genome-wide association studies.

PubMed

Syed, Hamzah; Jorgensen, Andrea L; Morris, Andrew P

2016-06-01

To evaluate the power to detect associations between SNPs and time-to-event outcomes across a range of pharmacogenomic study designs while comparing alternative regression approaches. Simulations were conducted to compare Cox proportional hazards modeling accounting for censoring and logistic regression modeling of a dichotomized outcome at the end of the study. The Cox proportional hazards model was demonstrated to be more powerful than the logistic regression analysis. The difference in power between the approaches was highly dependent on the rate of censoring. Initial evaluation of single-nucleotide polymorphism association signals using computationally efficient software with dichotomized outcomes provides an effective screening tool for some design scenarios, and thus has important implications for the development of analytical protocols in pharmacogenomic studies.

Experiments to Determine Whether Recursive Partitioning (CART) or an Artificial Neural Network Overcomes Theoretical Limitations of Cox Proportional Hazards Regression

NASA Technical Reports Server (NTRS)

Kattan, Michael W.; Hess, Kenneth R.; Kattan, Michael W.

1998-01-01

New computationally intensive tools for medical survival analyses include recursive partitioning (also called CART) and artificial neural networks. A challenge that remains is to better understand the behavior of these techniques in effort to know when they will be effective tools. Theoretically they may overcome limitations of the traditional multivariable survival technique, the Cox proportional hazards regression model. Experiments were designed to test whether the new tools would, in practice, overcome these limitations. Two datasets in which theory suggests CART and the neural network should outperform the Cox model were selected. The first was a published leukemia dataset manipulated to have a strong interaction that CART should detect. The second was a published cirrhosis dataset with pronounced nonlinear effects that a neural network should fit. Repeated sampling of 50 training and testing subsets was applied to each technique. The concordance index C was calculated as a measure of predictive accuracy by each technique on the testing dataset. In the interaction dataset, CART outperformed Cox (P less than 0.05) with a C improvement of 0.1 (95% Cl, 0.08 to 0.12). In the nonlinear dataset, the neural network outperformed the Cox model (P less than 0.05), but by a very slight amount (0.015). As predicted by theory, CART and the neural network were able to overcome limitations of the Cox model. Experiments like these are important to increase our understanding of when one of these new techniques will outperform the standard Cox model. Further research is necessary to predict which technique will do best a priori and to assess the magnitude of superiority.

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Survival analysis of postoperative nausea and vomiting in patients receiving patient-controlled epidural analgesia.

PubMed

Lee, Shang-Yi; Hung, Chih-Jen; Chen, Chih-Chieh; Wu, Chih-Cheng

2014-11-01

Postoperative nausea and vomiting as well as postoperative pain are two major concerns when patients undergo surgery and receive anesthetics. Various models and predictive methods have been developed to investigate the risk factors of postoperative nausea and vomiting, and different types of preventive managements have subsequently been developed. However, there continues to be a wide variation in the previously reported incidence rates of postoperative nausea and vomiting. This may have occurred because patients were assessed at different time points, coupled with the overall limitation of the statistical methods used. However, using survival analysis with Cox regression, and thus factoring in these time effects, may solve this statistical limitation and reveal risk factors related to the occurrence of postoperative nausea and vomiting in the following period. In this retrospective, observational, uni-institutional study, we analyzed the results of 229 patients who received patient-controlled epidural analgesia following surgery from June 2007 to December 2007. We investigated the risk factors for the occurrence of postoperative nausea and vomiting, and also assessed the effect of evaluating patients at different time points using the Cox proportional hazards model. Furthermore, the results of this inquiry were compared with those results using logistic regression. The overall incidence of postoperative nausea and vomiting in our study was 35.4%. Using logistic regression, we found that only sex, but not the total doses and the average dose of opioids, had significant effects on the occurrence of postoperative nausea and vomiting at some time points. Cox regression showed that, when patients consumed a higher average dose of opioids, this correlated with a higher incidence of postoperative nausea and vomiting with a hazard ratio of 1.286. Survival analysis using Cox regression showed that the average consumption of opioids played an important role in postoperative nausea and vomiting, a result not found by logistic regression. Therefore, the incidence of postoperative nausea and vomiting in patients cannot be reliably determined on the basis of a single visit at one point in time. Copyright © 2014. Published by Elsevier Taiwan.

Factors determining disease duration in Alzheimer's disease: a postmortem study of 103 cases using the Kaplan-Meier estimator and Cox regression.

PubMed

Armstrong, R A

2014-01-01

Factors associated with duration of dementia in a consecutive series of 103 Alzheimer's disease (AD) cases were studied using the Kaplan-Meier estimator and Cox regression analysis (proportional hazard model). Mean disease duration was 7.1 years (range: 6 weeks-30 years, standard deviation = 5.18); 25% of cases died within four years, 50% within 6.9 years, and 75% within 10 years. Familial AD cases (FAD) had a longer duration than sporadic cases (SAD), especially cases linked to presenilin (PSEN) genes. No significant differences in duration were associated with age, sex, or apolipoprotein E (Apo E) genotype. Duration was reduced in cases with arterial hypertension. Cox regression analysis suggested longer duration was associated with an earlier disease onset and increased senile plaque (SP) and neurofibrillary tangle (NFT) pathology in the orbital gyrus (OrG), CA1 sector of the hippocampus, and nucleus basalis of Meynert (NBM). The data suggest shorter disease duration in SAD and in cases with hypertensive comorbidity. In addition, degree of neuropathology did not influence survival, but spread of SP/NFT pathology into the frontal lobe, hippocampus, and basal forebrain was associated with longer disease duration.

Comparison of Cox's Regression Model and Parametric Models in Evaluating the Prognostic Factors for Survival after Liver Transplantation in Shiraz during 2000-2012.

PubMed

Adelian, R; Jamali, J; Zare, N; Ayatollahi, S M T; Pooladfar, G R; Roustaei, N

2015-01-01

Identification of the prognostic factors for survival in patients with liver transplantation is challengeable. Various methods of survival analysis have provided different, sometimes contradictory, results from the same data. To compare Cox's regression model with parametric models for determining the independent factors for predicting adults' and pediatrics' survival after liver transplantation. This study was conducted on 183 pediatric patients and 346 adults underwent liver transplantation in Namazi Hospital, Shiraz, southern Iran. The study population included all patients undergoing liver transplantation from 2000 to 2012. The prognostic factors sex, age, Child class, initial diagnosis of the liver disease, PELD/MELD score, and pre-operative laboratory markers were selected for survival analysis. Among 529 patients, 346 (64.5%) were adult and 183 (34.6%) were pediatric cases. Overall, the lognormal distribution was the best-fitting model for adult and pediatric patients. Age in adults (HR=1.16, p<0.05) and weight (HR=2.68, p<0.01) and Child class B (HR=2.12, p<0.05) in pediatric patients were the most important factors for prediction of survival after liver transplantation. Adult patients younger than the mean age and pediatric patients weighing above the mean and Child class A (compared to those with classes B or C) had better survival. Parametric regression model is a good alternative for the Cox's regression model.

Survival analysis of cervical cancer using stratified Cox regression

NASA Astrophysics Data System (ADS)

Purnami, S. W.; Inayati, K. D.; Sari, N. W. Wulan; Chosuvivatwong, V.; Sriplung, H.

2016-04-01

Cervical cancer is one of the mostly widely cancer cause of the women death in the world including Indonesia. Most cervical cancer patients come to the hospital already in an advanced stadium. As a result, the treatment of cervical cancer becomes more difficult and even can increase the death's risk. One of parameter that can be used to assess successfully of treatment is the probability of survival. This study raises the issue of cervical cancer survival patients at Dr. Soetomo Hospital using stratified Cox regression based on six factors such as age, stadium, treatment initiation, companion disease, complication, and anemia. Stratified Cox model is used because there is one independent variable that does not satisfy the proportional hazards assumption that is stadium. The results of the stratified Cox model show that the complication variable is significant factor which influent survival probability of cervical cancer patient. The obtained hazard ratio is 7.35. It means that cervical cancer patient who has complication is at risk of dying 7.35 times greater than patient who did not has complication. While the adjusted survival curves showed that stadium IV had the lowest probability of survival.

The use of machine learning for the identification of peripheral artery disease and future mortality risk.

PubMed

Ross, Elsie Gyang; Shah, Nigam H; Dalman, Ronald L; Nead, Kevin T; Cooke, John P; Leeper, Nicholas J

2016-11-01

A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aims of this study were to develop machine learning algorithms for the identification of disease and the prognostication of mortality risk and to determine whether such models perform better than classical statistical analyses. Focusing on peripheral artery disease (PAD), patient data were derived from a prospective, observational study of 1755 patients who presented for elective coronary angiography. We employed multiple supervised machine learning algorithms and used diverse clinical, demographic, imaging, and genomic information in a hypothesis-free manner to build models that could identify patients with PAD and predict future mortality. Comparison was made to standard stepwise linear regression models. Our machine-learned models outperformed stepwise logistic regression models both for the identification of patients with PAD (area under the curve, 0.87 vs 0.76, respectively; P = .03) and for the prediction of future mortality (area under the curve, 0.76 vs 0.65, respectively; P = .10). Both machine-learned models were markedly better calibrated than the stepwise logistic regression models, thus providing more accurate disease and mortality risk estimates. Machine learning approaches can produce more accurate disease classification and prediction models. These tools may prove clinically useful for the automated identification of patients with highly morbid diseases for which aggressive risk factor management can improve outcomes. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Identification of International Classification of Functioning, Disability and Health categories for patients with peripheral arterial disease.

PubMed

Vyskocil, Erich; Gruther, Wolfgang; Steiner, Irene; Schuhfried, Othmar

2014-07-01

Disease-specific categories of the International Classification of Functioning, Disability and Health have not yet been described for patients with chronic peripheral arterial obstructive disease (PAD). The authors examined the relationship between the categories of the Brief Core Sets for ischemic heart diseases with the Peripheral Artery Questionnaire and the ankle-brachial index to determine which International Classification of Functioning, Disability and Health categories are most relevant for patients with PAD. This is a retrospective cohort study including 77 patients with verified PAD. Statistical analyses of the relationship between International Classification of Functioning, Disability and Health categories as independent variables and the endpoints Peripheral Artery Questionnaire or ankle-brachial index were carried out by simple and stepwise linear regression models adjusting for age, sex, and leg (left vs. right). The stepwise linear regression model with the ankle-brachial index as dependent variable revealed a significant effect of the variables blood vessel functions and muscle endurance functions. Calculating a stepwise linear regression model with the Peripheral Artery Questionnaire as dependent variable, a significant effect of age, emotional functions, energy and drive functions, carrying out daily routine, as well as walking could be observed. This study identifies International Classification of Functioning, Disability and Health categories in the Brief Core Sets for ischemic heart diseases that show a significant effect on the ankle-brachial index and the Peripheral Artery Questionnaire score in patients with PAD. These categories provide fundamental information on functioning of patients with PAD and patient-centered outcomes for rehabilitation interventions.

Clinical utility of the AlphaFIM® instrument in stroke rehabilitation.

PubMed

Lo, Alexander; Tahair, Nicola; Sharp, Shelley; Bayley, Mark T

2012-02-01

The AlphaFIM instrument is an assessment tool designed to facilitate discharge planning of stroke patients from acute care, by extrapolating overall functional status from performance in six key Functional Independence Measure (FIM) instrument items. To determine whether acute care AlphaFIM rating is correlated to stroke rehabilitation outcomes. In this prospective observational study, data were analyzed from 891 patients referred for inpatient stroke rehabilitation through an Internet-based referral system. Simple linear and stepwise regression models determined correlations between rehabilitation-ready AlphaFIM rating and rehabilitation outcomes (admission and discharge FIM ratings, FIM gain, FIM efficiency, and length of stay). Covariates including demographic data, stroke characteristics, medical history, cognitive deficits, and activity tolerance were included in the stepwise regressions. The AlphaFIM instrument was significant in predicting admission and discharge FIM ratings at rehabilitation (adjusted R² 0.40 and 0.28, respectively; P < 0.0001) and was weakly correlated with FIM gain and length of stay (adjusted R² 0.04 and 0.09, respectively; P < 0.0001), but not FIM efficiency. AlphaFIM rating was inversely related to FIM gain. Age, bowel incontinence, left hemiparesis, and previous infarcts were negative predictors of discharge FIM rating on stepwise regression. Intact executive function and physical activity tolerance of 30 to 60 mins were predictors of FIM gain. The AlphaFIM instrument is a valuable tool for triaging stroke patients from acute care to rehabilitation and predicts functional status at discharge from rehabilitation. Patients with low AlphaFIM ratings have the potential to make significant functional gains and should not be denied admission to inpatient rehabilitation programs.

Proton radius from electron scattering data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Higinbotham, Douglas W.; Kabir, Al Amin; Lin, Vincent

Background: The proton charge radius extracted from recent muonic hydrogen Lamb shift measurements is significantly smaller than that extracted from atomic hydrogen and electron scattering measurements. The discrepancy has become known as the proton radius puzzle. Purpose: In an attempt to understand the discrepancy, we review high-precision electron scattering results from Mainz, Jefferson Lab, Saskatoon and Stanford. Methods: We make use of stepwise regression techniques using the F-test as well as the Akaike information criterion to systematically determine the predictive variables to use for a given set and range of electron scattering data as well as to provide multivariate errormore » estimates. Results: Starting with the precision, low four-momentum transfer (Q 2) data from Mainz (1980) and Saskatoon (1974), we find that a stepwise regression of the Maclaurin series using the F-test as well as the Akaike information criterion justify using a linear extrapolation which yields a value for the proton radius that is consistent with the result obtained from muonic hydrogen measurements. Applying the same Maclaurin series and statistical criteria to the 2014 Rosenbluth results on GE from Mainz, we again find that the stepwise regression tends to favor a radius consistent with the muonic hydrogen radius but produces results that are extremely sensitive to the range of data included in the fit. Making use of the high-Q 2 data on G E to select functions which extrapolate to high Q 2, we find that a Pad´e (N = M = 1) statistical model works remarkably well, as does a dipole function with a 0.84 fm radius, G E(Q 2) = (1 + Q 2/0.66 GeV 2) -2. Conclusions: Rigorous applications of stepwise regression techniques and multivariate error estimates result in the extraction of a proton charge radius that is consistent with the muonic hydrogen result of 0.84 fm; either from linear extrapolation of the extreme low-Q 2 data or by use of the Pad´e approximant for extrapolation using a larger range of data. Thus, based on a purely statistical analysis of electron scattering data, we conclude that the electron scattering result and the muonic hydrogen result are consistent. Lastly, it is the atomic hydrogen results that are the outliers.« less

Proton radius from electron scattering data

DOE PAGES

Higinbotham, Douglas W.; Kabir, Al Amin; Lin, Vincent; ...

2016-05-31

Background: The proton charge radius extracted from recent muonic hydrogen Lamb shift measurements is significantly smaller than that extracted from atomic hydrogen and electron scattering measurements. The discrepancy has become known as the proton radius puzzle. Purpose: In an attempt to understand the discrepancy, we review high-precision electron scattering results from Mainz, Jefferson Lab, Saskatoon and Stanford. Methods: We make use of stepwise regression techniques using the F-test as well as the Akaike information criterion to systematically determine the predictive variables to use for a given set and range of electron scattering data as well as to provide multivariate errormore » estimates. Results: Starting with the precision, low four-momentum transfer (Q 2) data from Mainz (1980) and Saskatoon (1974), we find that a stepwise regression of the Maclaurin series using the F-test as well as the Akaike information criterion justify using a linear extrapolation which yields a value for the proton radius that is consistent with the result obtained from muonic hydrogen measurements. Applying the same Maclaurin series and statistical criteria to the 2014 Rosenbluth results on GE from Mainz, we again find that the stepwise regression tends to favor a radius consistent with the muonic hydrogen radius but produces results that are extremely sensitive to the range of data included in the fit. Making use of the high-Q 2 data on G E to select functions which extrapolate to high Q 2, we find that a Pad´e (N = M = 1) statistical model works remarkably well, as does a dipole function with a 0.84 fm radius, G E(Q 2) = (1 + Q 2/0.66 GeV 2) -2. Conclusions: Rigorous applications of stepwise regression techniques and multivariate error estimates result in the extraction of a proton charge radius that is consistent with the muonic hydrogen result of 0.84 fm; either from linear extrapolation of the extreme low-Q 2 data or by use of the Pad´e approximant for extrapolation using a larger range of data. Thus, based on a purely statistical analysis of electron scattering data, we conclude that the electron scattering result and the muonic hydrogen result are consistent. Lastly, it is the atomic hydrogen results that are the outliers.« less

Box-Cox transformation of firm size data in statistical analysis

NASA Astrophysics Data System (ADS)

Chen, Ting Ting; Takaishi, Tetsuya

2014-03-01

Firm size data usually do not show the normality that is often assumed in statistical analysis such as regression analysis. In this study we focus on two firm size data: the number of employees and sale. Those data deviate considerably from a normal distribution. To improve the normality of those data we transform them by the Box-Cox transformation with appropriate parameters. The Box-Cox transformation parameters are determined so that the transformed data best show the kurtosis of a normal distribution. It is found that the two firm size data transformed by the Box-Cox transformation show strong linearity. This indicates that the number of employees and sale have the similar property as a firm size indicator. The Box-Cox parameters obtained for the firm size data are found to be very close to zero. In this case the Box-Cox transformations are approximately a log-transformation. This suggests that the firm size data we used are approximately log-normal distributions.

Prognostic Significance of Tumor Necrosis in Hilar Cholangiocarcinoma.

PubMed

Atanasov, Georgi; Schierle, Katrin; Hau, Hans-Michael; Dietel, Corinna; Krenzien, Felix; Brandl, Andreas; Wiltberger, Georg; Englisch, Julianna Paulina; Robson, Simon C; Reutzel-Selke, Anja; Pascher, Andreas; Jonas, Sven; Pratschke, Johann; Benzing, Christian; Schmelzle, Moritz

2017-02-01

Tumor necrosis and peritumoral fibrosis have both been suggested to have a prognostic value in selected solid tumors. However, little is known regarding their influence on tumor progression and prognosis in hilar cholangiocarcinoma (HC). Surgically resected tumor specimens of HC (n = 47) were analyzed for formation of necrosis and extent of peritumoral fibrosis. Tumor necrosis and grade of fibrosis were assessed histologically and correlated with clinicopathological characteristics, tumor recurrence, and patients' survival. Univariate Kaplan-Meier analysis and a stepwise multivariable Cox regression model were applied. Mild peritumoral fibrosis was evident in 12 tumor samples, moderate peritumoral fibrosis in 20, and high-grade fibrosis in 15. Necrosis was evident in 19 of 47 tumor samples. Patients with tumors characterized by necrosis showed a significantly decreased 5-year recurrence-free survival (37.9 vs. 25.7 %; p < .05) and a significantly decreased 5-year overall survival (42.6 vs. 12.4 %; p < .05), when compared with patients with tumors showing no necrosis. R status, tumor recurrence, and tumor necrosis were of prognostic value in the univariate analysis (all p < .05). Multivariate survival analysis confirmed tumor necrosis (p = .038) as the only independent prognostic variable. The assessment of tumor necrosis appears as a valuable additional prognostic tool in routine histopathological evaluation of HC. These observations might have implications for monitoring and more individualized multimodal therapeutic strategies.

Genetic variants in Fanconi Anemia Pathway Genes BRCA2 and FANCA Predict Melanoma Survival

PubMed Central

Liu, Zhensheng; Wang, Li-E; Chen, Wei V.; Zhu, Dakai; Amos, Christopher I.; Fang, Shenying; Lee, Jeffrey E.; Wei, Qingyi

2014-01-01

Cutaneous melanoma (CM) is the most lethal skin cancer. The Fanconi Anemia (FA) pathway involved in DNA crosslinks repair may affect CM susceptibility and prognosis. Using data derived from published genome-wide association study, we comprehensively analyzed the associations of 2339 common single nucleotide polymorphisms (SNPs) in 14 autosomal FA genes with overall survival (OS) in 858 CM patients. By performing false-positive report probability corrections and stepwise Cox proportional hazards regression analyses, we identified significant associations between CM OS and four putatively functional SNPs: BRCA2 rs10492396 [AG vs. GG: adjusted hazard ratio (adjHR)=1.85, 95% confident interval (CI)=1.16-2.95, P=0.010], rs206118 (CC vs. TT+TC: adjHR=2.44, 95% CI=1.27-4.67, P=0.007), rs3752447 (CC vs. TT+TC: adjHR=2.10, 95% CI=1.38-3.18, P=0.0005), and FANCA rs62068372 (TT vs. CC+CT: adjHR=1.85, 95% CI=1.27-2.69, P=0.001). Moreover, patients with an increasing number of unfavorable genotypes (NUG) of these loci had markedly reduced OS and melanoma-specific survival (MSS). The final model incorporating with NUG, tumor stage and Breslow thickness showed an improved discriminatory ability to classify both 5-year OS and 5-year MSS. Additional investigations, preferably prospective studies, are needed to validate our findings. PMID:25243787

Genetic variants in fanconi anemia pathway genes BRCA2 and FANCA predict melanoma survival.

PubMed

Yin, Jieyun; Liu, Hongliang; Liu, Zhensheng; Wang, Li-E; Chen, Wei V; Zhu, Dakai; Amos, Christopher I; Fang, Shenying; Lee, Jeffrey E; Wei, Qingyi

2015-02-01

Cutaneous melanoma (CM) is the most lethal skin cancer. The Fanconi anemia (FA) pathway involved in DNA crosslink repair may affect CM susceptibility and prognosis. Using data derived from published genome-wide association study, we comprehensively analyzed the associations of 2,339 common single-nucleotide polymorphisms (SNPs) in 14 autosomal FA genes with overall survival (OS) in 858 CM patients. By performing false-positive report probability corrections and stepwise Cox proportional hazards regression analyses, we identified significant associations between CM OS and four putatively functional SNPs: BRCA2 rs10492396 (AG vs. GG: adjusted hazard ratio (adjHR)=1.85, 95% confidence interval (CI)=1.16-2.95, P=0.010), rs206118 (CC vs. TT+TC: adjHR=2.44, 95% CI=1.27-4.67, P=0.007), rs3752447 (CC vs. TT+TC: adjHR=2.10, 95% CI=1.38-3.18, P=0.0005), and FANCA rs62068372 (TT vs. CC+CT: adjHR=1.85, 95% CI=1.27-2.69, P=0.001). Moreover, patients with an increasing number of unfavorable genotypes (NUG) of these loci had markedly reduced OS and melanoma-specific survival (MSS). The final model incorporating with NUG, tumor stage, and Breslow thickness showed an improved discriminatory ability to classify both 5-year OS and 5-year MSS. Additional investigations, preferably prospective studies, are needed to validate our findings.

Transcardiac increase in norepinephrine and prognosis in patients with chronic heart failure.

PubMed

Tsutamoto, Takayoshi; Nishiyama, Keizo; Sakai, Hiroshi; Tanaka, Toshinari; Fujii, Masanori; Yamamoto, Takashi; Yamaji, Masayuki; Horie, Minoru

2008-12-01

No previous study has compared the transcardiac gradient of norepinephrine (NE) and the prognosis of patients with chronic heart failure (CHF). To evaluate the prognostic role of the transcardiac gradient of NE in patients with CHF. We measured haemodynamic parameters and plasma levels of NE, brain natriuretic peptide (BNP) and N-terminal proBNP (NT-proBNP) in the aortic root (AO) and coronary sinus (CS) in 356 consecutive patients with CHF. During a median follow-up of 3.5 years, 40 patients died. Transcardiac gradients of BNP (273+/-276 vs. 472+/-433 pg/mL, p<0.0001), NT-proBNP (417+/-700 vs. 928+/-1093 pg/mL, p<0.0001) and NE (114+/-160 vs. 473+/-992 pg/mL, p<0.0001) were significantly higher in non-survivors than survivors. After adjustment for clinical variables associated with CHF including haemodynamics and neurohumoral factors, the transcardiac gradient of NE (p<0.0001) and plasma log NT-proBNP (p<0.0001) were independent prognostic predictors. Among 67 patients in whom 123I-metaiodobenzylguanidine (MIBG) could be performed, transcardiac increase in NE was correlated with the washout rate (r=0.398, p=0.0009) and was a superior predictor of mortality than MIBG parameters on stepwise multivariable Cox proportional hazards regression analyses. The transcardiac increase in NE is an independent and useful prognostic predictor for evaluating the prognosis of CHF patients.

Fast track surgery: a clinical audit.

PubMed

Carter, Jonathan; Szabo, Rebecca; Sim, Wee Wee; Pather, Selvan; Philp, Shannon; Nattress, Kath; Cotterell, Stephen; Patel, Pinki; Dalrymple, Chris

2010-04-01

Fast track surgery is a concept that utilises a variety of techniques to reduce the surgical stress response, allowing a shortened length of stay, improved outcomes and decreased time to full recovery. To evaluate a peri-operative Fast Track Surgical Protocol (FTSP) in patients referred for abdominal surgery. All patients undergoing a laparotomy over a 12-month period were entered prospectively on a clinical database. Data were retrospectively analysed. Over the study period, 72 patients underwent a laparotomy. Average patient age was 54 years and average weight and BMI were 67.2 kg and 26 respectively. Sixty three (88%) patients had a vertical midline incision (VMI). There were no intraoperative blood transfusions. The median length of stay (LOS) was 3.0 days. Thirty eight patients (53%) were discharged on or before post op day 3, seven (10%) of whom were discharged on postoperative day 2. On stepwise regression analysis, the following were found to be independently associated with reduced LOS: able to tolerate early enteral nutrition, good performance status, use of COX inhibitor and transverse incision. In comparison with colleagues at the SGOG not undertaking FTS for their patients, the authors' LOS was lower and the RANZCOG modified Quality Indicators (QI's) did not demonstrate excess morbidity. Patients undergoing fast track surgery can be discharged from hospital with a reduced LOS, without an increased readmission rate and with comparative outcomes to non-fast tracked patients.

Prognostic value of 6-minute walk corridor test in patients with mild to moderate heart failure: comparison with other methods of functional evaluation.

PubMed

Rostagno, Carlo; Olivo, Giuseppe; Comeglio, Marco; Boddi, Vieri; Banchelli, Michela; Galanti, Giorgio; Gensini, Gian Franco

2003-06-01

The study was designed to evaluate the prognostic value of the 6-min walk test (6MWT) in patients with mild to moderate congestive heart failure (CHF). Two hundred and fourteen patients (119 men and 95 women, mean age 64 years) were followed for a mean period of 34 months to assess event-free survival (death, heart transplantation). Sixty-six patients (34%) died (63 cardiovascular causes, 2 cancer and 1 stroke) and five patients underwent heart transplantation. For patients who walked <300 m during the 6MWT, survival was 62% compared with 82% in patients who walked 300-450 m or>450 m. With univariate analysis, NYHA class was the strongest predictor of death. LVEF (P<0.0001), aetiology of heart failure (P<0.001), LV filling pattern (P=0.002) and 6MWT distance (P<0.01) were all significantly related to survival. No significant relationship was found between survival, peak oxygen consumption or anaerobic threshold. Multivariate analysis using the Cox-stepwise regression model showed that LV fractional shortening (P<0.009) and 6MWT distance (P<0.0005) were the strongest prognostic markers. A 6MWT distance of <300 m is a simple and useful prognostic marker of subsequent cardiac death in unselected patients with mild to moderate CHF.

Postoperative complications in cirrhotic pediatric deceased donor liver transplantation: Focus on transfusion therapy.

PubMed

Nacoti, M; Cazzaniga, S; Colombo, G; Corbella, D; Fazzi, F; Fochi, O; Gattoni, C; Zambelli, M; Colledan, M; Bonanomi, E

2017-12-01

Intraoperative transfusions seem associated with patient death and graft failure after PLTx. A retrospective analysis of recipients' and donors' characteristics and transplantation data in a cohort of patients undergoing PLTx from 2002 to 2013 at the Bergamo General Hospital was performed. A two-stage hierarchical Cox proportional hazard regression with forward stepwise selection was used to identify the main risk factors for major complications. In addition, propensity score analysis was used to adjust risk estimates for possible selection biases in the use of blood products. Over the 12-year period, 232 pediatric cirrhotic patients underwent PLTx. One-year patient and graft survival rates were 92.3% and 83.7%, respectively. The Kaplan-Meier shows that the main decrease in both graft and patient survival occurs during the first months post-transplantation. At the same time, it appears that most of the complications occur during the first month post-transplantation. One-month and 1-year patient complication-free survival rates were 24.8% and 12.1%, respectively. Our study shows that intraoperative red blood cells and platelet transfusions are independent risk factors for developing one or more major complications in the first year after PLTx. Decreasing major complications will improve the health status and overall long-term patient survival after pediatric PLTx. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

CORRELATION PURSUIT: FORWARD STEPWISE VARIABLE SELECTION FOR INDEX MODELS

PubMed Central

Zhong, Wenxuan; Zhang, Tingting; Zhu, Yu; Liu, Jun S.

2012-01-01

In this article, a stepwise procedure, correlation pursuit (COP), is developed for variable selection under the sufficient dimension reduction framework, in which the response variable Y is influenced by the predictors X1, X2, …, Xp through an unknown function of a few linear combinations of them. Unlike linear stepwise regression, COP does not impose a special form of relationship (such as linear) between the response variable and the predictor variables. The COP procedure selects variables that attain the maximum correlation between the transformed response and the linear combination of the variables. Various asymptotic properties of the COP procedure are established, and in particular, its variable selection performance under diverging number of predictors and sample size has been investigated. The excellent empirical performance of the COP procedure in comparison with existing methods are demonstrated by both extensive simulation studies and a real example in functional genomics. PMID:23243388

Censored quantile regression with recursive partitioning-based weights

PubMed Central

Wey, Andrew; Wang, Lan; Rudser, Kyle

2014-01-01

Censored quantile regression provides a useful alternative to the Cox proportional hazards model for analyzing survival data. It directly models the conditional quantile of the survival time and hence is easy to interpret. Moreover, it relaxes the proportionality constraint on the hazard function associated with the popular Cox model and is natural for modeling heterogeneity of the data. Recently, Wang and Wang (2009. Locally weighted censored quantile regression. Journal of the American Statistical Association 103, 1117–1128) proposed a locally weighted censored quantile regression approach that allows for covariate-dependent censoring and is less restrictive than other censored quantile regression methods. However, their kernel smoothing-based weighting scheme requires all covariates to be continuous and encounters practical difficulty with even a moderate number of covariates. We propose a new weighting approach that uses recursive partitioning, e.g. survival trees, that offers greater flexibility in handling covariate-dependent censoring in moderately high dimensions and can incorporate both continuous and discrete covariates. We prove that this new weighting scheme leads to consistent estimation of the quantile regression coefficients and demonstrate its effectiveness via Monte Carlo simulations. We also illustrate the new method using a widely recognized data set from a clinical trial on primary biliary cirrhosis. PMID:23975800

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time‐to‐Event Analysis

PubMed Central

Gong, Xiajing; Hu, Meng

2018-01-01

Abstract Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time‐to‐event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high‐dimensional data featured by a large number of predictor variables. Our results showed that ML‐based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high‐dimensional data. The prediction performances of ML‐based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML‐based methods provide a powerful tool for time‐to‐event analysis, with a built‐in capacity for high‐dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. PMID:29536640

Immunohistochemical and morphometric evaluation of COX-1 and COX-2 in the remodeled lung in idiopathic pulmonary fibrosis and systemic sclerosis* ,**

PubMed Central

Parra, Edwin Roger; Lin, Flavia; Martins, Vanessa; Rangel, Maristela Peres; Capelozzi, Vera Luiza

2013-01-01

OBJECTIVE: To study the expression of COX-1 and COX-2 in the remodeled lung in systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF) patients, correlating that expression with patient survival. METHODS: We examined open lung biopsy specimens from 24 SSc patients and 30 IPF patients, using normal lung tissue as a control. The histological patterns included fibrotic nonspecific interstitial pneumonia (NSIP) in SSc patients and usual interstitial pneumonia (UIP) in IPF patients. We used immunohistochemistry and histomorphometry to evaluate the expression of COX-1 and COX-2 in alveolar septa, vessels, and bronchioles. We then correlated that expression with pulmonary function test results and evaluated its impact on patient survival. RESULTS: The expression of COX-1 and COX-2 in alveolar septa was significantly higher in IPF-UIP and SSc-NSIP lung tissue than in the control tissue. No difference was found between IPF-UIP and SSc-NSIP tissue regarding COX-1 and COX-2 expression. Multivariate analysis based on the Cox regression model showed that the factors associated with a low risk of death were younger age, high DLCO/alveolar volume, IPF, and high COX-1 expression in alveolar septa, whereas those associated with a high risk of death were advanced age, low DLCO/alveolar volume, SSc (with NSIP), and low COX-1 expression in alveolar septa. CONCLUSIONS: Our findings suggest that strategies aimed at preventing low COX-1 synthesis will have a greater impact on SSc, whereas those aimed at preventing high COX-2 synthesis will have a greater impact on IPF. However, prospective randomized clinical trials are needed in order to confirm that. PMID:24473763

Quantile Regression with Censored Data

ERIC Educational Resources Information Center

Lin, Guixian

2009-01-01

The Cox proportional hazards model and the accelerated failure time model are frequently used in survival data analysis. They are powerful, yet have limitation due to their model assumptions. Quantile regression offers a semiparametric approach to model data with possible heterogeneity. It is particularly powerful for censored responses, where the…

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol lowering drugs

PubMed Central

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin

2013-01-01

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs.

PubMed

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G; Shah, Arvind K; Lin, Jianxin

2013-10-15

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the deviance information criterion is used to select the best transformation model. Because the model is quite complex, we develop a novel Monte Carlo Markov chain sampling scheme to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol-lowering drugs where the goal is to jointly model the three-dimensional response consisting of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). Because the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately; however, a multivariate approach would be more appropriate because these variables are correlated with each other. We carry out a detailed analysis of these data by using the proposed methodology. Copyright © 2013 John Wiley & Sons, Ltd.

Prognostic Significance of Carbohydrate Antigen 19-9 in Unresectable Locally Advanced Pancreatic Cancer Treated With Dose-Escalated Intensity Modulated Radiation Therapy and Concurrent Full-Dose Gemcitabine: Analysis of a Prospective Phase 1/2 Dose Escalation Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vainshtein, Jeffrey M., E-mail: jvainsh@med.umich.edu; Schipper, Matthew; Zalupski, Mark M.

2013-05-01

Purpose: Although established in the postresection setting, the prognostic value of carbohydrate antigen 19-9 (CA19-9) in unresectable locally advanced pancreatic cancer (LAPC) is less clear. We examined the prognostic utility of CA19-9 in patients with unresectable LAPC treated on a prospective trial of intensity modulated radiation therapy (IMRT) dose escalation with concurrent gemcitabine. Methods and Materials: Forty-six patients with unresectable LAPC were treated at the University of Michigan on a phase 1/2 trial of IMRT dose escalation with concurrent gemcitabine. CA19-9 was obtained at baseline and during routine follow-up. Cox models were used to assess the effect of baseline factorsmore » on freedom from local progression (FFLP), distant progression (FFDP), progression-free survival (PFS), and overall survival (OS). Stepwise forward regression was used to build multivariate predictive models for each endpoint. Results: Thirty-eight patients were eligible for the present analysis. On univariate analysis, baseline CA19-9 and age predicted OS, CA19-9 at baseline and 3 months predicted PFS, gross tumor volume (GTV) and black race predicted FFLP, and CA19-9 at 3 months predicted FFDP. On stepwise multivariate regression modeling, baseline CA19-9, age, and female sex predicted OS; baseline CA19-9 and female sex predicted both PFS and FFDP; and GTV predicted FFLP. Patients with baseline CA19-9 ≤90 U/mL had improved OS (median 23.0 vs 11.1 months, HR 2.88, P<.01) and PFS (14.4 vs 7.0 months, HR 3.61, P=.001). CA19-9 progression over 90 U/mL was prognostic for both OS (HR 3.65, P=.001) and PFS (HR 3.04, P=.001), and it was a stronger predictor of death than either local progression (HR 1.46, P=.42) or distant progression (HR 3.31, P=.004). Conclusions: In patients with unresectable LAPC undergoing definitive chemoradiation therapy, baseline CA19-9 was independently prognostic even after established prognostic factors were controlled for, whereas CA19-9 progression strongly predicted disease progression and death. Future trials should stratify by baseline CA19-9 and incorporate CA19-9 progression as a criterion for progressive disease.« less

Use of a pretest strategy for physical therapist assistant programs to predict success rate on the national physical therapy exam.

PubMed

Sloas, Stacey B; Keith, Becky; Whitehead, Malcolm T

2013-01-01

This study investigated a pretest strategy that identified physical therapist assistant (PTA) students who were at risk of failure on the National Physical Therapy Examination (NPTE). Program assessment data from five cohorts of PTA students (2005-2009) were used to develop a stepwise multiple regression formula that predicted first-time NPTE licensure scores. Data used included the Nelson-Denny Reading Test, grades from eight core courses, grade point average upon admission to the program, and scores from three mock NPTE exams given during the program. Pearson correlation coefficients were calculated between each of the 15 variables and NPTE scores. Stepwise multiple regression analysis was performed using data collected at the ends of the first, second, and third (final) semesters of the program. Data from the class of 2010 were then used to validate the formula. The end-of-program formula accounted for the greatest variance (57%) in predicted scores. Those students scoring below a predicted scaled score of 620 were identified to be at risk of failure of the licensure exam. These students were counseled, and a remedial plan was developed based on regression predictions prior to them sitting for the licensure exam.

A comparison of time dependent Cox regression, pooled logistic regression and cross sectional pooling with simulations and an application to the Framingham Heart Study.

PubMed

Ngwa, Julius S; Cabral, Howard J; Cheng, Debbie M; Pencina, Michael J; Gagnon, David R; LaValley, Michael P; Cupples, L Adrienne

2016-11-03

Typical survival studies follow individuals to an event and measure explanatory variables for that event, sometimes repeatedly over the course of follow up. The Cox regression model has been used widely in the analyses of time to diagnosis or death from disease. The associations between the survival outcome and time dependent measures may be biased unless they are modeled appropriately. In this paper we explore the Time Dependent Cox Regression Model (TDCM), which quantifies the effect of repeated measures of covariates in the analysis of time to event data. This model is commonly used in biomedical research but sometimes does not explicitly adjust for the times at which time dependent explanatory variables are measured. This approach can yield different estimates of association compared to a model that adjusts for these times. In order to address the question of how different these estimates are from a statistical perspective, we compare the TDCM to Pooled Logistic Regression (PLR) and Cross Sectional Pooling (CSP), considering models that adjust and do not adjust for time in PLR and CSP. In a series of simulations we found that time adjusted CSP provided identical results to the TDCM while the PLR showed larger parameter estimates compared to the time adjusted CSP and the TDCM in scenarios with high event rates. We also observed upwardly biased estimates in the unadjusted CSP and unadjusted PLR methods. The time adjusted PLR had a positive bias in the time dependent Age effect with reduced bias when the event rate is low. The PLR methods showed a negative bias in the Sex effect, a subject level covariate, when compared to the other methods. The Cox models yielded reliable estimates for the Sex effect in all scenarios considered. We conclude that survival analyses that explicitly account in the statistical model for the times at which time dependent covariates are measured provide more reliable estimates compared to unadjusted analyses. We present results from the Framingham Heart Study in which lipid measurements and myocardial infarction data events were collected over a period of 26 years.

Greater association of peak neuromuscular performance with cortical bone geometry, bone mass and bone strength than bone density: A study in 417 older women.

PubMed

Belavý, Daniel L; Armbrecht, Gabriele; Blenk, Tilo; Bock, Oliver; Börst, Hendrikje; Kocakaya, Emine; Luhn, Franziska; Rantalainen, Timo; Rawer, Rainer; Tomasius, Frederike; Willnecker, Johannes; Felsenberg, Dieter

2016-02-01

We evaluated which aspects of neuromuscular performance are associated with bone mass, density, strength and geometry. 417 women aged 60-94years were examined. Countermovement jump, sit-to-stand test, grip strength, forearm and calf muscle cross-sectional area, areal bone mineral content and density (aBMC and aBMD) at the hip and lumbar spine via dual X-ray absorptiometry, and measures of volumetric vBMC and vBMD, bone geometry and section modulus at 4% and 66% of radius length and 4%, 38% and 66% of tibia length via peripheral quantitative computed tomography were performed. The first principal component of the neuromuscular variables was calculated to generate a summary neuromuscular variable. Percentage of total variance in bone parameters explained by the neuromuscular parameters was calculated. Step-wise regression was also performed. At all pQCT bone sites (radius, ulna, tibia, fibula), a greater percentage of total variance in measures of bone mass, cortical geometry and/or bone strength was explained by peak neuromuscular performance than for vBMD. Sit-to-stand performance did not relate strongly to bone parameters. No obvious differential in the explanatory power of neuromuscular performance was seen for DXA aBMC versus aBMD. In step-wise regression, bone mass, cortical morphology, and/or strength remained significant in relation to the first principal component of the neuromuscular variables. In no case was vBMD positively related to neuromuscular performance in the final step-wise regression models. Peak neuromuscular performance has a stronger relationship with leg and forearm bone mass and cortical geometry as well as proximal forearm section modulus than with vBMD. Copyright © 2015 Elsevier Inc. All rights reserved.

Prevalence of consistent condom use with various types of sex partners and associated factors among money boys in Changsha, China.

PubMed

Wang, Lian-Hong; Yan, Jin; Yang, Guo-Li; Long, Shuo; Yu, Yong; Wu, Xi-Lin

2015-04-01

Money boys with inconsistent condom use (less than 100% of the time) are at high risk of infection by human immunodeficiency virus (HIV) or sexually transmitted infection (STI), but relatively little research has examined their risk behaviors. We investigated the prevalence of consistent condom use (100% of the time) and associated factors among money boys. A cross-sectional study using a structured questionnaire was conducted among money boys in Changsha, China, between July 2012 and January 2013. Independent variables included socio-demographic data, substance abuse history, work characteristics, and self-reported HIV and STI history. Dependent variables included the consistent condom use with different types of sex partners. Among the participants, 82.4% used condoms consistently with male clients, 80.2% with male sex partners, and 77.1% with female sex partners in the past 3 months. A multiple stepwise logistic regression model identified four statistically significant factors associated with lower likelihoods of consistent condom use with male clients: age group, substance abuse, lack of an "employment" arrangement, and having no HIV test within the prior 6 months. In a similar model, only one factor associated significantly with lower likelihoods of consistent condom use with male sex partners was identified in multiple stepwise logistic regression analyses: having no HIV test within the prior six months. As for female sex partners, two significant variables were statistically significant in the multiple stepwise logistic regression analysis: having no HIV test within the prior 6 months and having STI history. Interventions which are linked with more realistic and acceptable HIV prevention methods are greatly warranted and should increase risk awareness and the behavior of consistent condom use in both commercial and personal relationship. © 2015 International Society for Sexual Medicine.

A model for predicting sulcus-to-sulcus diameter in posterior chamber phakic intraocular lens candidates: correlation between ocular biometric parameters.

PubMed

Ghoreishi, Mohammad; Abdi-Shahshahani, Mehdi; Peyman, Alireza; Pourazizi, Mohsen

2018-02-21

The aim of this study was to determine the correlation between ocular biometric parameters and sulcus-to-sulcus (STS) diameter. This was a cross-sectional study of preoperative ocular biometry data of patients who were candidates for phakic intraocular lens (IOL) surgery. Subjects underwent ocular biometry analysis, including refraction error evaluation using an autorefractor and Orbscan topography for white-to-white (WTW) corneal diameter and measurement. Pentacam was used to perform WTW corneal diameter and measurements of minimum and maximum keratometry (K). Measurements of STS and angle-to-angle (ATA) were obtained using a 50-MHz B-mode ultrasound device. Anterior optical coherence tomography was performed for anterior chamber depth measurement. Pearson's correlation test and stepwise linear regression analysis were used to find a model to predict STS. Fifty-eight eyes of 58 patients were enrolled. Mean age ± standard deviation of sample was 28.95 ± 6.04 years. The Pearson's correlation coefficient between STS with WTW, ATA, mean K was 0.383, 0.492, and - 0.353, respectively, which was statistically significant (all P < 0.001). Using stepwise linear regression analysis, there is a statistically significant association between STS with WTW (P = 0.011) and mean K (P = 0.025). The standardized coefficient was 0.323 and - 0.284 for WTW and mean K, respectively. The stepwise linear regression analysis equation was: (STS = 9.549 + 0.518 WTW - 0.083 mean K). Based on our result, given the correlation of STS with WTW and mean K and potential of direct and essay measurement of WTW and mean K, it seems that current IOL sizing protocols could be estimating with WTW and mean K.

Aerobic Fitness Does Not Contribute to Prediction of Orthostatic Intolerance

NASA Technical Reports Server (NTRS)

Convertino, Victor A.; Sather, Tom M.; Goldwater, Danielle J.; Alford, William R.

1986-01-01

Several investigations have suggested that orthostatic tolerance may be inversely related to aerobic fitness (VO (sub 2max)). To test this hypothesis, 18 males (age 29 to 51 yr) underwent both treadmill VO(sub 2max) determination and graded lower body negative pressures (LBNP) exposure to tolerance. VO(2max) was measured during the last minute of a Bruce treadmill protocol. LBNP was terminated based on pre-syncopal symptoms and LBNP tolerance (peak LBNP) was expressed as the cumulative product of LBNP and time (torr-min). Changes in heart rate, stroke volume cardiac output, blood pressure and impedance rheographic indices of mid-thigh-leg initial accumulation were measured at rest and during the final minute of LBNP. For all 18 subjects, mean (plus or minus SE) fluid accumulation index and leg venous compliance index at peak LBNP were 139 plus or minus 3.9 plus or minus 0.4 ml-torr-min(exp -2) x 10(exp 3), respectively. Pearson product-moment correlations and step-wise linear regression were used to investigate relationships with peak LBNP. Variables associated with endurance training, such as VO(sub 2max) and percent body fat were not found to correlate significantly (P is less than 0.05) with peak LBNP and did not add sufficiently to the prediction of peak LBNP to be included in the step-wise regression model. The step-wise regression model included only fluid accumulation index leg venous compliance index, and blood volume and resulted in a squared multiple correlation coefficient of 0.978. These data do not support the hypothesis that orthostatic tolerance as measured by LBNP is lower in individuals with high aerobic fitness.

Evaluation of Cox's model and logistic regression for matched case-control data with time-dependent covariates: a simulation study.

PubMed

Leffondré, Karen; Abrahamowicz, Michal; Siemiatycki, Jack

2003-12-30

Case-control studies are typically analysed using the conventional logistic model, which does not directly account for changes in the covariate values over time. Yet, many exposures may vary over time. The most natural alternative to handle such exposures would be to use the Cox model with time-dependent covariates. However, its application to case-control data opens the question of how to manipulate the risk sets. Through a simulation study, we investigate how the accuracy of the estimates of Cox's model depends on the operational definition of risk sets and/or on some aspects of the time-varying exposure. We also assess the estimates obtained from conventional logistic regression. The lifetime experience of a hypothetical population is first generated, and a matched case-control study is then simulated from this population. We control the frequency, the age at initiation, and the total duration of exposure, as well as the strengths of their effects. All models considered include a fixed-in-time covariate and one or two time-dependent covariate(s): the indicator of current exposure and/or the exposure duration. Simulation results show that none of the models always performs well. The discrepancies between the odds ratios yielded by logistic regression and the 'true' hazard ratio depend on both the type of the covariate and the strength of its effect. In addition, it seems that logistic regression has difficulty separating the effects of inter-correlated time-dependent covariates. By contrast, each of the two versions of Cox's model systematically induces either a serious under-estimation or a moderate over-estimation bias. The magnitude of the latter bias is proportional to the true effect, suggesting that an improved manipulation of the risk sets may eliminate, or at least reduce, the bias. Copyright 2003 JohnWiley & Sons, Ltd.

Integrative Bayesian variable selection with gene-based informative priors for genome-wide association studies.

PubMed

Zhang, Xiaoshuai; Xue, Fuzhong; Liu, Hong; Zhu, Dianwen; Peng, Bin; Wiemels, Joseph L; Yang, Xiaowei

2014-12-10

Genome-wide Association Studies (GWAS) are typically designed to identify phenotype-associated single nucleotide polymorphisms (SNPs) individually using univariate analysis methods. Though providing valuable insights into genetic risks of common diseases, the genetic variants identified by GWAS generally account for only a small proportion of the total heritability for complex diseases. To solve this "missing heritability" problem, we implemented a strategy called integrative Bayesian Variable Selection (iBVS), which is based on a hierarchical model that incorporates an informative prior by considering the gene interrelationship as a network. It was applied here to both simulated and real data sets. Simulation studies indicated that the iBVS method was advantageous in its performance with highest AUC in both variable selection and outcome prediction, when compared to Stepwise and LASSO based strategies. In an analysis of a leprosy case-control study, iBVS selected 94 SNPs as predictors, while LASSO selected 100 SNPs. The Stepwise regression yielded a more parsimonious model with only 3 SNPs. The prediction results demonstrated that the iBVS method had comparable performance with that of LASSO, but better than Stepwise strategies. The proposed iBVS strategy is a novel and valid method for Genome-wide Association Studies, with the additional advantage in that it produces more interpretable posterior probabilities for each variable unlike LASSO and other penalized regression methods.

Lateral-Directional Parameter Estimation on the X-48B Aircraft Using an Abstracted, Multi-Objective Effector Model

NASA Technical Reports Server (NTRS)

Ratnayake, Nalin A.; Waggoner, Erin R.; Taylor, Brian R.

2011-01-01

The problem of parameter estimation on hybrid-wing-body aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aerodynamic control effectors that act in coplanar motion. This adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of flight and simulation data must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, time-decorrelation techniques are applied to a model structure selected through stepwise regression for simulated and flight-generated lateral-directional parameter estimation data. A virtual effector model that uses mathematical abstractions to describe the multi-axis effects of clamshell surfaces is developed and applied. Comparisons are made between time history reconstructions and observed data in order to assess the accuracy of the regression model. The Cram r-Rao lower bounds of the estimated parameters are used to assess the uncertainty of the regression model relative to alternative models. Stepwise regression was found to be a useful technique for lateral-directional model design for hybrid-wing-body aircraft, as suggested by available flight data. Based on the results of this study, linear regression parameter estimation methods using abstracted effectors are expected to perform well for hybrid-wing-body aircraft properly equipped for the task.

COX-2 verexpression in pretreatment biopsies predicts response of rectal cancers to neoadjuvant radiochemotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Fraser M.; Reynolds, John V.; Kay, Elaine W.

2006-02-01

Purpose: To determine the utility of COX-2 expression as a response predictor for patients with rectal cancer who are undergoing neoadjuvant radiochemotherapy (RCT). Methods and Materials: Pretreatment biopsies (PTB) from 49 patients who underwent RCT were included. COX-2 and proliferation in PTB were assessed by immunohistochemistry (IHC) and apoptosis was detected by TUNEL stain. Response to treatment was assessed by a 5-point tumor-regression grade (TRG) based on the ratio of residual tumor to fibrosis. Results: Good response (TRG 1 + 2), moderate response (TRG 3), and poor response (TRG 4 + 5) were seen in 21 patients (42%), 11 patientsmore » (22%), and 17 patients (34%), respectively. Patients with COX-2 overexpression in PTB were more likely to demonstrate moderate or poor response (TRG 3 + 4) to treatment than were those with normal COX-2 expression (p = 0.026, chi-square test). Similarly, poor response was more likely if patients had low levels of spontaneous apoptosis in PTBs (p = 0.0007, chi-square test). Conclusions: COX-2 overexpression and reduced apoptosis in PTB can predict poor response of rectal cancer to RCT. As COX-2 inhibitors are commercially available, their administration to patients who overexpress COX-2 warrants assessment in clinical trials in an attempt to increase overall response rates.« less

Simple models for estimating local removals of timber in the northeast

Treesearch

David N. Larsen; David A. Gansner

1975-01-01

Provides a practical method of estimating subregional removals of timber and demonstrates its application to a typical problem. Stepwise multiple regression analysis is used to develop equations for estimating removals of softwood, hardwood, and all timber from selected characteristics of socioeconomic structure.

Predicting pork loin intramuscular fat using computer vision system.

PubMed

Liu, J-H; Sun, X; Young, J M; Bachmeier, L A; Newman, D J

2018-09-01

The objective of this study was to investigate the ability of computer vision system to predict pork intramuscular fat percentage (IMF%). Center-cut loin samples (n = 85) were trimmed of subcutaneous fat and connective tissue. Images were acquired and pixels were segregated to estimate image IMF% and 18 image color features for each image. Subjective IMF% was determined by a trained grader. Ether extract IMF% was calculated using ether extract method. Image color features and image IMF% were used as predictors for stepwise regression and support vector machine models. Results showed that subjective IMF% had a correlation of 0.81 with ether extract IMF% while the image IMF% had a 0.66 correlation with ether extract IMF%. Accuracy rates for regression models were 0.63 for stepwise and 0.75 for support vector machine. Although subjective IMF% has shown to have better prediction, results from computer vision system demonstrates the potential of being used as a tool in predicting pork IMF% in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

Relationships between presenteeism and work-related musculoskeletal disorders among physical therapists in the Republic of Korea.

PubMed

Bae, Young-Hyeon

2017-12-14

This study investigated the relationship between presenteeism and work-related musculoskeletal disorders (WMSDs) among physical therapists (PTs) in the Republic of Korea. Questionnaires were given to 600 PTs in the Republic of Korea. General and occupational characteristics and the prevalence of presenteeism and absenteeism were self-reported on the questionnaire. Stepwise regression analyses were used to evaluate the effects of presenteeism and other variables on general and occupational characteristics. Of the 490 PTs who responded, 399 (81.4%) reported at least one WMSD. There was a low incidence rate of absenteeism, but work impairment scores indicate there was a high incidence of presenteeism. In the stepwise regression analyses, the incidence of WMSDs was highest in cases of presenteeism. The results of this study demonstrate that there is a high incidence rate of WMSDs in Republic of Korean PTs, that WMSDs are related to presenteeism and that PTs demonstrate high presenteeism and low absenteeism.

Predictive value of grade point average (GPA), Medical College Admission Test (MCAT), internal examinations (Block) and National Board of Medical Examiners (NBME) scores on Medical Council of Canada qualifying examination part I (MCCQE-1) scores.

PubMed

Roy, Banibrata; Ripstein, Ira; Perry, Kyle; Cohen, Barry

2016-01-01

To determine whether the pre-medical Grade Point Average (GPA), Medical College Admission Test (MCAT), Internal examinations (Block) and National Board of Medical Examiners (NBME) scores are correlated with and predict the Medical Council of Canada Qualifying Examination Part I (MCCQE-1) scores. Data from 392 admitted students in the graduating classes of 2010-2013 at University of Manitoba (UofM), College of Medicine was considered. Pearson's correlation to assess the strength of the relationship, multiple linear regression to estimate MCCQE-1 score and stepwise linear regression to investigate the amount of variance were employed. Complete data from 367 (94%) students were studied. The MCCQE-1 had a moderate-to-large positive correlation with NBME scores and Block scores but a low correlation with GPA and MCAT scores. The multiple linear regression model gives a good estimate of the MCCQE-1 (R2 =0.604). Stepwise regression analysis demonstrated that 59.2% of the variation in the MCCQE-1 was accounted for by the NBME, but only 1.9% by the Block exams, and negligible variation came from the GPA and the MCAT. Amongst all the examinations used at UofM, the NBME is most closely correlated with MCCQE-1.

Optimizing separate phase light hydrocarbon recovery from contaminated unconfined aquifers

NASA Astrophysics Data System (ADS)

Cooper, Grant S.; Peralta, Richard C.; Kaluarachchi, Jagath J.

A modeling approach is presented that optimizes separate phase recovery of light non-aqueous phase liquids (LNAPL) for a single dual-extraction well in a homogeneous, isotropic unconfined aquifer. A simulation/regression/optimization (S/R/O) model is developed to predict, analyze, and optimize the oil recovery process. The approach combines detailed simulation, nonlinear regression, and optimization. The S/R/O model utilizes nonlinear regression equations describing system response to time-varying water pumping and oil skimming. Regression equations are developed for residual oil volume and free oil volume. The S/R/O model determines optimized time-varying (stepwise) pumping rates which minimize residual oil volume and maximize free oil recovery while causing free oil volume to decrease a specified amount. This S/R/O modeling approach implicitly immobilizes the free product plume by reversing the water table gradient while achieving containment. Application to a simple representative problem illustrates the S/R/O model utility for problem analysis and remediation design. When compared with the best steady pumping strategies, the optimal stepwise pumping strategy improves free oil recovery by 11.5% and reduces the amount of residual oil left in the system due to pumping by 15%. The S/R/O model approach offers promise for enhancing the design of free phase LNAPL recovery systems and to help in making cost-effective operation and management decisions for hydrogeologists, engineers, and regulators.

Cox Regression Models with Functional Covariates for Survival Data.

PubMed

Gellar, Jonathan E; Colantuoni, Elizabeth; Needham, Dale M; Crainiceanu, Ciprian M

2015-06-01

We extend the Cox proportional hazards model to cases when the exposure is a densely sampled functional process, measured at baseline. The fundamental idea is to combine penalized signal regression with methods developed for mixed effects proportional hazards models. The model is fit by maximizing the penalized partial likelihood, with smoothing parameters estimated by a likelihood-based criterion such as AIC or EPIC. The model may be extended to allow for multiple functional predictors, time varying coefficients, and missing or unequally-spaced data. Methods were inspired by and applied to a study of the association between time to death after hospital discharge and daily measures of disease severity collected in the intensive care unit, among survivors of acute respiratory distress syndrome.

Genetic Polymorphisms in RNA Binding Proteins Contribute to Breast Cancer Survival

PubMed Central

Upadhyay, Rohit; Sanduja, Sandhya; Kaza, Vimala; Dixon, Dan A.

2012-01-01

The RNA-binding proteins TTP and HuR control expression of numerous genes associated with breast cancer pathogenesis by regulating mRNA stability. However, the role of genetic variation in TTP (ZFP36) and HuR (ELAVL1) genes is unknown in breast cancer prognosis. A total of 251 breast cancer patients (170 Caucasians and 81 African-Americans) were enrolled and followed-up from 2001 to 2011 (or until death). Genotyping was performed for 10 SNPs in ZFP36 and 7 in ELAVL1 genes. On comparing both races with one another, significant differences were found for clinical and genetic variables. The influence of genetic polymorphisms on survival was analyzed by using Cox-regression, Kaplan-Meier analysis, and the log-rank test. Univariate (Kaplan-Meier/Cox-regression) and multivariate (Cox-regression) analysis showed that the TTP gene polymorphism ZFP36*2 A>G was significantly associated with poor prognosis of Caucasian patients (HR = 2.03; 95% CI = 1.09–3.76; P = 0.025; log-rank P = 0.022). None of the haplotypes, but presence of more than six risk genotypes in Caucasian patients, was significantly associated with poor prognosis (HR=2.42; 95% CI=1.17–4.99; P = 0.017; log-rank P = 0.007). The effect of ZFP36*2 A>G on gene expression was evaluated from patients' tissue samples. Both TTP mRNA and protein expression was significantly decreased in ZFP36*2 G allele carriers compared to A allele homozygotes. Conversely, upregulation of the TTP-target gene COX-2 was observed ZFP36*2 G allele carriers. Through its ability to attenuate TTP gene expression, the ZFP36*2 A>G gene polymorphism has appeared as a novel prognostic breast cancer marker in Caucasian patients. PMID:22907529

Depression and Related Problems in University Students

ERIC Educational Resources Information Center

Field, Tiffany; Diego, Miguel; Pelaez, Martha; Deeds, Osvelia; Delgado, Jeannette

2012-01-01

Method: Depression and related problems were studied in a sample of 283 university students. Results: The students with high depression scores also had high scores on anxiety, intrusive thoughts, controlling intrusive thoughts and sleep disturbances scales. A stepwise regression suggested that those problems contributed to a significant proportion…

Analyzing Teaching Performance of Instructors Using Data Mining Techniques

ERIC Educational Resources Information Center

Mardikyan, Sona; Badur, Bertain

2011-01-01

Student evaluations to measure the teaching effectiveness of instructor's are very frequently applied in higher education for many years. This study investigates the factors associated with the assessment of instructors teaching performance using two different data mining techniques; stepwise regression and decision trees. The data collected…

DEVELOPMENT OF RESIDENTIAL WOOD COMSUMPTION ESTIMATION MODELS

EPA Science Inventory

The report gives data on the distribution and usage of firewood, obtained from a pool of household wood use surveys. ased on a series of regression models developed using the STEPWISE procedure in the SAS statistical package, two variables appear to be most predictive of wood use...

Evaluating cardiovascular mortality in type 2 diabetes patients: an analysis based on competing risks Markov chains and additive regression models.

PubMed

Rosato, Rosalba; Ciccone, G; Bo, S; Pagano, G F; Merletti, F; Gregori, D

2007-06-01

Type 2 diabetes represents a condition significantly associated with increased cardiovascular mortality. The aims of the study are: (i) to estimate the cumulative incidence function for cause-specific mortality using Cox and Aalen model; (ii) to describe how the prediction of cardiovascular or other causes mortality changes for patients with different pattern of covariates; (iii) to show if different statistical methods may give different results. Cox and Aalen additive regression model through the Markov chain approach, are used to estimate the cause-specific hazard for cardiovascular or other causes mortality in a cohort of 2865 type 2 diabetic patients without insulin treatment. The models are compared in the estimation of the risk of death for patients of different severity. For younger patients with a better covariates profile, the Cumulative Incidence Function estimated by Cox and Aalen model was almost the same; for patients with the worst covariates profile, models gave different results: at the end of follow-up cardiovascular mortality rate estimated by Cox and Aalen model was 0.26 [95% confidence interval (CI) = 0.21-0.31] and 0.14 (95% CI = 0.09-0.18). Standard Cox and Aalen model capture the risk process for patients equally well with average profiles of co-morbidities. The Aalen model, in addition, is shown to be better at identifying cause-specific risk of death for patients with more severe clinical profiles. This result is relevant in the development of analytic tools for research and resource management within diabetes care.

An empirical study using permutation-based resampling in meta-regression

PubMed Central

2012-01-01

Background In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression. Methods We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials (herbal medicine trials). Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared final models and final P values between methods. Results We collected 110 trials across 5 intervention/outcome pairings and 5 to 10 trials per covariate. When applying large sample methods and permutation-based methods in our backwards stepwise regression the covariates in the final models were identical in all cases. The P values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases. Conclusions We present empirical evidence that permutation-based resampling may not change final models when using backwards stepwise regression, but may increase P values in meta-regression of multiple covariates for relatively small amount of trials. PMID:22587815

Comparative analysis of COX-2, vascular endothelial growth factor and microvessel density in human renal cell carcinomas.

PubMed

Hemmerlein, B; Galuschka, L; Putzer, N; Zischkau, S; Heuser, M

2004-12-01

Cyclooxygenase-2 (COX-2) and vascular endothelial growth factor (VEGF) are frequently up-regulated in malignant tumours and play a role in proliferation, apoptosis, angiogenesis and tumour invasion. In the present study, the expression of COX-2 and VEGF in renal cell carcinoma (RCC) was analysed and correlated with the microvessel density (MVD). COX-2 and VEGF were analysed by realtime reverse transcriptase-polymerase chain reaction and immunohistochemistry. The MVD was assessed by CD31 immunohistochemistry. The expression of COX-2 and VEGF was determined in the RCC cell lines A498 and Caki-1 under short-term hypoxia and in multicellular tumour cell aggregates. COX-2 was expressed in RCC by tumour epithelia, endothelia and macrophages in areas of cystic tumour regression and tumour necrosis. COX-2 protein in RCC was not altered in comparison with normal renal tissue. VEGF mRNA was up-regulated in RCC and positively correlated with MVD. RCC with high up-regulation of VEGF mRNA showed weak intracytoplasmic expression of VEGF in tumour cells. Intracytoplasmic VEGF protein expression was negatively correlated with MVD. In RCC with necrosis the MVD was reduced in comparison with RCC without necrosis. A498 RCC cells down-regulated COX-2 and up-regulated VEGF under conditions of hypoxia. In Caki-1 cells COX-2 expression remained stable, whereas VEGF was significantly up-regulated. In multicellular A498 cell aggregates COX-2 and VEGF were up-regulated centrally, whereas no gradient was found in Caki-1 cells. COX-2 and VEGF are potential therapeutic targets because COX-2 and VEGF are expressed in RCC and associated cell populations such as endothelia and monocytes/macrophages.

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

PubMed

Gong, Xiajing; Hu, Meng; Zhao, Liang

2018-05-01

Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data. The prediction performances of ML-based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML-based methods provide a powerful tool for time-to-event analysis, with a built-in capacity for high-dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

PubMed

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Prediction of troponin-T degradation using color image texture features in 10d aged beef longissimus steaks.

PubMed

Sun, X; Chen, K J; Berg, E P; Newman, D J; Schwartz, C A; Keller, W L; Maddock Carlin, K R

2014-02-01

The objective was to use digital color image texture features to predict troponin-T degradation in beef. Image texture features, including 88 gray level co-occurrence texture features, 81 two-dimension fast Fourier transformation texture features, and 48 Gabor wavelet filter texture features, were extracted from color images of beef strip steaks (longissimus dorsi, n = 102) aged for 10d obtained using a digital camera and additional lighting. Steaks were designated degraded or not-degraded based on troponin-T degradation determined on d 3 and d 10 postmortem by immunoblotting. Statistical analysis (STEPWISE regression model) and artificial neural network (support vector machine model, SVM) methods were designed to classify protein degradation. The d 3 and d 10 STEPWISE models were 94% and 86% accurate, respectively, while the d 3 and d 10 SVM models were 63% and 71%, respectively, in predicting protein degradation in aged meat. STEPWISE and SVM models based on image texture features show potential to predict troponin-T degradation in meat. © 2013.

Psychosocial work environment and mental health-related long-term sickness absence among nurses.

PubMed

Roelen, Corné A M; van Hoffen, Marieke F A; Waage, Siri; Schaufeli, Wilmar B; Twisk, Jos W R; Bjorvatn, Bjørn; Moen, Bente E; Pallesen, Ståle

2018-02-01

We investigated which job demands and job resources were predictive of mental health-related long-term sickness absence (LTSA) in nurses. The data of 2059 nurses were obtained from the Norwegian survey of Shift work, Sleep and Health. Job demands (psychological demands, role conflict, and harassment at the workplace) and job resources (social support at work, role clarity, and fair leadership) were measured at baseline and linked to mental health-related LTSA during 2-year follow-up. Cox regression models estimated hazard ratios (HR) and related 95% confidence intervals (CI). The c-statistic was used to investigate the discriminative ability of the Cox regression models. A total of 1533 (75%) nurses were included in the analyses; 103 (7%) of them had mental health-related LTSA during 2-year follow-up. Harassment (HR = 1.07; 95% CI 1.01-1.17) and social support (HR = 0.92; 95% CI 0.87-0.98) were associated with mental health-related LTSA. However, the Cox regression model did not discriminate between nurses with and without mental health-related LTSA (c = 0.59; 95% CI 0.53-0.65). Harassment was positively and social support at the workplace was negatively related to mental health-related LTSA, but both failed to discriminate between nurses with and without mental health-related LTSA during 2-year follow-up.

The effect of delayed graft function on graft and patient survival in kidney transplantation: an approach using competing events analysis.

PubMed

Fonseca, Isabel; Teixeira, Laetitia; Malheiro, Jorge; Martins, La Salete; Dias, Leonídio; Castro Henriques, António; Mendonça, Denisa

2015-06-01

In kidney transplantation, the impact of delayed graft function (DGF) on long-term graft and patient survival is controversial. We examined the impact of DGF on graft and recipient survival by accounting for the possibility that death with graft function may act as a competing risk for allograft failure. We used data from 1281 adult primary deceased-donor kidney recipients whose allografts functioned at least 1 year. The probability of graft loss occurrence is overestimated using the complement of Kaplan-Meier estimates (1-KM). Both the cause-specific Cox proportional hazard regression model (standard Cox) and the subdistribution hazard regression model proposed by Fine and Gray showed that DGF was associated with shorter time to graft failure (csHR = 2.0, P = 0.002; sHR = 1.57, P = 0.009), independent of acute rejection (AR) and after adjusting for traditional factors associated with graft failure. Regarding patient survival, DGF was a predictor of patient death using the cause-specific Cox model (csHR = 1.57, P = 0.029) but not using the subdistribution model. The probability of graft loss from competing end points should not be reported with the 1-KM. Application of a regression model for subdistribution hazard showed that, independent of AR, DGF has a detrimental effect on long-term graft survival, but not on patient survival. © 2015 Steunstichting ESOT.

Overexpression of epithelial cell adhesion molecule protein is associated with favorable prognosis in an unselected cohort of ovarian cancer patients.

PubMed

Battista, Marco Johannes; Cotarelo, Cristina; Jakobi, Sina; Steetskamp, Joscha; Makris, Georgios; Sicking, Isabel; Weyer, Veronika; Schmidt, Marcus

2014-07-01

The aim of this study was to evaluate the prognostic influence of epithelial cell adhesion molecule (EpCAM) in an unselected cohort of ovarian cancer (OC) patients. Expression of EpCAM was determined by immunohistochemistry in an unselected cohort of 117 patients with OC. Univariable and multivariable Cox regression analyses adjusted for age, tumor stage, histological grading, histological subtype, postoperative tumor burden and completeness of chemotherapy were performed in order to determine the prognostic influence of EpCAM. The Kaplan-Meier method is used to estimate survival rates. Univariable Cox regression analysis showed that overexpression of EpCAM is associated with favorable prognosis in terms of progression-free survival (PFS) (p = 0.011) and disease-specific survival (DSS) (p = 0.003). In multivariable Cox regression analysis, overexpression of EpCAM retains its significance independent of established prognostic factors for longer PFS [hazard ratios (HR) 0.408, 95 % confidence interval (CI) 0.197-0.846, p = 0.003] but not for PFS (HR 0.666, 95 % CI 0.366-1.212, p = 0.183). Kaplan-Meier plots demonstrate an influence on 5-year PFS rates (0 vs. 27.6 %, p = 0.048) and DSS rates (11.8 vs. 54.0 %, p = 0.018). These findings support the hypothesis that the expression of EpCAM is associated with favorable prognosis in OC.

An Exploring Model of Intelligence and Personality in Different Culture

ERIC Educational Resources Information Center

Wu, Yufeng; Qian, Guoying

2005-01-01

Middle school subjects of 13-21 years (from 4 nationalities) were used for studying the relationship between progressive cognition and personality characteristics by Raven's Standard Progressive Matrices and Eysenk's Personality Questionnaire. The results showed: (1) the correlation and stepwise regression were completely identical: P score was…

Switchgrass biomass composition traits and their effects on its digestion by ruminants and bioconversion to ethanol

USDA-ARS?s Scientific Manuscript database

Six generations of divergent breeding in switchgrass (Panicum virgatum L.) for forage in vitro digestibility (IVDMD) resulted in significant changes in 20 biomass composition traits. Stepwise multi-regression was used to determine which of the 20 composition traits had largest significant effects on...

Spatial Representation in Blind Children. 3: Effects of Individual Differences.

ERIC Educational Resources Information Center

Fletcher, Janet F.

1981-01-01

Data from a study of spatial representation in blind children were subjected to two stepwise regression analyses to determine the relationships between several subject related variables and responses to "map" (cognitive map) and "route" (sequential memory) questions about the position of furniture in a recently explored room. (Author/SBH)

Juvenile Offender Recidivism: An Examination of Risk Factors

ERIC Educational Resources Information Center

Calley, Nancy G.

2012-01-01

One hundred and seventy three male juvenile offenders were followed two years postrelease from a residential treatment facility to assess recidivism and factors related to recidivism. The overall recidivism rate was 23.9%. Logistic regression with stepwise and backward variable selection methods was used to examine the relationship between…

Knowing When to Retire: The First Step towards Financial Planning in Malaysia

ERIC Educational Resources Information Center

Kock, Tan Hoe; Yoong, Folk Jee

2011-01-01

This article draws upon expected retirement age cohorts as a main determinant to financial planning preparation in Malaysia. The return rate was 55% from 600 questionnaires distributed. Five hypotheses were analyzed using hierarchical and stepwise regression analysis. The results revealed that expected retirement age cohort variables made…

Comparison of Weibull and Lognormal Cure Models with Cox in the Survival Analysis Of Breast Cancer Patients in Rafsanjan.

PubMed

Hoseini, Mina; Bahrampour, Abbas; Mirzaee, Moghaddameh

2017-02-16

Breast cancer is the most common cancer after lung cancer and the second cause of death. In this study we compared Weibull and Lognormal Cure Models with Cox regression on the survival of breast cancer. A cohort study. The current study retrospective cohort study was conducted on 140 patients referred to Ali Ibn Abitaleb Hospital, Rafsanjan southeastern Iran from 2001 to 2015 suffering from breast cancer. We determined and analyzed the effective survival causes by different models using STATA14. According to AIC, log-normal model was more consistent than Weibull. In the multivariable Lognormal model, the effective factors like smoking, second -hand smoking, drinking herbal tea and the last breast-feeding period were included. In addition, using Cox regression factors of significant were the disease grade, size of tumor and its metastasis (p-value<0.05). As Rafsanjan is surrounded by pistachio orchards and pesticides applied by farmers, people of this city are exposed to agricultural pesticides and its harmful consequences. The effect of the pesticide on breast cancer was studied and the results showed that the effect of pesticides on breast cancer was not in agreement with the models used in this study. Based on different methods for survival analysis, researchers can decide how they can reach a better conclusion. This comparison indicates the result of semi-parametric Cox method is closer to clinical experiences evidences.

QSAR analyses of conformationally restricted 1,5-diaryl pyrazoles as selective COX-2 inhibitors: application of connection table representation of ligands.

PubMed

Prasanna, S; Manivannan, E; Chaturvedi, S C

2005-04-15

As a part of our continuing efforts in discerning the structural and physicochemical requirements for selective COX-2 over COX-1 inhibition among the fused pyrazole ring systems, herein we report the QSAR analyses of the title compounds. The conformational flexibility of the title compounds was examined using a simple connection table representation. The conformational investigation was aided by calculating a connection table parameter called fraction of rotable bonds, b_rotR encompassing the number of rotable bonds and b_count, the number of bonds including implicit hydrogens of each ligand. The hydrophobic and steric correlation of the title compounds towards selective COX-2 inhibition was reported previously in one of our recent publications. In this communication, we attempt to calculate Wang-Ford charges of the non-hydrogen common atoms of AM1 optimized geometries of the title compounds. Owing to the partial conformational flexibility of title compounds, conformationally restricted and unrestricted descriptors were calculated from MOE. Correlation analysis of these 2D, 3D and Wang-Ford charges was accomplished by linear regression analysis. 2D molecular descriptor b_single, 3D molecular descriptors glob, std_dim3 showed significant contribution towards COX-2 inhibitory activity. Balaban J, a connectivity topological index showed a negative and positive contribution towards COX-1 and selective COX-2 over COX-1 inhibition, respectively. Wang-Ford charges calculated on C(7) showed a significant contribution towards COX-1 inhibitory activity whereas charges calculated on C(8) were crucial in governing the selectivity of COX-2 over COX-1 inhibition among these congeners.

Prediction of five-year all-cause mortality in Chinese patients with type 2 diabetes mellitus - A population-based retrospective cohort study.

PubMed

Wan, Eric Yuk Fai; Fong, Daniel Yee Tak; Fung, Colman Siu Cheung; Yu, Esther Yee Tak; Chin, Weng Yee; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen

2017-06-01

This study aimed to develop and validate an all-cause mortality risk prediction model for Chinese primary care patients with type 2 diabetes mellitus(T2DM) in Hong Kong. A population-based retrospective cohort study was conducted on 132,462 Chinese patients who had received public primary care services during 2010. Each gender sample was randomly split on a 2:1 basis into derivation and validation cohorts and was followed-up for a median period of 5years. Gender-specific mortality risk prediction models showing the interaction effect between predictors and age were derived using Cox proportional hazards regression with forward stepwise approach. Developed models were compared with pre-existing models by Harrell's C-statistic and calibration plot using validation cohort. Common predictors of increased mortality risk in both genders included: age; smoking habit; diabetes duration; use of anti-hypertensive agents, insulin and lipid-lowering drugs; body mass index; hemoglobin A1c; systolic blood pressure(BP); total cholesterol to high-density lipoprotein-cholesterol ratio; urine albumin to creatinine ratio(urine ACR); and estimated glomerular filtration rate(eGFR). Prediction models showed better discrimination with Harrell"'s C-statistics of 0.768(males) and 0.782(females) and calibration power from the plots than previously established models. Our newly developed gender-specific models provide a more accurate predicted 5-year mortality risk for Chinese diabetic patients than other established models. Copyright © 2017 Elsevier Inc. All rights reserved.

The pro-apoptotic serum activity is an independent mortality predictor of patients with heart failure.

PubMed

Rössig, Lothar; Fichtlscherer, Stephan; Heeschen, Christopher; Berger, Jürgen; Dimmeler, Stefanie; Zeiher, Andreas M

2004-09-01

Systemic inflammation with elevated serum levels of circulating pro-inflammatory cytokines is a major determinant of prognosis in heart failure (HF). Since serum of patients with HF induces apoptosis of endothelial cells (EC), we aimed to determine whether the pro-apoptotic activity in the serum may predict prognosis of patients with HF. We measured the pro-apoptotic activity in the serum of 48 patients with HF of different aetiology by an ex vivo cell culture assay and subsequently monitored these patients for the single endpoint all-cause mortality. During follow-up, 16 patients died and 11 patients received a heart transplant. Survivors had a lower pro-apoptotic serum activity (P=0.007). By univariate analysis, pro-apoptotic serum activity, NYHA class, pro-BNP, low blood pressure, and creatinine levels were significantly associated with mortality. In a multivariable stepwise Cox-regression model, the pro-apoptotic serum activity (adjusted hazard ratio, HR=1.85 per %, P=0.008), elevated pro-BNP levels (HR=9.35 per log[pro-BNP], P=0.001), and low blood pressure (HR=0.96 per mmHg, P=0.041) remained as independent predictors of death. In this exploratory study, the pro-apoptotic serum capacity is independently associated with a worse prognosis in patients with HF, suggesting that the assessment of serum-induced EC apoptosis could provide an integrative estimate of the deleterious effects of various pro-inflammatory cytokines and other cytotoxic factors in HF.

Significance and outcome of nuclear anaplasia and mitotic index in prostatic adenocarcinomas.

PubMed

Kır, Gozde; Sarbay, Billur Cosan; Gumus, Eyup

2016-10-01

The Gleason grading system measures architectural differentiation and disregards nuclear atypia and the cell proliferation index. Several studies have reported that nuclear grade and mitotic index (MI) are prognostically useful. This study included 232 radical prostatectomy specimens. Nuclear anaplasia (NA) was determined on the basis of nucleomegali (at least 20µm); vesicular chromatin; eosinophilic macronucleoli, nuclear lobulation, and irregular thickened nuclear membranei. The proportion of area of NA was recorded in each tumor in 10% increments. The MI was defined as the number of mitotic figures in 10 consecutive high-power fields (HPF). In univariate analysis, significant differences included associations between biochemical prostate-specific antigen recurrence (BCR) and Gleason score, extraprostatic extension, positive surgical margin, the presence of high-pathologic stage, NA≥10% of tumor area, MI≥3/10 HPF, and preoperative prostate-specific antigen. In a stepwise Cox regression model, a positive surgical margin, the presence of a NA≥10% of tumor area, and a MI of≥3/10 HPF were independent predictors of BCR after radical prostatectomy. NA≥10% of tumor area appeared to have a stronger association with outcome than MI≥3/10 HPF, as still associated with BCR when Gleason score was in the model. The results of our study showed that, in addition to the conventional Gleason grading system, NA, and MI are useful prognostic parameters while evaluating long-term prognosis in prostatic adenocarcinoma. Copyright © 2016 Elsevier Inc. All rights reserved.

KIBRA; a novel biomarker predicting recurrence free survival of breast cancer patients receiving adjuvant therapy.

PubMed

Mudduwa, Lakmini; Peiris, Harshini; Gunasekara, Shania; Abeysiriwardhana, Deepthika; Liyanage, Nimsha; Rayala, Suresh K; Liyanage, Thusharie

2018-05-24

This study was carried out to evaluate the prognostic value of KIBRA in breast cancer. This retrospective study included breast cancer patients who sought the services of the immunohistochemistry laboratory of our unit from 2006 to 2015. Tissue microarrays were constructed and immunohistochemical staining was done to assess the KIBRA expression. The Kaplan-Meier model for univariate and Cox-regression model with backward stepwise factor retention method for multivariate analyses were used. Chi square test was used to find out the associations with the established prognostic features. A total of 1124 patients were included in the study and KIBRA staining of 909 breast cancers were available for analysis. Cytoplasmic KIBRA expression was seen in 39.5% and nuclear expression in 44.8%. Overall KIBRA-low breast cancers accounted for 41.5%. KIBRA nuclear expression was significantly associated with positive ER and PR expression. Luminal breast cancer patients who had endocrine therapy and KIBRA-low expression had a RFS disadvantage over those who were positive for KIBRA (p = 0.02). Similarly, patients who received chemotherapy and had overall KIBRA-low expression also demonstrated a RFS disadvantage compared to those who had overall positive KIBRA expression (p = 0.018). This effect of KIBRA was independent of the other factors considered for the model. Overall low-KIBRA expression has an independent effect on the RFS and predicts the RFS outcome of luminal breast cancer patients who received endocrine therapy and breast cancer patients who received chemotherapy.

Simulation program for estimating statistical power of Cox's proportional hazards model assuming no specific distribution for the survival time.

PubMed

Akazawa, K; Nakamura, T; Moriguchi, S; Shimada, M; Nose, Y

1991-07-01

Small sample properties of the maximum partial likelihood estimates for Cox's proportional hazards model depend on the sample size, the true values of regression coefficients, covariate structure, censoring pattern and possibly baseline hazard functions. Therefore, it would be difficult to construct a formula or table to calculate the exact power of a statistical test for the treatment effect in any specific clinical trial. The simulation program, written in SAS/IML, described in this paper uses Monte-Carlo methods to provide estimates of the exact power for Cox's proportional hazards model. For illustrative purposes, the program was applied to real data obtained from a clinical trial performed in Japan. Since the program does not assume any specific function for the baseline hazard, it is, in principle, applicable to any censored survival data as long as they follow Cox's proportional hazards model.

The role of multicollinearity in landslide susceptibility assessment by means of Binary Logistic Regression: comparison between VIF and AIC stepwise selection

NASA Astrophysics Data System (ADS)

Cama, Mariaelena; Cristi Nicu, Ionut; Conoscenti, Christian; Quénéhervé, Geraldine; Maerker, Michael

2016-04-01

Landslide susceptibility can be defined as the likelihood of a landslide occurring in a given area on the basis of local terrain conditions. In the last decades many research focused on its evaluation by means of stochastic approaches under the assumption that 'the past is the key to the future' which means that if a model is able to reproduce a known landslide spatial distribution, it will be able to predict the future locations of new (i.e. unknown) slope failures. Among the various stochastic approaches, Binary Logistic Regression (BLR) is one of the most used because it calculates the susceptibility in probabilistic terms and its results are easily interpretable from a geomorphological point of view. However, very often not much importance is given to multicollinearity assessment whose effect is that the coefficient estimates are unstable, with opposite sign and therefore difficult to interpret. Therefore, it should be evaluated every time in order to make a model whose results are geomorphologically correct. In this study the effects of multicollinearity in the predictive performance and robustness of landslide susceptibility models are analyzed. In particular, the multicollinearity is estimated by means of Variation Inflation Index (VIF) which is also used as selection criterion for the independent variables (VIF Stepwise Selection) and compared to the more commonly used AIC Stepwise Selection. The robustness of the results is evaluated through 100 replicates of the dataset. The study area selected to perform this analysis is the Moldavian Plateau where landslides are among the most frequent geomorphological processes. This area has an increasing trend of urbanization and a very high potential regarding the cultural heritage, being the place of discovery of the largest settlement belonging to the Cucuteni Culture from Eastern Europe (that led to the development of the great complex Cucuteni-Tripyllia). Therefore, identifying the areas susceptible to landslides may lead to a better understanding and mitigation for government, local authorities and stakeholders to plan the economic activities, minimize the damages costs, environmental and cultural heritage protection. The results show that although the VIF Stepwise selection allows a more stable selection of the controlling factors, the AIC Stepwise selection produces better predictive performance. Moreover, when working with replicates the effect of multicollinearity are statistically reduced by the application of the AIC stepwise selection and the results are easily interpretable in geomorphologic terms.

The importance of extent of choroid plexus cauterization in addition to endoscopic third ventriculostomy for infantile hydrocephalus: a retrospective North American observational study using propensity score-adjusted analysis.

PubMed

Fallah, Aria; Weil, Alexander G; Juraschka, Kyle; Ibrahim, George M; Wang, Anthony C; Crevier, Louis; Tseng, Chi-Hong; Kulkarni, Abhaya V; Ragheb, John; Bhatia, Sanjiv

2017-12-01

OBJECTIVE Combined endoscopic third ventriculostomy (ETC) and choroid plexus cauterization (CPC)-ETV/CPC- is being investigated to increase the rate of shunt independence in infants with hydrocephalus. The degree of CPC necessary to achieve improved rates of shunt independence is currently unknown. METHODS Using data from a single-center, retrospective, observational cohort study involving patients who underwent ETV/CPC for treatment of infantile hydrocephalus, comparative statistical analyses were performed to detect a difference in need for subsequent CSF diversion procedure in patients undergoing partial CPC (describes unilateral CPC or bilateral CPC that only extended from the foramen of Monro [FM] to the atrium on one side) or subtotal CPC (describes CPC extending from the FM to the posterior temporal horn bilaterally) using a rigid neuroendoscope. Propensity scores for extent of CPC were calculated using age and etiology. Propensity scores were used to perform 1) case-matching comparisons and 2) Cox multivariable regression, adjusting for propensity score in the unmatched cohort. Cox multivariable regression adjusting for age and etiology, but not propensity score was also performed as a third statistical technique. RESULTS Eighty-four patients who underwent ETV/CPC had sufficient data to be included in the analysis. Subtotal CPC was performed in 58 patients (69%) and partial CPC in 26 (31%). The ETV/CPC success rates at 6 and 12 months, respectively, were 49% and 41% for patients undergoing subtotal CPC and 35% and 31% for those undergoing partial CPC. Cox multivariate regression in a 48-patient cohort case-matched by propensity score demonstrated no added effect of increased extent of CPC on ETV/CPC survival (HR 0.868, 95% CI 0.422-1.789, p = 0.702). Cox multivariate regression including all patients, with adjustment for propensity score, demonstrated no effect of extent of CPC on ETV/CPC survival (HR 0.845, 95% CI 0.462-1.548, p = 0.586). Cox multivariate regression including all patients, with adjustment for age and etiology, but not propensity score, demonstrated no effect of extent of CPC on ETV/CPC survival (HR 0.908, 95% CI 0.495-1.664, p = 0.755). CONCLUSIONS Using multiple comparative statistical analyses, no difference in need for subsequent CSF diversion procedure was detected between patients in this cohort who underwent partial versus subtotal CPC. Further investigation regarding whether there is truly no difference between partial versus subtotal extent of CPC in larger patient populations and whether further gain in CPC success can be achieved with complete CPC is warranted.

A Review of the Study Designs and Statistical Methods Used in the Determination of Predictors of All-Cause Mortality in HIV-Infected Cohorts: 2002–2011

PubMed Central

Otwombe, Kennedy N.; Petzold, Max; Martinson, Neil; Chirwa, Tobias

2014-01-01

Background Research in the predictors of all-cause mortality in HIV-infected people has widely been reported in literature. Making an informed decision requires understanding the methods used. Objectives We present a review on study designs, statistical methods and their appropriateness in original articles reporting on predictors of all-cause mortality in HIV-infected people between January 2002 and December 2011. Statistical methods were compared between 2002–2006 and 2007–2011. Time-to-event analysis techniques were considered appropriate. Data Sources Pubmed/Medline. Study Eligibility Criteria Original English-language articles were abstracted. Letters to the editor, editorials, reviews, systematic reviews, meta-analysis, case reports and any other ineligible articles were excluded. Results A total of 189 studies were identified (n = 91 in 2002–2006 and n = 98 in 2007–2011) out of which 130 (69%) were prospective and 56 (30%) were retrospective. One hundred and eighty-two (96%) studies described their sample using descriptive statistics while 32 (17%) made comparisons using t-tests. Kaplan-Meier methods for time-to-event analysis were commonly used in the earlier period (n = 69, 76% vs. n = 53, 54%, p = 0.002). Predictors of mortality in the two periods were commonly determined using Cox regression analysis (n = 67, 75% vs. n = 63, 64%, p = 0.12). Only 7 (4%) used advanced survival analysis methods of Cox regression analysis with frailty in which 6 (3%) were used in the later period. Thirty-two (17%) used logistic regression while 8 (4%) used other methods. There were significantly more articles from the first period using appropriate methods compared to the second (n = 80, 88% vs. n = 69, 70%, p-value = 0.003). Conclusion Descriptive statistics and survival analysis techniques remain the most common methods of analysis in publications on predictors of all-cause mortality in HIV-infected cohorts while prospective research designs are favoured. Sophisticated techniques of time-dependent Cox regression and Cox regression with frailty are scarce. This motivates for more training in the use of advanced time-to-event methods. PMID:24498313

Stepwise group sparse regression (SGSR): gene-set-based pharmacogenomic predictive models with stepwise selection of functional priors.

PubMed

Jang, In Sock; Dienstmann, Rodrigo; Margolin, Adam A; Guinney, Justin

2015-01-01

Complex mechanisms involving genomic aberrations in numerous proteins and pathways are believed to be a key cause of many diseases such as cancer. With recent advances in genomics, elucidating the molecular basis of cancer at a patient level is now feasible, and has led to personalized treatment strategies whereby a patient is treated according to his or her genomic profile. However, there is growing recognition that existing treatment modalities are overly simplistic, and do not fully account for the deep genomic complexity associated with sensitivity or resistance to cancer therapies. To overcome these limitations, large-scale pharmacogenomic screens of cancer cell lines--in conjunction with modern statistical learning approaches--have been used to explore the genetic underpinnings of drug response. While these analyses have demonstrated the ability to infer genetic predictors of compound sensitivity, to date most modeling approaches have been data-driven, i.e. they do not explicitly incorporate domain-specific knowledge (priors) in the process of learning a model. While a purely data-driven approach offers an unbiased perspective of the data--and may yield unexpected or novel insights--this strategy introduces challenges for both model interpretability and accuracy. In this study, we propose a novel prior-incorporated sparse regression model in which the choice of informative predictor sets is carried out by knowledge-driven priors (gene sets) in a stepwise fashion. Under regularization in a linear regression model, our algorithm is able to incorporate prior biological knowledge across the predictive variables thereby improving the interpretability of the final model with no loss--and often an improvement--in predictive performance. We evaluate the performance of our algorithm compared to well-known regularization methods such as LASSO, Ridge and Elastic net regression in the Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (Sanger) pharmacogenomics datasets, demonstrating that incorporation of the biological priors selected by our model confers improved predictability and interpretability, despite much fewer predictors, over existing state-of-the-art methods.

Maintenance therapy of childhood acute lymphoblastic leukemia revisited-Should drug doses be adjusted by white blood cell, neutrophil, or lymphocyte counts?

PubMed

Schmiegelow, Kjeld; Nersting, Jacob; Nielsen, Stine Nygaard; Heyman, Mats; Wesenberg, Finn; Kristinsson, Jon; Vettenranta, Kim; Schrøeder, Henrik; Weinshilboum, Richard; Jensen, Katrine Lykke; Grell, Kathrine; Rosthoej, Susanne

2016-12-01

6-Mercaptopurine (6MP) and methotrexate (MTX) based maintenance therapy is a critical phase of childhood acute lymphoblastic leukemia treatment. Wide interindividual variations in drug disposition warrant frequent doses adjustments, but there is a lack of international consensus on dose adjustment guidelines. To identify relapse predictors, we collected 28,255 data sets on drug doses and blood counts (median: 47/patient) and analyzed erythrocyte (Ery) levels of cytotoxic 6MP/MTX metabolites in 9,182 blood samples (median: 14 samples/patient) from 532 children on MTX/6MP maintenance therapy targeted to a white blood cell count (WBC) of 1.5-3.5 × 10 9 /l. After a median follow-up of 13.8 years for patients in remission, stepwise Cox regression analysis did not find age, average doses of 6MP and MTX, hemoglobin, absolute lymphocyte counts, thrombocyte counts, or Ery levels of 6-thioguanine nucleotides or MTX (including its polyglutamates) to be significant relapse predictors. The parameters significantly associated with risk of relapse (N = 83) were male sex (hazard ratio [HR] 2.0 [1.3-3.1], P = 0.003), WBC at diagnosis (HR = 1.04 per 10 × 10 9 /l rise [1.00-1.09], P = 0.048), the absolute neutrophil count (ANC; HR = 1.7 per 10 9 /l rise [1.3-2.4], P = 0.0007), and Ery thiopurine methyltransferase activity (HR = 2.7 per IU/ml rise [1.1-6.7], P = 0.03). WBC was significantly related to ANC (Spearman correlation coefficient, r s  = 0.77; P < 0.001), and only a borderline significant risk factor for relapse (HR = 1.28 [95% CI: 1.00-1.64], P = 0.046) when ANC was excluded from the Cox model. This study indicates that a low neutrophil count is likely to be the best hematological target for dose adjustments of maintenance therapy. © 2016 Wiley Periodicals, Inc.

Prognostic and survival analysis of 837 Chinese colorectal cancer patients.

PubMed

Yuan, Ying; Li, Mo-Dan; Hu, Han-Guang; Dong, Cai-Xia; Chen, Jia-Qi; Li, Xiao-Fen; Li, Jing-Jing; Shen, Hong

2013-05-07

To develop a prognostic model to predict survival of patients with colorectal cancer (CRC). Survival data of 837 CRC patients undergoing surgery between 1996 and 2006 were collected and analyzed by univariate analysis and Cox proportional hazard regression model to reveal the prognostic factors for CRC. All data were recorded using a standard data form and analyzed using SPSS version 18.0 (SPSS, Chicago, IL, United States). Survival curves were calculated by the Kaplan-Meier method. The log rank test was used to assess differences in survival. Univariate hazard ratios and significant and independent predictors of disease-specific survival and were identified by Cox proportional hazard analysis. The stepwise procedure was set to a threshold of 0.05. Statistical significance was defined as P < 0.05. The survival rate was 74% at 3 years and 68% at 5 years. The results of univariate analysis suggested age, preoperative obstruction, serum carcinoembryonic antigen level at diagnosis, status of resection, tumor size, histological grade, pathological type, lymphovascular invasion, invasion of adjacent organs, and tumor node metastasis (TNM) staging were positive prognostic factors (P < 0.05). Lymph node ratio (LNR) was also a strong prognostic factor in stage III CRC (P < 0.0001). We divided 341 stage III patients into three groups according to LNR values (LNR1, LNR ≤ 0.33, n = 211; LNR2, LNR 0.34-0.66, n = 76; and LNR3, LNR ≥ 0.67, n = 54). Univariate analysis showed a significant statistical difference in 3-year survival among these groups: LNR1, 73%; LNR2, 55%; and LNR3, 42% (P < 0.0001). The multivariate analysis results showed that histological grade, depth of bowel wall invasion, and number of metastatic lymph nodes were the most important prognostic factors for CRC if we did not consider the interaction of the TNM staging system (P < 0.05). When the TNM staging was taken into account, histological grade lost its statistical significance, while the specific TNM staging system showed a statistically significant difference (P < 0.0001). The overall survival of CRC patients has improved between 1996 and 2006. LNR is a powerful factor for estimating the survival of stage III CRC patients.

A new model for estimating total body water from bioelectrical resistance

NASA Technical Reports Server (NTRS)

Siconolfi, S. F.; Kear, K. T.

1992-01-01

Estimation of total body water (T) from bioelectrical resistance (R) is commonly done by stepwise regression models with height squared over R, H(exp 2)/R, age, sex, and weight (W). Polynomials of H(exp 2)/R have not been included in these models. We examined the validity of a model with third order polynomials and W. Methods: T was measured with oxygen-18 labled water in 27 subjects. R at 50 kHz was obtained from electrodes placed on the hand and foot while subjects were in the supine position. A stepwise regression equation was developed with 13 subjects (age 31.5 plus or minus 6.2 years, T 38.2 plus or minus 6.6 L, W 65.2 plus or minus 12.0 kg). Correlations, standard error of estimates and mean differences were computed between T and estimated T's from the new (N) model and other models. Evaluations were completed with the remaining 14 subjects (age 32.4 plus or minus 6.3 years, T 40.3 plus or minus 8 L, W 70.2 plus or minus 12.3 kg) and two of its subgroups (high and low) Results: A regression equation was developed from the model. The only significant mean difference was between T and one of the earlier models. Conclusion: Third order polynomials in regression models may increase the accuracy of estimating total body water. Evaluating the model with a larger population is needed.

Association Between Smartphone Use and Musculoskeletal Discomfort in Adolescent Students.

PubMed

Yang, Shang-Yu; Chen, Ming-De; Huang, Yueh-Chu; Lin, Chung-Ying; Chang, Jer-Hao

2017-06-01

Despite the substantial increase in the number of adolescent smartphone users, few studies have investigated the behavioural effects of smartphone use on adolescent students as it relates to musculoskeletal discomfort. The purpose of this study was to explore the association between smartphone use and musculoskeletal discomfort in students at a Taiwanese junior college. We hypothesised that the duration of smartphone use would be associated with increased instances of musculoskeletal discomfort in these students. This cross-sectional study employed a convenience sampling method to recruit students from a junior college in southern Taiwan. All the students (n = 315) were asked to answer questionnaires on smartphone use. A descriptive analysis, stepwise regression, and logistic regression were used to examine specific components of smartphone use and their relationship to musculoskeletal discomfort. Nearly half of the participants experienced neck and shoulder discomfort. The stepwise regression results indicated that the number of body parts with discomfort (F = 6.009, p < 0.05) increased with hours spent using ancillary smartphone functions. The logistic regression analysis showed that the students who talked on the phone >3 h/day had a higher risk of upper back discomfort than did those who talked on the phone <1 h/day [odds ratio (OR) = 4.23, p < 0.05]. This study revealed that the relationship between smartphone use and musculoskeletal discomfort is related to the duration of smartphone ancillary function use. Moreover, hours spent talking on the phone was a predictor of upper back discomfort.

Bayesian dynamic regression models for interval censored survival data with application to children dental health.

PubMed

Wang, Xiaojing; Chen, Ming-Hui; Yan, Jun

2013-07-01

Cox models with time-varying coefficients offer great flexibility in capturing the temporal dynamics of covariate effects on event times, which could be hidden from a Cox proportional hazards model. Methodology development for varying coefficient Cox models, however, has been largely limited to right censored data; only limited work on interval censored data has been done. In most existing methods for varying coefficient models, analysts need to specify which covariate coefficients are time-varying and which are not at the time of fitting. We propose a dynamic Cox regression model for interval censored data in a Bayesian framework, where the coefficient curves are piecewise constant but the number of pieces and the jump points are covariate specific and estimated from the data. The model automatically determines the extent to which the temporal dynamics is needed for each covariate, resulting in smoother and more stable curve estimates. The posterior computation is carried out via an efficient reversible jump Markov chain Monte Carlo algorithm. Inference of each coefficient is based on an average of models with different number of pieces and jump points. A simulation study with three covariates, each with a coefficient of different degree in temporal dynamics, confirmed that the dynamic model is preferred to the existing time-varying model in terms of model comparison criteria through conditional predictive ordinate. When applied to a dental health data of children with age between 7 and 12 years, the dynamic model reveals that the relative risk of emergence of permanent tooth 24 between children with and without an infected primary predecessor is the highest at around age 7.5, and that it gradually reduces to one after age 11. These findings were not seen from the existing studies with Cox proportional hazards models.

Development of a five-year mortality model in systemic sclerosis patients by different analytical approaches.

PubMed

Beretta, Lorenzo; Santaniello, Alessandro; Cappiello, Francesca; Chawla, Nitesh V; Vonk, Madelon C; Carreira, Patricia E; Allanore, Yannick; Popa-Diaconu, D A; Cossu, Marta; Bertolotti, Francesca; Ferraccioli, Gianfranco; Mazzone, Antonino; Scorza, Raffaella

2010-01-01

Systemic sclerosis (SSc) is a multiorgan disease with high mortality rates. Several clinical features have been associated with poor survival in different populations of SSc patients, but no clear and reproducible prognostic model to assess individual survival prediction in scleroderma patients has ever been developed. We used Cox regression and three data mining-based classifiers (Naïve Bayes Classifier [NBC], Random Forests [RND-F] and logistic regression [Log-Reg]) to develop a robust and reproducible 5-year prognostic model. All the models were built and internally validated by means of 5-fold cross-validation on a population of 558 Italian SSc patients. Their predictive ability and capability of generalisation was then tested on an independent population of 356 patients recruited from 5 external centres and finally compared to the predictions made by two SSc domain experts on the same population. The NBC outperformed the Cox-based classifier and the other data mining algorithms after internal cross-validation (area under receiving operator characteristic curve, AUROC: NBC=0.759; RND-F=0.736; Log-Reg=0.754 and Cox= 0.724). The NBC had also a remarkable and better trade-off between sensitivity and specificity (e.g. Balanced accuracy, BA) than the Cox-based classifier, when tested on an independent population of SSc patients (BA: NBC=0.769, Cox=0.622). The NBC was also superior to domain experts in predicting 5-year survival in this population (AUROC=0.829 vs. AUROC=0.788 and BA=0.769 vs. BA=0.67). We provide a model to make consistent 5-year prognostic predictions in SSc patients. Its internal validity, as well as capability of generalisation and reduced uncertainty compared to human experts support its use at bedside. Available at: http://www.nd.edu/~nchawla/survival.xls.

[Risk factors on the recurrence of ischemic stroke and the establishment of a Cox's regression model].

PubMed

An, Ya-chen; Chen, Yun-xia; Wang, Yu-xun; Zhao, Xiao-jing; Wang, Yan; Zhang, Jiang; Li, Chun-ling; Peng, Yan-bo; Gao, Su-ling; Chang, Li-sha; Zhang, Li; Xue, Xin-hong; Chen, Rui-ying; Wang, Da-li

2011-08-01

To investigate the risk factors and establish the Cox's regression model on the recurrence of ischemic stroke. We retrospectively reviewed consecutive patients with ischemic stroke admitted to the Neurology Department of the Hebei United University Affiliated Hospital between January 1, 2008 and December 31, 2009. Cases had been followed since the onset of ischemic stroke. The follow-up program was finished in June 30, 2010. Kaplan-Meier methods were used to describe the recurrence rate. Monovariant and multivariate Cox's proportional hazard regression model were used to analyze the risk factors associated to the episodes of recurrence. And then, a recurrence model was set up. During the period of follow-up program, 79 cases were relapsed, with the recurrence rates as 12.75% in one year and 18.87% in two years. Monovariant and multivariate Cox's proportional hazard regression model showed that the independent risk factors that were associated with the recurrence appeared to be age (X₁) (RR = 1.025, 95%CI: 1.003 - 1.048), history of hypertension (X₂) (RR = 1.976, 95%CI: 1.014 - 3.851), history of family strokes (X₃) (RR = 2.647, 95%CI: 1.175 - 5.961), total cholesterol amount (X₄) (RR = 1.485, 95%CI: 1.214 - 1.817), ESRS total scores (X₅) (RR = 1.327, 95%CI: 1.057 - 1.666) and progression of the disease (X₆) (RR = 1.889, 95%CI: 1.123 - 3.178). Personal prognosis index (PI) of the recurrence model was as follows: PI = 0.025X₁ + 0.681X₂ + 0.973X₃ + 0.395X₄ + 0.283X₅ + 0.636X₆. The smaller the personal prognosis index was, the lower the recurrence risk appeared, while the bigger the personal prognosis index was, the higher the recurrence risk appeared. Age, history of hypertension, total cholesterol amount, total scores of ESRS, together with the disease progression were the independent risk factors associated with the recurrence episodes of ischemic stroke. Both recurrence model and the personal prognosis index equation were successful constructed.

Methodological comparison of marginal structural model, time-varying Cox regression, and propensity score methods: the example of antidepressant use and the risk of hip fracture.

PubMed

Ali, M Sanni; Groenwold, Rolf H H; Belitser, Svetlana V; Souverein, Patrick C; Martín, Elisa; Gatto, Nicolle M; Huerta, Consuelo; Gardarsdottir, Helga; Roes, Kit C B; Hoes, Arno W; de Boer, Antonius; Klungel, Olaf H

2016-03-01

Observational studies including time-varying treatments are prone to confounding. We compared time-varying Cox regression analysis, propensity score (PS) methods, and marginal structural models (MSMs) in a study of antidepressant [selective serotonin reuptake inhibitors (SSRIs)] use and the risk of hip fracture. A cohort of patients with a first prescription for antidepressants (SSRI or tricyclic antidepressants) was extracted from the Dutch Mondriaan and Spanish Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria (BIFAP) general practice databases for the period 2001-2009. The net (total) effect of SSRI versus no SSRI on the risk of hip fracture was estimated using time-varying Cox regression, stratification and covariate adjustment using the PS, and MSM. In MSM, censoring was accounted for by inverse probability of censoring weights. The crude hazard ratio (HR) of SSRI use versus no SSRI use on hip fracture was 1.75 (95%CI: 1.12, 2.72) in Mondriaan and 2.09 (1.89, 2.32) in BIFAP. After confounding adjustment using time-varying Cox regression, stratification, and covariate adjustment using the PS, HRs increased in Mondriaan [2.59 (1.63, 4.12), 2.64 (1.63, 4.25), and 2.82 (1.63, 4.25), respectively] and decreased in BIFAP [1.56 (1.40, 1.73), 1.54 (1.39, 1.71), and 1.61 (1.45, 1.78), respectively]. MSMs with stabilized weights yielded HR 2.15 (1.30, 3.55) in Mondriaan and 1.63 (1.28, 2.07) in BIFAP when accounting for censoring and 2.13 (1.32, 3.45) in Mondriaan and 1.66 (1.30, 2.12) in BIFAP without accounting for censoring. In this empirical study, differences between the different methods to control for time-dependent confounding were small. The observed differences in treatment effect estimates between the databases are likely attributable to different confounding information in the datasets, illustrating that adequate information on (time-varying) confounding is crucial to prevent bias. Copyright © 2016 John Wiley & Sons, Ltd.

[HIV/AIDS related mortality in southern Shanxi province and its risk factors].

PubMed

Ning, Shaoping; Xue, Zidong; Wei, Jun; Mu, Shengcai; Xu, Yajuan; Jia, Shaoxian; Qiu, Chao; Xu, Jianqing

2015-03-01

To explore factors influencing mortality rate of HIV/AIDS and to improve the effectiveness of antiretroviral therapy (ART). By means of retrospective cohort study and the AIDS control information system, HIV/AIDS case reports and antiviral treatment information of 4 cities in southern Shanxi province up to end of December 2012 were selected, to calculate the mortality rate and treatment coverage based on further data collected, along with analysis using the Cox proportional hazards survival regression. 4 040 cases confirmed of HIV/AIDS were included in this study. The average age was (36.0 ± 12.9) years, with 65.3% being male, 56.5% being married, 73.5% having junior high school education or lower, 58.4% being peasants, 54.3% with sexually transmitted infection (40.1% were heterosexual, 14.2% were homosexual), and 38.9% were infected via blood transmission (20.2% were former plasma donors, 16.2% blood transfusion or products recipients, 2.4% were injection drug users). Overall mortality decreased from 40.2 per 100 person/year in 2004 to 6.3 per 100 person/year in 2012, with treatment coverage concomitantly increasing from almost 14.8% to 63.4%. Cox proportional hazards survival regression was used on 4 040 qualified cases, demonstrating the top mortality risk factor was without antiretroviral therapy (RR = 14.9, 95% CI: 12.7-17.4). Cox proportional hazards survival regression was made on 1 938 cases of antiviral treatment, demonstrating that the mortality risk of underweight or obese before treatment was higher than those of normal and overweight cases (RR = 2.7, 95% CI: 1.6-4.5), and the mortality of those having a CD4(+) T-lymphocyte count ≤ 50 cells per µl before treatment was more than 50 cases (RR = 2.6, 95% CI: 1.5-4.5); Cox proportional hazards survival regression was made on 2 102 cases of untreated cases, demonstrating the mortality risk of those initially diagnosed as AIDS was higher than those initially diagnosed as HIV (RR = 3.4, 95% CI: 2.9-4.0). The ART could successfully make lower HIV/AIDS mortality rate, indicating effective ART can further decrease mortality.

The minimal residual QR-factorization algorithm for reliably solving subset regression problems

NASA Technical Reports Server (NTRS)

Verhaegen, M. H.

1987-01-01

A new algorithm to solve test subset regression problems is described, called the minimal residual QR factorization algorithm (MRQR). This scheme performs a QR factorization with a new column pivoting strategy. Basically, this strategy is based on the change in the residual of the least squares problem. Furthermore, it is demonstrated that this basic scheme might be extended in a numerically efficient way to combine the advantages of existing numerical procedures, such as the singular value decomposition, with those of more classical statistical procedures, such as stepwise regression. This extension is presented as an advisory expert system that guides the user in solving the subset regression problem. The advantages of the new procedure are highlighted by a numerical example.

Rumination, Age, and Years of Experience: A Predictive Study of Burnout

ERIC Educational Resources Information Center

McDuffy, Moriel S.

2016-01-01

This study used a non-experimental design to examine whether job satisfaction, rumination, age and years of experience predict burnout among human service workers serving high-risk populations. The study also used a stepwise regression to assess whether job satisfaction, rumination, age, or years of experience predict burnout equally. Burnout was…

Ecological correlates of flying squirrel microhabitat use and density in temperate rainforests of southeastern Alaska

Treesearch

Winston P. Smith; Scott M. Gende; Jeffrey V. Nichols

2004-01-01

We studied habitat relations of the Prince of Wales flying squirrel (Glaucomys sabrinus griseifrons), an endemic of the temperate, coniferous rainforest of southeastern Alaska, because of concerns over population viability from extensive clear-cut logging in the region. We used stepwise logistic regression to examine relationships between...

Relationships of Reading, MCAT, and USMLE Step 1 Test Results for Medical Students

ERIC Educational Resources Information Center

Haught, Patricia; Walls, Richard

2004-01-01

Students (N = 730) took the Nelson-Denny Reading Test (current forms G or H) during orientation to medical school. Stepwise regression analyses showed the Nelson-Denny Reading Vocabulary, Comprehension, and Rate were significant predictors of MCAT (taken prior to admission to medical school) verbal reasoning. Reading Vocabulary was a significant…

Potential for Suicide and Aggression in Delinquents at Juvenile Court in a Southern City.

ERIC Educational Resources Information Center

Battile, Allen O.; And Others

1993-01-01

Questioned 263 Juvenile Court offenders about whether they wished to be dead, kill themselves, or kill others and about their existential experiences, thoughts, and feelings. Used stepwise multiple logistic regression to pinpoint experiences associated with high likelihood of verbalizing wish for destructive behavior. Found sexual abuse as risk…

Nondestructive detection of zebra chip disease in potatoes using near-infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

Near-Infrared (NIR) spectroscopy in the wavelength region from 900 nm to 2600 nm was evaluated as the basis for a rapid, non-destructive method for the detection of Zebra Chip disease in potatoes and the measurement of sugar concentrations in affected tubers. Using stepwise regression in conjunction...

Student Physical Education Teachers' Well-Being: Contribution of Basic Psychological Needs

ERIC Educational Resources Information Center

Ciyin, Gülten; Erturan-Ilker, Gökçe

2014-01-01

This study adopted Self-Determination Theory tenets and aimed to explore whether student physical education (PE) teachers' satisfaction of the three basic psychological needs independently predicts well-being. 267 Turkish student PE teachers were recruited for the study. Two stepwise multiple regression analysis was performed in which each outcome…

Quality Curriculum for Under-Threes: The Impact of Structural Standards

ERIC Educational Resources Information Center

Wertfein, Monika; Spies-Kofler, Anita; Becker-Stoll, Fabienne

2009-01-01

The purpose of this study conducted in 36 infant-toddler centres ("Kinderkrippen") in the city of Munich in Bavaria/Germany was to explore structural characteristics of early child care and education and their effects on child care quality. Stepwise regressions and variance analysis (Manova) examined the relation between quality of care…

Scholarly Networking among Business Students: Structured Discussion Board Activity and Academic Outcomes

ERIC Educational Resources Information Center

Walker, Kristen; Curren, Mary T.; Kiesler, Tina; Lammers, H. Bruce; Goldenson, Jamie

2013-01-01

The authors' intent was to show the effect of student discussion board activity on academic outcomes, after accounting for past academic performance. Data were collected from 516 students enrolled in a junior-level required business course. Controlling for students' grade point average, stepwise regression showed a significant…

Factors Affecting Code Status in a University Hospital Intensive Care Unit

ERIC Educational Resources Information Center

Van Scoy, Lauren Jodi; Sherman, Michael

2013-01-01

The authors collected data on diagnosis, hospital course, and end-of-life preparedness in patients who died in the intensive care unit (ICU) with "full code" status (defined as receiving cardiopulmonary resuscitation), compared with those who didn't. Differences were analyzed using binary and stepwise logistic regression. They found no…

Variation in Environmentalism among University Students: Majoring in Outdoor Recreation, Parks, and Tourism Predicts Environmental Concerns and Behaviors

ERIC Educational Resources Information Center

Arnocky, Steven; Stroink, Mirella L.

2011-01-01

In a survey of Canadian university students (N = 205), the relationship between majoring in an outdoor recreation university program and environmental concern, cooperation, and behavior were examined. Stepwise linear regression indicated that enrollment in outdoor recreation was predictive of environmental behavior and ecological cooperation; and…

Identifying Pedophiles "Eligible" for Community Notification under Megan's Law: A Multivariate Model for Actuarially Anchored Decisions.

ERIC Educational Resources Information Center

Pallone, Nathaniel J.; Hennessy, James J.; Voelbel, Gerald T.

1998-01-01

A scientifically sound methodology for identifying offenders about whose presence the community should be notified is demonstrated. A stepwise multiple regression was calculated among incarcerated pedophiles (N=52) including both psychological and legal data; a precision-weighted equation produced 90.4% "true positives." This methodology can be…

Determination of benzo[a]pyrene in cigarette mainstream smoke by using mid-infrared spectroscopy associated with a novel chemometric algorithm.

PubMed

Zhang, Yan; Zou, Hong-Yan; Shi, Pei; Yang, Qin; Tang, Li-Juan; Jiang, Jian-Hui; Wu, Hai-Long; Yu, Ru-Qin

2016-01-01

Determination of benzo[a]pyrene (BaP) in cigarette smoke can be very important for the tobacco quality control and the assessment of its harm to human health. In this study, mid-infrared spectroscopy (MIR) coupled to chemometric algorithm (DPSO-WPT-PLS), which was based on the wavelet packet transform (WPT), discrete particle swarm optimization algorithm (DPSO) and partial least squares regression (PLS), was used to quantify harmful ingredient benzo[a]pyrene in the cigarette mainstream smoke with promising result. Furthermore, the proposed method provided better performance compared to several other chemometric models, i.e., PLS, radial basis function-based PLS (RBF-PLS), PLS with stepwise regression variable selection (Stepwise-PLS) as well as WPT-PLS with informative wavelet coefficients selected by correlation coefficient test (rtest-WPT-PLS). It can be expected that the proposed strategy could become a new effective, rapid quantitative analysis technique in analyzing the harmful ingredient BaP in cigarette mainstream smoke. Copyright © 2015 Elsevier B.V. All rights reserved.

[Aggression and related factors in elementary school students].

PubMed

Ji, Eun Sun; Jang, Mi Heui

2010-10-01

This study was done to explore the relationship between aggression and internet over-use, depression-anxiety, self-esteem, all of which are known to be behavior and psychological characteristics linked to "at-risk" children for aggression. Korean-Child Behavior Check List (K-CBCL), Korean-Internet Addiction Self-Test Scale, and Self-Esteem Scale by Rosenberg (1965) were used as measurement tools with a sample of 743, 5th-6th grade students from 3 elementary schools in Jecheon city. Chi-square, t-test, ANOVA, Pearson's correlation and stepwise multiple regression with SPSS/Win 13.0 version were used to analyze the collected data. Aggression for the elementary school students was positively correlated with internet over-use and depression-anxiety, whereas self-esteem was negatively correlated with aggression. Stepwise multiple regression analysis showed that 68.4% of the variance for aggression was significantly accounted for by internet over-use, depression-anxiety, and self-esteem. The most significant factor influencing aggression was depression-anxiety. These results suggest that earlier screening and intervention programs for depression-anxiety and internet over-use for elementary student will be helpful in preventing aggression.

Nucleated red blood cells in growth-restricted fetuses: associations with short-term neonatal outcome.

PubMed

Minior, V K; Bernstein, P S; Divon, M Y

2000-01-01

To determine the utility of the neonatal nucleated red blood cell (NRBC) count as an independent predictor of short-term perinatal outcome in growth-restricted fetuses. Hospital charts of neonates with a discharge diagnosis indicating a birth weight <10th percentile were reviewed for perinatal outcome. We studied all eligible neonates who had a complete blood count on the first day of life. After multiple gestations, anomalous fetuses and diabetic pregnancies were excluded; 73 neonates comprised the study group. Statistical analysis included ANOVA, simple and stepwise regression. Elevated NRBC counts were significantly associated with cesarean section for non-reassuring fetal status, neonatal intensive care unit admission and duration of neonatal intensive care unit stay, respiratory distress and intubation, thrombocytopenia, hyperbilirubinemia, intraventricular hemorrhage and neonatal death. Stepwise regression analysis including gestational age at birth, birth weight and NRBC count demonstrated that in growth-restricted fetuses, NRBC count was the strongest predictor of neonatal intraventricular hemorrhage, neonatal respiratory distress and neonatal death. An elevated NRBC count independently predicts adverse perinatal outcome in growth-restricted fetuses. Copyright 2000 S. Karger AG, Basel.

Optimizing the time-frame for the definition of bleeding-related death after acute variceal bleeding in cirrhosis.

PubMed

Merkel, C; Gatta, A; Bellumat, A; Bolognesi, M; Borsato, L; Caregaro, L; Cavallarin, G; Cielo, R; Cristina, P; Cucci, E; Donada, C; Donadon, V; Enzo, E; Martin, R; Mazzaro, C; Sacerdoti, D; Torboli, P

1996-01-01

To identify the best time-frame for defining bleeding-related death after variceal bleeding in patients with cirrhosis. Prospective long-term evaluation of a cohort of 155 patients admitted with variceal bleeding. Eight medical departments in seven hospitals in north-eastern Italy. Non-linear regression analysis of a hazard curve for death, and Cox's multiple regression analyses using different zero-time points. Cumulative hazard plots gave two slopes, the first corresponding to the risk of death from acute bleeding, the second a baseline risk of death. The first 30 days were outside the confidence limits of the regression curve for the baseline risk of death. Using Cox's regression analysis, the significant predictors of overall mortality risk were balanced between factors related to severity of bleeding and those related to severity of liver disease. If only deaths occurring after 30 days were considered, only predictors related to the severity of liver disease were found to be of importance. Thirty days after bleeding is considered to be a reasonable time-frame for the definition of bleeding-related death in patients with cirrhosis and variceal bleeding.

Comparably high retention and low relapse rates in different subpopulations of bipolar patients in a German non-interventional study.

PubMed

Kraemer, Susanne; Minarzyk, Anette; Eppendorfer, Steffen; Henneges, Carsten; Hundemer, Hans-Peter; Wilhelm, Stefan; Grunze, Heinz

2013-07-17

Although a range of pharmacotherapeutical options are available for the treatment of bipolar disorder, patient non-adherence to prescribed treatment regimens and early treatment discontinuation remain among the primary obstacles to effective treatment. Therefore, this observational study assessed time on mood stabilizing medication and retention rates in patients with bipolar disorder (BD). In an 18-month, prospective, multicenter, non-interventional study conducted in Germany 761 outpatients (≥18 years) with BD and on maintenance therapy were documented. For analysis, patients were stratified by baseline medication: monotherapy olanzapine (OM, N = 186), lithium (LM, N = 152), anticonvulsants (N = 216), other mood stabilizing medication (OMS, N = 44); combination therapy olanzapine/lithium (N = 47), olanzapine/anticonvulsant (N = 68), other combinations (OC, N = 48). Continuation on medication was assessed as retention rates with 95% confidence intervals. Time to discontinuation and relapse-free time were calculated by Kaplan-Meier analysis. A relapse was defined as increase to CGI-BP >3, worsening of CGI-BP by ≥2 points, hospitalization or death related to BD. A Cox regression was calculated for the discontinuation of mood stabilizing therapy (reference: OM). Logistic regression models with stepwise forward selection were used to explore possible predictors of maintenance of treatment and relapse. After 540 days (18 months), the overall retention rate of baseline medication was 87.7%, without notable differences between the cohorts. The overall mean time on mood stabilizing treatment was 444.7 days, with a range of 377.5 (OMS) to 481 (LM) by cohort. 74.0% of all patients were without relapse, with rates between the cohorts ranging from 58.4% (OC) to 80.2% (LM). Retention rates exceeded controlled trial results in all treatment cohorts, in addition to other explanations possibly reflecting that the physicians were expertly adapting treatment regimens to the individual patient's disease characteristics and special needs.

Secondary Prevention of Cardiovascular Disease in Patients With Type 2 Diabetes Mellitus: International Insights From the TECOS Trial (Trial Evaluating Cardiovascular Outcomes With Sitagliptin).

PubMed

Pagidipati, Neha J; Navar, Ann Marie; Pieper, Karen S; Green, Jennifer B; Bethel, M Angelyn; Armstrong, Paul W; Josse, Robert G; McGuire, Darren K; Lokhnygina, Yuliya; Cornel, Jan H; Halvorsen, Sigrun; Strandberg, Timo E; Delibasi, Tuncay; Holman, Rury R; Peterson, Eric D

2017-09-26

Intensive risk factor modification significantly improves outcomes for patients with diabetes mellitus and cardiovascular disease. However, the degree to which secondary prevention treatment goals are achieved in international clinical practice is unknown. Attainment of 5 secondary prevention parameters-aspirin use, lipid control (low-density lipoprotein cholesterol <70 mg/dL or statin therapy), blood pressure control (<140 mm Hg systolic, <90 mm Hg diastolic), angiotensin-converting enzyme inhibitor or angiotensin receptor blocker use, and nonsmoking status-was evaluated among 13 616 patients from 38 countries with diabetes mellitus and known cardiovascular disease at entry into TECOS (Trial Evaluating Cardiovascular Outcomes With Sitagliptin). Logistic regression was used to evaluate the association between individual and regional factors and secondary prevention achievement at baseline. Cox proportional hazards regression analysis was used to determine the association between baseline secondary prevention achievement and cardiovascular death, myocardial infarction, or stroke. Overall, 29.9% of patients with diabetes mellitus and cardiovascular disease achieved all 5 secondary prevention parameters at baseline, although 71.8% achieved at least 4 parameters. North America had the highest proportion (41.2%), whereas Western Europe, Eastern Europe, and Latin America had proportions of ≈25%. Individually, blood pressure control (57.9%) had the lowest overall attainment, whereas nonsmoking status had the highest (89%). Over a median 3.0 years of follow-up, a higher baseline secondary prevention score was associated with improved outcomes in a step-wise graded relationship (adjusted hazard ratio, 0.60; 95% confidence interval, 0.47-0.77 for those patients achieving all 5 measures versus those achieving ≤2). In an international trial population, significant opportunities exist to improve the quality of cardiovascular secondary prevention care among patients with diabetes mellitus and cardiovascular disease, which in turn could lead to reduced risk of downstream cardiovascular events. URL: http://www.clinicaltrials.gov. Unique identifier: NCT00790205. © 2017 American Heart Association, Inc.

Using instrumental variables to estimate a Cox's proportional hazards regression subject to additive confounding

PubMed Central

Tosteson, Tor D.; Morden, Nancy E.; Stukel, Therese A.; O'Malley, A. James

2014-01-01

The estimation of treatment effects is one of the primary goals of statistics in medicine. Estimation based on observational studies is subject to confounding. Statistical methods for controlling bias due to confounding include regression adjustment, propensity scores and inverse probability weighted estimators. These methods require that all confounders are recorded in the data. The method of instrumental variables (IVs) can eliminate bias in observational studies even in the absence of information on confounders. We propose a method for integrating IVs within the framework of Cox's proportional hazards model and demonstrate the conditions under which it recovers the causal effect of treatment. The methodology is based on the approximate orthogonality of an instrument with unobserved confounders among those at risk. We derive an estimator as the solution to an estimating equation that resembles the score equation of the partial likelihood in much the same way as the traditional IV estimator resembles the normal equations. To justify this IV estimator for a Cox model we perform simulations to evaluate its operating characteristics. Finally, we apply the estimator to an observational study of the effect of coronary catheterization on survival. PMID:25506259

Using instrumental variables to estimate a Cox's proportional hazards regression subject to additive confounding.

PubMed

MacKenzie, Todd A; Tosteson, Tor D; Morden, Nancy E; Stukel, Therese A; O'Malley, A James

2014-06-01

The estimation of treatment effects is one of the primary goals of statistics in medicine. Estimation based on observational studies is subject to confounding. Statistical methods for controlling bias due to confounding include regression adjustment, propensity scores and inverse probability weighted estimators. These methods require that all confounders are recorded in the data. The method of instrumental variables (IVs) can eliminate bias in observational studies even in the absence of information on confounders. We propose a method for integrating IVs within the framework of Cox's proportional hazards model and demonstrate the conditions under which it recovers the causal effect of treatment. The methodology is based on the approximate orthogonality of an instrument with unobserved confounders among those at risk. We derive an estimator as the solution to an estimating equation that resembles the score equation of the partial likelihood in much the same way as the traditional IV estimator resembles the normal equations. To justify this IV estimator for a Cox model we perform simulations to evaluate its operating characteristics. Finally, we apply the estimator to an observational study of the effect of coronary catheterization on survival.

Tibiofemoral contact forces during walking, running and sidestepping.

PubMed

Saxby, David J; Modenese, Luca; Bryant, Adam L; Gerus, Pauline; Killen, Bryce; Fortin, Karine; Wrigley, Tim V; Bennell, Kim L; Cicuttini, Flavia M; Lloyd, David G

2016-09-01

We explored the tibiofemoral contact forces and the relative contributions of muscles and external loads to those contact forces during various gait tasks. Second, we assessed the relationships between external gait measures and contact forces. A calibrated electromyography-driven neuromusculoskeletal model estimated the tibiofemoral contact forces during walking (1.44±0.22ms(-1)), running (4.38±0.42ms(-1)) and sidestepping (3.58±0.50ms(-1)) in healthy adults (n=60, 27.3±5.4years, 1.75±0.11m, and 69.8±14.0kg). Contact forces increased from walking (∼1-2.8 BW) to running (∼3-8 BW), sidestepping had largest maximum total (8.47±1.57 BW) and lateral contact forces (4.3±1.05 BW), while running had largest maximum medial contact forces (5.1±0.95 BW). Relative muscle contributions increased across gait tasks (up to 80-90% of medial contact forces), and peaked during running for lateral contact forces (∼90%). Knee adduction moment (KAM) had weak relationships with tibiofemoral contact forces (all R(2)<0.36) and the relationships were gait task-specific. Step-wise regression of multiple external gait measures strengthened relationships (0.20

Marital status and survival in patients with renal cell carcinoma.

PubMed

Li, Yan; Zhu, Ming-Xi; Qi, Si-Hua

2018-04-01

Previous studies have shown that marital status is an independent prognostic factor for survival in several types of cancer. In this study, we investigated the effects of marital status on survival outcomes among renal cell carcinoma (RCC) patients.We identified patients diagnosed with RCC between 1973 and 2013 from the Surveillance, Epidemiology and End Results (SEER) database. Kaplan-Meier analysis and Cox regression were used to identify the effects of marital status on overall survival (OS) and cancer-specific survival (CSS).We enrolled 97,662 eligible RCC patients, including 64,884 married patients, and 32,778 unmarried (9831 divorced/separated, 9692 widowed, and 13,255 single) patients at diagnosis. The 5-year OS and CSS rates of the married, separated/divorced, widowed, and single patients were 73.7%, 69.5%, 58.3%, and 73.2% (OS), and 82.2%, 80.7%, 75.7%, and 83.3% (CSS), respectively. Multivariate Cox regression showed that, compared with married patients, widowed individuals showed poorer OS (hazard ratio, 1.419; 95% confidence interval, 1.370-1.469) and CSS (hazard ratio, 1.210; 95% confidence interval, 1.144-1.279). Stratified analyses and multivariate Cox regression showed that, in the insured and uninsured groups, married patients had better survival outcomes while widowed patients suffered worse OS outcomes; however, this trend was not significant for CSS.In RCC patients, married patients had better survival outcomes while widowed patients tended to suffer worse survival outcomes in terms of both OS and CSS.

Marital status and survival in patients with renal cell carcinoma

PubMed Central

Li, Yan; Zhu, Ming-xi; Qi, Si-hua

2018-01-01

Abstract Previous studies have shown that marital status is an independent prognostic factor for survival in several types of cancer. In this study, we investigated the effects of marital status on survival outcomes among renal cell carcinoma (RCC) patients. We identified patients diagnosed with RCC between 1973 and 2013 from the Surveillance, Epidemiology and End Results (SEER) database. Kaplan–Meier analysis and Cox regression were used to identify the effects of marital status on overall survival (OS) and cancer-specific survival (CSS). We enrolled 97,662 eligible RCC patients, including 64,884 married patients, and 32,778 unmarried (9831 divorced/separated, 9692 widowed, and 13,255 single) patients at diagnosis. The 5-year OS and CSS rates of the married, separated/divorced, widowed, and single patients were 73.7%, 69.5%, 58.3%, and 73.2% (OS), and 82.2%, 80.7%, 75.7%, and 83.3% (CSS), respectively. Multivariate Cox regression showed that, compared with married patients, widowed individuals showed poorer OS (hazard ratio, 1.419; 95% confidence interval, 1.370–1.469) and CSS (hazard ratio, 1.210; 95% confidence interval, 1.144–1.279). Stratified analyses and multivariate Cox regression showed that, in the insured and uninsured groups, married patients had better survival outcomes while widowed patients suffered worse OS outcomes; however, this trend was not significant for CSS. In RCC patients, married patients had better survival outcomes while widowed patients tended to suffer worse survival outcomes in terms of both OS and CSS. PMID:29668592

Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining.

PubMed

Reps, Jenna M; Aickelin, Uwe; Hubbard, Richard B

2016-02-01

To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. We considered six drug families that are commonly associated with myocardial infarction in observational healthcare data, but where the causal relationship ground truth is known (adverse drug reaction or not). We applied emergent pattern mining to find itemsets of drugs and medical events that are associated with the development of myocardial infarction. These are the candidate confounding interaction terms. We then implemented a cohort study design using regularised cox regression that incorporated and accounted for the candidate confounding interaction terms. The methodology was able to account for signals generated due to confounding and a cox regression with elastic net regularisation correctly ranking the drug families known to be true adverse drug reactions above those that are not. This was not the case without the inclusion of the candidate confounding interaction terms, where confounding leads to a non-adverse drug reaction being ranked highest. The methodology is efficient, can identify high-order confounding interactions and does not require expert input to specify outcome specific confounders, so it can be applied for any outcome of interest to quickly refine its signals. The proposed method shows excellent potential to overcome some forms of confounding and therefore reduce the false positive rate for signal analysis using longitudinal data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Does Stepwise Voltage Ramping Protect the Kidney from Injury During Extracorporeal Shockwave Lithotripsy? Results of a Prospective Randomized Trial.

PubMed

Skuginna, Veronika; Nguyen, Daniel P; Seiler, Roland; Kiss, Bernhard; Thalmann, George N; Roth, Beat

2016-02-01

Renal damage is more frequent with new-generation lithotripters. However, animal studies suggest that voltage ramping minimizes the risk of complications following extracorporeal shock wave lithotripsy (SWL). In the clinical setting, the optimal voltage strategy remains unclear. To evaluate whether stepwise voltage ramping can protect the kidney from damage during SWL. A total of 418 patients with solitary or multiple unilateral kidney stones were randomized to receive SWL using a Modulith SLX-F2 lithotripter with either stepwise voltage ramping (n=213) or a fixed maximal voltage (n=205). SWL. The primary outcome was sonographic evidence of renal hematomas. Secondary outcomes included levels of urinary markers of renal damage, stone disintegration, stone-free rate, and rates of secondary interventions within 3 mo of SWL. Descriptive statistics were used to compare clinical outcomes between the two groups. A logistic regression model was generated to assess predictors of hematomas. Significantly fewer hematomas occurred in the ramping group(12/213, 5.6%) than in the fixed group (27/205, 13%; p=0.008). There was some evidence that the fixed group had higher urinary β2-microglobulin levels after SWL compared to the ramping group (p=0.06). Urinary microalbumin levels, stone disintegration, stone-free rate, and rates of secondary interventions did not significantly differ between the groups. The logistic regression model showed a significantly higher risk of renal hematomas in older patients (odds ratio [OR] 1.03, 95% confidence interval [CI] 1.00-1.05; p=0.04). Stepwise voltage ramping was associated with a lower risk of hematomas (OR 0.39, 95% CI 0.19-0.80; p=0.01). The study was limited by the use of ultrasound to detect hematomas. In this prospective randomized study, stepwise voltage ramping during SWL was associated with a lower risk of renal damage compared to a fixed maximal voltage without compromising treatment effectiveness. Lithotripsy is a noninvasive technique for urinary stone disintegration using ultrasonic energy. In this study, two voltage strategies are compared. The results show that a progressive increase in voltage during lithotripsy decreases the risk of renal hematomas while maintaining excellent outcomes. ISRCTN95762080. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Utility of an Abbreviated Dizziness Questionnaire to Differentiate Between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study.

PubMed

Roland, Lauren T; Kallogjeri, Dorina; Sinks, Belinda C; Rauch, Steven D; Shepard, Neil T; White, Judith A; Goebel, Joel A

2015-12-01

Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. Prospective multicenter. Four academic centers with experienced balance specialists. New dizzy patients. A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.

Needs of the Learning Effect on Instructional Website for Vocational High School Students

ERIC Educational Resources Information Center

Lo, Hung-Jen; Fu, Gwo-Liang; Chuang, Kuei-Chih

2013-01-01

The purpose of study was to understand the correlation between the needs of the learning effect on instructional website for the vocational high school students. Our research applied the statistic methods of product-moment correlation, stepwise regression, and structural equation method to analyze the questionnaire with the sample size of 377…

Asynchronous Knowledge Sharing and Conversation Interaction Impact on Grade in an Online Business Course

ERIC Educational Resources Information Center

Strang, Kenneth David

2011-01-01

Student knowledge sharing and conversation theory interactions were coded from asynchronous discussion forums to measure the effect of learning-oriented utterances on academic performance. The sample was 3 terms of an online business course (in an accredited MBA program) at a U.S.-based university. Correlation, stepwise regression, and multiple…

Information Scent Determines Attention Allocation and Link Selection among Multiple Information Patches on a Webpage

ERIC Educational Resources Information Center

Blackmon, Marilyn Hughes

2012-01-01

This paper draws from cognitive psychology and cognitive neuroscience to develop a preliminary similarity-choice theory of how people allocate attention among information patches on webpages while completing search tasks in complex informational websites. Study 1 applied stepwise multiple regression to a large dataset and showed that success rate…

Advances in variable selection methods I: Causal selection methods versus stepwise regression and principal component analysis on data of known and unknown functional relationships

EPA Science Inventory

Hydrological predictions at a watershed scale are commonly based on extrapolation and upscaling of hydrological behavior at plot and hillslope scales. Yet, dominant hydrological drivers at a hillslope may not be as dominant at the watershed scale because of the heterogeneity of w...

Handling Missing Data: Analysis of a Challenging Data Set Using Multiple Imputation

ERIC Educational Resources Information Center

Pampaka, Maria; Hutcheson, Graeme; Williams, Julian

2016-01-01

Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their…

Heterosexual Risk Behaviors Among Urban Young Adolescents

ERIC Educational Resources Information Center

O'Donnell, Lydia; Stueve, Ann; Wilson-Simmons, Renee; Dash, Kim; Agronick, Gail; JeanBaptiste, Varzi

2006-01-01

Urban 6th graders (n = 294) participate in a survey assessing early heterosexual risk behaviors as part of the Reach for Health Middle Childhood Study. About half the boys (47%) and 20% of girls report having a girlfriend or boyfriend; 42% of boys and 10% of girls report kissing and hugging for a long time. Stepwise regressions model the…

Beyond the Black-White Test Score Gap: Latinos' Early School Experiences and Literacy Outcomes

ERIC Educational Resources Information Center

Delgado, Enilda A.; Stoll, Laurie Cooper

2015-01-01

Data from the Early Childhood Longitudinal Survey-Birth Cohort are used to analyze the factors that lead to the reading readiness of children who participate in nonparental care the year prior to kindergarten (N = 4,550), with a specific focus on Latino children (N = 800). Stepwise multiple linear regression analysis demonstrates that reading…

Consequences of ignoring geologic variation in evaluating grazing impacts

Treesearch

Jonathan W. Long; Alvin L. Medina

2006-01-01

The geologic diversity of landforms in the Southwest complicates efforts to evaluate impacts of land uses such as livestock grazing. We examined a research study that evaluated relationships between trout biomass and stream habitat in the White Mountains of east-central Arizona. That study interpreted results of stepwise regressions and a nonparametric test of “grazed...

The Relationship of Selected Supply- and Demand-Side Factors to Forms of Perceived Discrimination among Adults with Multiple Sclerosis

ERIC Educational Resources Information Center

Roessler, Richard T.; Neath, Jeanne; McMahon, Brian T.; Rumrill, Phillip D.

2007-01-01

Single-predictor and stepwise multinomial logistic regression analyses and an external validation were completed on 3,082 allegations of employment discrimination by adults with multiple sclerosis. Women filed two thirds of the allegations, and individuals between 31 and 50 made the vast majority of discrimination charges (73%). Allegations…

Age, Sex, and Body Composition as Predictors of Children's Performance on Basic Motor Abilities and Health-Related Fitness Items.

ERIC Educational Resources Information Center

Pissanos, Becky W.; And Others

1983-01-01

Step-wise linear regressions were used to relate children's age, sex, and body composition to performance on basic motor abilities including balance, speed, agility, power, coordination, and reaction time, and to health-related fitness items including flexibility, muscle strength and endurance and cardiovascular functions. Eighty subjects were in…

Non-Steroidal Anti-Inflammatory Drugs and Cardiovascular Outcomes in Women: Results from the Women’s Health Initiative

PubMed Central

Bavry, Anthony A.; Thomas, Fridtjof; Allison, Matthew; Johnson, Karen C.; Howard, Barbara V.; Hlatky, Mark; Manson, JoAnn E.; Limacher, Marian C.

2014-01-01

Background Conclusive data regarding cardiovascular (CV) toxicity of non-steroidal anti-inflammatory drugs (NSAIDs) are sparse. We hypothesized that regular NSAID use is associated with increased risk for CV events in post-menopausal women, and that this association is stronger with greater cyclooxygenase (cox)-2 compared with cox-1 inhibition. Methods and Results Post-menopausal women enrolled in the Women’s Health Initiative (WHI) were classified as regular users or non-users of non-aspirin NSAIDs. Cox regression examined NSAID use as a time-varying covariate and its association with the primary outcome of total CV disease defined as CV death, nonfatal myocardial infarction, or nonfatal stroke. Secondary analyses considered the association of selective cox-2 inhibitors (e.g., celecoxib), non-selective agents with cox-2>cox-1 inhibition (e.g., naproxen), and non-selective agents with cox-1>cox-2 inhibition (e.g., ibuprofen) with the primary outcome. Overall, 160,801 participants were available for analysis (mean follow-up 11.2 years). Regular NSAID use at some point in time was reported by 53,142 participants. Regular NSAID use was associated with an increased hazard for CV events versus no NSAID use (HR=1.10[95% CI 1.06–1.15], Pitalic>0.001). Selective cox-2 inhibitors were associated with a modest increased hazard for CV events (HR=1.13[1.04–1.23], P=0.004; celecoxib only HR=1.13[1.01–1.27], P=0.031). Among aspirin users, concomitant selective cox-2 inhibitor use was no longer associated with increased hazard for CV events. There was an increased risk for agents with cox-2>cox-1 inhibition (HR=1.17[1.10–1.24], Pbold>0.001; naproxen only HR=1.22[1.12–1.34], P<0.001). This harmful association remained among concomitant aspirin users. We did not observe a risk elevation for agents with cox-1>cox-2 inhibition (HR=1.01[0.95–1.07], P=0.884; ibuprofen only HR=1.00[0.93–1.07], P=0.996). Conclusions Regular use of selective cox-2 inhibitors and non-selective NSAIDs with cox-2>cox-1 inhibition showed a modestly increased hazard for CV events. Non-selective agents with cox-1>cox-2 inhibition were not associated with increased CV risk. Clinical Trial Registration www.clinicaltrials.gov NCT00000611 PMID:25006185

Disorganized Symptoms Predicted Worse Functioning Outcome in Schizophrenia Patients with Established Illness.

PubMed

Ortiz, Bruno Bertolucci; Gadelha, Ary; Higuchi, Cinthia Hiroko; Noto, Cristiano; Medeiros, Daiane; Pitta, José Cássio do Nascimento; de Araújo Filho, Gerardo Maria; Hallak, Jaime Eduardo Cecílio; Bressan, Rodrigo Affonseca

Most patients with schizophrenia will have subsequent relapses of the disorder, with continuous impairments in functioning. However, evidence is lacking on how symptoms influence functioning at different phases of the disease. This study aims to investigate the relationship between symptom dimensions and functioning at different phases: acute exacerbation, nonremission and remission. Patients with schizophrenia were grouped into acutely ill (n=89), not remitted (n=89), and remitted (n=69). Three exploratory stepwise linear regression analyses were performed for each phase of schizophrenia, in which the five PANSS factors and demographic variables were entered as the independent variables and the total Global Assessment of Functioning Scale (GAF) score was entered as the dependent variable. An additional exploratory stepwise logistic regression analysis was performed to predict subsequent remission at discharge in the inpatient population. The Disorganized factor was the most significant predictor for acutely ill patients (p<0.001), while the Hostility factor was the most significant for not-remitted patients and the Negative factor was the most significant for remitted patients (p=0.001 and p<0.001, respectively). In the logistic regression, the Disorganized factor score presented a significant negative association with remission (p=0.007). Higher disorganization symptoms showed the greatest impact in functioning at acute phase, and prevented patients from achieving remission, suggesting it may be a marker of symptom severity and worse outcome in schizophrenia.

Delineating chalk sand distribution of Ekofisk formation using probabilistic neural network (PNN) and stepwise regression (SWR): Case study Danish North Sea field

NASA Astrophysics Data System (ADS)

Haris, A.; Nafian, M.; Riyanto, A.

2017-07-01

Danish North Sea Fields consist of several formations (Ekofisk, Tor, and Cromer Knoll) that was started from the age of Paleocene to Miocene. In this study, the integration of seismic and well log data set is carried out to determine the chalk sand distribution in the Danish North Sea field. The integration of seismic and well log data set is performed by using the seismic inversion analysis and seismic multi-attribute. The seismic inversion algorithm, which is used to derive acoustic impedance (AI), is model-based technique. The derived AI is then used as external attributes for the input of multi-attribute analysis. Moreover, the multi-attribute analysis is used to generate the linear and non-linear transformation of among well log properties. In the case of the linear model, selected transformation is conducted by weighting step-wise linear regression (SWR), while for the non-linear model is performed by using probabilistic neural networks (PNN). The estimated porosity, which is resulted by PNN shows better suited to the well log data compared with the results of SWR. This result can be understood since PNN perform non-linear regression so that the relationship between the attribute data and predicted log data can be optimized. The distribution of chalk sand has been successfully identified and characterized by porosity value ranging from 23% up to 30%.

Periodontitis in coronary heart disease patients: strong association between bleeding on probing and systemic biomarkers.

PubMed

Bokhari, Syed Akhtar H; Khan, Ayyaz A; Butt, Arshad K; Hanif, Mohammad; Izhar, Mateen; Tatakis, Dimitris N; Ashfaq, Mohammad

2014-11-01

Few studies have examined the relationship of individual periodontal parameters with individual systemic biomarkers. This study assessed the possible association between specific clinical parameters of periodontitis and systemic biomarkers of coronary heart disease risk in coronary heart disease patients with periodontitis. Angiographically proven coronary heart disease patients with periodontitis (n = 317), aged >30 years and without other systemic illness were examined. Periodontal clinical parameters of bleeding on probing (BOP), probing depth (PD), and clinical attachment level (CAL) and systemic levels of high-sensitivity C-reactive protein (CRP), fibrinogen (FIB) and white blood cells (WBC) were noted and analyzed to identify associations through linear and stepwise multiple regression analyses. Unadjusted linear regression showed significant associations between periodontal and systemic parameters; the strongest association (r = 0.629; p < 0.001) was found between BOP and CRP levels, the periodontal and systemic inflammation marker, respectively. Stepwise regression analysis models revealed that BOP was a predictor of systemic CRP levels (p < 0.0001). BOP was the only periodontal parameter significantly associated with each systemic parameter (CRP, FIB, and WBC). In coronary heart disease patients with periodontitis, BOP is strongly associated with systemic CRP levels; this association possibly reflects the potential significance of the local periodontal inflammatory burden for systemic inflammation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Effects of the estrous cycle, pregnancy and interferon tau on expression of cyclooxygenase two (COX-2) in ovine endometrium

PubMed Central

Kim, Seokwoon; Choi, Youngsok; Spencer, Thomas E; Bazer, Fuller W

2003-01-01

In sheep, the uterus produces luteolytic pulses of prostaglandin F2α (PGF) on Days 15 to 16 of estrous cycle to regress the corpus luteum (CL). These PGF pulses are produced by the endometrial lumenal epithelium (LE) and superficial ductal glandular epithelium (sGE) in response to binding of pituitary and/or luteal oxytocin to oxytocin receptors (OTR) and liberation of arachidonic acid, the precursor of PGF. Cyclooxygenase-one (COX-1) and COX-2 are rate-limiting enzymes in PGF synthesis, and COX-2 is the major form expressed in ovine endometrium. During pregnancy recognition, interferon tau (IFNτ), produced by the conceptus trophectoderm, acts in a paracrine manner to suppress development of the endometrial epithelial luteolytic mechanism by inhibiting transcription of estrogen receptor α (ERα) (directly) and OTR (indirectly) genes. Conflicting studies indicate that IFNτ increases, decreases or has no effect on COX-2 expression in bovine and ovine endometrial cells. In Study One, COX-2 mRNA and protein were detected solely in endometrial LE and sGE of both cyclic and pregnant ewes. During the estrous cycle, COX-2 expression increased from Days 10 to 12 and then decreased to Day 16. During early pregnancy, COX-2 expression increased from Days 10 to 12 and remained higher than in cyclic ewes. In Study Two, intrauterine infusion of recombinant ovine IFNτ in cyclic ewes from Days 11 to 16 post-estrus did not affect COX-2 expression in the endometrial epithelium. These results clearly indicate that IFNτ has no effect on expression of the COX-2 gene in the ovine endometrium. Therefore, antiluteolytic effects of IFNτ are to inhibit ERα and OTR gene transcription, thereby preventing endometrial production of luteolytic pulses of PGF. Indeed, expression of COX-2 in the endometrial epithelia as well as conceptus is likely to have a beneficial regulatory role in implantation and development of the conceptus. PMID:12956885

Joint effect of unlinked genotypes: application to type 2 diabetes in the EPIC-Potsdam case-cohort study.

PubMed

Knüppel, Sven; Meidtner, Karina; Arregui, Maria; Holzhütter, Hermann-Georg; Boeing, Heiner

2015-07-01

Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects. © 2015 John Wiley & Sons Ltd/University College London.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Kunkun, E-mail: ktg@illinois.edu; Inria Bordeaux – Sud-Ouest, Team Cardamom, 200 avenue de la Vieille Tour, 33405 Talence; Congedo, Pietro M.

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable formore » real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.« less

Sodium Intake and Osteoporosis. Findings From the Women's Health Initiative.

PubMed

Carbone, Laura; Johnson, Karen C; Huang, Ying; Pettinger, Mary; Thomas, Fridjtof; Cauley, Jane; Crandall, Carolyn; Tinker, Lesley; LeBoff, Meryl Susan; Wactawski-Wende, Jean; Bethel, Monique; Li, Wenjun; Prentice, Ross

2016-04-01

In this large, prospective, observational cohort study of postmenopausal women in the WHI, Cox proportional hazard regression models showed that sodium intake at or near recommended levels is not likely to impact bone metabolism.

An evaluation of treatment strategies for head and neck cancer in an African American population.

PubMed

Ignacio, D N; Griffin, J J; Daniel, M G; Serlemitsos-Day, M T; Lombardo, F A; Alleyne, T A

2013-07-01

This study evaluated treatment strategies for head and neck cancers in a predominantly African American population. Data were collected utilizing medical records and the tumour registry at the Howard University Hospital. Kaplan-Meier method was used for survival analysis and Cox proportional hazards regression analysis predicted the hazard of death. Analysis revealed that the main treatment strategy was radiation combined with platinum for all stages except stage I. Cetuximab was employed in only 1% of cases. Kaplan-Meier analysis revealed stage II patients had poorer outcome than stage IV while Cox proportional hazard regression analysis (p = 0.4662) showed that stage I had a significantly lower hazard of death than stage IV (HR = 0.314; p = 0.0272). Contributory factors included tobacco and alcohol but body mass index (BMI) was inversely related to hazard of death. There was no difference in survival using any treatment modality for African Americans.

Cyclooxygenase 2 gene polymorphisms and chronic periodontitis in a North Indian population: a pilot study

PubMed Central

Daing, Anika; Singh, Sarvendra Vikram; Saimbi, Charanjeet Singh; Khan, Mohammad Akhlaq

2012-01-01

Purpose Cyclooxygenase (COX) enzyme catalyzes the production of prostaglandins, which are important mediators of tissue destruction in periodontitis. Single nucleotide polymorphisms of COX2 enzyme have been associated with increasing susceptibility to inflammatory diseases. The present study evaluates the association of two single nucleotide polymorphisms in COX2 gene (-1195G>A and 8473C>T) with chronic periodontitis in North Indians. Methods Both SNPs and their haplotypes were used to explore the associations between COX2 polymorphisms and chronic periodontitis in 56 patients and 60 controls. Genotyping was done by polymerase chain reaction followed by restriction fragment length polymorphism. Chi-square test and logistic regression analysis were performed for association analysis. Results By the individual genotype analysis, mutant genotypes (GA and AA) of COX2 -1195 showed more than a two fold risk (odds ratio [OR]>2) and COX2 8473 (TC and CC) showed a reduced risk for the disease, but the findings were not statistically significant. Haplotype analysis showed that the frequency of the haplotype AT was higher in the case group and a significant association was found for haplotype AT (OR, 1.79; 95% confidence interval, 1.03 to 3.11; P=0.0370) indicating an association between the AT haplotype of COX2 gene SNPs and chronic periodontitis. Conclusions Individual genotypes of both the SNPs were not associated while haplotype AT was found to be associated with chronic periodontitis in North Indians. PMID:23185695

Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

PubMed

Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

2011-12-01

This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.

Quantile regression via vector generalized additive models.

PubMed

Yee, Thomas W

2004-07-30

One of the most popular methods for quantile regression is the LMS method of Cole and Green. The method naturally falls within a penalized likelihood framework, and consequently allows for considerable flexible because all three parameters may be modelled by cubic smoothing splines. The model is also very understandable: for a given value of the covariate, the LMS method applies a Box-Cox transformation to the response in order to transform it to standard normality; to obtain the quantiles, an inverse Box-Cox transformation is applied to the quantiles of the standard normal distribution. The purposes of this article are three-fold. Firstly, LMS quantile regression is presented within the framework of the class of vector generalized additive models. This confers a number of advantages such as a unifying theory and estimation process. Secondly, a new LMS method based on the Yeo-Johnson transformation is proposed, which has the advantage that the response is not restricted to be positive. Lastly, this paper describes a software implementation of three LMS quantile regression methods in the S language. This includes the LMS-Yeo-Johnson method, which is estimated efficiently by a new numerical integration scheme. The LMS-Yeo-Johnson method is illustrated by way of a large cross-sectional data set from a New Zealand working population. Copyright 2004 John Wiley & Sons, Ltd.

The TP53 gene polymorphisms and survival of sporadic breast cancer patients.

PubMed

Bišof, V; Salihović, M Peričić; Narančić, N Smolej; Skarić-Jurić, T; Jakić-Razumović, J; Janićijević, B; Rudan, P

2012-06-01

The TP53 gene polymorphisms, Arg72Pro and PIN3 (+16 bp), can have prognostic and predictive value in different cancers including breast cancer. The aim of the present study is to investigate a potential association between different genotypes of these polymorphisms and clinicopathological variables with survival of breast cancer patients in Croatian population. Ninety-four women with sporadic breast cancer were retrospectively analyzed. Median follow-up period was 67.9 months. The effects of basic clinical and histopathological characteristics of tumor on survival were tested by Cox's proportional hazards regression analysis. The TNM stage was associated with overall survival by Kaplan-Meier analysis, univariate, and multivariate Cox's proportional hazards regression analysis, while grade was associated with survival by Kaplan-Meier analysis and univariate Cox's proportional hazards regression analysis. Different genotypes of the Arg72Pro and PIN3 (+16 bp) polymorphisms had no significant impact on survival in breast cancer patients. However, in subgroup of patients treated with chemotherapy without anthracycline, the A2A2 genotype of the PIN3 (+16 bp) polymorphism was associated with poorer overall survival than other genotypes by Kaplan-Meier analysis (P = 0.048). The TP53 polymorphisms, Arg72Pro and PIN3 (+16 bp), had no impact on survival in unselected sporadic breast cancer patients in Croatian population. However, the results support the role of the A2A2 genotype of the PIN3 (+16 bp) polymorphism as a marker for identification of patients that may benefit from anthracycline-containing chemotherapy.

Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.

PubMed

Oh, Eric J; Shepherd, Bryan E; Lumley, Thomas; Shaw, Pamela A

2018-04-15

For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With nonlinear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of 2 common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic. Copyright © 2017 John Wiley & Sons, Ltd.

Does buccal cancer have worse prognosis than other oral cavity cancers?

PubMed

Camilon, P Ryan; Stokes, William A; Fuller, Colin W; Nguyen, Shaun A; Lentsch, Eric J

2014-06-01

To determine whether buccal squamous cell carcinoma has worse overall survival (OS) and disease-specific survival (DSS) than cancers in the rest of the oral cavity. Retrospective analysis of a large population database. We began with a Kaplan-Meier analysis of OS and DSS for buccal versus nonbuccal tumors with unmatched data, followed by an analysis of cases matched for race, age at diagnosis, stage at diagnosis, and treatment modality. This was supported by a univariate Cox regression comparing buccal cancer to nonbuccal cancer, followed by a multivariate Cox regression that included all significant variables studied. With unmatched data, buccal cancer had significantly lesser OS and DSS values than cancers in the rest of the oral cavity (P < .001). After case matching, the differences between OS and DSS for buccal cancer versus nonbuccal oral cancer were no longer significant. Univariate Cox regression models with respect to OS and DSS showed a significant difference between buccal cancer and nonbuccal cancer. However, with multivariate analysis, buccal hazard ratios for OS and DSS were not significant. With the largest series of buccal carcinoma to date, our study concludes that the OS and DSS of buccal cancer are similar to those of cancers in other oral cavity sites once age at diagnosis, tumor stage, treatment, and race are taken into consideration. The previously perceived poor prognosis of buccal carcinoma may be due to variations in tumor presentation, such as later stage and older patient age. 2b. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Assessing the prediction accuracy of cure in the Cox proportional hazards cure model: an application to breast cancer data.

PubMed

Asano, Junichi; Hirakawa, Akihiro; Hamada, Chikuma

2014-01-01

A cure rate model is a survival model incorporating the cure rate with the assumption that the population contains both uncured and cured individuals. It is a powerful statistical tool for prognostic studies, especially in cancer. The cure rate is important for making treatment decisions in clinical practice. The proportional hazards (PH) cure model can predict the cure rate for each patient. This contains a logistic regression component for the cure rate and a Cox regression component to estimate the hazard for uncured patients. A measure for quantifying the predictive accuracy of the cure rate estimated by the Cox PH cure model is required, as there has been a lack of previous research in this area. We used the Cox PH cure model for the breast cancer data; however, the area under the receiver operating characteristic curve (AUC) could not be estimated because many patients were censored. In this study, we used imputation-based AUCs to assess the predictive accuracy of the cure rate from the PH cure model. We examined the precision of these AUCs using simulation studies. The results demonstrated that the imputation-based AUCs were estimable and their biases were negligibly small in many cases, although ordinary AUC could not be estimated. Additionally, we introduced the bias-correction method of imputation-based AUCs and found that the bias-corrected estimate successfully compensated the overestimation in the simulation studies. We also illustrated the estimation of the imputation-based AUCs using breast cancer data. Copyright © 2014 John Wiley & Sons, Ltd.

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

A Prognostic Model to Predict Mortality among Non-Small-Cell Lung Cancer Patients in the U.S. Military Health System.

PubMed

Lin, Jie; Carter, Corey A; McGlynn, Katherine A; Zahm, Shelia H; Nations, Joel A; Anderson, William F; Shriver, Craig D; Zhu, Kangmin

2015-12-01

Accurate prognosis assessment after non-small-cell lung cancer (NSCLC) diagnosis is an essential step for making effective clinical decisions. This study is aimed to develop a prediction model with routinely available variables to assess prognosis in patients with NSCLC in the U.S. Military Health System. We used the linked database from the Department of Defense's Central Cancer Registry and the Military Health System Data Repository. The data set was randomly and equally split into a training set to guide model development and a testing set to validate the model prediction. Stepwise Cox regression was used to identify predictors of survival. Model performance was assessed by calculating area under the receiver operating curves and construction of calibration plots. A simple risk scoring system was developed to aid quick risk score calculation and risk estimation for NSCLC clinical management. The study subjects were 5054 patients diagnosed with NSCLC between 1998 and 2007. Age, sex, tobacco use, tumor stage, histology, surgery, chemotherapy, peripheral vascular disease, cerebrovascular disease, and diabetes mellitus were identified as significant predictors of survival. Calibration showed high agreement between predicted and observed event rates. The area under the receiver operating curves reached 0.841, 0.849, 0.848, and 0.838 during 1, 2, 3, and 5 years, respectively. This is the first NSCLC prognosis model for quick risk assessment within the Military Health System. After external validation, the model can be translated into clinical use both as a web-based tool and through mobile applications easily accessible to physicians, patients, and researchers.

Clinical impact of targeted therapies in patients with metastatic clear-cell renal cell carcinoma

PubMed Central

Nerich, Virginie; Hugues, Marion; Paillard, Marie Justine; Borowski, Laëtitia; Nai, Thierry; Stein, Ulrich; Nguyen Tan Hon, Thierry; Montcuquet, Philippe; Maurina, Tristan; Mouillet, Guillaume; Kleinclauss, François; Pivot, Xavier; Limat, Samuel; Thiery-Vuillemin, Antoine

2014-01-01

Introduction The aim of this retrospective clinical study was to assess, in the context of the recent evolution of systemic therapies, the potential effect of targeted therapies on overall survival (OS) of patients with metastatic clear-cell renal cell carcinoma (mccRCC) in daily practice. Patients and methods All consecutive patients with histologically confirmed mccRCC who received systemic therapy between January 2000 and December 2010 in two oncology treatment centers in our Franche-Comté region in eastern France were included in the analysis. The primary end point was OS. The analysis of prognostic factors was performed using a two-step approach: univariate then multivariate analysis with a stepwise Cox proportional hazards regression model. Results For the entire cohort of 111 patients, the median OS was 17 months (95% confidence interval [CI]; 13–22 months) and the two-year OS was 39%. Three prognostic factors were independent predictors of long survival: prior nephrectomy (hazard ratio =0.38 [0.22–0.64], P<0.0001); systemic therapy by targeted therapy (hazard ratio =0.50 [0.31–0.80], P=0.005); and lack of liver metastasis (hazard ratio =0.43 [0.22–0.82], P=0.002). Median OS was 21 months [14–29 months] for patients who received at least one targeted therapy compared with 12 months [7–15 months] for patients who were treated only by immunotherapy agents (P=0.003). Conclusion Our results suggest that targeted therapies are associated with improved OS in comparison with cytokines, which is in line with other publications. PMID:24600236

Post-Exercise Heart Rate Recovery Independently Predicts Clinical Outcome in Patients with Acute Decompensated Heart Failure.

PubMed

Youn, Jong-Chan; Lee, Hye Sun; Choi, Suk-Won; Han, Seong-Woo; Ryu, Kyu-Hyung; Shin, Eui-Cheol; Kang, Seok-Min

2016-01-01

Post-exercise heart rate recovery (HRR) is an index of parasympathetic function associated with clinical outcome in patients with chronic heart failure. However, its relationship with the pro-inflammatory response and prognostic value in consecutive patients with acute decompensated heart failure (ADHF) has not been investigated. We measured HRR and pro-inflammatory markers in 107 prospectively and consecutively enrolled, recovered ADHF patients (71 male, 59 ± 15 years, mean ejection fraction 28.9 ± 14.2%) during the pre-discharge period. The primary endpoint included cardiovascular (CV) events defined as CV mortality, cardiac transplantation, or rehospitalization due to HF aggravation. The CV events occurred in 30 (28.0%) patients (5 cardiovascular deaths and 7 cardiac transplantations) during the follow-up period (median 214 days, 11-812 days). When the patients with ADHF were grouped by HRR according to the Contal and O'Quigley's method, low HRR was shown to be associated with significantly higher levels of serum monokine-induced by gamma interferon (MIG) and poor clinical outcome. Multivariate Cox regression analysis revealed that low HRR was an independent predictor of CV events in both enter method and stepwise method. The addition of HRR to a model significantly increased predictability for CV events across the entire follow-up period. Impaired post-exercise HRR is associated with a pro-inflammatory response and independently predicts clinical outcome in patients with ADHF. These findings may explain the relationship between autonomic dysfunction and clinical outcome in terms of the inflammatory response in these patients.

MELD score measured day 10 after orthotopic liver transplantation predicts death and re-transplantation within the first year.

PubMed

Rostved, Andreas A; Lundgren, Jens D; Hillingsø, Jens; Peters, Lars; Mocroft, Amanda; Rasmussen, Allan

2016-11-01

The impact of early allograft dysfunction on the outcome after liver transplantation is yet to be established. We explored the independent predictive value of the Model for End-Stage Liver Disease (MELD) score measured in the post-transplant period on the risk of mortality or re-transplantation. Retrospective cohort study on adults undergoing orthotopic deceased donor liver transplantation from 2004 to 2014. The MELD score was determined prior to transplantation and daily until 21 days after. The risk of mortality or re-transplantation within the first year was assessed according to quartiles of MELD using unadjusted and adjusted stepwise Cox regression analysis. We included 374 consecutive liver transplant recipients of whom 60 patients died or were re-transplanted. The pre-transplant MELD score was comparable between patients with good and poor outcome, but from day 1 the MELD score significantly diversified and was higher in the poor outcome group (MELD score quartile 4 versus quartile 1-3 at day 10: HR 5.1, 95% CI: 2.8-9.0). This association remained after adjustment for non-identical blood type, autoimmune liver disease and hepatocellular carcinoma (adjusted HR 5.3, 95% CI: 2.9-9.5 for MELD scores at day 10). The post-transplant MELD score was not associated with pre-transplant MELD score or the Eurotransplant donor risk index. Early determination of the MELD score as an indicator of early allograft dysfunction after liver transplantation was a strong independent predictor of mortality or re-transplantation and was not influenced by the quality of the donor, or preoperative recipient risk factors.

Donation after cardiac death liver transplantation is associated with increased risk of end-stage renal disease.

PubMed

Ruebner, Rebecca L; Reese, Peter P; Abt, Peter L

2014-12-01

Limited organ supply has led to greater use of liver allografts with higher donor risk indices (DRI) and/or donated after cardiac death (DCD). DCD status is associated with acute kidney injury after liver transplantation; however, less is known about the association between donor quality and end-stage renal disease (ESRD). Using SRTR data, we assembled a cohort of liver transplant recipients from 2/2002 to 12/2010. We fit multivariable Cox regression models for ESRD. Model 1 included total DRI; model 2 included components of DRI, including DCD, as separate variables. Forty thousand four hundred and sixty-three liver transplant recipients were included. Median DRI was 1.40 (IQR 1.14, 1.72); 1822 (5%) received DCD livers. During median follow-up of 3.93 years, ESRD occurred in 2008 (5%) and death in 11 075 (27%) subjects. There was a stepwise increase in ESRD risk with higher DRI (DRI ≥1.14 and <1.40: HR 1.17, P = 0.06; DRI ≥1.40 and <1.72: HR 1.29, P = 0.003; DRI ≥1.72: HR 1.39, P < 0.001, compared with DRI <1.14). Adjusting for DRI components separately, DCD status was most strongly associated with ESRD (HR 1.40, P = 0.008). Higher DRI is associated with ESRD after liver transplantation, driven in part by DCD status. Donor quality is an important predictor of long-term renal outcomes in liver transplant recipients. © 2014 Steunstichting ESOT.

Risk of pacemaker implantation after uneventful successful cavotricuspid isthmus radiofrequency ablation in patients with common atrial flutter.

PubMed

Rodríguez-Mañero, Moisés; González-Melchor, Layla; Ballesteros, Gabriel; Raposeiras-Roubín, Sergio; García-Seara, Javier; López, Xesús Alberte Fernández; Cambeiro, Cristina González; Alcalde, Oscar; García-Bolao, Ignacio; Martínez-Sande, Luis; González-Juanatey, José Ramón

2016-01-01

Little is known about the risk of pacemaker implantation after common atrial flutter ablation in the long-term. We retrospectively reviewed the electrophysiology laboratory database at two Spanish University Hospitals from 1998 to 2012 to identify patients who had undergone successful ablation for cavotricuspid dependent atrial flutter. Cox regression analysis was used to examine the risk of pacemaker implantation. A total of 298 patients were considered eligible for inclusion. The mean age of the enrolled patients was 65.7±11. During 57.7±42.8 months, 30 patients (10.1%) underwent pacemaker implantation. In the stepwise multivariate models only heart rate at the time of the ablation (OR: 0.96; 95% CI: 0.93-0.98; p<0.0001) and intraventricular conduction disturbances in the baseline ECG (OR: 3.87; 95% CI: 1.54-9.70; p=0.004) were independents predictors of the need of pacemaker implantation. A heart rate of ≤65 bpm was identified as the optimal cut-off value to predict the need of pacemaker implantation in the follow-up (sensitivity: 79%, specificity: 74%) by ROC curve analyses. This is the first study of an association between the slow conducting common atrial flutter and subsequent risk of pacemaker implantation. In light of these findings, assessing it prior to ablation can be helpful for the risk stratification of sinus node disease or atrioventricular conduction disease requiring a pacemaker implantation in patients with persistent atrial flutter. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Predictors of non-vertebral fracture in older Chinese males and females: Mr. OS and Ms. OS (Hong Kong).

PubMed

Kwok, Timothy Chi Yui; Su, Yi; Khoo, Chyi Chyi; Leung, Jason; Kwok, Anthony; Orwoll, Eric; Woo, Jean; Leung, Ping Chung

2017-05-01

Clinical risk factors to predict fracture are useful in guiding management of patients with osteoporosis or falls. Clinical predictors may however be population specific because of differences in lifestyle, environment and ethnicity. Four thousand community-dwelling Chinese males and females with average ages of 72.4 and 72.6 years were followed up for incident fractures, with an average of 6.5 and 8.8 years, respectively. Clinical information was collected, and bone mineral density (BMD) measurements were carried out at baseline. Stepwise Cox regression models were used to identify risk factors of nonvertebral fractures, with BMD as covariate. Areas under the receiver-operating characteristic (ROC) curve (AUC) were compared among different risk models. The incidence rates of nonvertebral fractures were 10.3 and 20.5 per 1000 person years in males and females, respectively. In males, age ≥80, history of a fall in the past year, fracture history, chronic obstructive pulmonary disease, impaired visual depth perception and low physical health-related quality of life were significant fracture risk factors, independent of BMD. In females, the significant factors were fracture history, low visual acuity and slow narrow walking speed. The clinical risk factors had a significant influence on fracture risk irrespective of osteoporosis status, even having a better risk discrimination than BMD alone, especially in males. The best risk prediction model consisted both BMD and clinical risk factors. Clinical risk factors have additive value to hip BMD in predicting nonvertebral fractures in older Chinese people and may predict them better than BMD alone in older Chinese males.

Predictors of Global Self-Worth and Academic Performance among Regular Education, Learning Disabled, and Continuation High School Students.

ERIC Educational Resources Information Center

Wiest, Dudley J.; Wong, Eugene H.; Kreil, Dennis A.

1998-01-01

The ability of measures of perceived competence, control, and autonomy support to predict self-worth and academic performance was studied across groups of high school students. Stepwise regression analyses indicate these variables in model predict self-worth and grade point average. In addition, levels of school status and depression predict…

Tailoring Multimedia Instruction to Soldier Needs

DTIC Science & Technology

2014-12-01

Pretest Score (Mean % Items Correct) 39% 34% 48% 51% 51% 45% Posttest (Mean % Items Correct) 47% 44% 66% 60% 63% 56...Stepwise regression was used to examine the relationship between Soldiers’ posttest scores (criterion) and their pretest scores, training time, type of...differences among IMI types had no effect.) Pretest scores predicted posttest scores for both Adjust Indirect Fire (βstandardized = .66, t = 6.36

The Effect of College Selection Factors on Persistence: An Examination of Black and Latino Males in the Community College

ERIC Educational Resources Information Center

Wood, J. Luke; Harris, Frank, III

2015-01-01

The purpose of this study was to understand the relationship (if any) between college selection factors and persistence for Black and Latino males in the community college. Using data derived from the Educational Longitudinal Study, backwards stepwise logistic regression models were developed for both groups. Findings are contextualized in light…

Factors influencing storm-generated suspended-sediment concentrations and loads in four basins of contrasting land use, humid-tropical Puerto Rico

Treesearch

A. C. Gellis; NO-VALUE

2013-01-01

The significant characteristics controlling the variability in storm-generated suspended-sediment loads and concentrations were analyzed for four basins of differing land use (forest, pasture, cropland, and urbanizing) in humid-tropical Puerto Rico. Statistical analysis involved stepwise regression on factor scores. The explanatory variables were attributes of flow,...

Illuminating Tradespace Decisions Using Efficient Experimental Space-Filling Designs for the Engineered Resilient System Architecture

DTIC Science & Technology

2015-06-30

7. Building Statistical Metamodels using Simulation Experimental Designs ............................................... 34 7.1. Statistical Design...system design drivers across several different domain models, our methodology uses statistical metamodeling to approximate the simulations’ behavior. A...output. We build metamodels using a number of statistical methods that include stepwise regression, boosted trees, neural nets, and bootstrap forest

Illuminating Tradespace Decisions Using Efficient Experimental Space-Filling Designs for the Engineered Resilient System Architecture

DTIC Science & Technology

2015-06-01

7. Building Statistical Metamodels using Simulation Experimental Designs ............................................... 34 7.1. Statistical Design...system design drivers across several different domain models, our methodology uses statistical metamodeling to approximate the simulations’ behavior. A...output. We build metamodels using a number of statistical methods that include stepwise regression, boosted trees, neural nets, and bootstrap forest

Analysis of oscillatory motion of a light airplane at high values of lift coefficient

NASA Technical Reports Server (NTRS)

Batterson, J. G.

1983-01-01

A modified stepwise regression is applied to flight data from a light research air-plane operating at high angles at attack. The well-known phenomenon referred to as buckling or porpoising is analyzed and modeled using both power series and spline expansions of the aerodynamic force and moment coefficients associated with the longitudinal equations of motion.

"Hits" (Not "Discussion Posts") Predict Student Success in Online Courses: A Double Cross-Validation Study

ERIC Educational Resources Information Center

Ramos, Cheryl; Yudko, Errol

2008-01-01

The efficacy of individual components of an online course on positive course outcome was examined via stepwise multiple regression analysis. Outcome was measured as the student's total score on all exams given during the course. The predictors were page hits, discussion posts, and discussion reads. The vast majority of the variance of outcome was…

Factors Associated with Level of Living in Washington County, Mississippi. Technical Bulletin No. 1501.

ERIC Educational Resources Information Center

McCoy, John L.

Step-wise multiple regression and typological analysis were used to analyze the extent to which selected factors influence vertical mobility and achieved level of living. A sample of 418 male household heads who were 18 to 45 years old in Washington County, Mississippi were interviewed during 1971. A prescreening using census and local housing…

The Role of Perceived Learning and Communities of Inquiry in Predicting International Students' Course Grades in Computer-Mediated Graduate Courses

ERIC Educational Resources Information Center

Wendt, Jillian L.; Nisbet, Deanna L.

2017-01-01

This study examined the predictive relationship among international students' sense of community, perceived learning, and end-of-course grades in computer-mediated, U.S. graduate-level courses. The community of inquiry (CoI) framework served as the theoretical foundation for the study. Step-wise hierarchical multiple regression showed no…

Assessment of weather-associated causes of red spruce winter injury and consequences to aboveground carbon sequestration

Treesearch

Paul G. Schaberg; Brynne E. Lazarus; Gary J. Hawley; Joshua M. Halman; Catherine H. Borer; Christopher F. Hansen

2011-01-01

Despite considerable study, it remains uncertain what environmental factors contribute to red spruce (Picea rubens Sarg.) foliar winter injury and how much this injury influences tree C stores. We used a long-term record of winter injury in a plantation in New Hampshire and conducted stepwise linear regression analyses with local weather and regional...

Prognostic Value of Pretherapeutic Tumor-to-Blood Standardized Uptake Ratio in Patients with Esophageal Carcinoma.

PubMed

Bütof, Rebecca; Hofheinz, Frank; Zöphel, Klaus; Stadelmann, Tobias; Schmollack, Julia; Jentsch, Christina; Löck, Steffen; Kotzerke, Jörg; Baumann, Michael; van den Hoff, Jörg

2015-08-01

Despite ongoing efforts to develop new treatment options, the prognosis for patients with inoperable esophageal carcinoma is still poor and the reliability of individual therapy outcome prediction based on clinical parameters is not convincing. The aim of this work was to investigate whether PET can provide independent prognostic information in such a patient group and whether the tumor-to-blood standardized uptake ratio (SUR) can improve the prognostic value of tracer uptake values. (18)F-FDG PET/CT was performed in 130 consecutive patients (mean age ± SD, 63 ± 11 y; 113 men, 17 women) with newly diagnosed esophageal cancer before definitive radiochemotherapy. In the PET images, the metabolically active tumor volume (MTV) of the primary tumor was delineated with an adaptive threshold method. The blood standardized uptake value (SUV) was determined by manually delineating the aorta in the low-dose CT. SUR values were computed as the ratio of tumor SUV and blood SUV. Uptake values were scan-time-corrected to 60 min after injection. Univariate Cox regression and Kaplan-Meier analysis with respect to overall survival (OS), distant metastases-free survival (DM), and locoregional tumor control (LRC) was performed. Additionally, a multivariate Cox regression including clinically relevant parameters was performed. In multivariate Cox regression with respect to OS, including T stage, N stage, and smoking state, MTV- and SUR-based parameters were significant prognostic factors for OS with similar effect size. Multivariate analysis with respect to DM revealed smoking state, MTV, and all SUR-based parameters as significant prognostic factors. The highest hazard ratios (HRs) were found for scan-time-corrected maximum SUR (HR = 3.9) and mean SUR (HR = 4.4). None of the PET parameters was associated with LRC. Univariate Cox regression with respect to LRC revealed a significant effect only for N stage greater than 0 (P = 0.048). PET provides independent prognostic information for OS and DM but not for LRC in patients with locally advanced esophageal carcinoma treated with definitive radiochemotherapy in addition to clinical parameters. Among the investigated uptake-based parameters, only SUR was an independent prognostic factor for OS and DM. These results suggest that the prognostic value of tracer uptake can be improved when characterized by SUR instead of SUV. Further investigations are required to confirm these preliminary results. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Assessment of plant species diversity based on hyperspectral indices at a fine scale.

PubMed

Peng, Yu; Fan, Min; Song, Jingyi; Cui, Tiantian; Li, Rui

2018-03-19

Fast and nondestructive approaches of measuring plant species diversity have been a subject of excessive scientific curiosity and disquiet to environmentalists and field ecologists worldwide. In this study, we measured the hyperspectral reflectances and plant species diversity indices at a fine scale (0.8 meter) in central Hunshandak Sandland of Inner Mongolia, China. The first-order derivative value (FD) at each waveband and 37 hyperspectral indices were used to assess plant species diversity. Results demonstrated that the stepwise linear regression of FD can accurately estimate the Simpson (R 2  = 0.83), Pielou (R 2  = 0.87) and Shannon-Wiener index (R 2  = 0.88). Stepwise linear regression of FD (R 2  = 0.81, R 2  = 0.82) and spectral vegetation indices (R 2  = 0.51, R 2  = 0.58) significantly predicted the Margalef and Gleason index. It was proposed that the Simpson, Pielou and Shannon-Wiener indices, which are widely used as plant species diversity indicators, can be precisely estimated through hyperspectral indices at a fine scale. This research promotes the development of methods for assessment of plant diversity using hyperspectral data.

Comparison of bioavailable vanadium in alfalfa rhizosphere soil extracted by an improved BCR procedure and EDTA, HCl, and NaNO₃ single extractions in a pot experiment with V-Cd treatments.

PubMed

Yang, Jie; Teng, Yanguo; Zuo, Rui; Song, Liuting

2015-06-01

The BCR sequential extraction procedure was compared with EDTA, HCl, and NaNO3 single extractions for evaluating vanadium bioavailability in alfalfa rhizosphere soil. The amounts of vanadium extracted by these methods were in the following order: BCR (bioavailable V) > EDTA ≈ HCl > NaNO3. Both correlation analysis and stepwise regression were adopted to illustrate the extractable vanadium between different reagents. The correlation coefficients between extracted vanadium and the vanadium contents in alfalfa roots were R NaNO3 = 0.948, R HCl = 0.902, R EDTA = 0.816, and R bioavailable V = 0.819. The stepwise multiple regression equation of the NaNO3 extraction was the most significant at a 95 % confidence interval. The influence of pH, total organic carbon, and cadmium content of soil to vanadium bioavailability were not definite. In summary, both the BCR sequential extraction and the single extraction methods were valid approaches for predicting vanadium bioavailability in alfalfa rhizosphere soil, especially the single extractions.

Environmental influences on alcohol consumption practices of alcoholic beverage servers.

PubMed

Nusbaumer, Michael R; Reiling, Denise M

2002-11-01

Public drinking establishments have long been associated with heavy drinking among both their patrons and servers. Whether these environments represent locations where heavy drinking is learned (learning hypothesis) or simply places where already-heavy drinkers gather in a supportive environment (selection hypothesis) remains an important question. A sample of licensed alcoholic beverage servers in the state of Indiana, USA, was surveyed to better understand the drinking behaviors of servers within the alcohol service industry. Responses (N = 938) to a mailed questionnaire were analyzed to assess the relative influence of environmental and demographic factors on the drinking behavior of servers. Stepwise regression revealed "drinking on the job" as the most influential environmental factor on heavy drinking behaviors, followed by age and gender as influential demographic factors. Support was found for the selection hypothesis, but not for the learning hypothesis. Policy implications are discussed. factors on the drinking behavior of servers. Stepwise regression revealed "drinking on the job" as the most influential environmental factor on heavy drinking behaviors, followed by age and gender as influential demographic factors. Support was found for the selection hypothesis, but not for the learning hypothesis. Policy implications are discussed.

Handheld Tissue Hardness Meters for Assessing the Mechanical Properties of Skeletal Muscle: A Feasibility Study.

PubMed

Chino, Kentaro; Takahashi, Hideyuki

2016-09-01

The purpose of this study was to examine the feasibility of using handheld tissue hardness meters to assess the mechanical properties of skeletal muscle. This observational study included 33 healthy men (age, 22.4 ± 4.4 years) and 33 healthy women (age, 23.7 ± 4.2 years). Participants were placed in a supine position, and tissue hardness overlying the rectus femoris and the shear modulus of the muscle were measured on the right side of the body at 50% thigh length. In the same position, subcutaneous adipose tissue thickness and muscle thickness were measured using B-mode ultrasonography. To examine the associations of subcutaneous adipose tissue thickness, muscle thickness, and muscle shear modulus with tissue hardness, linear regression using a stepwise bidirectional elimination approach was performed. Stepwise linear regression revealed that subcutaneous adipose tissue thickness (r = -0.38, P = .002) and muscle shear modulus (r = 0.27, P = .03) were significantly associated with tissue hardness. Significant associations among adipose tissue thickness, muscle shear modulus, and tissue hardness show the limitations and feasibility of handheld tissue hardness meters for assessing the mechanical properties of skeletal muscles. Copyright © 2016. Published by Elsevier Inc.

Satisfaction among early and mid-career dentists in a metropolitan dental hospital in China

PubMed Central

Cui, Xiaoxi; Dunning, David G; An, Na

2017-01-01

A growing body of research has examined career satisfaction among dentists using a standardized instrument, dentist satisfaction survey (DSS). This project examined career satisfaction of early to mid-career dentists in China, a population whose career satisfaction, heretofore, has not been studied. This is an especially critical time to examine career satisfaction because of health care reform measures being implemented in China. A culturally sensitive Chinese-language version of the DSS (CDSS) was developed and electronically administered to 367 early and mid-career dentists in a tertiary dental hospital in Beijing, China. One hundred and seventy respondents completed the survey. The average total career score was 123, with a range of 82–157. Data analysis showed some significant differences in total career score and several subscales based on gender, working hours per week, and years in practice. A stepwise regression model revealed that two variables predicted total career score: working hours per week and gender. Stepwise regression also demonstrated that four subscales significantly predicted the overall professional satisfaction subscale score: respect, delivery of care, income and patient relations. Implications of these results are discussed in light of the health care delivery system and dentist career paths in China. PMID:29355243

Satisfaction among early and mid-career dentists in a metropolitan dental hospital in China.

PubMed

Cui, Xiaoxi; Dunning, David G; An, Na

2017-01-01

A growing body of research has examined career satisfaction among dentists using a standardized instrument, dentist satisfaction survey (DSS). This project examined career satisfaction of early to mid-career dentists in China, a population whose career satisfaction, heretofore, has not been studied. This is an especially critical time to examine career satisfaction because of health care reform measures being implemented in China. A culturally sensitive Chinese-language version of the DSS (CDSS) was developed and electronically administered to 367 early and mid-career dentists in a tertiary dental hospital in Beijing, China. One hundred and seventy respondents completed the survey. The average total career score was 123, with a range of 82-157. Data analysis showed some significant differences in total career score and several subscales based on gender, working hours per week, and years in practice. A stepwise regression model revealed that two variables predicted total career score: working hours per week and gender. Stepwise regression also demonstrated that four subscales significantly predicted the overall professional satisfaction subscale score: respect, delivery of care, income and patient relations. Implications of these results are discussed in light of the health care delivery system and dentist career paths in China.

Functional polymorphisms of cyclooxygenase-2 (COX-2) gene and risk for esophageal squmaous cell carcinoma.

PubMed

Upadhyay, Rohit; Jain, Meenu; Kumar, Shaleen; Ghoshal, Uday Chand; Mittal, Balraj

2009-04-26

Cyclooxygenase-2 (COX-2) influences carcinogenesis through regulation of angiogenesis, apoptosis and cytokine expression. We aimed to evaluate association of COX-2 polymorphisms with predisposition to esophageal squamous cell carcinoma (ESCC), its phenotype variability and modulation of environmental risk in northern Indian population. We genotyped 174 patients with ESCC and 216 controls for COX-2 gene polymorphisms (-765G>C; -1195G>A; -1290A>G; 3'UTR 8473T>C) using PCR-RFLP. Data were statistically analyzed using chi-square test and logistic regression model. COX-2 -765C allele carriers were at increased risk for ESCC (OR=1.66; 95% CI=1.08-2.54; P=0.004). However, -1195G>A; -1290A>G; 3'UTR 8473T>C polymorphisms of COX-2 gene were not significantly associated with ESCC. We observed significantly enhanced risk for ESCC due to interaction between COX-2 -1195GAx-765GC+CC genotypes (OR=4.60; 95% CI=1.63-13.01; P=0.004). High risk to ESCC was also observed with respect to COX-2 haplotypes, A(-1290)G(-1195)C(-765)T(8473) and A(-1290)A(-1195)C(-765)T(8473) [OR=3.35; 95% CI=0.83-13.44; P=0.089; OR=4.28; 95% CI=0.43-42.40; P=0.246] however, it was not statistically significant. Stratification of subjects based on gender showed that females were at higher risk for ESCC due to COX-2 -765C carrier genotypes (OR=2.97; 95% CI=1.23-7.18; P=0.016). In association of genotypes with clinical characteristics, -765C carrier genotype conferred risk of ESCC in middle third of esophagus (OR=1.78; 95% CI=1.08-2.93; P=0.023). In case-only analysis, interaction of environmental risk factors and COX-2 genotypes did not further modulate the risk for ESCC. In summary, COX-2 -765G>C polymorphism confers ESCC susceptibility particularly in females and patients with middle third anatomical location of the tumor. Interaction of COX-2 -1195GA and -765C carrier genotypes also modulates ESCC risk.

Impact of livestock Scale on Rice Production in Battambang of Cambodia

NASA Astrophysics Data System (ADS)

Siek, D.; Xu, S. W.; Wyu; Ahmed, A.-G.

2017-10-01

Increasing the awareness of environmental protection especially in the rural regions is important as most the farmers reside in that region. Crop-livestock proudciton has proven in many ways to encourage environmental protection. This study analyzes among other factors the impacto of livestock scale on rice production. Two regressions: Ordinary Least Square (OLS) and stepwise regression was applied to investigate these interrelationship. The result stress of three factors encouraging livestock production namely size of farmland, scale of livestock and income acquired from other jobs. The study further provides recommends to the government based on the findings of the study.

Anthropometric Survey of US Army Personnel (1988): Correlation Coefficients and Regression Equations. Part 5. Stepwise and Standard Multiple Regression Tables

DTIC Science & Technology

1990-05-01

0.759 0.744 0.768 0.753 106 (THUMBBR) THUMB BREADTH -0.652 -0.673 -0.539 -0.663 217 (LIPLGTHH) LIP LENGTH HEADBOARD 0.017 0.019 0.020 51 (FTBRHOR) FOOT...DEPENDENT VARIABLE: (106) THUMB BREADTH (THUBBR) MODEL INDEPENDENT VARIABLE 1 2 3 4 5 INTERCEPT 6.621 5.016 6.267 5.697 4.528 59 (HANDCIRC) HAND...95 (SLLSPEL) SLEEVE LENGTH: SPINE-ELBOW -0.020 -0.019 -C.018 9 (BLFTCIRC) BALL OF FOOT CIRCUMFERENCE -0.032 -0.039 106 (THUMBBR) THUMB BREADTH 0.228

Relationship between COMLEX-USA scores and performance on the American Osteopathic Board of Emergency Medicine Part I certifying examination.

PubMed

Li, Feiming; Gimpel, John R; Arenson, Ethan; Song, Hao; Bates, Bruce P; Ludwin, Fredric

2014-04-01

Few studies have investigated how well scores from the Comprehensive Osteopathic Medical Licensing Examination-USA (COMLEX-USA) series predict resident outcomes, such as performance on board certification examinations. To determine how well COMLEX-USA predicts performance on the American Osteopathic Board of Emergency Medicine (AOBEM) Part I certification examination. The target study population was first-time examinees who took AOBEM Part I in 2011 and 2012 with matched performances on COMLEX-USA Level 1, Level 2-Cognitive Evaluation (CE), and Level 3. Pearson correlations were computed between AOBEM Part I first-attempt scores and COMLEX-USA performances to measure the association between these examinations. Stepwise linear regression analysis was conducted to predict AOBEM Part I scores by the 3 COMLEX-USA scores. An independent t test was conducted to compare mean COMLEX-USA performances between candidates who passed and who failed AOBEM Part I, and a stepwise logistic regression analysis was used to predict the log-odds of passing AOBEM Part I on the basis of COMLEX-USA scores. Scores from AOBEM Part I had the highest correlation with COMLEX-USA Level 3 scores (.57) and slightly lower correlation with COMLEX-USA Level 2-CE scores (.53). The lowest correlation was between AOBEM Part I and COMLEX-USA Level 1 scores (.47). According to the stepwise regression model, COMLEX-USA Level 1 and Level 2-CE scores, which residency programs often use as selection criteria, together explained 30% of variance in AOBEM Part I scores. Adding Level 3 scores explained 37% of variance. The independent t test indicated that the 397 examinees passing AOBEM Part I performed significantly better than the 54 examinees failing AOBEM Part I in all 3 COMLEX-USA levels (P<.001 for all 3 levels). The logistic regression model showed that COMLEX-USA Level 1 and Level 3 scores predicted the log-odds of passing AOBEM Part I (P=.03 and P<.001, respectively). The present study empirically supported the predictive and discriminant validities of the COMLEX-USA series in relation to the AOBEM Part I certification examination. Although residency programs may use COMLEX-USA Level 1 and Level 2-CE scores as partial criteria in selecting residents, Level 3 scores, though typically not available at the time of application, are actually the most statistically related to performances on AOBEM Part I.

Network regularised Cox regression and multiplex network models to predict disease comorbidities and survival of cancer.

PubMed

Xu, Haoming; Moni, Mohammad Ali; Liò, Pietro

2015-12-01

In cancer genomics, gene expression levels provide important molecular signatures for all types of cancer, and this could be very useful for predicting the survival of cancer patients. However, the main challenge of gene expression data analysis is high dimensionality, and microarray is characterised by few number of samples with large number of genes. To overcome this problem, a variety of penalised Cox proportional hazard models have been proposed. We introduce a novel network regularised Cox proportional hazard model and a novel multiplex network model to measure the disease comorbidities and to predict survival of the cancer patient. Our methods are applied to analyse seven microarray cancer gene expression datasets: breast cancer, ovarian cancer, lung cancer, liver cancer, renal cancer and osteosarcoma. Firstly, we applied a principal component analysis to reduce the dimensionality of original gene expression data. Secondly, we applied a network regularised Cox regression model on the reduced gene expression datasets. By using normalised mutual information method and multiplex network model, we predict the comorbidities for the liver cancer based on the integration of diverse set of omics and clinical data, and we find the diseasome associations (disease-gene association) among different cancers based on the identified common significant genes. Finally, we evaluated the precision of the approach with respect to the accuracy of survival prediction using ROC curves. We report that colon cancer, liver cancer and renal cancer share the CXCL5 gene, and breast cancer, ovarian cancer and renal cancer share the CCND2 gene. Our methods are useful to predict survival of the patient and disease comorbidities more accurately and helpful for improvement of the care of patients with comorbidity. Software in Matlab and R is available on our GitHub page: https://github.com/ssnhcom/NetworkRegularisedCox.git. Copyright © 2015. Published by Elsevier Ltd.

The influence of sarcopenia on survival and surgical complications in ovarian cancer patients undergoing primary debulking surgery.

PubMed

Rutten, I J G; Ubachs, J; Kruitwagen, R F P M; van Dijk, D P J; Beets-Tan, R G H; Massuger, L F A G; Olde Damink, S W M; Van Gorp, T

2017-04-01

Sarcopenia, severe skeletal muscle loss, has been identified as a prognostic factor in various malignancies. This study aims to investigate whether sarcopenia is associated with overall survival (OS) and surgical complications in patients with advanced ovarian cancer undergoing primary debulking surgery (PDS). Ovarian cancer patients (n = 216) treated with PDS were enrolled retrospectively. Total skeletal muscle surface area was measured on axial computed tomography at the level of the third lumbar vertebra. Optimum stratification was used to find the optimal skeletal muscle index cut-off to define sarcopenia (≤38.73 cm 2 /m 2 ). Cox-regression and Kaplan-Meier analysis were used to analyse the relationship between sarcopenia and OS. The effect of sarcopenia on the development of major surgical complications was studied with logistic regression. Kaplan-Meier analysis showed a significant survival disadvantage for patients with sarcopenia compared to patients without sarcopenia (p = 0.010). Sarcopenia univariably predicted OS (HR 1.536 (95% CI 1.105-2.134), p = 0.011) but was not significant in multivariable Cox-regression analysis (HR 1.362 (95% CI 0.968-1.916), p = 0.076). Significant predictors for OS in multivariable Cox-regression analysis were complete PDS, treatment in a specialised centre and the development of major complications. Sarcopenia was not predictive of major complications. Sarcopenia was not predictive of OS or major complications in ovarian cancer patients undergoing primary debulking surgery. However a strong trend towards a survival disadvantage for patients with sarcopenia was seen. Future prospective studies should focus on interventions to prevent or reverse sarcopenia and possibly increase ovarian cancer survival. Complete cytoreduction remains the strongest predictor of ovarian cancer survival. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Improving prediction of metal uptake by Chinese cabbage (Brassica pekinensis L.) based on a soil-plant stepwise analysis.

PubMed

Zhang, Sha; Song, Jing; Gao, Hui; Zhang, Qiang; Lv, Ming-Chao; Wang, Shuang; Liu, Gan; Pan, Yun-Yu; Christie, Peter; Sun, Wenjie

2016-11-01

It is crucial to develop predictive soil-plant transfer (SPT) models to derive the threshold values of toxic metals in contaminated arable soils. The present study was designed to examine the heavy metal uptake pattern and to improve the prediction of metal uptake by Chinese cabbage grown in agricultural soils with multiple contamination by Cd, Cu, Ni, Pb, and Zn. Pot experiments were performed with 25 historically contaminated soils to determine metal accumulation in different parts of Chinese cabbage. Different soil bioavailable metal fractions were determined using different extractants (0.43M HNO3, 0.01M CaCl2, 0.005M DTPA, and 0.01M LWMOAs), soil moisture samplers, and diffusive gradients in thin films (DGT), and the fractions were compared with shoot metal uptake using both direct and stepwise multiple regression analysis. The stepwise approach significantly improved the prediction of metal uptake by cabbage over the direct approach. Strongly pH dependent or nonlinear relationships were found for the adsorption of root surfaces and in root-shoot uptake processes. Metals were linearly translocated from the root surface to the root. Therefore, the nonlinearity of uptake pattern is an important explanation for the inadequacy of the direct approach in some cases. The stepwise approach offers an alternative and robust method to study the pattern of metal uptake by Chinese cabbage (Brassica pekinensis L.). Copyright © 2016. Published by Elsevier B.V.

[Contents of vitreous humor of dead body with different postmortem intervals].

PubMed

Tao, Tao; Xu, Jing; Luo, Tong-Xing; Liao, Zhi-Gang; Pan, Hong-Fu

2006-11-01

To establish regression correlations between postmortem interval (PMI) and contents of human vitreous humor of dead bodies for forensic purposes. The human vitreous humor were taken from 126 dead bodies between 0.5 to 216 hours after death, and 11 chemical elements were detected by the OLYMPUS AU400 auto-biochemistry instrument. (1) The glucose, natrium and chlorine in human vitreous humor decreased, while the urea, creatinine, uric acid, potassium, calcium, magnesium, phosphorus, and micro-protein increased after death. The change of glucose, potassium and phosphorus were well correlated with the PMI (r = 0.824, 0.967, 0.880). But the uric acid and micro-protein did not have a good correlation with the PMI(r = 0.350, 0.153). (2) The stepwise regression analysis established the following equations for the PMI (Y): Y = -35. 15+6.05X, R2 = 0.957 (X = potassium); Y = -27.83+ 5.49X(1) - 1.35X(2), R2 = 0.960 (X(1) = potassium, X(2) = glucose); Y = -6.37+3.93X(1) -2.29X(2) + 5.36X(3), R2 = 0.966 (X(1) = potassium, X(2) = glucose, X(3) = phosphorus). (1) Eleven chemical components in human vitreous humor change after death, among which postassium has the best linear correlation with the PMI within 72 hours after death. (2) The accuracy of the estimation of PMI could be improved by establishing a multi-variable equation through stepwise regression.

Predicting the demand of physician workforce: an international model based on "crowd behaviors".

PubMed

Tsai, Tsuen-Chiuan; Eliasziw, Misha; Chen, Der-Fang

2012-03-26

Appropriateness of physician workforce greatly influences the quality of healthcare. When facing the crisis of physician shortages, the correction of manpower always takes an extended time period, and both the public and health personnel suffer. To calculate an appropriate number of Physician Density (PD) for a specific country, this study was designed to create a PD prediction model, based on health-related data from many countries. Twelve factors that could possibly impact physicians' demand were chosen, and data of these factors from 130 countries (by reviewing 195) were extracted. Multiple stepwise-linear regression was used to derive the PD prediction model, and a split-sample cross-validation procedure was performed to evaluate the generalizability of the results. Using data from 130 countries, with the consideration of the correlation between variables, and preventing multi-collinearity, seven out of the 12 predictor variables were selected for entry into the stepwise regression procedure. The final model was: PD = (5.014 - 0.128 × proportion under age 15 years + 0.034 × life expectancy)2, with R2 of 80.4%. Using the prediction equation, 70 countries had PDs with "negative discrepancy", while 58 had PDs with "positive discrepancy". This study provided a regression-based PD model to calculate a "norm" number of PD for a specific country. A large PD discrepancy in a country indicates the needs to examine physician's workloads and their well-being, the effectiveness/efficiency of medical care, the promotion of population health and the team resource management.

Development of a Bayesian model to estimate health care outcomes in the severely wounded

PubMed Central

Stojadinovic, Alexander; Eberhardt, John; Brown, Trevor S; Hawksworth, Jason S; Gage, Frederick; Tadaki, Douglas K; Forsberg, Jonathan A; Davis, Thomas A; Potter, Benjamin K; Dunne, James R; Elster, E A

2010-01-01

Background: Graphical probabilistic models have the ability to provide insights as to how clinical factors are conditionally related. These models can be used to help us understand factors influencing health care outcomes and resource utilization, and to estimate morbidity and clinical outcomes in trauma patient populations. Study design: Thirty-two combat casualties with severe extremity injuries enrolled in a prospective observational study were analyzed using step-wise machine-learned Bayesian belief network (BBN) and step-wise logistic regression (LR). Models were evaluated using 10-fold cross-validation to calculate area-under-the-curve (AUC) from receiver operating characteristics (ROC) curves. Results: Our BBN showed important associations between various factors in our data set that could not be developed using standard regression methods. Cross-validated ROC curve analysis showed that our BBN model was a robust representation of our data domain and that LR models trained on these findings were also robust: hospital-acquired infection (AUC: LR, 0.81; BBN, 0.79), intensive care unit length of stay (AUC: LR, 0.97; BBN, 0.81), and wound healing (AUC: LR, 0.91; BBN, 0.72) showed strong AUC. Conclusions: A BBN model can effectively represent clinical outcomes and biomarkers in patients hospitalized after severe wounding, and is confirmed by 10-fold cross-validation and further confirmed through logistic regression modeling. The method warrants further development and independent validation in other, more diverse patient populations. PMID:21197361

The role of chemoprevention by selective cyclooxygenase-2 inhibitors in colorectal cancer patients - a population-based study

PubMed Central

2012-01-01

Background There are limited population-based studies focusing on the chemopreventive effects of selective cyclooxygenase-2 (COX-2) inhibitors against colorectal cancer. The purpose of this study is to assess the trends and dose–response effects of various medication possession ratios (MPR) of selective COX-2 inhibitor used for chemoprevention of colorectal cancer. Methods A population-based case–control study was conducted using the Taiwan Health Insurance Research Database (NHIRD). The study comprised 21,460 colorectal cancer patients and 79,331 controls. The conditional logistic regression was applied to estimate the odds ratios (ORs) for COX-2 inhibitors used for several durations (5 years, 3 years, 1 year, 6 months and 3 months) prior to the index date. Results In patients receiving selective COX-2 inhibitors, the OR was 0.51 (95% CI=0.29~0.90, p=0.021) for an estimated 5-year period in developing colorectal cancer. ORs showing significant protection effects were found in 10% of MPRs for 5-year, 3-year, and 1-year usage. Risk reduction against colorectal cancer by selective COX-2 inhibitors was observed as early as 6 months after usage. Conclusion Our results indicate that selective COX-2 inhibitors may reduce the development of colorectal cancer by at least 10% based on the MPRs evaluated. Given the limited number of clinical reports from general populations, our results add to the knowledge of chemopreventive effects of selective COX-2 inhibitors against cancer in individuals at no increased risk of colorectal cancer. PMID:23217168

Estimation of standard liver volume in Chinese adult living donors.

PubMed

Fu-Gui, L; Lu-Nan, Y; Bo, L; Yong, Z; Tian-Fu, W; Ming-Qing, X; Wen-Tao, W; Zhe-Yu, C

2009-12-01

To determine a formula predicting the standard liver volume based on body surface area (BSA) or body weight in Chinese adults. A total of 115 consecutive right-lobe living donors not including the middle hepatic vein underwent right hemi-hepatectomy. No organs were used from prisoners, and no subjects were prisoners. Donor anthropometric data including age, gender, body weight, and body height were recorded prospectively. The weights and volumes of the right lobe liver grafts were measured at the back table. Liver weights and volumes were calculated from the right lobe graft weight and volume obtained at the back table, divided by the proportion of the right lobe on computed tomography. By simple linear regression analysis and stepwise multiple linear regression analysis, we correlated calculated liver volume and body height, body weight, or body surface area. The subjects had a mean age of 35.97 +/- 9.6 years, and a female-to-male ratio of 60:55. The mean volume of the right lobe was 727.47 +/- 136.17 mL, occupying 55.59% +/- 6.70% of the whole liver by computed tomography. The volume of the right lobe was 581.73 +/- 96.137 mL, and the estimated liver volume was 1053.08 +/- 167.56 mL. Females of the same body weight showed a slightly lower liver weight. By simple linear regression analysis and stepwise multiple linear regression analysis, a formula was derived based on body weight. All formulae except the Hong Kong formula overestimated liver volume compared to this formula. The formula of standard liver volume, SLV (mL) = 11.508 x body weight (kg) + 334.024, may be applied to estimate liver volumes in Chinese adults.

Generating linear regression model to predict motor functions by use of laser range finder during TUG.

PubMed

Adachi, Daiki; Nishiguchi, Shu; Fukutani, Naoto; Hotta, Takayuki; Tashiro, Yuto; Morino, Saori; Shirooka, Hidehiko; Nozaki, Yuma; Hirata, Hinako; Yamaguchi, Moe; Yorozu, Ayanori; Takahashi, Masaki; Aoyama, Tomoki

2017-05-01

The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals. This study included 99 community-dwelling women aged 72.9 ± 6.3 years. Step length, step width, single support time, variability of the aforementioned parameters, gait velocity, cadence, reaction time from starting signal to first step, and minimum distance between the foot and a marker placed to 3 in front of the chair were measured using our analysis system. The 10-m walk test, five times sit-to-stand (FTSTS) test, and one-leg standing (OLS) test were used to assess motor function. Stepwise multivariate linear regression analysis was used to determine which TUG test parameters were associated with each motor function test. Finally, we calculated a predictive model for each motor function test using each regression coefficient. In stepwise linear regression analysis, step length and cadence were significantly associated with the 10-m walk test, FTSTS and OLS test. Reaction time was associated with the FTSTS test, and step width was associated with the OLS test. Each predictive model showed a strong correlation with the 10-m walk test and OLS test (P < 0.01), which was not significant higher correlation than TUG test time. We showed which TUG test parameters were associated with each motor function test. Moreover, the TUG test time regarded as the lower extremity function and mobility has strong predictive ability in each motor function test. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Evaluating Disease Severity in Chronic Pain Patients with and without Fibromyalgia: A Comparison of the Symptom Impact Questionnaire and the Polysymptomatic Distress Scale.

PubMed

Friend, Ronald; Bennett, Robert M

2015-12-01

To compare the relative effectiveness of the Polysymptomatic Distress Scale (PSD) with the Symptom Impact Questionnaire (SIQR), the disease-neutral revision of the updated Fibromyalgia Impact Questionnaire (FIQR), in their ability to assess disease activity in patients with rheumatic disorders both with and without fibromyalgia (FM). The study included 321 patients from 8 clinical practices with some 16 different chronic pain disorders. Disease severity was assessed by the Medical Outcomes Study Short Form-36 (SF-36). Univariate analyses were used to assess the magnitude of PSD and SIQR correlations with SF-36 subscales. Hierarchical stepwise regression was used to evaluate the unique contribution of the PSD and SIQR to the SF-36. Random forest regression probed the relative importance of the SIQR and PSD components as predictors of SF-36. The correlations with the SF-36 subscales were significantly higher for the SIQR (0.48 to 0.78) than the PSD (0.29 to 0.56; p < 0.001). Stepwise regression revealed that the SIQR was contributing additional unique variance on SF-36 subscales, which was not the case for the PSD. Random forest regression showed SIQR Function, Symptoms, and Global Impact subscales were more important predictors of SF-36 than the PSD. The single SIQR pain item contributed 55% of SF-36 pain variance compared to 23% with the 19-point WPI (the Widespread Pain Index component of PSD). The SIQR, the disease-neutral revision of the updated FIQ, has several important advantages over the PSD in the evaluation of disease severity in chronic pain disorders.

Adaptive surrogate modeling by ANOVA and sparse polynomial dimensional decomposition for global sensitivity analysis in fluid simulation

NASA Astrophysics Data System (ADS)

Tang, Kunkun; Congedo, Pietro M.; Abgrall, Rémi

2016-06-01

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable for real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.

Concurrent Validity of Hill's Educational Cognitive Style Model as a Prototype for Successful Academic Programs Among Lower-Class Students.

ERIC Educational Resources Information Center

London, David T.

Data from the stepwise multiple regression of four educational cognitive style predictor sets on each of six academic competence criteria were used to define the concurrent validity of Hill's educational cognitive style model. The purpose was to determine how appropriate it may be to use this model as a prototype for successful academic programs…

Do Basic Skills Predict Youth Unemployment (16- to 24-Year-Olds) Also when Controlled for Accomplished Upper-Secondary School? A Cross-Country Comparison

ERIC Educational Resources Information Center

Lundetrae, Kjersti; Gabrielsen, Egil; Mykletun, Reidar

2010-01-01

Basic skills and educational level are closely related, and both might affect employment. Data from the Adult Literacy and Life Skills Survey were used to examine whether basic skills in terms of literacy and numeracy predicted youth unemployment (16-24 years) while controlling for educational level. Stepwise logistic regression showed that in…

Objective Quantification of Pre-and Postphonosurgery Vocal Fold Vibratory Characteristics Using High-Speed Videoendoscopy and a Harmonic Waveform Model

ERIC Educational Resources Information Center

Ikuma, Takeshi; Kunduk, Melda; McWhorter, Andrew J.

2014-01-01

Purpose: The model-based quantitative analysis of high-speed videoendoscopy (HSV) data at a low frame rate of 2,000 frames per second was assessed for its clinical adequacy. Stepwise regression was employed to evaluate the HSV parameters using harmonic models and their relationships to the Voice Handicap Index (VHI). Also, the model-based HSV…

A statistical model of expansion in a colony of black-tailed prairie dogs

Treesearch

R. P. Cincotta; Daniel W. Uresk; R. M. Hansen

1988-01-01

To predict prairie dog establishment in areas adjacent to a colony we sample: (1) VISIBILITY through the vegetation using a target, (2) POPULATION DENSITY at the cology edge, (3) DISTANCE from the edge to the potential site of settlement, and (4) % FORB COVER. Step-wise regression analysis indicated that establishment of prairie dogs in adjacent prairie was most likely...

Factors that influence the efficacy of acarbose and metformin as initial therapy in Chinese patients with newly diagnosed type 2 diabetes: a subanalysis of the MARCH trial.

PubMed

Zhang, Jinping; Wang, Na; Xing, Xiaoyan; Yang, Zhaojun; Wang, Xin; Yang, Wenying

2016-01-01

To conduct a subanalysis of the randomized MARCH (Metformin and AcaRbose in Chinese as the initial Hypoglycemic treatment) trial to investigate whether specific characteristics are associated with the efficacy of either acarbose or metformin as initial therapy. A total of 657 type 2 diabetes patients who were randomly assigned to 48 weeks of therapy with either acarbose or metformin in the MARCH trial were divided into two groups based upon their hemoglobin A1c (HbA1c) levels at the end of follow-up: HbA1c <7% (<53 mmol/mol) and ≥7% (≥53 mmol/mol). Univariate, multivariate, and stepwise linear regression analyses were applied to identify the factors associated with treatment efficacy. Because this was a subanalysis, no measurement was performed. Univariate analysis showed that the efficacy of acarbose and metformin was influenced by HbA1c, fasting blood glucose (FBG), and 2 hour postprandial venous blood glucose (2hPPG) levels, as well as by changes in body mass index (BMI) (p ≤ 0.006). Multivariate analysis and stepwise linear regression analyses indicated that lower baseline 2hPPG values and greater changes in BMI were factors that positively influenced efficacy in both treatment groups (p ≤ 0.05). Stepwise regression model analysis also revealed that a lower baseline homeostasis model assessment-estimated insulin resistance (HOMA-IR) and higher serum insulin area under the curve (AUC) were factors positively influencing HbA1c normalization in all patients (p ≤ 0.032). Newly diagnosed type 2 diabetes patients with lower baseline 2hPPG and HOMA-IR values are more likely to achieve glucose control with acarbose or metformin treatment. Furthermore, the change in BMI after acarbose or metformin treatment is also a factor influencing HbA1c normalization. A prospective study with a larger sample size is necessary to confirm our results as well as measure β cell function and examine the influence of the patients' dietary habits.

Applications of modern statistical methods to analysis of data in physical science

NASA Astrophysics Data System (ADS)

Wicker, James Eric

Modern methods of statistical and computational analysis offer solutions to dilemmas confronting researchers in physical science. Although the ideas behind modern statistical and computational analysis methods were originally introduced in the 1970's, most scientists still rely on methods written during the early era of computing. These researchers, who analyze increasingly voluminous and multivariate data sets, need modern analysis methods to extract the best results from their studies. The first section of this work showcases applications of modern linear regression. Since the 1960's, many researchers in spectroscopy have used classical stepwise regression techniques to derive molecular constants. However, problems with thresholds of entry and exit for model variables plagues this analysis method. Other criticisms of this kind of stepwise procedure include its inefficient searching method, the order in which variables enter or leave the model and problems with overfitting data. We implement an information scoring technique that overcomes the assumptions inherent in the stepwise regression process to calculate molecular model parameters. We believe that this kind of information based model evaluation can be applied to more general analysis situations in physical science. The second section proposes new methods of multivariate cluster analysis. The K-means algorithm and the EM algorithm, introduced in the 1960's and 1970's respectively, formed the basis of multivariate cluster analysis methodology for many years. However, several shortcomings of these methods include strong dependence on initial seed values and inaccurate results when the data seriously depart from hypersphericity. We propose new cluster analysis methods based on genetic algorithms that overcomes the strong dependence on initial seed values. In addition, we propose a generalization of the Genetic K-means algorithm which can accurately identify clusters with complex hyperellipsoidal covariance structures. We then use this new algorithm in a genetic algorithm based Expectation-Maximization process that can accurately calculate parameters describing complex clusters in a mixture model routine. Using the accuracy of this GEM algorithm, we assign information scores to cluster calculations in order to best identify the number of mixture components in a multivariate data set. We will showcase how these algorithms can be used to process multivariate data from astronomical observations.

Low-dose aspirin, non-steroidal anti-inflammatory drugs, selective COX-2 inhibitors and breast cancer recurrence

PubMed Central

Cronin-Fenton, Deirdre P; Heide-Jørgensen, Uffe; Ahern, Thomas P; Lash, Timothy L; Christiansen, Peer; Ejlertsen, Bent; Sørensen, Henrik T

2017-01-01

Background Aspirin, non-steroidal anti-inflammatory drugs (NSAIDs), and selective COX-2 inhibitors may improve outcomes in breast cancer patients. We investigated the association of aspirin, NSAIDs, and use of selective COX-2 inhibitors with breast cancer recurrence. Methods We identified incident stage I–III Danish breast cancer patients in the Danish Breast Cancer Cooperative Group registry, who were diagnosed during 1996–2008. Prescriptions for aspirin (>99% low-dose aspirin), NSAIDs, and selective COX-2 inhibitors were ascertained from the National Prescription Registry (NPR). Follow-up began on the date of breast cancer primary surgery and continued until the first of recurrence, death, emigration, or 01/01/2013. We used Cox regression models to compute hazard ratios (HR) and corresponding 95% confidence intervals (95%CI) associating prescriptions with recurrence, adjusting for confounders. Results We identified 34,188 breast cancer patients with 233,130 person-years of follow-up. Median follow-up was 7.1 years; 5,325 patients developed recurrent disease. Use of aspirin, NSAIDs, or selective COX-2 inhibitors was not associated with the rate of recurrence (HRadjusted aspirin=1.0, 95% CI=0.90, 1.1; NSAIDs=0.99, 95% CI=0.92, 1.1; selective COX-2 inhibitors=1.1, 95% CI=0.98, 1.2), relative to non-use. Pre-diagnostic use of the exposure drugs was associated with reduced recurrence rates (HRaspirin=0.92, 95%CI=0.82, 1.0; HRNSAIDs=0.86, 95%CI=0.81, 0.91; HRsCOX-2inhibitors=0.88, 95%CI=0.83, 0.95). Conclusions This prospective cohort study suggests that post-diagnostic prescriptions for aspirin, NSAIDs, and selective COX-2 inhibitors have little or no association with the rate of breast cancer recurrence. Pre-diagnostic use of the drugs was, however, associated with a reduced rate of breast cancer recurrence. PMID:27007644

Anti-inflammatory use may not negatively impact oncologic outcomes following intravesical BCG for high-grade non-muscle-invasive bladder cancer.

PubMed

Singla, Nirmish; Haddad, Ahmed Q; Passoni, Niccolo M; Meissner, Matthew; Lotan, Yair

2017-01-01

To evaluate whether anti-inflammatory agents affect outcomes in patients receiving intravesical BCG therapy for high-grade (HG) non-muscle-invasive bladder cancer (NMIBC). We reviewed the records of 203 patients in a prospective database of HG NMIBC from 2006 to 2012 at a single institution. Patients who had muscle-invasive disease (n = 32), low-grade pathology (n = 4), underwent early cystectomy within 3 months (n = 25), had <3 months of follow-up (n = 11), or did not receive an induction course of intravesical BCG (n = 32) were excluded. Clinicopathologic data were tabulated including demographics, comorbidities, pathologic stage and grades, intravesical therapy, and concomitant use of aspirin, NSAIDs, COX inhibitors, and statins. Multivariate Cox regression analysis explored predictive factors for recurrence, progression (stage progression or progression to cystectomy), cancer-specific survival (CSS), and overall survival (OS). Ninety-nine patients with HG NMIBC who received at least one induction course of intravesical BCG were identified, with median follow-up of 31.4 months. There were 20 (20.2 %) deaths, including 6 (6.1 %) patients with bladder cancer-related mortality. 13 % patients experienced tumor progression and 27 % underwent cystectomy following failure of intravesical therapy. Anti-inflammatory use included statins (65 %), aspirin (63 %), or non-aspirin NSAIDs/COX inhibitors (26 %). Anti-inflammatory use was not significantly predictive of recurrence, progression, or mortality outcomes on Cox regression. CIS stage was associated with higher progression, while age, BMI, and Charlson score were independent predictors of overall mortality. Despite speculation of inhibitory effects on BCG immunomodulation there was no evidence that anti-inflammatory agents impacted oncologic outcomes in patients receiving BCG for HG NMIBC.

Prognostic Impact of Neutrophil/Lymphocyte Ratio, Platelet Count, CRP, and Albumin Levels in Metastatic Colorectal Cancer Patients Treated with FOLFIRI-Bevacizumab.

PubMed

Artaç, Mehmet; Uysal, Mükremin; Karaağaç, Mustafa; Korkmaz, Levent; Er, Zehra; Güler, Tunç; Börüban, Melih Cem; Bozcuk, Hakan

2017-06-01

Metastatic colorectal cancer (mCRC) is a lethal disease and fluorouracil-leucovorin-irinotecan (FOLFIRI) plus bevacizumab (bev) is a standard approach. Hence, there is a strong need for identifying new prognostic factors to show the efficacy of FOLFIRI-bev. This is a retrospective study including patients (n = 90) with mCRC from two centers in Turkey. Neutrophil/lymphocyte (N/L) ratio, platelet count, albumin, and C-reactive protein (CRP) were recorded before FOLFIRI-bev therapy. The efficacy of these factors on progression-free survival (PFS) was analyzed with Kaplan Meier and Cox regression analysis. And the cutoff value of N/L ratio was analyzed with ROC analysis. The median age was 56 years (range 21-80). Forty-seven percent of patients with N/L ratio >2.5 showed progressive disease versus 43 % in patients with N/L ratio <2.5 (p = 0.025). The median PFS was 8.1 months for the patients with N/L ratio >2.5 versus 13.5 months for the patients with N/L ratio <2.5 (p = 0.025). At univariate Cox regression analysis, high baseline neutrophil count, LDH, N/L ratio, and CRP were all significantly associated with poor prognosis. At multivariate Cox regression analysis, CRP was confirmed to be a better independent prognostic factor. CRP variable was divided into above the upper limit of normal (ULN) and normal value. The median PFSs of the patients with normal and above ULN were 11.3 versus 5.8 months, respectively (p = 0.022). CRP and N/L ratio are potential predictors for advanced mCRC treated with FOLFIRI-bev.

Long-term allopurinol use decreases the risk of prostate cancer in patients with gout: a population-based study.

PubMed

Shih, H-J; Kao, M-C; Tsai, P-S; Fan, Y-C; Huang, C-J

2017-09-01

Clinical observations indicated an increased risk of developing prostate cancer in gout patients. Chronic inflammation is postulated to be one crucial mechanism for prostate carcinogenesis. Allopurinol, a widely used antigout agent, possesses potent anti-inflammation capacity. We elucidated whether allopurinol decreases the risk of prostate cancer in gout patients. We analyzed data retrieved from Taiwan National Health Insurance Database between January 2000 and December 2012. Patients diagnosed with gout during the study period with no history of prostate cancer and who had never used allopurinol were selected. Four allopurinol use cohorts (that is, allopurinol use (>365 days), allopurinol use (181-365 days), allopurinol use (91-180 days) and allopurinol use (31-90 days)) and one cohort without using allopurinol (that is, allopurinol use (No)) were included. The study end point was the diagnosis of new-onset prostate cancer. Multivariable Cox proportional hazards regression and propensity score-adjusted Cox regression models were used to estimate the association between the risk of prostate cancer and allopurinol treatment in gout patients after adjusting for potential confounders. A total of 25 770 gout patients (aged between 40 and 100 years) were included. Multivariable Cox regression analyses revealed that the risk of developing prostate cancer in the allopurinol use (>365 days) cohort was significantly lower than the allopurinol use (No) cohort (adjusted hazard ratio (HR)=0.64, 95% confidence interval (CI)=0.45-0.9, P=0.011). After propensity score adjustment, the trend remained the same (adjusted HR=0.66, 95% CI=0.46-0.93, P=0.019). Long-term (more than 1 year) allopurinol use may associate with a decreased risk of prostate cancer in gout patients.

Birth by Caesarean Section and the Risk of Adult Psychosis: A Population-Based Cohort Study

PubMed Central

O’Neill, Sinéad M.; Curran, Eileen A.; Dalman, Christina; Kenny, Louise C.; Kearney, Patricia M.; Clarke, Gerard; Cryan, John F.; Dinan, Timothy G.; Khashan, Ali S.

2016-01-01

Despite the biological plausibility of an association between obstetric mode of delivery and psychosis in later life, studies to date have been inconclusive. We assessed the association between mode of delivery and later onset of psychosis in the offspring. A population-based cohort including data from the Swedish National Registers was used. All singleton live births between 1982 and 1995 were identified (n = 1 345 210) and followed-up to diagnosis at age 16 or later. Mode of delivery was categorized as: unassisted vaginal delivery (VD), assisted VD, elective Caesarean section (CS) (before onset of labor), and emergency CS (after onset of labor). Outcomes included any psychosis; nonaffective psychoses (including schizophrenia only) and affective psychoses (including bipolar disorder only and depression with psychosis only). Cox regression analysis was used reporting partially and fully adjusted hazard ratios (HR) with 95% confidence intervals (CI). Sibling-matched Cox regression was performed to adjust for familial confounding factors. In the fully adjusted analyses, elective CS was significantly associated with any psychosis (HR 1.13, 95% CI 1.03, 1.24). Similar findings were found for nonaffective psychoses (HR 1.13, 95% CI 0.99, 1.29) and affective psychoses (HR 1.17, 95% CI 1.05, 1.31) (χ2 for heterogeneity P = .69). In the sibling-matched Cox regression, this association disappeared (HR 1.03, 95% CI 0.78, 1.37). No association was found between assisted VD or emergency CS and psychosis. This study found that elective CS is associated with an increase in offspring psychosis. However, the association did not persist in the sibling-matched analysis, implying the association is likely due to familial confounding by unmeasured factors such as genetics or environment. PMID:26615187

A comparison between standard methods and structural nested modelling when bias from a healthy worker survivor effect is suspected: an iron-ore mining cohort study.

PubMed

Björ, Ove; Damber, Lena; Jonsson, Håkan; Nilsson, Tohr

2015-07-01

Iron-ore miners are exposed to extremely dusty and physically arduous work environments. The demanding activities of mining select healthier workers with longer work histories (ie, the Healthy Worker Survivor Effect (HWSE)), and could have a reversing effect on the exposure-response association. The objective of this study was to evaluate an iron-ore mining cohort to determine whether the effect of respirable dust was confounded by the presence of an HWSE. When an HWSE exists, standard modelling methods, such as Cox regression analysis, produce biased results. We compared results from g-estimation of accelerated failure-time modelling adjusted for HWSE with corresponding unadjusted Cox regression modelling results. For all-cause mortality when adjusting for the HWSE, cumulative exposure from respirable dust was associated with a 6% decrease of life expectancy if exposed ≥15 years, compared with never being exposed. Respirable dust continued to be associated with mortality after censoring outcomes known to be associated with dust when adjusting for the HWSE. In contrast, results based on Cox regression analysis did not support that an association was present. The adjustment for the HWSE made a difference when estimating the risk of mortality from respirable dust. The results of this study, therefore, support the recommendation that standard methods of analysis should be complemented with structural modelling analysis techniques, such as g-estimation of accelerated failure-time modelling, to adjust for the HWSE. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Sodium Valproate, a Histone Deacetylase Inhibitor, Is Associated With Reduced Stroke Risk After Previous Ischemic Stroke or Transient Ischemic Attack.

PubMed

Brookes, Rebecca L; Crichton, Siobhan; Wolfe, Charles D A; Yi, Qilong; Li, Linxin; Hankey, Graeme J; Rothwell, Peter M; Markus, Hugh S

2018-01-01

A variant in the histone deacetylase 9 ( HDAC9 ) gene is associated with large artery stroke. Therefore, inhibiting HDAC9 might offer a novel secondary preventative treatment for ischemic stroke. The antiepileptic drug sodium valproate (SVA) is a nonspecific inhibitor of HDAC9. We tested whether SVA therapy given after ischemic stroke was associated with reduced recurrent stroke rate. Data were pooled from 3 prospective studies recruiting patients with previous stroke or transient ischemic attack and long-term follow-up: the South London Stroke Register, The Vitamins to Prevent Stroke Study, and the Oxford Vascular Study. Patients receiving SVA were compared with patients who received antiepileptic drugs other than SVA using survival analysis and Cox Regression. A total of 11 949 patients with confirmed ischemic event were included. Recurrent stroke rate was lower in patient taking SVA (17 of 168) than other antiepileptic drugs (105 of 530; log-rank survival analysis P =0.002). On Cox regression, controlling for potential cofounders, SVA remained associated with reduced stroke (hazard ratio=0.44; 95% confidence interval: 0.3-0.7; P =0.002). A similar result was obtained when patients taking SVA were compared with all cases not taking SVA (Cox regression, hazard ratio=0.47; 95% confidence interval: 0.29-0.77; P =0.003). These results suggest that exposure to SVA, an inhibitor of HDAC, may be associated with a lower recurrent stroke risk although we cannot exclude residual confounding in this study design. This supports the hypothesis that HDAC9 is important in the ischemic stroke pathogenesis and that its inhibition, by SVA or a more specific HDAC9 inhibitor, is worthy of evaluation as a treatment to prevent recurrent ischemic stroke. © 2017 The Authors.

Racial differences in the outcome of patients with urothelial carcinoma of the upper urinary tract: an international study.

PubMed

Matsumoto, Kazumasa; Novara, Giacomo; Gupta, Amit; Margulis, Vitaly; Walton, Thomas J; Roscigno, Marco; Ng, Casey; Kikuchi, Eiji; Zigeuner, Richard; Kassouf, Wassim; Fritsche, Hans-Martin; Ficarra, Vincenzo; Martignoni, Guido; Tritschler, Stefan; Rodriguez, Joaquin Carballido; Seitz, Christian; Weizer, Alon; Remzi, Mesut; Raman, Jay D; Bolenz, Christian; Bensalah, Karim; Koppie, Theresa M; Karakiewicz, Pierre I; Wood, Christopher G; Montorsi, Francesco; Iwamura, Masatsugu; Shariat, Shahrokh F

2011-10-01

•To assess the impact of differences in ethnicity on clinico-pathological characteristics and outcomes of patients with upper urinary tract urothelial carcinoma (UTUC) in a large multi-center series of patients treated with radical nephroureterectomy (RNU). •We retrospectively collected the data of 2163 patients treated with RNU at 20 academic centres in America, Asia, and Europe. •Univariable and multivariable Cox regression models addressed recurrence-free survival (RFS) and cancer-specific survival (CSS). •In all, 1794 (83%) patients were Caucasian and 369 (17%) were Japanese. All the main clinical and pathological features were significantly different between the two ethnicities. •The median follow-up of the whole cohort was 36 months. At last follow-up, 554 patients (26%) developed disease recurrence and 461 (21%) were dead from UTUC. •The 5-year RFS and CSS estimates were 71.5% and 74.2%, respectively, for Caucasian patients compared with 68.8% and 75.4%, respectively, for Japanese patients. •On univariable Cox regression analyses, ethnicity was not significantly associated with either RFS (P= 0.231) or CSS (P= 0.752). •On multivariable Cox regression analyses that adjusted for the effects of age, gender, surgical type, T stage, grade, tumour architecture, presence of concomitant carcinoma in situ, lymphovascular invasion, tumour necrosis, and lymph node status, ethnicity was not associated with either RFS (hazard ratio [HR] 1.1; P= 0.447) or CSS (HR 1.0; P= 0.908). •There were major differences in the clinico-pathological characteristics of Caucasian and Japanese patients. •However, RFS and CSS probabilities were not affected by ethnicity and race was not an independent predictor of either recurrence or cancer-related death. © 2011 THE AUTHORS; BJU INTERNATIONAL © 2011 BJU INTERNATIONAL.

Hypoalbuminaemia predicts outcome in adult patients with congenital heart disease

PubMed Central

Kempny, Aleksander; Diller, Gerhard-Paul; Alonso-Gonzalez, Rafael; Uebing, Anselm; Rafiq, Isma; Li, Wei; Swan, Lorna; Hooper, James; Donovan, Jackie; Wort, Stephen J; Gatzoulis, Michael A; Dimopoulos, Konstantinos

2015-01-01

Background In patients with acquired heart failure, hypoalbuminaemia is associated with increased risk of death. The prevalence of hypoproteinaemia and hypoalbuminaemia and their relation to outcome in adult patients with congenital heart disease (ACHD) remains, however, unknown. Methods Data on patients with ACHD who underwent blood testing in our centre within the last 14 years were collected. The relation between laboratory, clinical or demographic parameters at baseline and mortality was assessed using Cox proportional hazards regression analysis. Results A total of 2886 patients with ACHD were included. Mean age was 33.3 years (23.6–44.7) and 50.1% patients were men. Median plasma albumin concentration was 41.0 g/L (38.0–44.0), whereas hypoalbuminaemia (<35 g/L) was present in 13.9% of patients. The prevalence of hypoalbuminaemia was significantly higher in patients with great complexity ACHD (18.2%) compared with patients with moderate (11.3%) or simple ACHD lesions (12.1%, p<0.001). During a median follow-up of 5.7 years (3.3–9.6), 327 (11.3%) patients died. On univariable Cox regression analysis, hypoalbuminaemia was a strong predictor of outcome (HR 3.37, 95% CI 2.67 to 4.25, p<0.0001). On multivariable Cox regression, after adjusting for age, sodium and creatinine concentration, liver dysfunction, functional class and disease complexity, hypoalbuminaemia remained a significant predictor of death. Conclusions Hypoalbuminaemia is common in patients with ACHD and is associated with a threefold increased risk of risk of death. Hypoalbuminaemia, therefore, should be included in risk-stratification algorithms as it may assist management decisions and timing of interventions in the growing ACHD population. PMID:25736048

Empirical and targeted therapy of candidemia with fluconazole versus echinocandins: a propensity score-derived analysis of a population-based, multicentre prospective cohort.

PubMed

López-Cortés, L E; Almirante, B; Cuenca-Estrella, M; Garnacho-Montero, J; Padilla, B; Puig-Asensio, M; Ruiz-Camps, I; Rodríguez-Baño, J

2016-08-01

We compared the clinical efficacy of fluconazole and echinocandins in the treatment of candidemia in real practice. The CANDIPOP study is a prospective, population-based cohort study on candidemia carried out between May 2010 and April 2011 in 29 Spanish hospitals. Using strict inclusion criteria, we separately compared the impact of empirical and targeted therapy with fluconazole or echinocandins on 30-day mortality. Cox regression, including a propensity score (PS) for receiving echinocandins, stratified analysis on the PS quartiles and PS-based matched analyses, were performed. The empirical and targeted therapy cohorts comprised 316 and 421 cases, respectively; 30-day mortality was 18.7% with fluconazole and 33.9% with echinocandins (p 0.02) in the empirical therapy group and 19.8% with fluconazole and 27.7% with echinocandins (p 0.06) in the targeted therapy group. Multivariate Cox regression analysis including PS showed that empirical therapy with fluconazole was associated with better prognosis (adjusted hazard ratio 0.38; 95% confidence interval 0.17-0.81; p 0.01); no differences were found within each PS quartile or in cases matched according to PS. Targeted therapy with fluconazole did not show a significant association with mortality in the Cox regression analysis (adjusted hazard ratio 0.77; 95% confidence interval 0.41-1.46; p 0.63), in the PS quartiles or in PS-matched cases. The results were similar among patients with severe sepsis and septic shock. Empirical or targeted treatment with fluconazole was not associated with increased 30-day mortality compared to echinocandins among adults with candidemia. Copyright © 2016 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Changes in the expression of prostaglandin family members in bovine corpus luteum during the oestrous cycle and pregnancy.

PubMed

Berisha, Bajram; Schams, Dieter; Rodler, Daniela; Sinowatz, Fred; Pfaffl, Michael W

2018-06-06

The aim of this study was to characterize certain prostaglandin family members in the bovine corpus luteum (CL) during the oestrous cycle and pregnancy. The CL tissue was assigned to the following stages of the oestrous cycle: 1-2, 3-4, 5-7, 8-12, 13-16, >18 days (after regression) and of pregnancy: 1-2, 3-4, 6-7 and >8 months. In these samples, we investigated prostaglandin F2alpha (PTGF), prostaglandin E2 (PTGE) and their receptors (PTGFR, PTGER2, PTGER4), cyclooxygenase 2 (COX-2), PTGF synthase (PTGFS) and PTGE synthase (PTGES). The expression of mRNA was measured by RT-qPCR, hormones by EIA and localization by immunohistochemistry. The mRNA expression of COX-2, PTGFS and PTGES in CL during the early luteal phase was high followed by a continuous and significant downregulation afterwards, as well as during all phases of pregnancy. The concentration of PTGF in CL tissue was high during the early luteal phase, decreased significantly in the mid-luteal phase, and increased again afterwards. In contrast, the concentration of PTGE increased significantly during late luteal phase followed by a decrease during regression. The PTGE level increased again during late pregnancy. Immunohistochemically, the large granulose-luteal cells show strong staining for COX-2 and PTGES during the early luteal stage followed by lower activity afterwards. During pregnancy, most of the luteal cells were only weakly positive or negative. In conclusion, our results indicate that the examined prostaglandin family members are involved in the local mechanisms that regulate luteal function, specifically during CL formation, function and regression and during pregnancy in the cow. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Validation of a two-tier grading system in an unselected, consecutive cohort of serous ovarian cancer patients.

PubMed

Battista, Marco Johannes; Cotarelo, Cristina; Almstedt, Katrin; Heimes, Anne-Sophie; Makris, Georgios-Marios; Weyer, Veronika; Schmidt, Marcus

2016-09-01

New insights into the carcinogenesis of ovarian cancer (OC) lead to the definition of low-grade and high-grade serous OC. In this study, we validated the MD Anderson Cancer Center (MDACC) two-tier grading system and compared it with the traditional three-tier grading system as suggested by the International Federation of Gynecology and Obstetrics (FIGO). Consecutive patients with serous OC were enrolled. These two grading systems were assessed independently from each other. Kaplan-Meier estimates and Cox-regression analyses were performed to validate and compare their prognostic impact. 143 consecutive patients entered the study. According to the Kaplan-Meier estimates, the MDACC grading system (p = 0.001) predicted the progression free survival (PFS) more precisely than the FIGO system (p = 0.025). The MDACC grading system (p = 0.008) but not the FIGO system (p = 0.329) showed a statistically significant difference in terms of disease specific survival (DSS). Multivariable Cox-regression analyses revealed an independent prognostic impact of the MDACC grading system but not of the FIGO system for PFS (HR 1.570; 95 % CI 1.007-2.449; p = 0.047, and HR 0.712; 95 % CI 0.476-1.066; p = 0.099, respectively). Concerning DSS, the two-tier grading system but not the FIGO system showed a prognostic impact in a univariable Cox-regression analysis (HR 2.152; 95 % CI 1.207-3.835; p = 0.009, and HR 1.258; 95 % CI 0.801-1.975; p = 0.319, respectively). We were able to validate the MDACC grading system in serous OC. Moreover, this grading system was stronger associated with survival than the FIGO system.

PSHREG: A SAS macro for proportional and nonproportional subdistribution hazards regression

PubMed Central

Kohl, Maria; Plischke, Max; Leffondré, Karen; Heinze, Georg

2015-01-01

We present a new SAS macro %pshreg that can be used to fit a proportional subdistribution hazards model for survival data subject to competing risks. Our macro first modifies the input data set appropriately and then applies SAS's standard Cox regression procedure, PROC PHREG, using weights and counting-process style of specifying survival times to the modified data set. The modified data set can also be used to estimate cumulative incidence curves for the event of interest. The application of PROC PHREG has several advantages, e.g., it directly enables the user to apply the Firth correction, which has been proposed as a solution to the problem of undefined (infinite) maximum likelihood estimates in Cox regression, frequently encountered in small sample analyses. Deviation from proportional subdistribution hazards can be detected by both inspecting Schoenfeld-type residuals and testing correlation of these residuals with time, or by including interactions of covariates with functions of time. We illustrate application of these extended methods for competing risk regression using our macro, which is freely available at: http://cemsiis.meduniwien.ac.at/en/kb/science-research/software/statistical-software/pshreg, by means of analysis of a real chronic kidney disease study. We discuss differences in features and capabilities of %pshreg and the recent (January 2014) SAS PROC PHREG implementation of proportional subdistribution hazards modelling. PMID:25572709

Derivation of the linear-logistic model and Cox's proportional hazard model from a canonical system description.

PubMed

Voit, E O; Knapp, R G

1997-08-15

The linear-logistic regression model and Cox's proportional hazard model are widely used in epidemiology. Their successful application leaves no doubt that they are accurate reflections of observed disease processes and their associated risks or incidence rates. In spite of their prominence, it is not a priori evident why these models work. This article presents a derivation of the two models from the framework of canonical modeling. It begins with a general description of the dynamics between risk sources and disease development, formulates this description in the canonical representation of an S-system, and shows how the linear-logistic model and Cox's proportional hazard model follow naturally from this representation. The article interprets the model parameters in terms of epidemiological concepts as well as in terms of general systems theory and explains the assumptions and limitations generally accepted in the application of these epidemiological models.

Soil sail content estimation in the yellow river delta with satellite hyperspectral data

USGS Publications Warehouse

Weng, Yongling; Gong, Peng; Zhu, Zhi-Liang

2008-01-01

Soil salinization is one of the most common land degradation processes and is a severe environmental hazard. The primary objective of this study is to investigate the potential of predicting salt content in soils with hyperspectral data acquired with EO-1 Hyperion. Both partial least-squares regression (PLSR) and conventional multiple linear regression (MLR), such as stepwise regression (SWR), were tested as the prediction model. PLSR is commonly used to overcome the problem caused by high-dimensional and correlated predictors. Chemical analysis of 95 samples collected from the top layer of soils in the Yellow River delta area shows that salt content was high on average, and the dominant chemicals in the saline soil were NaCl and MgCl2. Multivariate models were established between soil contents and hyperspectral data. Our results indicate that the PLSR technique with laboratory spectral data has a strong prediction capacity. Spectral bands at 1487-1527, 1971-1991, 2032-2092, and 2163-2355 nm possessed large absolute values of regression coefficients, with the largest coefficient at 2203 nm. We obtained a root mean squared error (RMSE) for calibration (with 61 samples) of RMSEC = 0.753 (R2 = 0.893) and a root mean squared error for validation (with 30 samples) of RMSEV = 0.574. The prediction model was applied on a pixel-by-pixel basis to a Hyperion reflectance image to yield a quantitative surface distribution map of soil salt content. The result was validated successfully from 38 sampling points. We obtained an RMSE estimate of 1.037 (R2 = 0.784) for the soil salt content map derived by the PLSR model. The salinity map derived from the SWR model shows that the predicted value is higher than the true value. These results demonstrate that the PLSR method is a more suitable technique than stepwise regression for quantitative estimation of soil salt content in a large area. ?? 2008 CASI.

Explanation of the variance in quality of life and activity capacity of patients with heart failure by laboratory data.

PubMed

Athanasopoulos, Leonidas V; Dritsas, Athanasios; Doll, Helen A; Cokkinos, Dennis V

2010-08-01

This study was conducted to explain the variance in quality of life (QoL) and activity capacity of patients with congestive heart failure from pathophysiological changes as estimated by laboratory data. Peak oxygen consumption (peak VO2) and ventilation (VE)/carbon dioxide output (VCO2) slope derived from cardiopulmonary exercise testing, plasma N-terminal prohormone of B-type natriuretic peptide (NT-proBNP), and echocardiographic markers [left atrium (LA), left ventricular ejection fraction (LVEF)] were measured in 62 patients with congestive heart failure, who also completed the Minnesota Living with Heart Failure Questionnaire and the Specific Activity Questionnaire. All regression models were adjusted for age and sex. On linear regression analysis, peak VO2 with P value less than 0.001, VE/VCO2 slope with P value less than 0.01, LVEF with P value less than 0.001, LA with P=0.001, and logNT-proBNP with P value less than 0.01 were found to be associated with QoL. On stepwise multiple linear regression, peak VO2 and LVEF continued to be predictive, accounting for 40% of the variability in Minnesota Living with Heart Failure Questionnaire score. On linear regression analysis, peak VO2 with P value less than 0.001, VE/VCO2 slope with P value less than 0.001, LVEF with P value less than 0.05, LA with P value less than 0.001, and logNT-proBNP with P value less than 0.001 were found to be associated with activity capacity. On stepwise multiple linear regression, peak VO2 and LA continued to be predictive, accounting for 53% of the variability in Specific Activity Questionnaire score. Peak VO2 is independently associated both with QoL and activity capacity. In addition to peak VO2, LVEF is independently associated with QoL, and LA with activity capacity.

Statistical methods for astronomical data with upper limits. II - Correlation and regression

NASA Technical Reports Server (NTRS)

Isobe, T.; Feigelson, E. D.; Nelson, P. I.

1986-01-01

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

Prediction of all-cause death in hemodialysis patients using elevated postdialysis pulse wave velocity.

PubMed

Fu, Xiaohong; Yang, Jihong; Fan, Zhaoxin; Chen, Xianguang; Wu, Jie; Li, Jie; Wu, Hua

2016-02-01

To identify the relationship between predialysis pulse wave velocity (PWV), postdialysis PWV during 1 hemodialysis (HD) session, and deaths in maintenance HD patients. 43 patients were recruited. PWV was measured before and after one HD session and dialysis- related data were recorded. Clinical data such as blood pressure, blood lipids, and blood glucose, were carefully observed and managed in a 5-year follow-up. The association between all-cause death, predialysis PWV, postdialysis PWV, change of PWV (ΔPWV), and other related variables were analyzed. After 5 years, 17 patients (39.5%) died. Univariate Cox regression analysis showed that all-cause death of the patients significantly correlated with age, postdialysis PWV, and ΔPWV. Multivariate Cox regression analysis revealed that postdialysis PWV was an independent predictor for all-cause death in these patients (HR: 1.377, 95% CI: 1.146 - 1.656, p = 0.001). Elevated postdialysis PWV significantly correlated with and was an independent predictor for all-cause death in maintenance HD patients.

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model.

PubMed

Austin, Peter C

2018-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest.

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model

PubMed Central

Austin, Peter C.

2017-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest. PMID:29321694

Box–Cox Transformation and Random Regression Models for Fecal egg Count Data

PubMed Central

da Silva, Marcos Vinícius Gualberto Barbosa; Van Tassell, Curtis P.; Sonstegard, Tad S.; Cobuci, Jaime Araujo; Gasbarre, Louis C.

2012-01-01

Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used in an effort to achieve normality before analysis. However, the transformed data are often still not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box–Cox transformation to approach normality and to estimate (co)variance components. We also proposed using random regression models (RRM) for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box–Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated. PMID:22303406

Box-Cox Transformation and Random Regression Models for Fecal egg Count Data.

PubMed

da Silva, Marcos Vinícius Gualberto Barbosa; Van Tassell, Curtis P; Sonstegard, Tad S; Cobuci, Jaime Araujo; Gasbarre, Louis C

2011-01-01

Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used in an effort to achieve normality before analysis. However, the transformed data are often still not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box-Cox transformation to approach normality and to estimate (co)variance components. We also proposed using random regression models (RRM) for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box-Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated.

NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.

PubMed

Zou, Meng; Liu, Zhaoqi; Zhang, Xiang-Sun; Wang, Yong

2015-10-15

In prognosis and survival studies, an important goal is to identify multi-biomarker panels with predictive power using molecular characteristics or clinical observations. Such analysis is often challenged by censored, small-sample-size, but high-dimensional genomic profiles or clinical data. Therefore, sophisticated models and algorithms are in pressing need. In this study, we propose a novel Area Under Curve (AUC) optimization method for multi-biomarker panel identification named Nearest Centroid Classifier for AUC optimization (NCC-AUC). Our method is motived by the connection between AUC score for classification accuracy evaluation and Harrell's concordance index in survival analysis. This connection allows us to convert the survival time regression problem to a binary classification problem. Then an optimization model is formulated to directly maximize AUC and meanwhile minimize the number of selected features to construct a predictor in the nearest centroid classifier framework. NCC-AUC shows its great performance by validating both in genomic data of breast cancer and clinical data of stage IB Non-Small-Cell Lung Cancer (NSCLC). For the genomic data, NCC-AUC outperforms Support Vector Machine (SVM) and Support Vector Machine-based Recursive Feature Elimination (SVM-RFE) in classification accuracy. It tends to select a multi-biomarker panel with low average redundancy and enriched biological meanings. Also NCC-AUC is more significant in separation of low and high risk cohorts than widely used Cox model (Cox proportional-hazards regression model) and L1-Cox model (L1 penalized in Cox model). These performance gains of NCC-AUC are quite robust across 5 subtypes of breast cancer. Further in an independent clinical data, NCC-AUC outperforms SVM and SVM-RFE in predictive accuracy and is consistently better than Cox model and L1-Cox model in grouping patients into high and low risk categories. In summary, NCC-AUC provides a rigorous optimization framework to systematically reveal multi-biomarker panel from genomic and clinical data. It can serve as a useful tool to identify prognostic biomarkers for survival analysis. NCC-AUC is available at http://doc.aporc.org/wiki/NCC-AUC. ywang@amss.ac.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Influence of overstory on snow depth and density in hemlock-spruce stands: implications for management of deer habitat in Southeastern Alaska.

Treesearch

Thomas A. Hanley; Cathy L. Rose

1987-01-01

Snow depth and density were measured in 33 stands of western hemlock-Sitka spruce (Tsuga heterophylla [Rat] Sarg.-Picea sitchensis [Bong.] Carr.) over a 3-year period. The stands, near Juneau, Alaska, provided broad ranges of species composition, age, over-story canopy coverage, tree density, and wood volume. Stepwise multiple regression analyses indicated that both...

Patient satisfaction in Dental Healthcare Centers.

PubMed

Ali, Dena A

2016-01-01

This study aimed to (1) measure the degree of patient satisfaction among the clinical and nonclinical dental services offered at specialty dental centers and (2) investigate the factors associated with the degree of overall satisfaction. Four hundred and ninety-seven participants from five dental centers were recruited for this study. Each participant completed a self-administered questionnaire to measure patient satisfaction with clinical and nonclinical dental services. Analysis of variance, t-tests, a general linear model, and stepwise regression analysis was applied. The respondents were generally satisfied, but internal differences were observed. The exhibited highest satisfaction with the dentists' performance, followed by the dental assistants' services, and the lowest satisfaction with the center's physical appearance and accessibility. Females, participants with less than a bachelor's degree, and younger individuals were more satisfied with the clinical and nonclinical dental services. The stepwise regression analysis revealed that the coefficient of determination (R (2)) was 40.4%. The patient satisfaction with the performance of the dentists explained 42.6% of the overall satisfaction, whereas their satisfaction with the clinical setting explained 31.5% of the overall satisfaction. Additional improvements with regard to the accessibility and physical appearance of the dental centers are needed. In addition, interventions regarding accessibility, particularly when booking an appointment, are required.

Psychophysiological responses to competition and the big five personality traits.

PubMed

Binboga, Erdal; Guven, Senol; Catıkkaş, Fatih; Bayazıt, Onur; Tok, Serdar

2012-06-01

This study examines the relationship between psychophysiological arousal, cognitive anxiety, and personality traits in young taekwondo athletes. A total of 20 male and 10 female taekwondo athletes (mean age = 18.6 years; ± 1.8) volunteered for the study. The Five Factor Personality Inventory and the state scale of the Spielberger State-Trait Anxiety Inventory (STAI) were used to measure personality and cognitive state anxiety. Electrodermal activity (EDA) was measured twice, one day and approximately one hour prior to the competition, to determine psychophysiological arousal. Descriptive statistics, Pearson product-moment correlations, and stepwise regression were used to analyze the data. Several "Big Five" facets were related to the EDA delta scores that were measured both one day and one hour before the competition. Two stepwise regressions were conducted to examine whether personality traits could significantly predict both EDA delta scores. The final model, containing only neuroticism from the Big Five factors, can significantly explain the variations in the EDA delta scores measured one day before the competition. Agreeableness can significantly explain variations in the EDA delta scores measured one hour before the competition. No relationship was found between cognitive anxiety and the EDA delta scores measured one hour before the competition. In conclusion, personality traits, especially agreeableness and neuroticism, might be useful in understanding arousal responses to competition.

Feet deformities are correlated with impaired balance and postural stability in seniors over 75

PubMed Central

Puszczalowska-Lizis, Ewa; Bujas, Przemyslaw; Omorczyk, Jaroslaw; Jandzis, Slawomir

2017-01-01

Objective Understanding the factors and mechanisms that determine balance in seniors appears vital in terms of their self-reliance and overall safety. The study aimed to determine the relationship between the features of feet structure and the indicators of postural stability in the elderly. Methods The study group comprised 80 seniors (41F, 39M; aged 75–85 years). CQ-ST podoscope and the CQ-Stab 2P two-platform posturograph were used as primary research tools. The data were analyzed based on Spearman’s rank correlation and forward stepwise regression. Results Analysis of forward stepwise regression identified the left foot length in females and Clarke’s angle of the left foot in men as significant and independent predictors of postural up to 30% of the variance of dependent variables. Conclusions Longer feet provide older women with better stability, whereas in men, the lowering of the longitudinal arch results in postural deterioration. In the elderly, the left lower limb shows greater activity in the stabilizing processes in the standing position than the right one. In gerontological rehabilitation special attention should be paid to the individually tailored, gender-specific treatment, with a view to enhancing overall safety and quality of seniors’ lives. PMID:28877185

Psychophysiological Responses to Competition and the Big Five Personality Traits

PubMed Central

Binboga, Erdal; Guven, Senol; Çatıkkaş, Fatih; Bayazıt, Onur; Tok, Serdar

2012-01-01

This study examines the relationship between psychophysiological arousal, cognitive anxiety, and personality traits in young taekwondo athletes. A total of 20 male and 10 female taekwondo athletes (mean age = 18.6 years; ± 1.8) volunteered for the study. The Five Factor Personality Inventory and the state scale of the Spielberger State-Trait Anxiety Inventory (STAI) were used to measure personality and cognitive state anxiety. Electrodermal activity (EDA) was measured twice, one day and approximately one hour prior to the competition, to determine psychophysiological arousal. Descriptive statistics, Pearson product-moment correlations, and stepwise regression were used to analyze the data. Several “Big Five” facets were related to the EDA delta scores that were measured both one day and one hour before the competition. Two stepwise regressions were conducted to examine whether personality traits could significantly predict both EDA delta scores. The final model, containing only neuroticism from the Big Five factors, can significantly explain the variations in the EDA delta scores measured one day before the competition. Agreeableness can significantly explain variations in the EDA delta scores measured one hour before the competition. No relationship was found between cognitive anxiety and the EDA delta scores measured one hour before the competition. In conclusion, personality traits, especially agreeableness and neuroticism, might be useful in understanding arousal responses to competition. PMID:23486906

Motor Nerve Conduction Velocity In Postmenopausal Women with Peripheral Neuropathy.

PubMed

Singh, Akanksha; Asif, Naiyer; Singh, Paras Nath; Hossain, Mohd Mobarak

2016-12-01

The post-menopausal phase is characterized by a decline in the serum oestrogen and progesterone levels. This phase is also associated with higher incidence of peripheral neuropathy. To explore the relationship between the peripheral motor nerve status and serum oestrogen and progesterone levels through assessment of Motor Nerve Conduction Velocity (MNCV) in post-menopausal women with peripheral neuropathy. This cross-sectional study was conducted at Jawaharlal Nehru Medical College during 2011-2013. The study included 30 post-menopausal women with peripheral neuropathy (age: 51.4±7.9) and 30 post-menopausal women without peripheral neuropathy (control) (age: 52.5±4.9). They were compared for MNCV in median, ulnar and common peroneal nerves and serum levels of oestrogen and progesterone estimated through enzyme immunoassays. To study the relationship between hormone levels and MNCV, a stepwise linear regression analysis was done. The post-menopausal women with peripheral neuropathy had significantly lower MNCV and serum oestrogen and progesterone levels as compared to control subjects. Stepwise linear regression analysis showed oestrogen with main effect on MNCV. The findings of the present study suggest that while the post-menopausal age group is at a greater risk of peripheral neuropathy, it is the decline in the serum estrogen levels which is critical in the development of peripheral neuropathy.

STEP and STEPSPL: Computer programs for aerodynamic model structure determination and parameter estimation

NASA Technical Reports Server (NTRS)

Batterson, J. G.

1986-01-01

The successful parametric modeling of the aerodynamics for an airplane operating at high angles of attack or sideslip is performed in two phases. First the aerodynamic model structure must be determined and second the associated aerodynamic parameters (stability and control derivatives) must be estimated for that model. The purpose of this paper is to document two versions of a stepwise regression computer program which were developed for the determination of airplane aerodynamic model structure and to provide two examples of their use on computer generated data. References are provided for the application of the programs to real flight data. The two computer programs that are the subject of this report, STEP and STEPSPL, are written in FORTRAN IV (ANSI l966) compatible with a CDC FTN4 compiler. Both programs are adaptations of a standard forward stepwise regression algorithm. The purpose of the adaptation is to facilitate the selection of a adequate mathematical model of the aerodynamic force and moment coefficients of an airplane from flight test data. The major difference between STEP and STEPSPL is in the basis for the model. The basis for the model in STEP is the standard polynomial Taylor's series expansion of the aerodynamic function about some steady-state trim condition. Program STEPSPL utilizes a set of spline basis functions.

Relation between trinucleotide GAA repeat length and sensory neuropathy in Friedreich's ataxia.

PubMed

Santoro, L; De Michele, G; Perretti, A; Crisci, C; Cocozza, S; Cavalcanti, F; Ragno, M; Monticelli, A; Filla, A; Caruso, G

1999-01-01

To verify if GAA expansion size in Friedreich's ataxia could account for the severity of sensory neuropathy. Retrospective study of 56 patients with Friedreich's ataxia selected according to homozygosity for GAA expansion and availability of electrophysiological findings. Orthodromic sensory conduction velocity in the median nerve was available in all patients and that of the tibial nerve in 46 of them. Data of sural nerve biopsy and of a morphometric analysis were available in 12 of the selected patients. The sensory action potential amplitude at the wrist (wSAP) and at the medial malleolus (m mal SAP) and the percentage of myelinated fibres with diameter larger than 7, 9, and 11 microm in the sural nerve were correlated with disease duration and GAA expansion size on the shorter (GAA1) and larger (GAA2) expanded allele in each pair. Pearson's correlation test and stepwise multiple regression were used for statistical analysis. A significant inverse correlation between GAA1 size and wSAP, m mal SAP, and percentage of myelinated fibres was found. Stepwise multiple regression showed that GAA1 size significantly affects electrophysiological and morphometric data, whereas duration of disease has no effect. The data suggest that the severity of the sensory neuropathy is probably genetically determined and that it is not progressive.

Quantifying Parkinson's disease finger-tapping severity by extracting and synthesizing finger motion properties.

PubMed

Sano, Yuko; Kandori, Akihiko; Shima, Keisuke; Yamaguchi, Yuki; Tsuji, Toshio; Noda, Masafumi; Higashikawa, Fumiko; Yokoe, Masaru; Sakoda, Saburo

2016-06-01

We propose a novel index of Parkinson's disease (PD) finger-tapping severity, called "PDFTsi," for quantifying the severity of symptoms related to the finger tapping of PD patients with high accuracy. To validate the efficacy of PDFTsi, the finger-tapping movements of normal controls and PD patients were measured by using magnetic sensors, and 21 characteristics were extracted from the finger-tapping waveforms. To distinguish motor deterioration due to PD from that due to aging, the aging effect on finger tapping was removed from these characteristics. Principal component analysis (PCA) was applied to the age-normalized characteristics, and principal components that represented the motion properties of finger tapping were calculated. Multiple linear regression (MLR) with stepwise variable selection was applied to the principal components, and PDFTsi was calculated. The calculated PDFTsi indicates that PDFTsi has a high estimation ability, namely a mean square error of 0.45. The estimation ability of PDFTsi is higher than that of the alternative method, MLR with stepwise regression selection without PCA, namely a mean square error of 1.30. This result suggests that PDFTsi can quantify PD finger-tapping severity accurately. Furthermore, the result of interpreting a model for calculating PDFTsi indicated that motion wideness and rhythm disorder are important for estimating PD finger-tapping severity.

Patient satisfaction in Dental Healthcare Centers

PubMed Central

Ali, Dena A.

2016-01-01

Objectives: This study aimed to (1) measure the degree of patient satisfaction among the clinical and nonclinical dental services offered at specialty dental centers and (2) investigate the factors associated with the degree of overall satisfaction. Materials and Methods: Four hundred and ninety-seven participants from five dental centers were recruited for this study. Each participant completed a self-administered questionnaire to measure patient satisfaction with clinical and nonclinical dental services. Analysis of variance, t-tests, a general linear model, and stepwise regression analysis was applied. Results: The respondents were generally satisfied, but internal differences were observed. The exhibited highest satisfaction with the dentists’ performance, followed by the dental assistants’ services, and the lowest satisfaction with the center's physical appearance and accessibility. Females, participants with less than a bachelor's degree, and younger individuals were more satisfied with the clinical and nonclinical dental services. The stepwise regression analysis revealed that the coefficient of determination (R2) was 40.4%. The patient satisfaction with the performance of the dentists explained 42.6% of the overall satisfaction, whereas their satisfaction with the clinical setting explained 31.5% of the overall satisfaction. Conclusion: Additional improvements with regard to the accessibility and physical appearance of the dental centers are needed. In addition, interventions regarding accessibility, particularly when booking an appointment, are required. PMID:27403045

[Key physical parameters of hawthorn leaf granules by stepwise regression analysis method].

PubMed

Jiang, Qie-Ying; Zeng, Rong-Gui; Li, Zhe; Luo, Juan; Zhao, Guo-Wei; Lv, Dan; Liao, Zheng-Gen

2017-05-01

The purpose of this study was to investigate the effect of key physical properties of hawthorn leaf granule on its dissolution behavior. Hawthorn leaves extract was utilized as a model drug. The extract was mixed with microcrystalline cellulose or starch with the same ratio by using different methods. Appropriate amount of lubricant and disintegrating agent was added into part of the mixed powder, and then the granules were prepared by using extrusion granulation and high shear granulation. The granules dissolution behavior was evaluated by using equilibrium dissolution quantity and dissolution rate constant of the hypericin as the indicators. Then the effect of physical properties on dissolution behavior was analyzed through the stepwise regression analysis method. The equilibrium dissolution quantity of hypericin and adsorption heat constant in hawthorn leaves were positively correlated with the monolayer adsorption capacity and negatively correlated with the moisture absorption rate constant. The dissolution rate constants were decreased with the increase of Hausner rate, monolayer adsorption capacity and adsorption heat constant, and were increased with the increase of Carr index and specific surface area. Adsorption heat constant, monolayer adsorption capacity, moisture absorption rate constant, Carr index and specific surface area were the key physical properties of hawthorn leaf granule to affect its dissolution behavior. Copyright© by the Chinese Pharmaceutical Association.

Predicting Retention Times of Naturally Occurring Phenolic Compounds in Reversed-Phase Liquid Chromatography: A Quantitative Structure-Retention Relationship (QSRR) Approach

PubMed Central

Akbar, Jamshed; Iqbal, Shahid; Batool, Fozia; Karim, Abdul; Chan, Kim Wei

2012-01-01

Quantitative structure-retention relationships (QSRRs) have successfully been developed for naturally occurring phenolic compounds in a reversed-phase liquid chromatographic (RPLC) system. A total of 1519 descriptors were calculated from the optimized structures of the molecules using MOPAC2009 and DRAGON softwares. The data set of 39 molecules was divided into training and external validation sets. For feature selection and mapping we used step-wise multiple linear regression (SMLR), unsupervised forward selection followed by step-wise multiple linear regression (UFS-SMLR) and artificial neural networks (ANN). Stable and robust models with significant predictive abilities in terms of validation statistics were obtained with negation of any chance correlation. ANN models were found better than remaining two approaches. HNar, IDM, Mp, GATS2v, DISP and 3D-MoRSE (signals 22, 28 and 32) descriptors based on van der Waals volume, electronegativity, mass and polarizability, at atomic level, were found to have significant effects on the retention times. The possible implications of these descriptors in RPLC have been discussed. All the models are proven to be quite able to predict the retention times of phenolic compounds and have shown remarkable validation, robustness, stability and predictive performance. PMID:23203132

Predictors of competitive achievement among pubescent synchronized swimmers: an analysis of the solo-figure competition.

PubMed

Peric, M; Cavar, M; Zenic, N; Sekulic, D; Sajber, D

2014-02-01

This study examined the applicability of sport-specific fitness tests (SSTs), anthropometrics, and respiratory parameters in predicting competitive results among pubescent synchronized swimmers. A total of 25 synchronized swimmers (16-17 years; 166.2 ± 5.4 cm; and 58.4 ± 4.3 kg) volunteered for this study. The independent variables were body mass, body height, Body Mass Index (BMI), body fat percentage (BF%), lean body mass percentage, respiratory variables, and four SSTs (two specific power tests plus one aerobic- and one anaerobic-endurance test). The dependent variable was competitive achievement in the solo figure competition. The reliability analyses, Pearson's correlation coefficient and forward stepwise regression were calculated. The SSTs were reliable for testing fitness status among pubescent synchronized swimmers. The forward stepwise regression retained two SSTs, BF% and forced vital capacity (FVC, relative for age and stature) in a set of predictors of competitive achievement. Significant Beta coefficients are found for aerobic-endurance, SST and FVC. The sport-specific measure of aerobic endurance and FVC appropriately predicted competitive achievement with regard to the figures used in the competition when competitive results (the dependent variable) were obtained. Athletes and coaches should be aware of the probable negative influence of very low body fat levels on competitive achievement.

Regulatory effect of the AMPK-COX-2 signaling pathway in curcumin-induced apoptosis in HT-29 colon cancer cells.

PubMed

Lee, Yun-Kyoung; Park, Song Yi; Kim, Young-Min; Park, Ock Jin

2009-08-01

AMP-activated protein kinase (AMPK), a highly conserved protein in eukaryotes, functions as a major metabolic switch to maintain energy homeostasis. It also intrinsically regulates the mammalian cell cycle. Moreover, the AMPK cascade has emerged as an important pathway implicated in cancer control. In this study we investigated the effects of curcumin on apoptosis and the regulatory effect of the AMPK-cyclooxygenase-2 (COX-2) pathway in curcumin-induced apoptosis. Curcumin has shown promise as a chemopreventive agent because of its in vivo regression of various animal-model colon cancers. This study focused on exploiting curcumin to apply antitumorigenic effects through modulation of the AMPK-COX-2 cascade. Curcumin exhibited a potent apoptotic effect on HT-29 colon cancer cells at concentrations of 50 micromol/L and above. These apoptotic effects were correlated with the decrease in pAkt and COX-2, as well as the increase in p-AMPK. Cell cycle analysis showed that curcumin induced G(1)-phase arrest. Further study with AMPK synthetic inhibitor Compound C has shown that increased concentrations of Compound C would abolish AMPK expression, accompanied by a marked increase in COX-2 as well as pAkt expression in curcumin-treated HT-29 cells. By inhibiting AMPK with Compound C, we found that curcumin-treated colon cancer cells were no longer undergoing apoptosis; rather, they were proliferative. These results indicate that AMPK is crucial in apoptosis induced by curcumin and further that the pAkt-AMPK-COX-2 cascade or AMPK-pAkt-COX-2 pathway is important in cell proliferation and apoptosis in colon cancer cells.

Determination of dietary iron requirements by full expression of iron-containing cytochrome c oxidase in the heart of broilers from 22 to 42 d of age.

PubMed

Liao, Xiudong; Ma, Chunyan; Lu, Lin; Zhang, Liyang; Luo, Xugang

2017-10-01

The present study was carried out to determine dietary Fe requirements for the full expression of Fe-containing enzyme in broilers chicks from 22 to 42 d of age. At 22 d of age, 288 Arbor Acres male chicks were randomly assigned to one of six treatments with six replicates and fed a basal maize-soyabean-meal diet (control, containing 47·0 mg Fe/kg) or the basal diet supplemented with 20, 40, 60, 80 or 100 mg Fe/kg from FeSO4.7H2O for 21 d. Regression analysis was performed to estimate the optimal dietary Fe level using quadratic models. Liver cytochrome c oxidase (Cox), heart Cox and kidney succinate dehydrogenase mRNA levels as well as heart COX activity were affected (P<0·08) by dietary Fe level, and COX mRNA level and activity in heart of broilers increased quadratically (P<0·03) as dietary Fe level increased. The estimates of dietary Fe requirements were 110 and 104 mg/kg for the full expression of Cox mRNA and for its activity in the heart of broilers, respectively. The results from this study indicate that COX mRNA level and activity in the heart are new and sensitive criteria to evaluate the dietary Fe requirements of broilers, and the dietary Fe requirements would be 104-110 mg/kg to support the full expression of COX in the heart of broiler chicks from 22 to 42 d of age, which are higher than the current National Research Council Fe requirement (80 mg/kg) of broiler chicks from 1 to 21 d or 22 to 42 d of age.

Preadmission use of nonaspirin nonsteroidal anti-inflammatory drugs and 30-day stroke mortality.

PubMed

Schmidt, Morten; Hováth-Puhó, Erzsébet; Christiansen, Christian Fynbo; Petersen, Karin L; Bøtker, Hans Erik; Sørensen, Henrik Toft

2014-11-25

To examine whether preadmission use of nonaspirin nonsteroidal anti-inflammatory drugs (NSAIDs) influenced 30-day stroke mortality. We conducted a nationwide population-based cohort study. Using medical databases, we identified all first-time stroke hospitalizations in Denmark between 2004 and 2012 (n = 100,043) and subsequent mortality. We categorized NSAID use as current (prescription redemption within 60 days before hospital admission), former, and nonuse. Current use was further classified as new or long-term use. Cox regression was used to compute hazard ratios (HRs) of death within 30 days, controlling for potential confounding through multivariable adjustment and propensity score matching. The adjusted HR of death for ischemic stroke was 1.19 (95% confidence interval [CI]: 1.02-1.38) for current users of selective cyclooxygenase (COX)-2 inhibitors compared with nonusers, driven by the effect among new users (1.42, 95% CI: 1.14-1.77). Comparing the different COX-2 inhibitors, the HR was driven by new use of older traditional COX-2 inhibitors (1.42, 95% CI: 1.14-1.78) among which it was 1.53 (95% CI: 1.02-2.28) for etodolac and 1.28 (95% CI: 0.98-1.68) for diclofenac. The propensity score-matched analysis supported the association between older COX-2 inhibitors and ischemic stroke mortality. There was no association for former users. Mortality from intracerebral hemorrhage was not associated with use of nonselective NSAIDs or COX-2 inhibitors. Preadmission use of COX-2 inhibitors was associated with increased 30-day mortality after ischemic stroke, but not hemorrhagic stroke. Use of nonselective NSAIDs at time of admission was not associated with mortality from ischemic stroke or intracerebral hemorrhage. © 2014 American Academy of Neurology.

An introduction to g methods.

PubMed

Naimi, Ashley I; Cole, Stephen R; Kennedy, Edward H

2017-04-01

Robins' generalized methods (g methods) provide consistent estimates of contrasts (e.g. differences, ratios) of potential outcomes under a less restrictive set of identification conditions than do standard regression methods (e.g. linear, logistic, Cox regression). Uptake of g methods by epidemiologists has been hampered by limitations in understanding both conceptual and technical details. We present a simple worked example that illustrates basic concepts, while minimizing technical complications. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Financial Issues and Relationship Outcomes among Cohabiting Individuals

ERIC Educational Resources Information Center

Dew, Jeffrey

2011-01-01

Few studies have examined how financial relationship issues are associated with cohabiting individuals' risk of union dissolution or marriage. Competing-risks Cox regressions using the cohabiting data in the National Survey of Families and Households (N = 483) found that financial disagreements predicted union dissolution, whereas disagreements…

Serum chemerin levels are independently associated with quality of life in colorectal cancer survivors: A pilot study

PubMed Central

Lee, Jee-Yon; Lee, Mi-Kyung; Kim, Nam-Kyu; Chu, Sang-Hui; Lee, Duk-Chul; Lee, Hye-Sun

2017-01-01

Background Colorectal cancer (CRC) survivors are known to experience various symptoms that significantly affect their quality of life (QOL); therefore, it is important to identify clinical markers related with CRC survivor QOL. Here we investigated the relationship between serum chemerin levels, a newly identified proinflammatory adipokine, and QOL in CRC survivors. Methods A data of total of 110 CRC survivors were analysed in the study. Serum chemerin levels were measured with an enzyme immunoassay analyser. Functional Assessment of Cancer Therapy (FACT) scores were used as an indicator of QOL in CRC survivors. Results Weak but not negligible relationships were observed between serum chemerin levels and FACT-General (G) (r = -0.22, p<0.02), FACT-Colorectal cancer (C) (r = -0.23, p<0.02) and FACT-Fatigue (F) scores (r = -0.27, p<0.01) after adjusting for confounding factors. Both stepwise and enter method multiple linear regression analyses confirmed that serum chemerin levels were independently associated with FACT-G (stepwise: β = -0.15, p<0.01; enter: β = -0.12, p = 0.02), FACT-C (stepwise: β = -0.19, p<0.01; enter; β = -0.14, p = 0.02) and FACT-F scores (stepwise: β = -0.23, p<0.01; enter: β = -0.20, p<0.01). Conclusions Our results demonstrate a weak inverse relationship between serum chemerin and CRC survivor QOL. Although it is impossible to determine causality, our findings suggest that serum chemerin levels may have a significant association with CRC survivor QOL. Further prospective studies are required to confirm the clinical significance of our pilot study. PMID:28475614

A survey of variable selection methods in two Chinese epidemiology journals

PubMed Central

2010-01-01

Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163) via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44%) used stepwise procedures, 89 (41%) tested individual regression coefficients, but 33 (15%) did not mention how variables were selected. Sixty percent (58/97) of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals. PMID:20920252

Prediction of new onset of end stage renal disease in Chinese patients with type 2 diabetes mellitus - a population-based retrospective cohort study.

PubMed

Wan, Eric Yuk Fai; Fong, Daniel Yee Tak; Fung, Colman Siu Cheung; Yu, Esther Yee Tak; Chin, Weng Yee; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen

2017-08-01

Since diabetes mellitus (DM) is the leading cause of end stage renal disease (ESRD), this study aimed to develop a 5-year ESRD risk prediction model among Chinese patients with Type 2 DM (T2DM) in primary care. A retrospective cohort study was conducted on 149,333 Chinese adult T2DM primary care patients without ESRD in 2010. Using the derivation cohort over a median of 5 years follow-up, the gender-specific models including the interaction effect between predictors and age were derived using Cox regression with a forward stepwise approach. Harrell's C-statistic and calibration plot were applied to the validation cohort to assess discrimination and calibration of the models. Prediction models showed better discrimination with Harrell's C-statistics of 0.866 (males) and 0.862 (females) and calibration power from the plots than other established models. The predictors included age, usages of anti-hypertensive drugs, anti-glucose drugs, and Hemogloblin A1c, blood pressure, urine albumin/creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR). Specific predictors for male were smoking and presence of sight threatening diabetic retinopathy while additional predictors for female included longer duration of diabetes and quadratic effect of body mass index. Interaction factors with age showed a greater weighting of insulin and urine ACR in younger males, and eGFR in younger females. Our newly developed gender-specific models provide a more accurate 5-year ESRD risk predictions for Chinese diabetic primary care patients than other existing models. The models included several modifiable risk factors that clinicians can use to counsel patients, and to target at in the delivery of care to patients.

The impact of patients’ involvement in cooking on their mortality and morbidity: A 19-year follow-up of patients diagnosed with type 2 diabetes mellitus

PubMed Central

Siersma, Volkert; Køster-Rasmussen, Rasmus; Olivarius, Niels De Fine; Waldorff, Frans Boch

2015-01-01

Abstract Objective. This study explored the impact of involvement in cooking on long-term morbidity and mortality among patients newly diagnosed with type 2 diabetes mellitus (T2DM). Design and subjects. Data are from the population-based study Diabetes Care in General Practice. In baseline questionnaires, 1348 patients newly diagnosed with T2DM gave information on how frequently they consumed a warm main meal and how often they cooked it themselves. The selected patients were followed up for 19 years in the Danish National Patient Registry and the Danish Register of Causes of Death. Main outcome measures. This study analysed the association between involvement in cooking and each of seven pre-specified outcomes was analysed in Cox regression models with stepwise adjustment for possible confounders and mediators. Results. 92% of the patients with T2DM consumed a warm main meal = five times per week. Among these, women who cooked for themselves less than once a week had a higher risk of diabetes-related deaths (HR 1.86 [95% CI 1.03–3.35], p = 0.039) and stroke (HR 2.47 [95% CI 1.08–5.65], p = 0.033), after adjustment for confounders. For men, infrequent cooking was not related to increased risk for the outcomes investigated. Conclusions. In patients newly diagnosed with T2DM and with a regular intake of warm main meals, infrequent involvement in cooking was associated with an increased risk of diabetes-related death and stroke for women, but not for men. General practitioners should pay special attention to managing diabetes treatment in female patients newly diagnosed with T2DM who report infrequent involvement in cooking. PMID:25592166

Association of cardiac troponin I with disease severity and outcomes in patients with pulmonary hypertension.

PubMed

Vélez-Martínez, Mariella; Ayers, Colby; Mishkin, Joseph D; Bartolome, Sonja B; García, Christine K; Torres, Fernando; Drazner, Mark H; de Lemos, James A; Turer, Aslan T; Chin, Kelly M

2013-06-15

Previous studies have identified cardiac troponin I (cTnI) as an important marker in pulmonary hypertension (PH) prognosis. However, traditional assays are limited by poor sensitivity, even among patients at high risk. cTnI was measured in 255 PH patients using a new highly sensitive (hs) assay. Other measures included demographics, creatinine, 6-minute walk distance, hemodynamics, cardiac magnetic resonance imaging, and B-type natriuretic peptide level. The association between cTnI and survival was assessed using Kaplan-Meier analysis and Cox regression. cTnI was detectable with the hs assay in 95% of the patients with a median level of 6.9 pg/ml (IQR 2.7-12.6 pg/ml). Higher cTnI levels associated with higher levels of B-type natriuretic peptide, shorter 6-minute walk distance, and more severe hemodynamic and cardiac magnetic resonance imaging abnormalities. During a median follow-up of 3.5 years, 60 individuals died. Unadjusted event rates increased across higher cTnI quartiles (3, 5, 13, 17 events/100 person-years, respectively, p trend = 0.002). cTnI in the fourth (vs first) quartile remained associated with death in a final stepwise multivariable model that included clinical variables and hemodynamics (adjusted hazard ratio 5.3, 95% confidence interval 1.8-15.6). In conclusion, cTnI levels, detectable with a novel hs assay, identify patients with PH who have more severe hemodynamic and cardiac structural abnormalities and provide novel and independent prognostic information. This hs assay has the potential to detect more at-risk patients and improve current risk-stratification algorithms. Copyright © 2013 Elsevier Inc. All rights reserved.

Risk factors for adverse outcomes after endovascular therapy for critical limb ischemia with tissue loss due to infrainguinal artery disease.

PubMed

Tnishibe, Toshiya; Yamamoto, Kiyohito; Toguchi, Kayo; Seike, Yoshimasa; Ito, Naoki; Nishibe, Masayasu; Koizumi, Jun; Dardik, Alan; Ogino, Hitoshi

2016-10-01

The purpose of this study was to analyze the risk factors for an adverse outcome after endovascular therapy (EVT) for critical limb ischemia (CLI) with tissue loss due to infrainguinal artery disease. We retrospectively reviewed the charts of patients with tissue loss (Rutherford class 5 and 6) due to infrainguinal artery disease who were managed with endovascular therapy (EVT) between January 2006 and December 2013. The primary endpoint was amputation-free survival (AFS), while the secondary endpoints were freedom from a major adverse limb event (MALE) plus perioperative (30 days) death (POD), limb salvage, and survival rates at one year. Multivariable perioperative predictors of AFS were identified using the stepwise Cox proportional hazards regression model. A total of 65 patients underwent EVT for infrainguinal artery disease on 72 limbs. The technical success rate was 94% (68/72), while the clinical success was attained in 54 of 72 limbs (72%). The AFS, MALE + POD, limb salvage, and survival rates at one year were 76%, 86%, 91%, and 81%, respectively. The multivariate analysis demonstrated that major tissue loss classified as Rutherford class 6 (HR, 5.68; 95% CI, 2.29-14.13; P<0.05) was negatively associated with decreased AFS, while clinical success (HR, 0.25; 95% CI, 0.11-0.60; P<0.05) was positively associated with increased AFS. EVT resulted in an acceptable rate of AFS, MALE+POD, limb salvage, and survival. However, we must keep in mind that there are significant limitations to be considered for EVT in patients with major tissue loss, and that, even if revascularization could be successfully performed, a significant number of the treated limbs are still in a critical situation, such as major amputation or death.

Impact of Polymyxin B Associated Acute Kidney Injury in 1-Year Mortality and Renal Function Recovery.

PubMed

Gomes, Eduardo C; Falci, Diego R; Bergo, Pedro; Zavascki, Alexandre P; Rigatto, Maria Helena

2018-03-01

To evaluate the impact of polymyxin B (PMB)- associated Acute Kidney Injury (AKI) in 1-year mortality and renal function recovery. Patients >18 years old who survived the first 30-days after PMB therapy were followed for 1-year. The impact of AKI and Renal Failure (using RIFLE score) in 1-year mortality was analyzed, along with other confounding variables. Variables with a P value ≤0.2 were included in a forward stepwise Cox regression model. In the subgroup of patients who developed AKI, we evaluated renal function recovery. A total of 234 patients were included for analyses. Of these, 108 (46.1%) died, in a median time of 63 (38.3-102.5) days. The use of other nephrotoxic drugs along with PMB (P=0.05), renal failure (P=0.03), dialysis (P<0.01) and re-exposure to PMB (P<0.01), were all significantly related to 1-year mortality, while male gender had a protective effect (P=0.01). Independent factors related to death were age (aHR 1.02, 95%CI 1.00-1.03, P=0.02), re-exposure to PMB (aHR 2.69, 95%CI 1.82-3.95, P<0.01), and male gender (aHR0.6, 95%CI 0.41-0.87, P=0.01), when controlled for renal failure (aHR 1.28, 95%CI 0.78-2.10, P=0.34).Thirty one of 94 (33%) patients who developed AKI had renal function recovery within one-year. Mortality rates were high in the first year after PMB use and only one third of patients who develop AKI return to baseline renal function. Strategies to reduce renal toxicity are urgently needed in these patients. Copyright © 2018. Published by Elsevier B.V.

The Benefit of Chemotherapy in Esophageal Cancer Patients With Residual Disease After Trimodality Therapy.

PubMed

Kim, Grace J; Koshy, Matthew; Hanlon, Alexandra L; Horiba, M Naomi; Edelman, Martin J; Burrows, Whitney M; Battafarano, Richard J; Suntharalingam, Mohan

2016-04-01

The objective of this retrospective study was to determine the potential benefits of chemotherapy in esophageal cancer patients treated with chemoradiation followed by surgery. At our institution, 145 patients completed trimodality therapy from 1993 to 2009. Neoadjuvant treatment predominantly consisted of 5-fluorouracil and cisplatin with a concurrent median radiation dose of 50.4 Gy. Sixty-two patients received chemotherapy postoperatively. The majority (49/62) received 3 cycles of docetaxel. Within the entire cohort, a 5-year overall survival (OS) benefit was found in those who received postoperative chemotherapy, OS 37.1% versus 18.0% (P=0.024). The response after neoadjuvant chemoradiation was as follows: 33.8% had a pathologic complete response and 62.8% with residual disease. A 5-year OS and cause-specific survival (CSS) advantage were associated with postoperative chemotherapy among those with macroscopic residual disease after neoadjuvant therapy: OS 38.7% versus 13.9% (P=0.016), CSS 42.8% versus 18.8% (P=0.048). This benefit was not seen in those with a pathologic complete response or those with microscopic residual. A stepwise multivariate Cox regression model evaluating the partial response group revealed that postoperative chemotherapy and M stage were independent predictors of overall and CSS. This analysis revealed that patients with gross residual disease after trimodality therapy for esophageal cancer who received postoperative chemotherapy had an improved overall and CSS. These data suggest that patients with residual disease after trimodality therapy and a reasonable performance status may benefit from postoperative chemotherapy. Prospective trials are needed to confirm these results to define the role of postoperative treatment after trimodality therapy.

Hepatitis C virus recurrence after liver transplantation: a 10-year evaluation.

PubMed

Gitto, Stefano; Belli, Luca Saverio; Vukotic, Ranka; Lorenzini, Stefania; Airoldi, Aldo; Cicero, Arrigo Francesco Giuseppe; Vangeli, Marcello; Brodosi, Lucia; Panno, Arianna Martello; Di Donato, Roberto; Cescon, Matteo; Grazi, Gian Luca; De Carlis, Luciano; Pinna, Antonio Daniele; Bernardi, Mauro; Andreone, Pietro

2015-04-07

To evaluate the predictors of 10-year survival of patients with hepatitis C recurrence. Data from 358 patients transplanted between 1989 and 2010 in two Italian transplant centers and with evidence of hepatitis C recurrence were analyzed. A χ(2), Fisher's exact test and Kruskal Wallis' test were used for categorical and continuous variables, respectively. Survival analysis was performed at 10 years after transplant using the Kaplan-Meier method, and a log-rank test was used to compare groups. A P level less than 0.05 was considered significant for all tests. Multivariate analysis of the predictive role of different variables on 10-year survival was performed by a stepwise Cox logistic regression. The ten-year survival of the entire population was 61.2%. Five groups of patients were identified according to the virological response or lack of a response to antiviral treatment and, among those who were not treated, according to the clinical status (mild hepatitis C recurrence, "too sick to be treated" and patients with comorbidities contraindicating the treatment). While the 10-year survival of treated and untreated patients was not different (59.1% vs 64.7%, P = 0.192), patients with a sustained virological response had a higher 10-year survival rate than both the "non-responders" (84.7% vs 39.8%, P < 0.0001) and too sick to be treated (84.7% vs 0%, P < 0.0001). Sustained virological responders had a survival rate comparable to patients untreated with mild recurrence (84.7% vs 89.3%). A sustained virological response and young donor age were independent predictors of 10-year survival. Sustained virological response significantly increased long-term survival. Awaiting the interferon-free regimen global availability, antiviral treatment might be questionable in selected subjects with mild hepatitis C recurrence.

Anthropometric parameters of nutritional assessment as predictive factors of arteriovenous fistula malfunction in patients undergoing hemodialysis.

PubMed

Gagliardi, Gian Manlio; Mancuso, Domenico; Falbo, Enrica; Mollica, Francesco; Mollica, Agata; Barcellona, Elisabetta; Senatore, Massimo; Bonofiglio, Renzo

2012-01-01

To evaluate the role of body mass index (BMI), waist circumference (W-C) and waist/hip ratio (WHR) on arteriovenous fistula (AVF) dysfunction. We evaluated 84 HD patients with an average follow-up period of 31.3 ± 8.1 months, identifying 8 stenosis (STN) and 17 thrombosis (THR) cases. The association between paired variables was tested with Pearson's coefficient (r) and p-value, whereas the prognostic value on STN and THR was analysed using Cox's regression. The significant independent variables were indentified with an inverse step-wise approach defining the data as hazard ratio (HR). A double-event (Stenosis/Thrombosis) model, function of Body mass index and Waist/hip ratio was used. Arteriovenous fistula survival was assessed with the Kaplan-Meyer curve and the calculations were carried out with Graph-Pad. On univariate analysis, THR showed direct correlation with BMI (r=0.44, p<0.01), W-C (r=0.39, p<0.05) WHR (r=0.37, p<0.01), Hemoglobin (p<0.001), C-Reactive protein (p=0.01), Calcium/Phosforus product (p=0.03), Parathyroid hormone (p=0.03) and inverse with albumin (p<0.001) and systolic blood pressure (p=0.003). On multivariate analysis, BMI variations were not predictive of STN and THR, whereas each unitary WHR and W-C increase was predictive of an increase of risk of events (3.8% and 2.1% respectively). The prognostic power of W-C per STN (HR 1: 1.19; p<0.05) and THR (HR: 1.28; p<0.01) remained significant even after being adjusted to account for traditional risk factors. Abdominal obesity increases the risk of AVF dysfunction. The W-C and WHR parameters, not BMI, emerge as independent STN and THR predictors.

Treatment of Cheyne-Stokes respiration reduces arrhythmic events in chronic heart failure.

PubMed

Bitter, Thomas; Gutleben, Klaus-Jürgen; Nölker, Georg; Westerheide, Nina; Prinz, Christian; Dimitriadis, Zisis; Horstkotte, Dieter; Vogt, Jürgen; Oldenburg, Olaf

2013-10-01

This study aimed to investigate whether adequate treatment of Cheyne-Stokes respiration (CSR) reduces the risk of arrhythmic events in patients with chronic heart failure (CHF). A cohort of 403 registry patients with CHF (LVEF≤45%, NYHA-class≥2) and implanted cardioverter-defibrillator devices (ICD) was studied. They underwent overnight polygraphy, with 221 having mild or no CSR (apnea-hypopnea index [AHI]<15/h), and 182 having moderate to severe CSR (AHI>15/h). Latter ones were offered therapy with adaptive servoventilation (ASV), which 96 patients accepted and 86 rejected. During follow-up (21± 15 months) defibrillator therapies were recorded in addition to clinical and physiologic measures of heart failure severity. Event-free survival from (a) appropriate cardioverter-defibrillator therapies and (b) appropriately monitored ventricular arrhythmias was shorter in the untreated CSR group compared to the treated CSR and the no CSR group. Stepwise Cox proportional hazard regression analysis showed untreated CSR (a: hazard ratio [HR] 1.99, 95% confidence interval [CI] 1.46-2.72, P < 0.001; b: HR 2.19, 95%CI 1.42-3.37, P < 0.001), but not treated CSR (a: HR 1.06, 95%CI 0.74-1.50; P = 0.77; b: HR 1.21, 95%CI 0.75-1.93, P = 0.43) was an independent risk factor. The treated CSR group showed improvements in cardiac function and respiratory stability compared to the untreated CSR group. This study demonstrates a decrease of appropriate defibrillator therapies by ASV treated CSR in patients with CHF and ICD. A reduced exposure to hyperventilation, hypoxia, and improvement in indices of CHF severity and neurohumoral disarrangements are potential causative mechanisms. © 2013 Wiley Periodicals, Inc.

Suture, synthetic, or biologic in contaminated ventral hernia repair.

PubMed

Bondre, Ioana L; Holihan, Julie L; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K

2016-02-01

Data are lacking to support the choice between suture, synthetic mesh, or biologic matrix in contaminated ventral hernia repair (VHR). We hypothesize that in contaminated VHR, suture repair is associated with the lowest rate of surgical site infection (SSI). A multicenter database of all open VHR performed at from 2010-2011 was reviewed. All patients with follow-up of 1 mo and longer were included. The primary outcome was SSI as defined by the Centers for Disease Control and Prevention. The secondary outcome was hernia recurrence (assessed clinically or radiographically). Multivariate analysis (stepwise regression for SSI and Cox proportional hazard model for recurrence) was performed. A total of 761 VHR were reviewed for a median (range) follow-up of 15 (1-50) mo: there were 291(38%) suture, 303 (40%) low-density and/or mid-density synthetic mesh, and 167(22%) biologic matrix repair. On univariate analysis, there were differences in the three groups including ethnicity, ASA, body mass index, institution, diabetes, primary versus incisional hernia, wound class, hernia size, prior VHR, fascial release, skin flaps, and acute repair. The unadjusted outcomes for SSI (15.1%; 17.8%; 21.0%; P = 0.280) and recurrence (17.8%; 13.5%; 21.5%; P = 0.074) were not statistically different between groups. On multivariate analysis, biologic matrix was associated with a nonsignificant reduction in both SSI and recurrences, whereas synthetic mesh associated with fewer recurrences compared to suture (hazard ratio = 0.60; P = 0.015) and nonsignificant increase in SSI. Interval estimates favored biologic matrix repair in contaminated VHR; however, these results were not statistically significant. In the absence of higher level evidence, surgeons should carefully balance risk, cost, and benefits in managing contaminated ventral hernia repair. Copyright © 2016 Elsevier Inc. All rights reserved.

Factors associated with progression of diabetic nephropathy in Japanese elderly patients with type 2 diabetes: sub-analysis of the Japanese Elderly Diabetes Intervention Trial.

PubMed

Araki, Shin-ichi; Nishio, Yoshihiko; Araki, Atsushi; Umegaki, Hiroyuki; Sakurai, Takashi; Iimuro, Satoshi; Ohashi, Yasuo; Uzu, Takashi; Maegawa, Hiroshi; Kashiwagi, Atsunori; Ito, Hideki

2012-04-01

Diabetic nephropathy is a serious complication in patients with type 2 diabetes. The aim of this study was to explore the factors associated with the progression of this complication in elderly patients with type 2 diabetes. This retrospective study of a subgroup of patients registered with the Japanese Elderly Diabetes Intervention Trial included 621 Japanese patients with type 2 diabetes mellitus (age ≥ 65 years, 346 with normoalbuminuria, 190 with microalbuminuria and 85 with overt proteinuria). Multivariate Cox proportional hazard regression model with a backward stepwise procedure was applied to select factors with significant effects on worsening of nephropathy stage and the doubling of serum creatinine. During the follow up (median 52 months), 21% of patients progressed from normoalbuminuria and microalbuminuria to a worse nephropathy stage. Aging, female sex and high-density lipoprotein cholesterol were identified as independent and significant factors that worsen nephropathy stage. Also, 6.1% of patients showed doubling of serum creatinine during follow up. A positive history of cardiovascular disease, hyperuricemia and conventional therapy were identified as significant factors involved in the doubling of serum creatinine. The cumulative incidence of the doubling of serum creatinine was significantly lower in the intensive therapy group than the conventional therapy group (P = 0.016), although that of progression of nephropathy stage was similar in the two groups. We identified several factors associated with the progression of diabetic nephropathy in elderly patients with type 2 diabetes. The results suggest that multiple risk factor intervention seems important in preventing deterioration of renal dysfunction. © 2012 Japan Geriatrics Society.

Pleural Fluid Adenosine Deaminase (ADA) Predicts Survival in Patients with Malignant Pleural Effusion.

PubMed

Terra, Ricardo Mingarini; Antonangelo, Leila; Mariani, Alessandro Wasum; de Oliveira, Ricardo Lopes Moraes; Teixeira, Lisete Ribeiro; Pego-Fernandes, Paulo Manuel

2016-08-01

Systemic and local inflammations have been described as relevant prognostic factors in patients with cancer. However, parameters that stand for immune activity in the pleural space have not been tested as predictors of survival in patients with malignant pleural effusion. The objective of this study was to evaluate pleural lymphocytes and Adenosine Deaminase (ADA) as predictors of survival in patients with recurrent malignant pleural effusion. Retrospective cohort study includes patients who underwent pleurodesis for malignant pleural effusion in a tertiary center. Pleural fluid protein concentration, lactate dehydrogenase, glucose, oncotic cytology, cell count, and ADA were collected before pleurodesis and analyzed. Survival analysis was performed considering pleurodesis as time origin, and death as the event. Backwards stepwise Cox regression was used to find predictors of survival. 156 patients (out of 196 potentially eligible) were included in this study. Most were female (72 %) and breast cancer was the most common underlying malignancy (53 %). Pleural fluid ADA level was stratified as low (<15 U/L), normal (15 ≤ ADA < 40), and high (≥40). Low and high ADA levels were associated with worse survival when compared to normal ADA (logrank: 0.0024). In multivariable analysis, abnormal ADA (<15 or ADA ≥ 40) and underlying malignancies different from lymphoma, lung, or breast cancer were associated with worse survival. Pleural fluid cell count and lymphocytes number and percentage did not correlate with survival. Pleural fluid Adenosine Deaminase levels (<15 or ≥40 U/L) and neoplasms other than lung, breast, or lymphoma are independent predictors of worse survival in patients with malignant pleural effusion who undergo pleurodesis.

Extracolonic Cancer in Inflammatory Bowel Disease: Data from the GETECCU Eneida Registry.

PubMed

Chaparro, María; Ramas, M; Benítez, J M; López-García, A; Juan, A; Guardiola, J; Mínguez, M; Calvet, X; Márquez, L; Fernández Salazar, L I; Bujanda, L; García, C; Zabana, Y; Lorente, R; Barrio, J; Hinojosa, E; Iborra, M; Cajal, M Domínguez; Van Domselaar, M; García-Sepulcre, M F; Gomollón, F; Piqueras, M; Alcaín, G; García-Sánchez, V; Panés, J; Domènech, E; García-Esquinas, E; Rodríguez-Artalejo, F; Gisbert, J P

2017-07-01

The objective of this study was (a) To know the prevalence and distribution of extracolonic cancer (EC) in patients with inflammatory bowel disease (IBD); (b) To estimate the incidence rate of EC; (c) To evaluate the association between EC and treatment with immunosuppressants and anti-tumor necrosis factor (TNF) agents. This was an observational cohort study. IBD and inclusion in the ENEIDA Project (a prospectively maintained registry) from GETECCU. Patients with EC before the diagnosis of IBD, lack of relevant data for this study, and previous treatment with immunosuppressants other than corticosteroids, thiopurines, methotrexate, or anti-TNF agents. The Kaplan-Meier method was used to evaluate the impact of several variables on the risk of EC, and any differences between survival curves were evaluated using the log-rank test. Stepwise multivariate Cox regression analysis was used to investigate factors potentially associated with the development of EC, including drugs for the treatment of IBD, during follow-up. A total of 11,011 patients met the inclusion criteria and were followed for a median of 98 months. Forty-eight percent of patients (5,303) had been exposed to immunosuppressants or anti-TNF drugs, 45.8% had been exposed to thiopurines, 4.7% to methotrexate, and 21.6% to anti-TNF drugs. The prevalence of EC was 3.6%. In the multivariate analysis, age (HR=1.05, 95% CI=1.04-1.06) and having smoked (hazards ratio (HR)=1.47, 95% confidence interval (CI)=1.10-1.80) were the only variables associated with a higher risk of EC. Neither immunosuppressants nor anti-TNF drugs seem to increase the risk of EC. Older age and smoking were associated with a higher prevalence of EC.

Midlife cardiovascular fitness and dementia: A 44-year longitudinal population study in women.

PubMed

Hörder, Helena; Johansson, Lena; Guo, XinXin; Grimby, Gunnar; Kern, Silke; Östling, Svante; Skoog, Ingmar

2018-04-10

To investigate whether greater cardiovascular fitness in midlife is associated with decreased dementia risk in women followed up for 44 years. A population-based sample of 1,462 women 38 to 60 years of age was examined in 1968. Of these, a systematic subsample comprising 191 women completed a stepwise-increased maximal ergometer cycling test to evaluate cardiovascular fitness. Subsequent examinations of dementia incidence were done in 1974, 1980, 1992, 2000, 2005, and 2009. Dementia was diagnosed according to DSM-III-R criteria on the basis of information from neuropsychiatric examinations, informant interviews, hospital records, and registry data up to 2012. Cox regressions were performed with adjustment for socioeconomic, lifestyle, and medical confounders. Compared with medium fitness, the adjusted hazard ratio for all-cause dementia during the 44-year follow-up was 0.12 (95% confidence interval [CI] 0.03-0.54) among those with high fitness and 1.41 (95% CI 0.72-2.79) among those with low fitness. High fitness delayed age at dementia onset by 9.5 years and time to dementia onset by 5 years compared to medium fitness. Among Swedish women, a high cardiovascular fitness in midlife was associated with a decreased risk of subsequent dementia. Promotion of a high cardiovascular fitness may be included in strategies to mitigate or prevent dementia. Findings are not causal, and future research needs to focus on whether improved fitness could have positive effects on dementia risk and when during the life course a high cardiovascular fitness is most important. Copyright © 2018 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

Prognostic value of plasma midregional pro-adrenomedullin and C-terminal-pro-endothelin-1 in chronic heart failure outpatients.

PubMed

Adlbrecht, Christopher; Hülsmann, Martin; Strunk, Guido; Berger, Rudolf; Mörtl, Deddo; Struck, Joachim; Morgenthaler, Nils G; Bergmann, Andreas; Jakowitsch, Johannes; Maurer, Gerald; Lang, Irene M; Pacher, Richard

2009-04-01

The identification of chronic heart failure (CHF) patients at high risk of adverse outcome remains a challenge. New peptides are emerging that may give additional information. In CHF patients, endothelin (ET) levels predict mortality risk. Adrenomedullin has been shown to predict mortality in ischaemic heart failure, but not in unselected or non-ischaemic CHF patients. Moreover, ADM and ET have never been assessed in one model. The aim of the present study was to assess the prognostic value of midregional-pro-adrenomedullin (MR-proADM) and C-terminal-pro-endothelin-1 (CT-proET-1) in outpatients with CHF. We measured plasma MR-proADM and CT-proET-1 levels in 786 consecutive CHF outpatients and compared them with B-type natriuretic peptide (BNP) levels. At 24-month follow-up, 233 patients had died. A stepwise forward Cox regression model with age, sex, estimated glomerular filtration rate, NYHA > II, left ventricular ejection fraction (LVEF), MR-proADM, CT-proET-1, and BNP as possible predictors revealed that MR-proADM levels [hazard ratio (HR) = 1.77, P < 0.001] in addition to age (HR = 1.02, P = 0.004), ejection fraction (HR = 0.98, P = 0.004), and NYHA > II (HR = 1.86, P < 0.001) were predictors of death at 24 months. When the analysis was repeated dependent on NYHA-stage, MR-proADM (HR = 2.12, P < 0.001) and LVEF (HR = 0.96, P = 0.006) were significant markers, but only in patients with mild/moderate CHF. Our data suggest that MR-proADM may be an important prognostic humoral marker, especially in mild/moderately symptomatic and non-ischaemic CHF patients.

Renal transplantation across the donor-specific antibody barrier: Graft outcome and cancer risk after desensitization therapy.

PubMed

Yang, Ching-Yao; Lee, Chih-Yuan; Yeh, Chi-Chuan; Tsai, Meng-Kun

2016-06-01

Desensitization regimens including use of intravenous immune globulin and rituximab have been reported to overcome renal transplant hyperacute rejection. A retrospective case-control study was performed to assess the results and complications of renal transplantation with desensitization therapy for donor-specific antibody (DSA) in a transplant center in Asia, where donor exchange was usually not allowed. Between January 2007 and December 2013, 22 patients with DSA received live-donor renal transplantation after desensitization (DSA group). During the same period, the DSA group was compared to the NSA group (152 renal transplants) who had no specific antibody to the donors (66 from deceased donors and 86 from living relatives). Rejection, renal function, graft and patient survival rates, infection, and cancer incidence were reviewed and analyzed from medical records. The DSA group (46.8%) had significantly higher acute rejection rates than the NSA group (13.7%) at the 1-year follow-up. The estimated renal function, 5-year graft, and patient survival rates were comparable between the groups. The DSA group (19.6%) had significantly higher 5-year de novo cancer incidence than the NSA group (8.5%; p = 0.028); three patients of the DSA group developed urothelial carcinoma 17.0 ± 3.0 months after transplantation. By using stepwise Cox regression analysis, desensitization therapy was identified as the sole independent risk factor for post-transplant urothelial carcinoma. When compared to renal transplantation without DSA, desensitization therapy for DSA resulted in equivalent renal transplant outcome but potentially increased risk of urothelial carcinoma after transplantation. Copyright © 2015. Published by Elsevier B.V.

Burden of Liver Abscess and Survival Risk Score in Thailand: A Population-Based Study

PubMed Central

Poovorawan, Kittiyod; Pan-ngum, Wirichada; Soonthornworasiri, Ngamphol; Kulrat, Chotipa; Kittitrakul, Chatporn; Wilairatana, Polrat; Treeprasertsuk, Sombat; Kitsahawong, Bubpha; Phaosawasdi, Kamthorn

2016-01-01

In Thailand, the burden of liver abscess, a life-threatening infectious disease, has not been thoroughly evaluated. We developed a predictive scoring system to estimate survival of patients with liver abscess using information from the 2008–2013 Nationwide Hospital Admission Data to evaluate the burden of liver abscess in Thailand. All patients with primary diagnosis of pyogenic liver abscess (PLA) and amoebic liver abscess (ALA) were included. Epidemiological data, baseline characteristics, hospital course, and survival were analyzed. Overall, 11,296 admissions comprising 8,423 patients from 844 hospitals across Thailand were eligible for analysis. The mean age was 52 ± 17 years and 66.1% of patients were male. ALA was significantly prevalent in southern and western border regions of Thailand, and PLA occurred nationwide. The highest incidence of liver abscess occurred in the rainy season (June–November, P < 0.01). The median length of hospital stay was 8 days (interquartile range = 4–13 days), and mean direct cost of hospitalization was 846 ± 1,574 USD. The overall inhospital mortality rate was 2.8%. Incidence of ALA decreased over the 5-year study period, whereas PLA incidence increased (P < 0.01). Using multivariable Cox regression methods with stepwise variable selection, we developed a final model with five highly significant baseline parameters associated with increased 60-day mortality: older age, PLA, underlying chronic kidney disease, cirrhosis, and human immunodeficiency virus infection. Range of estimated probability of 60-day survival was 95–16% at cumulative risk score 0–13. This simplified score is practical, and may help clinicians prioritize patients requiring more intensive care. PMID:27325801

Childhood socio-economic status, school failure and drug abuse: a Swedish national cohort study.

PubMed

Gauffin, Karl; Vinnerljung, Bo; Fridell, Mats; Hesse, Morten; Hjern, Anders

2013-08-01

To investigate whether socio-economic status (SES) in childhood and school failure at 15 years of age predict illicit drug abuse in youth and young adulthood. Register study in a Swedish national cohort born 1973-88 (n = 1,405,763), followed from age 16 to 20-35 years. Cox regression analyses were used to calculate hazard ratios (HR) for any indication of drug abuse. Our outcomes were hospital admissions, death and criminality associated with illicit drug abuse. Data on socio-demographics, school grades and parental psychosocial problems were collected from censuses (1985 and 1990) and national registers. School failure was defined as having mean school grades from the final year in primary school lower than -1 standard deviation and/or no grades in core subjects. School failure was a strong predictor of illicit drug abuse with an HR of 5.87 (95% CI: 5.76-5.99) after adjustment for age and sex. Childhood SES was associated with illicit drug abuse later in life in a stepwise manner. The lowest stratum had a HR of 2.28 (95% CI: 2.20-2.37) compared with the highest stratum as the reference, when adjusted for other socio-demographic variables. In the fully adjusted model, the effect of SES was greatly attenuated to an HR of 1.23 (95% CI: 1.19-1.28) in the lowest SES category, while the effect of school failure remained high with an HR of 4.22 (95% CI: 4.13-4.31). School failure and childhood socio-economic status predict illicit drug abuse independently in youth and young adults in Sweden. © 2013 Society for the Study of Addiction.

The impact of patients' involvement in cooking on their mortality and morbidity: a 19-year follow-up of patients diagnosed with type 2 diabetes mellitus.

PubMed

Jandorf, Sofie; Siersma, Volkert; Køster-Rasmussen, Rasmus; de Fine Olivarius, Niels; Waldorff, Frans Boch

2015-03-01

This study explored the impact of involvement in cooking on long-term morbidity and mortality among patients newly diagnosed with type 2 diabetes mellitus (T2DM). Data are from the population-based study Diabetes Care in General Practice. In baseline questionnaires, 1348 patients newly diagnosed with T2DM gave information on how frequently they consumed a warm main meal and how often they cooked it themselves. The selected patients were followed up for 19 years in the Danish National Patient Registry and the Danish Register of Causes of Death. This study analysed the association between involvement in cooking and each of seven pre-specified outcomes was analysed in Cox regression models with stepwise adjustment for possible confounders and mediators. 92% of the patients with T2DM consumed a warm main meal ≥ five times per week. Among these, women who cooked for themselves less than once a week had a higher risk of diabetes-related deaths (HR 1.86 [95% CI 1.03-3.35], p = 0.039) and stroke (HR 2.47 [95% CI 1.08-5.65], p = 0.033), after adjustment for confounders. For men, infrequent cooking was not related to increased risk for the outcomes investigated. In patients newly diagnosed with T2DM and with a regular intake of warm main meals, infrequent involvement in cooking was associated with an increased risk of diabetes-related death and stroke for women, but not for men. General practitioners should pay special attention to managing diabetes treatment in female patients newly diagnosed with T2DM who report infrequent involvement in cooking.

Cohort Study on Predictors of Need for Nursing Care in Alzheimer's Disease: An Analysis of Healthcare Data.

PubMed

Brüggenjürgen, Bernd; Andersohn, Frank; Burkowitz, Jörg; Ezzat, Nadja; Gaudig, Maren; Willich, Stefan N

2016-10-18

The individual and societal burden of Alzheimer's disease (AD) is substantial. Identifying relevant factors deteriorating AD and inducing need for nursing care would be of high relevance for healthcare planning. The main objective of this study was the identification of predictors of first assignment of a level of long-term care in AD, used as an approximation for disease progression. In a retrospective cohort study using data from a large German statutory health and long-term care insurance (SHI) company, co-morbidities and drug exposure were evaluated with respect to their predictive value for disease progression (first day the amount of daily nursing care exceeded 1.5 hours). Time to disease progression was modeled using COX-proportional hazard regression with stepwise selection of predictor variables. The risk of nursing care need increased substantially with increasing age. Number of hospitalizations and number of different drugs used were significant indicators for progression, whereas outpatient visits were associated with a reduced need for care. Gender did not indicate significant influence on progression. Malignant neoplasms of ill-defined, secondary, and unspecified sites, malnutrition, renal failure, and injuries increased the risk of need for nursing care most significantly. Among prescribed drugs, significant increased risks were associated with drugs used in diabetes, preparations for treatment of wounds and ulcers, antiseptics and disinfectants, and analgesics. Physical comorbidities are relevant contributors to an increase in need for nursing care. Some medical predicting conditions may be linked to cognition, while others may be directly linked to demand for care. AD patients with these comorbidities should be monitored with special attention, as they may be under an increased risk of care dependency.

Impact of Low Diastolic Blood Pressure on Risk of Cardiovascular Death in Elderly Patients With Coronary Artery Disease After Revascularization　- The CREDO-Kyoto Registry Cohort-1.

PubMed

Kai, Hisashi; Kimura, Takeshi; Fukuda, Kenji; Fukumoto, Yoshihiro; Kakuma, Tatsuyuki; Furukawa, Yutaka

2016-04-25

We investigated the effects of age and low diastolic blood pressure (DBP) on cardiovascular death in patients with coronary artery disease (CAD) after coronary revascularization. Stable, chronic CAD patients after coronary revascularization in the CREDO-Kyoto registry cohort-1 were allocated to the Young (≤64 years, n=2,619), Young-Old (65-74 years, n=2,932), and Old-Old (≥75 years, n=1,629) groups. Kaplan-Meier analysis showed that the crude cumulative incidence of cardiovascular death was higher in Young-Old patients with DBP <70 mmHg (P<0.001) and in Old-Old patients with DBP <60 mmHg (P=0.017), but not <70 mmHg (P=0.629), compared with each counterpart. Low DBP did not increase cardiovascular death in young patients. After adjustments with independent predictors, DBP <60 mmHg did not increase the cardiovascular death in the Old-Old group (HR=1.579 [95% CI, 0.944-2.642], P=0.082) and DBP <70 mmHg remained a predictor in the Young-Old group (HR=1.665 [1.094-2.532], P=0.017). On multivariate stepwise Cox proportional hazard regression analysis, independent predictors for cardiovascular death in low DBP patients were creatinine clearance (CCr; inversely), prior cerebrovascular disease, and aortic disease in the Young-Old group and CCr (inversely) and malignancy in the Old-Old group. DBP <60 mmHg was not an independent factor for predicting cardiovascular death in Old-Old revascularized CAD patients, whereas DBP <70 mmHg remained a predictor in the Young-Old. (Circ J 2016; 80: 1232-1241).

Predictors of short-term mortality, cognitive and physical decline in older adults in northwest Russia: a population-based prospective cohort study.

PubMed

Turusheva, Anna; Frolova, Elena; Hegendoerfer, Eralda; Degryse, Jean-Marie

2017-08-01

The classical phenotype, accumulated deficit model and self-report approach of frailty were found not useful in older adults in northwest Russia. More research is needed to identify predictors of adverse outcomes in this population. The aim of this study is to identify predictors of mortality, autonomy and cognitive decline in a population that is characterized by a high cardiovascular morbidity and mortality rate. A population-based prospective cohort study of 611 community-dwelling individuals 65+. Anthropometry, medical history nutritional status were recorded. An evaluation of cognitive, physical and autonomy function, spirometry, and laboratory tests were performed. The total follow-up was 5 years. Multiple imputation, backward stepwise Cox regression analysis, C-statistic, risk reclassification analysis and the bootstrapping techniques were used to analyze the data. We found that the combination of increasing age, male sex, low physical function, low mid-arm muscle area, low forced expiratory volume in 1 s and anemia was associated with mortality for people 65+. The substitution of anemia with anemia + high level of C-reactive protein (hCRP) and the addition of high brain natriuretic peptide (hBNP) levels improved the classification of older persons at risk for mortality. The combination of low physical function, low mid-arm muscle area, low forced expiratory volume in 1 s, anemia with hCRP levels and hBNP identified older persons at a higher risk for mortality. These predictors may be used for the development of a prediction model to detect older people who are at risk for adverse health outcomes in northwest Russia.

Spatial and temporal variability of reference evapotranspiration and influenced meteorological factors in the Jialing River Basin, China

NASA Astrophysics Data System (ADS)

Herath, Imali Kaushalya; Ye, Xuchun; Wang, Jianli; Bouraima, Abdel-Kabirou

2018-02-01

Reference evapotranspiration (ETr) is one of the important parameters in the hydrological cycle. The spatio-temporal variation of ETr and other meteorological parameters that influence ETr were investigated in the Jialing River Basin (JRB), China. The ETr was estimated using the CROPWAT 8.0 computer model based on the Penman-Montieth equation for the period 1964-2014. Mean temperature (MT), relative humidity (RH), sunshine duration (SD), and wind speed (WS) were the main input parameters of CROPWAT while 12 meteorological stations were evaluated. Linear regression and Mann-Kendall methods were applied to study the spatio-temporal trends while the inverse distance weighted (IDW) method was used to identify the spatial distribution of ETr. Stepwise regression and partial correlation methods were used to identify the meteorological variables that most significantly influenced the changes in ETr. The highest annual ETr was found in the northern part of the basin, whereas the lowest rate was recorded in the western part. In the autumn, the highest ETr was recorded in the southeast part of JRB. The annual ETr reflected neither significant increasing nor decreasing trends. Except for the summer, ETr is slightly increasing in other seasons. The MT significantly increased whereas SD and RH were significantly decreased during the 50-year period. Partial correlation and stepwise regression methods found that the impact of meteorological parameters on ETr varies on an annual and seasonal basis while SD, MT, and RH contributed to the changes of annual and seasonal ETr in the JRB.

Reliability of a Bayesian network to predict an elevated aldosterone-to-renin ratio.

PubMed

Ducher, Michel; Mounier-Véhier, Claire; Lantelme, Pierre; Vaisse, Bernard; Baguet, Jean-Philippe; Fauvel, Jean-Pierre

2015-05-01

Resistant hypertension is common, mainly idiopathic, but sometimes related to primary aldosteronism. Thus, most hypertension specialists recommend screening for primary aldosteronism. To optimize the selection of patients whose aldosterone-to-renin ratio (ARR) is elevated from simple clinical and biological characteristics. Data from consecutive patients referred between 1 June 2008 and 30 May 2009 were collected retrospectively from five French 'European excellence hypertension centres' institutional registers. Patients were included if they had at least one of: onset of hypertension before age 40 years, resistant hypertension, history of hypokalaemia, efficient treatment by spironolactone, and potassium supplementation. An ARR>32 ng/L and aldosterone>160 ng/L in patients treated without agents altering the renin-angiotensin system was considered as elevated. Bayesian network and stepwise logistic regression were used to predict an elevated ARR. Of 334 patients, 89 were excluded (31 for incomplete data, 32 for taking agents that alter the renin-angiotensin system and 26 for other reasons). Among 245 included patients, 110 had an elevated ARR. Sensitivity reached 100% or 63.3% using Bayesian network or logistic regression, respectively, and specificity reached 89.6% or 67.2%, respectively. The area under the receiver-operating-characteristic curve obtained with the Bayesian network was significantly higher than that obtained by stepwise regression (0.93±0.02 vs. 0.70±0.03; P<0.001). In hypertension centres, Bayesian network efficiently detected patients with an elevated ARR. An external validation study is required before use in primary clinical settings. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland.

PubMed

Kolasa-Wiecek, Alicja

2015-04-01

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO2 emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH4 emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R2=0.90. For N2O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N2O emission is the peat and wood fuel consumption. Copyright © 2015. Published by Elsevier B.V.

Differentiating major depressive disorder in youths with attention deficit hyperactivity disorder.

PubMed

Diler, Rasim Somer; Daviss, W Burleson; Lopez, Adriana; Axelson, David; Iyengar, Satish; Birmaher, Boris

2007-09-01

Youths with attention deficit hyperactivity disorders (ADHD) frequently have comorbid major depressive disorders (MDD) sharing overlapping symptoms. Our objective was to examine which depressive symptoms best discriminate MDD among youths with ADHD. One-hundred-eleven youths with ADHD (5.2-17.8 years old) and their parents completed interviews with the K-SADS-PL and respective versions of the child or the parent Mood and Feelings Questionnaire (MFQ-C, MFQ-P). Controlling for group differences, logistic regression was used to calculate odds ratios reflecting the accuracy with which various depressive symptoms on the MFQ-C or MFQ-P discriminated MDD. Stepwise logistic regression then identified depressive symptoms that best discriminated the groups with and without MDD, using cross-validated misclassification rate as the criterion. Symptoms that discriminated youths with MDD (n=18) from those without MDD (n=93) were 4 of 6 mood/anhedonia symptoms, all 14 depressed cognition symptoms, and only 3 of 11 physical/vegetative symptoms. Mild irritability, miserable/unhappy moods, and symptoms related to sleep, appetite, energy levels and concentration did not discriminate MDD. A stepwise logistic regression correctly classified 89% of the comorbid MDD subjects, with only age, anhedonia at school, thoughts about killing self, thoughts that bad things would happen, and talking more slowly remaining in the final model. Results of this study may not generalize to community samples because subjects were drawn largely from a university-based outpatient psychiatric clinic. These findings stress the importance of social withdrawal, anhedonia, depressive cognitions, suicidal thoughts, and psychomotor retardation when trying to identify MDD among ADHD youths.

Identification of Key Beliefs Explaining Male Circumcision Motivation Among Adolescent Boys in Zimbabwe: Targets for Behavior Change Communication.

PubMed

Kasprzyk, Danuta; Tshimanga, Mufuta; Hamilton, Deven T; Gorn, Gerald J; Montaño, Daniel E

2018-02-01

Male circumcision (MC) significantly reduces HIV acquisition among men, leading WHO/UNAIDS to recommend high HIV and low MC prevalence countries circumcise 80% of adolescents and men age 15-49. Despite significant investment to increase MC capacity only 27% of the goal has been achieved in Zimbabwe. To increase adoption, research to create evidence-based messages is greatly needed. The Integrated Behavioral Model (IBM) was used to investigate factors affecting MC motivation among adolescents. Based on qualitative elicitation study results a survey was designed and administered to a representative sample of 802 adolescent boys aged 13-17 in two urban and two rural areas in Zimbabwe. Multiple regression analysis found all six IBM constructs (2 attitude, 2 social influence, 2 personal agency) significantly explained MC intention (R 2  = 0.55). Stepwise regression analysis of beliefs underlying each IBM belief-based construct found 9 behavioral, 6 injunctive norm, 2 descriptive norm, 5 efficacy, and 8 control beliefs significantly explained MC intention. A final stepwise regression of all the significant IBM construct beliefs identified 12 key beliefs best explaining intention. Similar analyses were carried out with subgroups of adolescents by urban-rural and age. Different sets of behavioral, normative, efficacy, and control beliefs were significant for each sub-group. This study demonstrates the application of theory-driven research to identify evidence-based targets for the design of effective MC messages for interventions to increase adolescents' motivation. Incorporating these findings into communication campaigns is likely to improve demand for MC.

Socioeconomic position and survival after lung cancer: Influence of stage, treatment and comorbidity among Danish patients with lung cancer diagnosed in 2004-2010.

PubMed

Dalton, Susanne O; Steding-Jessen, Marianne; Jakobsen, Erik; Mellemgaard, Anders; Østerlind, Kell; Schüz, Joachim; Johansen, Christoffer

2015-05-01

To address social inequality in survival after lung cancer, it is important to consider how socioeconomic position (SEP) influences prognosis. We investigated whether SEP influenced receipt of first-line treatment and whether socioeconomic differences in survival could be explained by differences in stage, treatment and comorbidity. In the Danish Lung Cancer Register, we identified 13 045 patients with lung cancer diagnosed in 2004-2010, with information on stage, histology, performance status and first-line treatment. We obtained age, gender, vital status, comorbid conditions and socioeconomic information (education, income and cohabitation status) from nationwide population-based registers. Associations between SEP and receipt of first-line treatment were analysed in multivariate logistic regression models and those with overall mortality in Cox regression models with stepwise inclusion of possible mediators. For both low- and high-stage lung cancer, adjusted ORs for first-line treatment were reduced in patients with short education and low income, although the OR for education did not reach statistical significance in men with high-stage disease. Patients with high-stage disease who lived alone were less likely to receive first-line treatment. The socioeconomic difference in overall survival was partly explained by differences in stage, treatment and comorbidity, although some differences remained after adjustment. Among patients with high-stage disease, the hazard ratio (HR) for death of those with low income was 1.12 (95% CI 1.05-1.19) in comparison with those with high income. Among patients with low-stage disease, those who lived alone had a 14% higher risk for dying (95% CI 1.05-1.25) than those who lived with a partner. The differences in risk for death by SEP were greatest in the first six months after diagnosis. Socioeconomic differences in survival after lung cancer are partly explained by social inequality in stage, first-line treatment and comorbidity. Efforts should be made to improve early diagnosis and adherence to first-line treatment recommendations among disadvantaged lung cancer patients.

Application and validation of Cox regression models in a single-center series of double kidney transplantation.

PubMed

Santori, G; Fontana, I; Bertocchi, M; Gasloli, G; Magoni Rossi, A; Tagliamacco, A; Barocci, S; Nocera, A; Valente, U

2010-05-01

A useful approach to reduce the number of discarded marginal kidneys and to increase the nephron mass is double kidney transplantation (DKT). In this study, we retrospectively evaluated the potential predictors for patient and graft survival in a single-center series of 59 DKT procedures performed between April 21, 1999, and September 21, 2008. The kidney recipients of mean age 63.27 +/- 5.17 years included 16 women (27%) and 43 men (73%). The donors of mean age 69.54 +/- 7.48 years included 32 women (54%) and 27 men (46%). The mean posttransplant dialysis time was 2.37 +/- 3.61 days. The mean hospitalization was 20.12 +/- 13.65 days. Average serum creatinine (SCr) at discharge was 1.5 +/- 0.59 mg/dL. In view of the limited numbers of recipient deaths (n = 4) and graft losses (n = 8) that occurred in our series, the proportional hazards assumption for each Cox regression model with P < .05 was tested by using correlation coefficients between transformed survival times and scaled Schoenfeld residuals, and checked with smoothed plots of Schoenfeld residuals. For patient survival, the variables that reached statistical significance were donor SCr (P = .007), donor creatinine cleararance (P = .023), and recipient age (P = .047). Each significant model passed the Schoenfeld test. By entering these variables into a multivariate Cox model for patient survival, no further significance was observed. In the univariate Cox models performed for graft survival, statistical significance was noted for donor SCr (P = .027), SCr 3 months post-DKT (P = .043), and SCr 6 months post-DKT (P = .017). All significant univariate models for graft survival passed the Schoenfeld test. A final multivariate model retained SCr at 6 months (beta = 1.746, P = .042) and donor SCr (beta = .767, P = .090). In our analysis, SCr at 6 months seemed to emerge from both univariate and multivariate Cox models as a potential predictor of graft survival among DKT. Multicenter studies with larger recipient populations and more graft losses should be performed to confirm our findings. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Attrition in Psychotherapy: A Survival Analysis

ERIC Educational Resources Information Center

Roseborough, David John; McLeod, Jeffrey T.; Wright, Florence I.

2016-01-01

Purpose: Attrition is a common problem in psychotherapy and can be defined as clients ending treatment before achieving an optimal response. Method: This longitudinal, archival study utilized data for 3,728 clients, using the Outcome Questionnaire 45.2. A Cox regression proportional hazards (hazard ratios) model was used in order to better…

Severe Pain Predicts Greater Likelihood of Subsequent Suicide

ERIC Educational Resources Information Center

Ilgen, Mark A.; Zivin, Kara; Austin, Karen L.; Bohnert, Amy S. B.; Czyz, Ewa K.; Valenstein, Marcia; Kilbourne, Amy M.

2010-01-01

Using data from the 1999 Large Health Survey of Veterans, Veterans Affairs' medical records, and the National Death Index (N = 260,254), the association between self-reported pain severity and suicide among veterans as examined, after accounting for demographic variables and psychiatric diagnoses. A Cox proportional hazards regression demonstrated…

In vitro chemo-sensitivity assay guided chemotherapy is associated with prolonged overall survival in cancer patients.

PubMed

Udelnow, Andrej; Schönfęlder, Manfred; Würl, Peter; Halloul, Zuhir; Meyer, Frank; Lippert, Hans; Mroczkowski, Paweł

2013-06-01

The overall survival (OS) of patients suffering From various tumour entities was correlated with the results of in vitro-chemosensitivity assay (CSA) of the in vivo applied drugs. Tumour specimen (n=611) were dissected in 514 patients and incubated for primary tumour cell culture. The histocytological regression assay was performed 5 days after adding chemotherapeutic substances to the cell cultures. n=329 patients undergoing chemotherapy were included in the in vitro/in vivo associations. OS was assessed and in vitro response groups compared using survival analysis. Furthermore Cox-regression analysis was performed on OS including CSA, age, TNM classification and treatment course. The growth rate of the primary was 73-96% depending on tumour entity. The in-vitro response rate varied with histology and drugs (e.g. 8-18% for methotrexate and 33-83% for epirubicine). OS was significantly prolonged for patients treated with in vitro effective drugs compared to empiric therapy (log-rank-test, p=0.0435). Cox-regression revealed that application of in vitro effective drugs, residual tumour and postoperative radiotherapy determined the death risk independently. When patients were treated with drugs effective in our CSA, OS was significantly prolonged compared to empiric therapy. CSA guided chemotherapy should be compared to empiric treatment by a prospective randomized trial.

A nonparametric method for assessment of interactions in a median regression model for analyzing right censored data.

PubMed

Lee, MinJae; Rahbar, Mohammad H; Talebi, Hooshang

2018-01-01

We propose a nonparametric test for interactions when we are concerned with investigation of the simultaneous effects of two or more factors in a median regression model with right censored survival data. Our approach is developed to detect interaction in special situations, when the covariates have a finite number of levels with a limited number of observations in each level, and it allows varying levels of variance and censorship at different levels of the covariates. Through simulation studies, we compare the power of detecting an interaction between the study group variable and a covariate using our proposed procedure with that of the Cox Proportional Hazard (PH) model and censored quantile regression model. We also assess the impact of censoring rate and type on the standard error of the estimators of parameters. Finally, we illustrate application of our proposed method to real life data from Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study to test an interaction effect between type of injury and study sites using median time for a trauma patient to receive three units of red blood cells. The results from simulation studies indicate that our procedure performs better than both Cox PH model and censored quantile regression model based on statistical power for detecting the interaction, especially when the number of observations is small. It is also relatively less sensitive to censoring rates or even the presence of conditionally independent censoring that is conditional on the levels of covariates.

Parameter estimation in Cox models with missing failure indicators and the OPPERA study.

PubMed

Brownstein, Naomi C; Cai, Jianwen; Slade, Gary D; Bair, Eric

2015-12-30

In a prospective cohort study, examining all participants for incidence of the condition of interest may be prohibitively expensive. For example, the "gold standard" for diagnosing temporomandibular disorder (TMD) is a physical examination by a trained clinician. In large studies, examining all participants in this manner is infeasible. Instead, it is common to use questionnaires to screen for incidence of TMD and perform the "gold standard" examination only on participants who screen positively. Unfortunately, some participants may leave the study before receiving the "gold standard" examination. Within the framework of survival analysis, this results in missing failure indicators. Motivated by the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study, a large cohort study of TMD, we propose a method for parameter estimation in survival models with missing failure indicators. We estimate the probability of being an incident case for those lacking a "gold standard" examination using logistic regression. These estimated probabilities are used to generate multiple imputations of case status for each missing examination that are combined with observed data in appropriate regression models. The variance introduced by the procedure is estimated using multiple imputation. The method can be used to estimate both regression coefficients in Cox proportional hazard models as well as incidence rates using Poisson regression. We simulate data with missing failure indicators and show that our method performs as well as or better than competing methods. Finally, we apply the proposed method to data from the OPPERA study. Copyright © 2015 John Wiley & Sons, Ltd.

Nowcasting of Low-Visibility Procedure States with Ordered Logistic Regression at Vienna International Airport

NASA Astrophysics Data System (ADS)

Kneringer, Philipp; Dietz, Sebastian; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Low-visibility conditions have a large impact on aviation safety and economic efficiency of airports and airlines. To support decision makers, we develop a statistical probabilistic nowcasting tool for the occurrence of capacity-reducing operations related to low visibility. The probabilities of four different low visibility classes are predicted with an ordered logistic regression model based on time series of meteorological point measurements. Potential predictor variables for the statistical models are visibility, humidity, temperature and wind measurements at several measurement sites. A stepwise variable selection method indicates that visibility and humidity measurements are the most important model inputs. The forecasts are tested with a 30 minute forecast interval up to two hours, which is a sufficient time span for tactical planning at Vienna Airport. The ordered logistic regression models outperform persistence and are competitive with human forecasters.

RNA Viruses that Cause Hemorrhagic, Encephalitic, and Febrile Disease

DTIC Science & Technology

1990-01-01

doses to levels that are subopti- effective dose (ED,0) values for Rift Valley mal for cures in other bunyavirus mouse Fever ( RVF ) virus (ED,, = 80 g...serum protein and AST Etiologic Agent (SGOT) identified in the placebo group by logistic regression], utilizing a stepwise lo- RVF , an old-world...treatment of H FRS in this study. Treatment reduced mortality RVF , distributed throughout sub-Saharan and improved several important aspects of Africa

Population dynamics of pond zooplankton II Daphnia ambigua Scourfield

USGS Publications Warehouse

Angino, E.E.; Armitage, K.B.; Saxena, B.

1973-01-01

Calcium was the most important of 27 environmental components affecting density for a 50 week period. Simultaneous stepwise regression accounted for more variability in total number/1 and in the number of ovigerous females/1 than did any of the lag analyses; 1-week lag accounted for the greatest amount of variability in clutch size. Total number and clutch size were little affected by measures of food. ?? 1973 Dr. W. Junk b.v. Publishers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Penna, M.L.; Duchiade, M.P.

The authors report the results of an investigation into the possible association between air pollution and infant mortality from pneumonia in the Rio de Janeiro Metropolitan Area. This investigation employed multiple linear regression analysis (stepwise method) for infant mortality from pneumonia in 1980, including the study population's areas of residence, incomes, and pollution exposure as independent variables. With the income variable included in the regression, a statistically significant association was observed between the average annual level of particulates and infant mortality from pneumonia. While this finding should be accepted with caution, it does suggest a biological association between these variables.more » The authors' conclusion is that air quality indicators should be included in studies of acute respiratory infections in developing countries.« less

Gastrointestinal toxicity among patients taking selective COX-2 inhibitors or conventional NSAIDs, alone or combined with proton pump inhibitors: a case-control study.

PubMed

Bakhriansyah, Mohammad; Souverein, Patrick C; de Boer, Anthonius; Klungel, Olaf H

2017-10-01

To assess the risk of gastrointestinal perforation, ulcers, or bleeding (PUB) associated with the use of conventional nonsteroidal anti-inflammatory drugs (NSAIDs) with proton pump inhibitors (PPIs) and selective COX-2 inhibitors, with or without PPIs compared with conventional NSAIDs. A case-control study was performed within conventional NSAIDs and/or selective COX-2 inhibitors users identified from the Dutch PHARMO Record Linkage System in the period 1998-2012. Cases were patients aged ≥18 years with a first hospital admission for PUB. For each case, up to four controls were matched for age and sex at the date a case was hospitalized (index date). Logistic regression analysis was used to calculate odds ratios (ORs). At the index date, 2634 cases and 5074 controls were current users of conventional NSAIDs or selective COX-2 inhibitors. Compared with conventional NSAIDs, selective COX-2 inhibitors with PPIs had the lowest risk of PUB (adjusted OR 0.51, 95% confidence interval [CI]: 0.35-0.73) followed by selective COX-2 inhibitors (adjusted OR 0.66, 95%CI: 0.48-0.89) and conventional NSAIDs with PPIs (adjusted OR 0.79, 95%CI: 0.68-0.92). Compared with conventional NSAIDs, the risk of PUB was lower for those aged ≥75 years taking conventional NSAIDs with PPIs compared with younger patients (adjusted interaction OR 0.79, 95%CI: 0.64-0.99). However, those aged ≥75 years taking selective COX-2 inhibitors, the risk was higher compared with younger patients (adjusted interaction OR 1.22, 95%CI: 1.01-1.47). Selective COX-2 inhibitors with PPIs, selective COX-2 inhibitors, and conventional NSAIDs with PPIs were associated with lower risks of PUB compared with conventional NSAIDs. These effects were modified by age. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

"Selective" switching from non-selective to selective non-steroidal anti-inflammatory drugs.

PubMed

Bennett, Kathleen; Teeling, Mary; Feely, John

2003-11-01

Non-steroidal anti inflammatory drugs (NSAIDs) are thought to account for almost 25% of all reported adverse drug reactions, primarily gastrointestinal (GI) toxicity. Selective cyclo-oxygenase-2 (COX-2) inhibitors have been shown to preferentially inhibit activity of the COX-2 enzyme, which maintains anti-inflammatory activity but reduces GI toxicity. To determine the degree of switching from non-selective NSAIDs to COX-2 inhibitors and to examine the factors that were associated with switching. The General Medical Services prescription database (1.2 million people) was examined for NSAID prescriptions from December 1999 through November 2001. All those receiving non-selective NSAIDs and those switching to selective COX-2 inhibitors after at least 1 month on a non-selective NSAID were identified (non-switchers and switchers, respectively). Age, sex, dose of non-selective NSAID and co-prescribing of anti-peptic ulcer (anti-PU) drugs were considered between switchers and non-switchers, and odds ratios (OR) calculated using logistic regression. The effect of chronic use (> or =3 months prescription of a non-selective NSAID during the study period) on switching was also evaluated. A total of 81,538 of 480,573 patients (17%) initially prescribed non-selective NSAIDs were switched to COX-2 inhibitors during the study. The elderly (65 years or older) were more likely to be switched to a COX-2 inhibitor [OR=1.81, 95% confidence interval (CI) 1.79, 1.84]. Women were also more likely to be switched to COX-2 inhibitor therapy (OR=1.25, 95% CI 1.23, 1.27). Previous but not subsequent prescribing of anti-PU drugs was also associated with switching. Chronic users showed similar switching patterns. Prescribers are more likely to switch older female patients and those with a past history of peptic ulcers from non-selective NSAIDs to COX-2 inhibitors. This suggests that doctors take risk factors into consideration when prescribing NSAIDs. The relatively low rate of switching may suggest that prescribers still have concerns over the place of COX-2 inhibitors and reserve their use to those patients particularly at risk of NSAID-induced GI toxicity.

Relaxing the rule of ten events per variable in logistic and Cox regression.

PubMed

Vittinghoff, Eric; McCulloch, Charles E

2007-03-15

The rule of thumb that logistic and Cox models should be used with a minimum of 10 outcome events per predictor variable (EPV), based on two simulation studies, may be too conservative. The authors conducted a large simulation study of other influences on confidence interval coverage, type I error, relative bias, and other model performance measures. They found a range of circumstances in which coverage and bias were within acceptable levels despite less than 10 EPV, as well as other factors that were as influential as or more influential than EPV. They conclude that this rule can be relaxed, in particular for sensitivity analyses undertaken to demonstrate adequate control of confounding.

Factors associated with Iowa rural hospitals' decision to convert to critical access hospital status.

PubMed

Li, Pengxiang; Ward, Marcia M; Schneider, John E

2009-01-01

The Balanced Budget Act (BBA) of 1997 allowed some rural hospitals meeting certain requirements to convert to Critical Access Hospitals (CAHs) and changed their Medicare reimbursement from prospective to cost-based. Some subsequent CAH-related laws reduced restrictions and increased payments, and the number of CAHs grew rapidly. To examine factors related to hospitals' decisions to convert and time to CAH conversion. Eighty-nine rural hospitals in Iowa were characterized and observed from 1998 to 2005. Cox proportional hazards models were used to identify the determinants of time to CAH conversion. T-test and one-covariate Cox regression indicated that, in 1998, Iowa rural hospitals with more staffed beds, discharges, and acute inpatient days, higher operating margin, lower skilled swing bed days relative to acute days, and located in relatively high density counties were more likely to convert later or not convert before 2006. Multiple Cox regression with baseline covariates indicated that lower number of discharges and average length of stay (ALOS) were significant after controlling all other covariates. Iowa rural hospitals' decisions regarding CAH conversion were influenced by hospital size, financial condition, skilled swing bed days relative to acute days, length of stay, proportion of Medicare acute days, and geographic factors. Although financial concerns are often cited in surveys as the main reason for conversion, lower number of discharges and ALOS are the most prominent factors affecting rural hospitals' decision on when to convert.

Resveratrol promotes regression of renal carcinoma cells via a renin-angiotensin system suppression-dependent mechanism.

PubMed

Li, Jianchang; Qiu, Mingning; Chen, Lieqian; Liu, Lei; Tan, Guobin; Liu, Jianjun

2017-02-01

The aim of the present study was to investigate the effect of resveratrol on renal carcinoma cells and explore possible renin-angiotensin system-associated mechanisms. Subsequent to resveratrol treatment, the cell viability, apoptosis rate, cytotoxicity levels, caspase 3/7 activity and the levels of angiotensin II (AngII), AngII type 1 receptor (AT1R), vascular endothelial growth factor (VEGF) and cyclooxygenase-2 (COX-2) were evaluated in renal carcinoma cells. The effects of AngII, AT1R, VEGF and COX-2 on resveratrol-induced cell growth inhibition and apoptosis were also examined. The results indicated that resveratrol treatment may suppress growth, induce apoptosis, and decrease AngII, AT1R, VEGF and COX-2 levels in renal carcinoma ACHN and A498 cells. In addition, resveratrol-induced cell growth suppression and apoptosis were reversed when co-culturing with AT1R or VEGF. Thus, resveratrol may suppress renal carcinoma cell proliferation and induce apoptosis via an AT1R/VEGF pathway.

Papillary type 2 versus clear cell renal cell carcinoma: Survival outcomes.

PubMed

Simone, G; Tuderti, G; Ferriero, M; Papalia, R; Misuraca, L; Minisola, F; Costantini, M; Mastroianni, R; Sentinelli, S; Guaglianone, S; Gallucci, M

2016-11-01

To compare the cancer specific survival (CSS) between p2-RCC and a Propensity Score Matched (PSM) cohort of cc-RCC patients. Fifty-five (4.6%) patients with p2-RCC and 920 cc-RCC patients were identified within a prospectively maintained institutional dataset of 1205 histologically proved RCC patients treated with either RN or PN. Univariable and multivariable Cox regression analyses were used to identify predictors of CSS after surgical treatment. A 1:2 PSM analysis based on independent predictors of oncologic outcomes was employed and CSS was compared between PSM selected cc-RCC patients using Kaplan-Meier and Cox regression analysis. Overall, 55 (4.6%) p2-RCC and 920 (76.3%) cc-RCC patients were selected from the database; p2-RCC were significantly larger (p = 0.001), more frequently locally advanced (p < 0.001) and node positive (p < 0.001) and had significantly higher Fuhrman grade (p < 0.001) than cc-RCC. On multivariable Cox regression analysis age (p = 0.025), histologic subtype (p = 0.029), pN stage (p = 0.006), size, pT stage, cM stage, sarcomatoid features and Fuhrman grade (all p < 0.001) were independent predictors of CSS. After applying the PSM, 82 cc-RCC selected cases were comparable to 41 p2-RCC for age (p = 0.81), tumor size (p = 0.39), pT (p = 1.00) and pN (p = 0.62) stages, cM stage (p = 0.71) and Fuhrman grade (p = 1). In this PSM cohort, 5 yr CSS was significantly lower in the p2-RCC (63% vs 72.4%; p = 0.047). At multivariable Cox analysis p2 histology was an independent predictor of CSM (HR 2.46, 95% CI 1.04-5.83; p = 0.041). We confirmed the tendency of p2-RCC to present as locally advanced and metastatic disease more frequently than cc-RCC and demonstrated p2-RCC histology as an independent predictor of worse oncologic outcomes. Copyright © 2016 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Synthesis and reception of prostaglandins in corpora lutea of domestic cat and lynx.

PubMed

Zschockelt, Lina; Amelkina, Olga; Siemieniuch, Marta J; Kowalewski, Mariusz P; Dehnhard, Martin; Jewgenow, Katarina; Braun, Beate C

2016-08-01

Felids show different reproductive strategies related to the luteal phase. Domestic cats exhibit a seasonal polyoestrus and ovulation is followed by formation of corpora lutea (CL). Pregnant and non-pregnant cycles are reflected by diverging plasma progesterone (P4) profiles. Eurasian and Iberian lynxes show a seasonal monooestrus, in which physiologically persistent CL (perCL) support constantly elevated plasma P4 levels. Prostaglandins (PGs) represent key regulators of reproduction, and we aimed to characterise PG synthesis in feline CL to identify their contribution to the luteal lifespan. We assessed mRNA and protein expression of PG synthases (PTGS2/COX2, PTGES, PGFS/AKR1C3) and PG receptors (PTGER2, PTGER4, PTGFR), and intra-luteal levels of PGE2 and PGF2α Therefore, CL of pregnant (pre-implantation, post-implantation, regression stages) and non-pregnant (formation, development/maintenance, early regression, late regression stages) domestic cats, and prooestrous Eurasian (perCL, pre-mating) and metoestrous Iberian (perCL, freshCL, post-mating) lynxes were investigated. Expression of PTGS2/COX2, PTGES and PTGER4 was independent of the luteal stage in the investigated species. High levels of luteotrophic PGE2 in perCL might be associated with persistence of luteal function in lynxes. Signals for PGFS/AKR1C3 expression were weak in mid and late luteal stages of cats but were absent in lynxes, concomitant with low PGF2α levels in these species. Thus, regulation of CL regression by luteal PGF2α seems negligible. In contrast, expression of PTGFR was evident in nearly all investigated CL of cat and lynxes, implying that luteal regression, e.g. at the end of pregnancy, is triggered by extra-luteal PGF2α. © 2016 Society for Reproduction and Fertility.

Associations between state economic and health systems capacities and service use by children with special health care needs.

PubMed

Margolis, Lewis H; Mayer, Michelle; Clark, Kathryn A; Farel, Anita M

2011-08-01

To examine the relationship between measures of state economic, political, health services, and Title V capacity and individual level measures of the well-being of CSHCN. We selected five measures of Title V capacity from the Title V Information System and 13 state capacity measures from a variety of data sources, and eight indicators of intermediate health outcomes from the National Survey of Children with Special Health Care Needs. To assess the associations between Title V capacity and health services outcomes, we used stepwise regression to identify significant capacity measures while accounting for the survey design and clustering of observations by state. To assess the associations between economic, political and health systems capacity and health outcomes we fit weighted logistic regression models for each outcome, using a stepwise procedure to reduce the models. Using statistically significant capacity measures from the stepwise models, we fit reduced random effects logistic regression models to account for clustering of observations by state. Few measures of Title V and state capacity were associated with health services outcomes. For health systems measures, a higher percentage of uninsured children was associated with decreased odds of receipt of early intervention services, decreased odds of receipt of professional care coordination, and increased odds of delayed or missed care. Parents in states with higher per capita Medicaid expenditures on children were more likely to report receipt of special education services. Only two state capacity measures were associated explicitly with Title V: states with higher generalist physician to population ratios were associated with a greater likelihood of parent report of having heard of Title V and states with higher per capita gross state product were less likely to be associated with a report of using Title V services, conditional on having heard of Title V. The state level measure of family participation in Title V governance was negatively associated with receipt of care coordination and having used Title V services. The measures of state economic, political, health systems, and Title V capacity that we have analyzed are only weakly associated with the well-being of children with special health care needs. If Congress and other policymakers increase the expectations of the states in assuring that the needs of CSHCN and their families are addressed, it is essential to be cognizant of the capacities of the states to undertake that role.

Bootstrapping Cox’s Regression Model.

DTIC Science & Technology

1985-11-01

crucial points a multivariate martingale central limit theorem. Involved in this is a p x p covariance matrix Z with elements T j2= f {2(s8 ) - s(l)( s ,8o...1980). The statistical analaysis of failure time data. Wiley, New York. Meyer, P.-A. (1971). Square integrable martingales, a survey. Lecture Notes

Adolescent Suicide Attempters: What Predicts Future Suicidal Acts?

ERIC Educational Resources Information Center

Groholt, Berit; Ekeberg, Oivind; Haldorsen, Tor

2006-01-01

Predictors for repetition of suicide attempts were evaluated among 92 adolescent suicide attempters 9 years after an index suicide attempt (90% females). Five were dead, two by suicide. Thirty-one (42%) of 73 had repeated a suicide attempt. In multiple Cox regression analysis, four factors had an independent predictive effect: comorbid disorders,…

The reproductive outcome of female patients with myotonic dystrophy type 1 (DM1) undergoing PGD is not affected by the size of the expanded CTG repeat tract

PubMed Central

Seneca, Sara; De Rademaeker, Marjan; Sermon, Karen; De Rycke, Martine; De Vos, Michel; Haentjens, Patrick; Devroey, Paul; Liebaers, Ingeborg

2010-01-01

Purpose This study aims to analyze the relationship between trinucleotide repeat length and reproductive outcome in a large cohort of DM1 patients undergoing ICSI and PGD. Methods Prospective cohort study. The effect of trinucleotide repeat length on reproductive outcome per patient was analyzed using bivariate analysis (T-test) and multivariate analysis using Kaplan-Meier and Cox regression analysis. Results Between 1995 and 2005, 205 cycles of ICSI and PGD were carried out for DM1 in 78 couples. The number of trinucleotide repeats does not have an influence on reproductive outcome when adjusted for age, BMI, basal FSH values, parity, infertility status and male or female affected. Cox regression analysis indicates that cumulative live birth rate is not influenced by the number of trinucleotide repeats. The only factor with a significant effect is age (p < 0.05). Conclusion There is no evidence of an effect of trinucleotide repeat length on reproductive outcome in patients undergoing ICSI and PGD. PMID:20221684

Serum Uric Acid Levels and Risk of Incident Hypertriglyceridemia: A Longitudinal Population-based Epidemiological Study.

PubMed

Zheng, Rongjiong; Ren, Ping; Chen, Qingmei; Yang, Tianmeng; Chen, Changxi; Mao, Yushan

2017-09-01

Hypertriglyceridemia is one of lipid metabolism abnormalities; however, it is still debatable whether serum uric acid is a cause or a consequence of hypertriglyceridemia. We performed the study to investigate the longitudinal association between serum uric acid levels and hypertriglyceridemia. The study included 4190 subjects without hypertriglyceridemia. The subjects had annual health examinations for 8 years to assess incident hyperglyceridemia, and the subjects were divided into groups based on the serum uric acid quartile. Cox regression models were used to analyze the risk factors of development hypertriglyceridemia. During follow-up, 1461 (34.9%) subjects developed hypertriglyceridemia over 8 years of follow-up. The cumulative incidence of hypertriglyceridemia was 28.2%, 29.1%, 36.9%, and 45.6% in quartile 1,2,3 and 4, respectively ( P for trend <0.001). Cox regression analyses indicated that serum uric acid levels were independently and positively associated with the risk of incident hypertriglyceridemia. Hypertriglyceridemia has become a serious public health problem. This longitudinal study demonstrates that high serum uric acid levels increase the risk of hypertriglyceridemia. © 2017 by the Association of Clinical Scientists, Inc.

Triglyceride and glucose (TyG) index as a predictor of incident hypertension: a 9-year longitudinal population-based study.

PubMed

Zheng, Rongjiong; Mao, Yushan

2017-09-13

Hypertension and the triglyceride and glucose index both have been associated with insulin resistance; however, the longitudinal association remains unclear. This study was designed to investigate the longitudinal association between the triglyceride and glucose index and incident hypertension among the Chinese population. We studied 4686 subjects (3177 males and 1509 females) and followed up for 9 years. The subjects were divided into four groups based on the triglyceride and glucose index. Univariate and multivariate Cox regression models were used to analyse the risk factors of hypertension. After 9 years of follow-up, 2047 subjects developed hypertension. The overall 9-year cumulative incidence of hypertension was 43.7%, ranging from 28.5% in quartile 1 to 36.9% in quartile 2, 49.2% in quartile 3 and 59.8% in quartile 4 (p for trend < 0.001). Cox regression analyses indicated that higher triglyceride and glucose index was associated with an increased risk of subsequent incident hypertension. The triglyceride and glucose index can predict the incident hypertension among the Chinese population.

Time to detection of circulating microbubbles as a risk factor for symptoms of altitude decompression sickness

NASA Technical Reports Server (NTRS)

Kumar, K. V.; Calkins, Dick S.; Waligora, James M.; Gilbert, John H., III; Powell, Michael R.

1992-01-01

This study investigated the association between time at onset of circulating microbubbles (CMB) and symptoms of altitude decompression sickness (DCS), using Cox proportional hazard regression models. The study population consisted of 125 individuals who participated in direct ascent, simulated extravehicular activities profiles. Using individual CMB status as a time-dependent variable, we found that the hazard for symptoms increased significantly (at the end of 180 min at altitude) in the presence of CMB (Hazard Ratio = 29.59; 95 percent confidence interval (95 percent CI) = 7.66-114.27), compared to no CMB. Further examination was conducted on the subgroup of individuals who developed microbubbles during the test (n = 49), by using Cox regression. Individuals with late onset of CMB (greater than 60 min at altitude) showed a significantly reduced risk of symptoms (hazard ratio = 0.92; 95 percent CI = 0.89-0.95), compared to those with early onset (equal to or less than 60 min), while controlling for other risk factors. We conclude that time to detection of circulating microbubbles is an independent determinant of symptoms of DCS.

Relationship between serum bilirubin concentrations and diabetic nephropathy in Shanghai Han's patients with type 1 diabetes mellitus.

PubMed

Li, Xu; Zhang, Lei; Chen, Haibing; Guo, Kaifeng; Yu, Haoyong; Zhou, Jian; Li, Ming; Li, Qing; Li, Lianxi; Yin, Jun; Liu, Fang; Bao, Yuqian; Han, Junfeng; Jia, Weiping

2017-03-31

Recent studies highlight a negative association between total bilirubin concentrations and albuminuria in patients with type 2 diabetes mellitus. Our study evaluated the relationship between bilirubin concentrations and the prevalence of diabetic nephropathy (DN) in Chinese patients with type 1 diabetes mellitus (T1DM). A total of 258 patients with T1DM were recruited and bilirubin concentrations were compared between patients with or without diabetic nephropathy. Multiple stepwise regression analysis was used to examine the relationship between bilirubin concentrations and 24 h urinary microalbumin. Binary logistic regression analysis was performed to assess independent risk factors for diabetic nephropathy. Participants were divided into four groups according to the quartile of total bilirubin concentrations (Q1, 0.20-0.60; Q2, 0.60-0.80; Q3, 0.80-1.00; Q4, 1.00-1.90 mg/dL) and the chi-square test was used to compare the prevalence of DN in patients with T1DM. The median bilirubin level was 0.56 (interquartile: 0.43-0.68 mg/dL) in the DN group, significantly lower than in the non-DN group (0.70 [interquartile: 0.58-0.89 mg/dL], P < 0.001). Spearman's correlational analysis showed bilirubin concentrations were inversely correlated with 24 h urinary microalbumin (r = -0.13, P < 0.05) and multiple stepwise regression analysis showed bilirubin concentrations were independently associated with 24 h urinary microalbumin. In logistic regression analysis, bilirubin concentrations were significantly inversely associated with nephropathy. In addition, in stratified analysis, from the first to the fourth quartile group, increased bilirubin concentrations were associated with decreased prevalence of DN from 21.90% to 2.00%. High bilirubin concentrations are independently and negatively associated with albuminuria and the prevalence of DN in patients with T1DM.

The relationship between hemoglobin level and the type 1 diabetic nephropathy in Anhui Han's patients.

PubMed

Jiang, Jun; Lei, Lan; Zhou, Xiaowan; Li, Peng; Wei, Ren

2018-02-20

Recent studies have shown that low hemoglobin (Hb) level promote the progression of chronic kidney disease. This study assessed the relationship between Hb level and type 1 diabetic nephropathy (DN) in Anhui Han's patients. There were a total of 236 patients diagnosed with type 1 diabetes mellitus and (T1DM) seen between January 2014 and December 2016 in our centre. Hemoglobin levels in patients with DN were compared with those without DN. The relationship between Hb level and the urinary albumin-creatinine ratio (ACR) was examined by Spearman's correlational analysis and multiple stepwise regression analysis. The binary logistic multivariate regression analysis was performed to analyze the correlated factors for type 1 DN, calculate the Odds Ratio (OR) and 95%confidence interval (CI). The predicting value of Hb level for DN was evaluated by area under receiver operation characteristic curve (AUROC) for discrimination and Hosmer-Lemeshow goodness-of-fit test for calibration. The average Hb levels in the DN group (116.1 ± 20.8 g/L) were significantly lower than the non-DN group (131.9 ± 14.4 g/L) , P < 0.001. Hb levels were independently correlated with the urinary ACR in multiple stepwise regression analysis. The logistic multivariate regression analysis showed that the Hb level (OR: 0.936, 95% CI: 0.910 to 0.963, P < 0.001) was inversely correlated with DN in patients with T1DM. In sub-analysis, low Hb level (Hb < 120g/L in female, Hb < 130g/L in male) was still negatively associated with DN in patients with T1DM. The AUROC was 0.721 (95% CI: 0.655 to 0.787) in assessing the discrimination of the Hb level for DN. The value of P was 0.593 in Hosmer-Lemeshow goodness-of-fit test. In Anhui Han's patients with T1DM, the Hb level is inversely correlated with urinary ACR and DN. This article is protected by copyright. All rights reserved.

Emission and distribution of phosphine in paddy fields and its relationship with greenhouse gases.

PubMed

Chen, Weiyi; Niu, Xiaojun; An, Shaorong; Sheng, Hong; Tang, Zhenghua; Yang, Zhiquan; Gu, Xiaohong

2017-12-01

Phosphine (PH 3 ), as a gaseous phosphide, plays an important role in the phosphorus cycle in ecosystems. In this study, the emission and distribution of phosphine, carbon dioxide (CO 2 ) and methane (CH 4 ) in paddy fields were investigated to speculate the future potential impacts of enhanced greenhouse effect on phosphorus cycle involved in phosphine by the method of Pearson correlation analysis and multiple linear regression analysis. During the whole period of rice growth, there was a significant positive correlation between CO 2 emission flux and PH 3 emission flux (r=0.592, p=0.026, n=14). Similarly, a significant positive correlation of emission flux was also observed between CH 4 and PH 3 (r=0.563, p=0.036, n=14). The linear regression relationship was determined as [PH 3 ] flux =0.007[CO 2 ] flux +0.063[CH 4 ] flux -4.638. No significant differences were observed for all values of matrix-bound phosphine (MBP), soil carbon dioxide (SCO 2 ), and soil methane (SCH 4 ) in paddy soils. However, there was a significant positive correlation between MBP and SCO 2 at heading, flowering and ripening stage. The correlation coefficients were 0.909, 0.890 and 0.827, respectively. In vertical distribution, MBP had the analogical variation trend with SCO 2 and SCH 4 . Through Pearson correlation analysis and multiple stepwise linear regression analysis, pH, redox potential (Eh), total phosphorus (TP) and acid phosphatase (ACP) were identified as the principal factors affecting MBP levels, with correlative rankings of Eh>pH>TP>ACP. The multiple stepwise regression model ([MBP]=0.456∗[ACP]+0.235∗[TP]-1.458∗[Eh]-36.547∗[pH]+352.298) was obtained. The findings in this study hold great reference values to the global biogeochemical cycling of phosphorus in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Destination bedside: using research findings to visualize optimal unit layouts and health information technology in support of bedside care.

PubMed

Watkins, Nicholas; Kennedy, Mary; Lee, Nelson; O'Neill, Michael; Peavey, Erin; Ducharme, Maria; Padula, Cynthia

2012-05-01

This study explored the impact of unit design and healthcare information technology (HIT) on nursing workflow and patient-centered care (PCC). Healthcare information technology and unit layout-related predictors of nursing workflow and PCC were measured during a 3-phase study involving questionnaires and work sampling methods. Stepwise multiple linear regressions demonstrated several HIT and unit layout-related factors that impact nursing workflow and PCC.

Visual Analysis of North Atlantic Hurricane Trends Using Parallel Coordinates and Statistical Techniques

DTIC Science & Technology

2008-07-07

analyzing multivariate data sets. The system was developed using the Java Development Kit (JDK) version 1.5; and it yields interactive performance on a... script and captures output from the MATLAB’s “regress” and “stepwisefit” utilities that perform simple and stepwise regression, respectively. The MATLAB...Statistical Association, vol. 85, no. 411, pp. 664–675, 1990. [9] H. Hauser, F. Ledermann, and H. Doleisch, “ Angular brushing of extended parallel coordinates

Predicting alienation in a sample of Nigerian Igbo subjects.

PubMed

Morah, E I

1990-08-01

Seeman in 1959 suggested that alienation is a multidimensional concept. Using two aspects of Seeman's concept of alienation, powerlessness and social alienation, and two concepts derived from Lachar's 1978 Minnesota Multiphasic Personality Inventory Cookbook, emotional and self-alienation, the present work was undertaken to ascertain which concept will more likely predict feelings of alienation. A stepwise multiple regression showed that among 160 Nigerian (Igbo) subjects the feeling of powerlessness predicted alienation more than did the other concept.

Behavioural disorders in 6-year-old children and pyrethroid insecticide exposure: the PELAGIE mother-child cohort.

PubMed

Viel, Jean-François; Rouget, Florence; Warembourg, Charline; Monfort, Christine; Limon, Gwendolina; Cordier, Sylvaine; Chevrier, Cécile

2017-03-01

The potential impact of environmental exposure to pyrethroid insecticides on child neurodevelopment has only just started to receive attention despite their widespread use. We investigated the associations between prenatal and childhood exposure to pyrethroid insecticides and behavioural skills in 6-year-olds. The PELAGIE cohort enrolled 3421 pregnant women from Brittany, France between 2002 and 2006. 428 mothers were randomly selected for the study when their children turned 6, and 287 (67%) agreed to participate. Children's behaviour was assessed using the Strengths and Difficulties Questionnaire (SDQ). Three subscales (prosocial behaviour, internalising disorders and externalising disorders) were considered. Five pyrethroid metabolites were measured in maternal and child urine samples collected between 6 and 19 gestational weeks and at 6 years of age, respectively. Logistic regression and reverse-scale Cox regression models were used to estimate the associations between SDQ scores and urinary pyrethroid metabolite concentrations, adjusting for organophosphate metabolite concentrations and potential confounders. Increased prenatal cis -3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid (DCCA) concentrations were associated with internalising difficulties (Cox p value=0.05). For childhood 3-phenoxybenzoic acid (PBA) concentrations, a positive association was observed with externalising difficulties (Cox p value=0.04) and high ORs were found for abnormal or borderline social behaviour (OR 2.93, 95% CI 1.27 to 6.78, and OR 1.91, 95% CI 0.80 to 4.57, for the intermediate and highest metabolite categories, respectively). High childhood trans -DCCA concentrations were associated with reduced externalising disorders (Cox p value=0.03). The present study suggests that exposure to certain pyrethroids, at environmental levels, may negatively affect neurobehavioral development by 6 years of age. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Effect of a community intervention programme promoting social interactions on functional disability prevention for older adults: propensity score matching and instrumental variable analyses, JAGES Taketoyo study.

PubMed

Hikichi, Hiroyuki; Kondo, Naoki; Kondo, Katsunori; Aida, Jun; Takeda, Tokunori; Kawachi, Ichiro

2015-09-01

The efficacy of promoting social interactions to improve the health of older adults is not fully established due to residual confounding and selection bias. The government of Taketoyo town, Aichi Prefecture, Japan, developed a resident-centred community intervention programme called 'community salons', providing opportunities for social interactions among local older residents. To evaluate the impact of the programme, we conducted questionnaire surveys for all older residents of Taketoyo. We carried out a baseline survey in July 2006 (prior to the introduction of the programme) and assessed the onset of functional disability during March 2012. We analysed the data of 2421 older people. In addition to the standard Cox proportional hazard regression, we conducted Cox regression with propensity score matching (PSM) and an instrumental variable (IV) analysis, using the number of community salons within a radius of 350 m from the participant's home as an instrument. In the 5 years after the first salon was launched, the salon participants showed a 6.3% lower incidence of functional disability compared with non-participants. Even adjusting for sex, age, equivalent income, educational attainment, higher level activities of daily living and depression, the Cox adjusted HR for becoming disabled was 0.49 (95% CI 0.33 to 0.72). Similar results were observed using PSM (HR 0.52, 95% CI 0.33 to 0.83) and IV-Cox analysis (HR 0.50, 95% CI 0.34 to 0.74). A community health promotion programme focused on increasing social interactions among older adults may be effective in preventing the onset of disability. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Prayer at Midlife is Associated with Reduced Risk of Cognitive Decline in Arabic Women

PubMed Central

Inzelberg, Rivka; Afgin, Anne E; Massarwa, Magda; Schechtman, Edna; Israeli-Korn, Simon D.; Strugatsky, Rosa; Abuful, Amin; Kravitz, Efrat; Farrer, Lindsay A.; Friedland, Robert P.

2013-01-01

Midlife habits may be important for the later development of Alzheimer's disease (AD). We estimated the contribution of midlife prayer to the development of cognitive decline. In a door-to-door survey, residents aged ≥65 years were systematically evaluated in Arabic including medical history, neurological, cognitive examination, and a midlife leisure-activities questionnaire. Praying was assessed by the number of monthly praying hours at midlife. Stepwise logistic regression models were used to evaluate the effect of prayer on the odds of mild cognitive impairment (MCI) and AD versus cognitively normal individuals. Of 935 individuals that were approached, 778 [normal controls (n=448), AD (n=92) and MCI (n=238)] were evaluated. A higher proportion of cognitively normal individuals engaged in prayer at midlife [(87%) versus MCI (71%) or AD (69%) (p<0.0001)]. Since 94% of males engaged in prayer, the effect on cognitive decline could not be assessed in men. Among women, stepwise logistic regression adjusted for age and education, showed that prayer was significantly associated with reduced risk of MCI (p=0.027, OR=0.55, 95% CI 0.33-0.94), but not AD. Among individuals endorsing prayer activity, the amount of prayer was not associated with MCI or AD in either gender. Praying at midlife is associated with lower risk of mild cognitive impairment in women. PMID:23116476

Quantitative evaluation of light scattering intensities of the crystalline lens for radiation related minimal change in interventional radiologists: a cross-sectional pilot study.

PubMed

Abe, Toshi; Furui, Shigeru; Sasaki, Hiroshi; Sakamoto, Yasuo; Suzuki, Shigeru; Ishitake, Tatsuya; Terasaki, Kinuyo; Kohtake, Hiroshi; Norbash, Alexander M; Behrman, Richard H; Hayabuchi, Naofumi

2013-03-01

To evaluate low-dose X-ray radiation effects on the eye by measuring the amount of light scattering in specific regions of the lens, we compared exposed subjects (interventional radiologists) with unexposed subjects (employees of medical service companies), as a pilot study. According to numerous exclusionary rules, subjects with confounding variables contributing to cataract formation were excluded. Left eye examinations were performed on 68 exposed subjects and 171 unexposed subjects. The eye examinations consisted of an initial screening examination, followed by Scheimpflug imaging of the lens using an anterior eye segment analysis system. The subjects were assessed for the quantity of light scattering intensities found in each of the six layers of the lens. Multiple stepwise regression analyses were performed with the stepwise regression for six variables: age, radiation exposure, smoking, drinking, wearing glasses and workplace. In addition, an age-matched comparison between exposed and unexposed subjects was performed. Minimal increased light scattering intensity in the posterior subcapsular region showed statistical significance. Our results indicate that occupational radiation exposure in interventional radiologists may affect the posterior subcapsular region of the lens. Since by its very nature this retrospective study had many limitations, further well-designed studies concerning minimal radiation-related lens changes should be carried out in a low-dose exposure group.

Biomechanical correlates of symptomatic and asymptomatic neurophysiological impairment in high school football.

PubMed

Breedlove, Evan L; Robinson, Meghan; Talavage, Thomas M; Morigaki, Katherine E; Yoruk, Umit; O'Keefe, Kyle; King, Jeff; Leverenz, Larry J; Gilger, Jeffrey W; Nauman, Eric A

2012-04-30

Concussion is a growing public health issue in the United States, and chronic traumatic encephalopathy (CTE) is the chief long-term concern linked to repeated concussions. Recently, attention has shifted toward subconcussive blows and the role they may play in the development of CTE. We recruited a cohort of high school football players for two seasons of observation. Acceleration sensors were placed in the helmets, and all contact activity was monitored. Pre-season computer-based neuropsychological tests and functional magnetic resonance imaging (fMRI) tests were also obtained in order to assess cognitive and neurophysiological health. In-season follow-up scans were then obtained both from individuals who had sustained a clinically-diagnosed concussion and those who had not. These changes were then related through stepwise regression to history of blows recorded throughout the football season up to the date of the scan. In addition to those subjects who had sustained a concussion, a substantial portion of our cohort who did not sustain concussions showed significant neurophysiological changes. Stepwise regression indicated significant relationships between the number of blows sustained by a subject and the ensuing neurophysiological change. Our findings reinforce the hypothesis that the effects of repetitive blows to the head are cumulative and that repeated exposure to subconcussive blows is connected to pathologically altered neurophysiology. Copyright © 2012 Elsevier Ltd. All rights reserved.

Simple Patchy-Based Simulators Used to Explore Pondscape Systematic Dynamics

PubMed Central

Fang, Wei-Ta; Chou, Jui-Yu; Lu, Shiau-Yun

2014-01-01

Thousands of farm ponds disappeared on the tableland in Taoyuan County, Taiwan since 1920s. The number of farm ponds that have disappeared is 1,895 (37%), 2,667 ponds remain (52%), and only 537 (11%) new ponds were created within a 757 km2 area in Taoyuan, Taiwan between 1926 and 1960. In this study, a geographic information system (GIS) and logistic stepwise regression model were used to detect pond-loss rates and to understand the driving forces behind pondscape changes. The logistic stepwise regression model was used to develop a series of relationships between pondscapes affected by intrinsic driving forces (patch size, perimeter, and patch shape) and external driving forces (distance from the edge of the ponds to the edges of roads, rivers, and canals). The authors concluded that the loss of ponds was caused by pond intrinsic factors, such as pond perimeter; a large perimeter increases the chances of pond loss, but also increases the possibility of creating new ponds. However, a large perimeter is closely associated with circular shapes (lower value of the mean pond-patch fractal dimension [MPFD]), which characterize the majority of newly created ponds. The method used in this study might be helpful to those seeking to protect this unique landscape by enabling the monitoring of patch-loss problems by using simple patchy-based simulators. PMID:24466281

The influence of attention deficits on functional recovery post stroke during the first 12 months after discharge from hospital.

PubMed

Hyndman, D; Pickering, R M; Ashburn, A

2008-06-01

Attention deficits have been linked to poor recovery after stroke and may predict outcome. We explored the influence of attention on functional recovery post stroke in the first 12 months after discharge from hospital. People with stroke completed measures of attention, balance, mobility and activities of daily living (ADL) ability at the point of discharge from hospital, and 6 and 12 months later. We used correlational analysis and stepwise linear regression to explore potential predictors of outcome. We recruited 122 men and women, mean age 70 years. At discharge, 56 (51%) had deficits of divided attention, 45 (37%) of sustained attention, 43 (36%) of auditory selective attention and 41 (37%) had visual selective attention deficits. Attention at discharge correlated with mobility, balance and ADL outcomes 12 months later. After controlling for the level of the outcome at discharge, correlations remained significant in only five of the 12 relationships. Stepwise linear regression revealed that the outcome measured at discharge, days until discharge and number of medications were better predictors of outcome: in no case was an attention variable at discharge selected as a predictor of outcome at 12 months. Although attention and function correlated significantly, this correlation was reduced after controlling for functional ability at discharge. Furthermore, side of lesion and the attention variables were not demonstrated as important predictors of outcome 12 months later.

Predicting psychopharmacological drug effects on actual driving performance (SDLP) from psychometric tests measuring driving-related skills.

PubMed

Verster, Joris C; Roth, Thomas

2012-03-01

There are various methods to examine driving ability. Comparisons between these methods and their relationship with actual on-road driving is often not determined. The objective of this study was to determine whether laboratory tests measuring driving-related skills could adequately predict on-the-road driving performance during normal traffic. Ninety-six healthy volunteers performed a standardized on-the-road driving test. Subjects were instructed to drive with a constant speed and steady lateral position within the right traffic lane. Standard deviation of lateral position (SDLP), i.e., the weaving of the car, was determined. The subjects also performed a psychometric test battery including the DSST, Sternberg memory scanning test, a tracking test, and a divided attention test. Difference scores from placebo for parameters of the psychometric tests and SDLP were computed and correlated with each other. A stepwise linear regression analysis determined the predictive validity of the laboratory test battery to SDLP. Stepwise regression analyses revealed that the combination of five parameters, hard tracking, tracking and reaction time of the divided attention test, and reaction time and percentage of errors of the Sternberg memory scanning test, together had a predictive validity of 33.4%. The psychometric tests in this test battery showed insufficient predictive validity to replace the on-the-road driving test during normal traffic.

Factors associated with fall-related fractures in Parkinson's disease.

PubMed

Cheng, Kuei-Yueh; Lin, Wei-Che; Chang, Wen-Neng; Lin, Tzu-Kong; Tsai, Nai-Wen; Huang, Chih-Cheng; Wang, Hung-Chen; Huang, Yung-Cheng; Chang, Hsueh-Wen; Lin, Yu-Jun; Lee, Lian-Hui; Cheng, Ben-Chung; Kung, Chia-Te; Chang, Ya-Ting; Su, Chih-Min; Chiang, Yi-Fang; Su, Yu-Jih; Lu, Cheng-Hsien

2014-01-01

Fall-related fracture is one of the most disabling features of idiopathic Parkinson's disease (PD). A better understanding of the associated factors is needed to predict PD patients who will require treatment. This prospective study enrolled 100 adult idiopathic PD patients. Stepwise logistic regressions were used to evaluate the relationships between clinical factors and fall-related fracture. Falls occurred in 56 PD patients, including 32 with fall-related fractures. The rate of falls in the study period was 2.2 ± 1.4 per 18 months. The percentage of osteoporosis was 34% (19/56) and 11% in PD patients with and without falls, respectively. Risk factors associated with fall-related fracture were sex, underlying knee osteoarthritis, mean Unified Parkinson's Disease Rating Scale score, mean Morse fall scale, mean Hoehn and Yahr stage, and exercise habit. By stepwise logistic regression, sex and mean Morse fall scale were independently associated with fall-related fracture. Females had an odds ratio of 3.8 compared to males and the cut-off value of the Morse fall scale for predicting fall-related fracture was 72.5 (sensitivity 72% and specificity 70%). Higher mean Morse fall scales (>72.5) and female sex are associated with higher risk of fall-related fractures. Preventing falls in the high-risk PD group is an important safety issue and highly relevant for their quality of life. Copyright © 2013 Elsevier Ltd. All rights reserved.

Identification of factors that affect the adoption of an ergonomic intervention among Emergency Medical Service workers.

PubMed

Weiler, Monica R; Lavender, Steven A; Crawford, J Mac; Reichelt, Paul A; Conrad, Karen M; Browne, Michael W

2012-01-01

This study explored factors contributing to intervention adoption decisions among Emergency Medical Service (EMS) workers. Emergency Medical Service workers (n = 190), from six different organisations, participated in a two-month longitudinal study following the introduction of a patient transfer-board (also known as slide-board) designed to ease lateral transfers of patients to and from ambulance cots. Surveys administered at baseline, after one month and after two months sampled factors potentially influencing the EMS providers' decision process. 'Ergonomics Advantage' and 'Patient Advantage' entered into a stepwise regression model predicting 'intention to use' at the end of month one (R (2 )= 0.78). After the second month, the stepwise regression indicated only two factors were predictive of intention to use: 'Ergonomics Advantage,' and 'Endorsed by Champions' (R (2 )= 0.58). Actual use was predicted by: 'Ergonomics Advantage' and 'Previous Tool Experience.' These results relate to key concepts identified in the diffusion of innovation literature and have the potential to further ergonomics intervention adoption efforts. Practitioner Summary. This study explored factors that potentially facilitate the adoption of voluntarily used ergonomics interventions. EMS workers were provided with foldable transfer-boards (slideboards) designed to reduce the physical demands when laterally transferring patients. Factors predictive of adoption measures included perceived ergonomics advantage, the endorsement by champions, and prior tool experience.

Prayer at midlife is associated with reduced risk of cognitive decline in Arabic women.

PubMed

Inzelberg, Rivka; Afgin, Anne E; Massarwa, Magda; Schechtman, Edna; Israeli-Korn, Simon D; Strugatsky, Rosa; Abuful, Amin; Kravitz, Efrat; Farrer, Lindsay A; Friedland, Robert P

2013-03-01

Midlife habits may be important for the later development of Alzheimer's disease (AD). We estimated the contribution of midlife prayer to the development of cognitive decline. In a door-to-door survey, residents aged ≥65 years were systematically evaluated in Arabic including medical history, neurological, cognitive examination, and a midlife leisure-activities questionnaire. Praying was assessed by the number of monthly praying hours at midlife. Stepwise logistic regression models were used to evaluate the effect of prayer on the odds of mild cognitive impairment (MCI) and AD versus cognitively normal individuals. Of 935 individuals that were approached, 778 [normal controls (n=448), AD (n=92) and MCI (n=238)] were evaluated. A higher proportion of cognitively normal individuals engaged in prayer at midlife [(87%) versus MCI (71%) or AD (69%) (p<0.0001)]. Since 94% of males engaged in prayer, the effect on cognitive decline could not be assessed in men. Among women, stepwise logistic regression adjusted for age and education, showed that prayer was significantly associated with reduced risk of MCI (p=0.027, OR=0.55, 95% CI 0.33-0.94), but not AD. Among individuals endorsing prayer activity, the amount of prayer was not associated with MCI or AD in either gender. Praying at midlife is associated with lower risk of mild cognitive impairment in women.

Dietary acculturation and body composition predict American Hmong children's blood pressure.

PubMed

Smith, Chery; Franzen-Castle, Lisa

2012-01-01

Determine how dietary acculturation, anthropometric measures (height, weight, circumferences, and skinfolds), body mass index (BMI), and waist hip ratios (WHRs) are associated with blood pressure (BP) measures in Hmong children living in Minnesota. Acculturation was measured using responses to questions regarding language usage, social connections, and diet. Dietary assessment was completed using the multiple-pass 24-h dietary recall method on two different days. Anthropometric and BP measurement were taken using standard procedures, and BMI and WHR were calculated. Data analyses included descriptive statistics, ANOVA, and stepwise regression analyses. Using stepwise regression analysis, hip circumference (HC) predicted boys' systolic (S)BP (R(2) = 0.55). For girls' SBP, mid-upper arm circumference, WHR, low calcium consumption, and height percentile jointly explained 41% of the total variation. Mid upper arm circumference (MAC) and carbohydrate consumption predicted 35% of the variance for boys' diastolic (D)BP, and HC, dairy consumption, and calcium intake predicted 31% of the total variance for girls' DBP. Responses to dietary acculturation questions revealed between group differences for breakfast with half of the younger Born-Thailand/Laos (Born-T/L) consuming mostly Hmong food, while at dinner Born-US consumed a mixed diet and Born-T/L were more likely to consume Hmong food. Dietary acculturation and body composition predict Hmong children's BP. Copyright © 2012 Wiley Periodicals, Inc.

The investigation of the relationship between probability of suicide and reasons for living in psychiatric inpatients.

PubMed

Eskiyurt, Reyhan; Ozkan, Birgul

2017-01-01

This study was carried out to determine the reasons of the suicide probability and reasons for living of the inpatients hospitalized at the psychiatry clinic and to analyze the relationship between them. The sample of the study consisted of 192 patients who were hospitalized in psychiatric clinics between February and May 2016 and who agreed to participate in the study. In collecting data, personal information form, suicide probability scale (SPS), reasons for living inventory (RFL), and Beck's depression inventory (BDI) were used. Stepwise regression method was used to determine the factors that predict suicide probability. In the study, as a result of analyses made, the median score on the SPS was found 76.0, the median score on the RFL was found 137.0, the median score on the BDI of the patients was found 13.5, and it was found that patients with a high probability of suicide had less reasons for living and that their depression levels were very high. As a result of stepwise regression analysis, it was determined that suicidal ideation, reasons for living, maltreatment, education level, age, and income status were the predictors of suicide probability ( F = 61.125; P < 0.001). It was found that the patients who hospitalized in the psychiatric clinic have high suicide probability and the reasons of living are strong predictors of suicide probability in accordance with the literature.

QSRR modeling for diverse drugs using different feature selection methods coupled with linear and nonlinear regressions.

PubMed

Goodarzi, Mohammad; Jensen, Richard; Vander Heyden, Yvan

2012-12-01

A Quantitative Structure-Retention Relationship (QSRR) is proposed to estimate the chromatographic retention of 83 diverse drugs on a Unisphere poly butadiene (PBD) column, using isocratic elutions at pH 11.7. Previous work has generated QSRR models for them using Classification And Regression Trees (CART). In this work, Ant Colony Optimization is used as a feature selection method to find the best molecular descriptors from a large pool. In addition, several other selection methods have been applied, such as Genetic Algorithms, Stepwise Regression and the Relief method, not only to evaluate Ant Colony Optimization as a feature selection method but also to investigate its ability to find the important descriptors in QSRR. Multiple Linear Regression (MLR) and Support Vector Machines (SVMs) were applied as linear and nonlinear regression methods, respectively, giving excellent correlation between the experimental, i.e. extrapolated to a mobile phase consisting of pure water, and predicted logarithms of the retention factors of the drugs (logk(w)). The overall best model was the SVM one built using descriptors selected by ACO. Copyright © 2012 Elsevier B.V. All rights reserved.

External validation of a Cox prognostic model: principles and methods

PubMed Central

2013-01-01

Background A prognostic model should not enter clinical practice unless it has been demonstrated that it performs a useful role. External validation denotes evaluation of model performance in a sample independent of that used to develop the model. Unlike for logistic regression models, external validation of Cox models is sparsely treated in the literature. Successful validation of a model means achieving satisfactory discrimination and calibration (prediction accuracy) in the validation sample. Validating Cox models is not straightforward because event probabilities are estimated relative to an unspecified baseline function. Methods We describe statistical approaches to external validation of a published Cox model according to the level of published information, specifically (1) the prognostic index only, (2) the prognostic index together with Kaplan-Meier curves for risk groups, and (3) the first two plus the baseline survival curve (the estimated survival function at the mean prognostic index across the sample). The most challenging task, requiring level 3 information, is assessing calibration, for which we suggest a method of approximating the baseline survival function. Results We apply the methods to two comparable datasets in primary breast cancer, treating one as derivation and the other as validation sample. Results are presented for discrimination and calibration. We demonstrate plots of survival probabilities that can assist model evaluation. Conclusions Our validation methods are applicable to a wide range of prognostic studies and provide researchers with a toolkit for external validation of a published Cox model. PMID:23496923

Cystic Fibrosis Associated with Worse Survival After Liver Transplantation.

PubMed

Black, Sylvester M; Woodley, Frederick W; Tumin, Dmitry; Mumtaz, Khalid; Whitson, Bryan A; Tobias, Joseph D; Hayes, Don

2016-04-01

Survival in cystic fibrosis patients after liver transplantation and liver-lung transplantation is not well studied. To discern survival rates after liver transplantation and liver-lung transplantation in patients with and without cystic fibrosis. The United Network for Organ Sharing database was queried from 1987 to 2013. Univariate Cox proportional hazards, multivariate Cox models, and propensity score matching were performed. Liver transplant and liver-lung transplant were performed in 212 and 53 patients with cystic fibrosis, respectively. Univariate Cox proportional hazards regression identified lower survival in cystic fibrosis after liver transplant compared to a reference non-cystic fibrosis liver transplant cohort (HR 1.248; 95 % CI 1.012, 1.541; p = 0.039). Supplementary analysis found graft survival was similar across the 3 recipient categories (log-rank test: χ(2) 2.68; p = 0.262). Multivariate Cox models identified increased mortality hazard among cystic fibrosis patients undergoing liver transplantation (HR 2.439; 95 % CI 1.709, 3.482; p < 0.001) and liver-lung transplantation (HR 2.753; 95 % CI 1.560, 4.861; p < 0.001). Propensity score matching of cystic fibrosis patients undergoing liver transplantation to non-cystic fibrosis controls identified a greater mortality hazard in the cystic fibrosis cohort using a Cox proportional hazards model stratified on matched pairs (HR 3.167; 95 % CI 1.265, 7.929, p = 0.014). Liver transplantation in cystic fibrosis is associated with poorer long-term patient survival compared to non-cystic fibrosis patients, although the difference is not due to graft survival.

The antagonistic effect between STAT1 and Survivin and its clinical significance in gastric cancer.

PubMed

Deng, Hao; Zhen, Hongyan; Fu, Zhengqi; Huang, Xuan; Zhou, Hongyan; Liu, Lijiang

2012-01-01

In previous studies, we observed that STAT1 and Survivin correlated negatively with gastric cancer tissues, and that the functions of the IFN-γ-STAT1 pathway and Survivin in gastric cancer are the same as those reported for other types of cancer. In this study, the SGC7901 gastric cancer cell line and 83 gastric cancer specimens were used to confirm the relationship between STAT1 and Survivin, as well as the clinical significance of this relationship in gastric cancer. IFN-γ and STAT1 and Survivin antisense oligonucleotides (ASONs) were used to knock down the expression in SGC7901 cells. The protein expression of STAT1 and Survivin was tested by immunocytochemical and image analysis methods. A gastric cancer tissue microarray was prepared and tested by immunohistochemical methods. Data were analyzed by the Spearman's rank correlation analysis, the χ(2) test and Cox's multivariate regression analysis. Upon knockdown of IFN-γ, STAT1 and Survivin expression by ASON in the SGC7901 cell line, an antagonistic effect was observed between STAT1 and Survivin. In gastric cancer tissues, STAT1 showed a negative correlation with depth of invasion (p<0.05) in gastric cancer tissues exhibiting a negative Survivin protein expression. Furthermore, in tissues exhibiting a negative STAT1 protein expression, Survivin correlated negatively with N stage (p<0.05). Pathological and molecular markers were used to conduct Cox's multivariate regression analysis, and depth of invasion and N stage were found to be prognostic factors (p<0.05). On the other hand, in tissues exhibiting a negative Survivin protein expression, Cox's multivariate regression analysis revealed that the differentiation type and STAT1 protein expression were prognostic factors (p<0.05). There is an antagonistic effect between STAT1 and Survivin in gastric cancer, and this antagonistic effect is of clinical significance in gastric cancer.

Sodium Valproate, a Histone Deacetylase Inhibitor, Is Associated With Reduced Stroke Risk After Previous Ischemic Stroke or Transient Ischemic Attack

PubMed Central

Brookes, Rebecca L.; Crichton, Siobhan; Wolfe, Charles D.A.; Yi, Qilong; Li, Linxin; Hankey, Graeme J.; Rothwell, Peter M.

2018-01-01

Background and Purpose— A variant in the histone deacetylase 9 (HDAC9) gene is associated with large artery stroke. Therefore, inhibiting HDAC9 might offer a novel secondary preventative treatment for ischemic stroke. The antiepileptic drug sodium valproate (SVA) is a nonspecific inhibitor of HDAC9. We tested whether SVA therapy given after ischemic stroke was associated with reduced recurrent stroke rate. Methods— Data were pooled from 3 prospective studies recruiting patients with previous stroke or transient ischemic attack and long-term follow-up: the South London Stroke Register, The Vitamins to Prevent Stroke Study, and the Oxford Vascular Study. Patients receiving SVA were compared with patients who received antiepileptic drugs other than SVA using survival analysis and Cox Regression. Results— A total of 11 949 patients with confirmed ischemic event were included. Recurrent stroke rate was lower in patient taking SVA (17 of 168) than other antiepileptic drugs (105 of 530; log-rank survival analysis P=0.002). On Cox regression, controlling for potential cofounders, SVA remained associated with reduced stroke (hazard ratio=0.44; 95% confidence interval: 0.3–0.7; P=0.002). A similar result was obtained when patients taking SVA were compared with all cases not taking SVA (Cox regression, hazard ratio=0.47; 95% confidence interval: 0.29–0.77; P=0.003). Conclusions— These results suggest that exposure to SVA, an inhibitor of HDAC, may be associated with a lower recurrent stroke risk although we cannot exclude residual confounding in this study design. This supports the hypothesis that HDAC9 is important in the ischemic stroke pathogenesis and that its inhibition, by SVA or a more specific HDAC9 inhibitor, is worthy of evaluation as a treatment to prevent recurrent ischemic stroke. PMID:29247141

Birth by Caesarean Section and the Risk of Adult Psychosis: A Population-Based Cohort Study.

PubMed

O'Neill, Sinéad M; Curran, Eileen A; Dalman, Christina; Kenny, Louise C; Kearney, Patricia M; Clarke, Gerard; Cryan, John F; Dinan, Timothy G; Khashan, Ali S

2016-05-01

Despite the biological plausibility of an association between obstetric mode of delivery and psychosis in later life, studies to date have been inconclusive. We assessed the association between mode of delivery and later onset of psychosis in the offspring. A population-based cohort including data from the Swedish National Registers was used. All singleton live births between 1982 and 1995 were identified (n= 1,345,210) and followed-up to diagnosis at age 16 or later. Mode of delivery was categorized as: unassisted vaginal delivery (VD), assisted VD, elective Caesarean section (CS) (before onset of labor), and emergency CS (after onset of labor). Outcomes included any psychosis; nonaffective psychoses (including schizophrenia only) and affective psychoses (including bipolar disorder only and depression with psychosis only). Cox regression analysis was used reporting partially and fully adjusted hazard ratios (HR) with 95% confidence intervals (CI). Sibling-matched Cox regression was performed to adjust for familial confounding factors. In the fully adjusted analyses, elective CS was significantly associated with any psychosis (HR 1.13, 95% CI 1.03, 1.24). Similar findings were found for nonaffective psychoses (HR 1.13, 95% CI 0.99, 1.29) and affective psychoses (HR 1.17, 95% CI 1.05, 1.31) (χ(2)for heterogeneityP= .69). In the sibling-matched Cox regression, this association disappeared (HR 1.03, 95% CI 0.78, 1.37). No association was found between assisted VD or emergency CS and psychosis. This study found that elective CS is associated with an increase in offspring psychosis. However, the association did not persist in the sibling-matched analysis, implying the association is likely due to familial confounding by unmeasured factors such as genetics or environment. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

PubMed

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach

PubMed Central

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Introduction Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. Aim The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Methods Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate – adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Results Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. Conclusion To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research. PMID:26080057

Applying Additive Hazards Models for Analyzing Survival in Patients with Colorectal Cancer in Fars Province, Southern Iran

PubMed

Madadizadeh, Farzan; Ghanbarnejad, Amin; Ghavami, Vahid; Zare Bandamiri, Mohammad; Mohammadianpanah, Mohammad

2017-04-01

Introduction: Colorectal cancer (CRC) is a commonly fatal cancer that ranks as third worldwide and third and the fifth in Iranian women and men, respectively. There are several methods for analyzing time to event data. Additive hazards regression models take priority over the popular Cox proportional hazards model if the absolute hazard (risk) change instead of hazard ratio is of primary concern, or a proportionality assumption is not made. Methods: This study used data gathered from medical records of 561 colorectal cancer patients who were admitted to Namazi Hospital, Shiraz, Iran, during 2005 to 2010 and followed until December 2015. The nonparametric Aalen’s additive hazards model, semiparametric Lin and Ying’s additive hazards model and Cox proportional hazards model were applied for data analysis. The proportionality assumption for the Cox model was evaluated with a test based on the Schoenfeld residuals and for test goodness of fit in additive models, Cox-Snell residual plots were used. Analyses were performed with SAS 9.2 and R3.2 software. Results: The median follow-up time was 49 months. The five-year survival rate and the mean survival time after cancer diagnosis were 59.6% and 68.1±1.4 months, respectively. Multivariate analyses using Lin and Ying’s additive model and the Cox proportional model indicated that the age of diagnosis, site of tumor, stage, and proportion of positive lymph nodes, lymphovascular invasion and type of treatment were factors affecting survival of the CRC patients. Conclusion: Additive models are suitable alternatives to the Cox proportionality model if there is interest in evaluation of absolute hazard change, or no proportionality assumption is made. Creative Commons Attribution License

Utilization of nonsteroidal anti-inflammatory drugs and antisecretory agents: a managed care claims analysis.

PubMed

Ofman, Joshua J; Badamgarav, Enkhe; Henning, James M; Knight, Kevin; Laine, Loren

2004-06-15

To describe patients initiating nonsteroidal anti-inflammatory drug (NSAID) therapy with regard to gastrointestinal and cardiac risks and patterns of antisecretory agent use, and to explore the relation between therapy type and subsequent outcomes. We studied patients aged 18 years or older who had continuous coverage from 1998 to 2001 and who had initiated treatment with cyclooxygenase-2 (COX-2) selective inhibitors or nonselective NSAIDs. Patients were categorized with respect to gastrointestinal and cardiac risk profiles. Proton pump inhibitor use within 15 days of initiating NSAID therapy was considered prophylactic. Logistic regression analysis was used to evaluate associations between treatment and hospitalization events, cardiac events, and health care costs. We identified 106,564 eligible NSAID initiators: 65.2% used COX-2 inhibitors and 34.8% used traditional NSAIDs. Users of COX-2 inhibitors were more likely to be at higher risk of gastrointestinal bleeding and cardiac events than were NSAID users. Proton pump inhibitor prophylaxis was most common among users of COX-2 inhibitors, but was only 11% in patients at high risk of gastrointestinal bleeding. There were no differences among treatment groups in terms of gastrointestinal or cardiac events. Initiation of COX-2 inhibitor therapy was associated with greater total health care costs. Although we found that COX-2 inhibitors were used more frequently than were traditional NSAIDs in certain groups of patients with varying cardiac or gastrointestinal risk, we did not find that their use resulted in reductions in clinical events, cotherapy with proton pump inhibitors, or costs, suggesting that a better understanding of the relation between NSAID treatment strategies and outcomes in patients with differing risk characteristics is needed.

Caries risk assessment in schoolchildren - a form based on Cariogram® software

PubMed Central

CABRAL, Renata Nunes; HILGERT, Leandro Augusto; FABER, Jorge; LEAL, Soraya Coelho

2014-01-01

Identifying caries risk factors is an important measure which contributes to best understanding of the cariogenic profile of the patient. The Cariogram® software provides this analysis, and protocols simplifying the method were suggested. Objectives The aim of this study was to determine whether a newly developed Caries Risk Assessment (CRA) form based on the Cariogram® software could classify schoolchildren according to their caries risk and to evaluate relationships between caries risk and the variables in the form. Material and Methods 150 schoolchildren aged 5 to 7 years old were included in this survey. Caries prevalence was obtained according to International Caries Detection and Assessment System (ICDAS) II. Information for filling in the form based on Cariogram® was collected clinically and from questionnaires sent to parents. Linear regression and a forward stepwise multiple regression model were applied to correlate the variables included in the form with the caries risk. Results Caries prevalence, in primary dentition, including enamel and dentine carious lesions was 98.6%, and 77.3% when only dentine lesions were considered. Eighty-six percent of the children were classified as at moderate caries risk. The forward stepwise multiple regression model result was significant (R2=0.904; p<0.00001), showing that the most significant factors influencing caries risk were caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources. Conclusion The use of the form based on the Cariogram® software enabled classification of the schoolchildren at low, moderate and high caries risk. Caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources are the variables that were shown to be highly correlated with caries risk. PMID:25466473

Urinary Incontinence of Women in a Nationwide Study in Sri Lanka: Prevalence and Risk Factors.

PubMed

Pathiraja, Ramya; Prathapan, Shamini; Goonawardena, Sampatha

2017-05-23

Urinary incontinence, be stress incontinence or urge incontinence or a mixed type incontinence affects women of all ages. The aim of this study was to describe the prevalence and risk factors of urinary incontinence in Sri Lanka. A community based cross-sectional study was performed in Sri Lanka. The age group of the women in Sri Lanka was categorized into 3 age groups: Less than or equal to 35 years, 36 to 50 years of age and more than or equal to 51 years of age. A sample size of 675 women was obtained from each age category obtaining a total sample of 2025 from Sri Lanka. An interviewer-administered questionnaire consisting of two parts; Socio demographic factors, Medical and Obstetric History, and the King's Health Questionnaire (KHQ), was used for data collection. Stepwise logistic regression analysis was performed. The Prevalence of women with only stress incontinence was 10%, with urge incontinence was 15.6% and with stress and urge incontinence was 29.9%. Stepwise logistic regression analysis showed that the age groups of 36 - 50 years (OR = 2.03; 95% CI = 1.56 - 2.63) and 51 years and above (OR = 2.61; 95% CI= 1.95 - 3.48), Living in one of the districts in Sri Lanka (OR = 4.58; 95% CI = 3.35 - 6.27) and having given birth to multiple children (OR = 1.1; 95% CI = 1.02 - 1.21), diabetes mellitus (OR = 1.97; 95% CI = 1.19 - 3.23), and respiratory diseases (OR = 2.17; 95% CI = 1.48 - 3.19 ) showed a significant risk in the regression analysis. The risk factor, mostly modifiable, if prevented early, could help to reduce the symptoms of urinary incontinence.

Socio-economic factors associated with infant mortality in Italy: an ecological study.

PubMed

Dallolio, Laura; Di Gregori, Valentina; Lenzi, Jacopo; Franchino, Giuseppe; Calugi, Simona; Domenighetti, Gianfranco; Fantini, Maria Pia

2012-08-16

One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Associations between infant mortality rates in the 20 Italian regions (2006-2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15-64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = -0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = -0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels.

Evidence-based identification of key beliefs explaining adult male circumcision motivation in Zimbabwe: targets for behavior change messaging.

PubMed

Montaño, Daniel E; Kasprzyk, Danuta; Hamilton, Deven T; Tshimanga, Mufuta; Gorn, Gerald

2014-05-01

Male circumcision (MC) reduces HIV acquisition among men, leading WHO/UNAIDS to recommend a goal to circumcise 80 % of men in high HIV prevalence countries. Significant investment to increase MC capacity in priority countries was made, yet only 5 % of the goal has been achieved in Zimbabwe. The integrated behavioral model (IBM) was used as a framework to investigate the factors affecting MC motivation among men in Zimbabwe. A survey instrument was designed based on elicitation study results, and administered to a representative household-based sample of 1,201 men aged 18-30 from two urban and two rural areas in Zimbabwe. Multiple regression analysis found all five IBM constructs significantly explained MC Intention. Nearly all beliefs underlying the IBM constructs were significantly correlated with MC Intention. Stepwise regression analysis of beliefs underlying each construct respectively found that 13 behavioral beliefs, 5 normative beliefs, 4 descriptive norm beliefs, 6 efficacy beliefs, and 10 control beliefs were significant in explaining MC Intention. A final stepwise regression of the five sets of significant IBM construct beliefs identified 14 key beliefs that best explain Intention. Similar analyses were carried out with subgroups of men by urban-rural and age. Different sets of behavioral, normative, efficacy, and control beliefs were significant for each sub-group, suggesting communication messages need to be targeted to be most effective for sub-groups. Implications for the design of effective MC demand creation messages are discussed. This study demonstrates the application of theory-driven research to identify evidence-based targets for intervention messages to increase men's motivation to get circumcised and thereby improve demand for male circumcision.

Factors Associated With Work Ability in Patients Undergoing Surgery for Cervical Radiculopathy.

PubMed

Ng, Eunice; Johnston, Venerina; Wibault, Johanna; Löfgren, Håkan; Dedering, Åsa; Öberg, Birgitta; Zsigmond, Peter; Peolsson, Anneli

2015-08-15

Cross-sectional study. To investigate the factors associated with work ability in patients undergoing surgery for cervical radiculopathy. Surgery is a common treatment of cervical radiculopathy in people of working age. However, few studies have investigated the impact on the work ability of these patients. Patients undergoing surgery for cervical radiculopathy (n = 201) were recruited from spine centers in Sweden to complete a battery of questionnaires and physical measures the day before surgery. The associations between various individual, psychological, and work-related factors and self-reported work ability were investigated by Spearman rank correlation coefficient, multivariate linear regression, and forward stepwise regression analyses. Factors that were significant (P < 0.05) in each statistical analysis were entered into the successive analysis to reveal the factors most related to work ability. Work ability was assessed using the Work Ability Index. The mean Work Ability Index score was 28 (SD, 9.0). The forward stepwise regression analysis revealed 6 factors significantly associated with work ability, which explained 62% of the variance in the Work Ability Index. Factors highly correlated with greater work ability included greater self-efficacy in performing self-cares, lower physical load on the neck at work, greater self-reported chance of being able to work in 6 months' time, greater use of active coping strategies, lower frequency of hand weakness, and higher health-related quality of life. Psychological, work-related and individual factors were significantly associated with work ability in patients undergoing surgery for cervical radiculopathy. High self-efficacy was most associated with greater work ability. Consideration of these factors by surgeons preoperatively may provide optimal return to work outcomes after surgery. 3.

Evaluation of job satisfaction and working atmosphere of dental nurses in Germany.

PubMed

Goetz, Katja; Hasse, Philipp; Campbell, Stephen M; Berger, Sarah; Dörfer, Christof E; Hahn, Karolin; Szecsenyi, Joachim

2016-02-01

The purpose of the study was to assess the level of job satisfaction of dental nurses in ambulatory care and to explore the impact of aspects of working atmosphere on and their association with job satisfaction. This cross-sectional study was based on a job satisfaction survey. Data were collected from 612 dental nurses working in 106 dental care practices. Job satisfaction was measured with the 10-item Warr-Cook-Wall job satisfaction scale. Working atmosphere was measured with five items. Linear regression analyses were performed in which each item of the job satisfaction scale was handled as dependent variables. A stepwise linear regression analysis was performed with overall job satisfaction and the five items of working atmosphere, job satisfaction, and individual characteristics. The response rate was 88.3%. Dental nurses were satisfied with 'colleagues' and least satisfied with 'income.' Different aspects of job satisfaction were mostly associated with the following working atmosphere issues: 'responsibilities within the practice team are clear,' 'suggestions for improvement are taken seriously,' 'working atmosphere in the practice team is good,' and 'made easier to admit own mistakes.' Within the stepwise linear regression analysis, the aspect 'physical working condition' (β = 0.304) showed the highest association with overall job satisfaction. The total explained variance of the 14 associated variables was 0.722 with overall job satisfaction. Working atmosphere within this discrete sample of dental care practice seemed to be an important influence on reported working condition and job satisfaction for dental nurses. Because of the high association of job satisfaction with physical working condition, the importance of paying more attention to an ergonomic working position for dental nurses to ensure optimal quality of care is highlighted. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Factors affecting match performance in professional Australian football.

PubMed

Sullivan, Courtney; Bilsborough, Johann C; Cianciosi, Michael; Hocking, Joel; Cordy, Justin T; Coutts, Aaron J

2014-05-01

To determine the physical activity measures and skill-performance characteristics that contribute to coaches' perception of performance and player performance rank in professional Australian Football (AF). Prospective, longitudinal. Physical activity profiles were assessed via microtechnology (GPS and accelerometer) from 40 professional AF players from the same team during 15 Australian Football League games. Skill-performance measure and player-rank scores (Champion Data Rank) were provided by a commercial statistical provider. The physical-performance variables, skill involvements, and individual player performance scores were expressed relative to playing time for each quarter. A stepwise multiple regression was used to examine the contribution of physical activity and skill involvements to coaches' perception of performance and player rank in AF. Stepwise multiple-regression analysis revealed that 42.2% of the variance in coaches' perception of a player's performance could be explained by the skill-performance characteristics (player rank/min, effective kicks/min, pressure points/min, handballs/min, and running bounces/ min), with a small contribution from physical activity measures (accelerations/min) (adjusted R2 = .422, F6,282 = 36.054, P < .001). Multiple regression also revealed that 66.4% of the adjusted variance in player rank could be explained by total disposals/min, effective kicks/min, pressure points/min, kick clangers/min, marks/min, speed (m/min), and peak speed (adjusted R2 = .664, F7,281 = 82.289, P < .001). Increased physical activity throughout a match (speed [m/min] β - 0.097 and peak speed β - 0.116) negatively affects player rank in AF. Skill performance rather than increased physical activity is more important to coaches' perception of performance and player rank in professional AF.

Seminal Plasma HIV-1 RNA Concentration Is Strongly Associated with Altered Levels of Seminal Plasma Interferon-γ, Interleukin-17, and Interleukin-5

PubMed Central

Hoffman, Jennifer C.; Anton, Peter A.; Baldwin, Gayle Cocita; Elliott, Julie; Anisman-Posner, Deborah; Tanner, Karen; Grogan, Tristan; Elashoff, David; Sugar, Catherine; Yang, Otto O.

2014-01-01

Abstract Seminal plasma HIV-1 RNA level is an important determinant of the risk of HIV-1 sexual transmission. We investigated potential associations between seminal plasma cytokine levels and viral concentration in the seminal plasma of HIV-1-infected men. This was a prospective, observational study of paired blood and semen samples from 18 HIV-1 chronically infected men off antiretroviral therapy. HIV-1 RNA levels and cytokine levels in seminal plasma and blood plasma were measured and analyzed using simple linear regressions to screen for associations between cytokines and seminal plasma HIV-1 levels. Forward stepwise regression was performed to construct the final multivariate model. The median HIV-1 RNA concentrations were 4.42 log10 copies/ml (IQR 2.98, 4.70) and 2.96 log10 copies/ml (IQR 2, 4.18) in blood and seminal plasma, respectively. In stepwise multivariate linear regression analysis, blood HIV-1 RNA level (p<0.0001) was most strongly associated with seminal plasma HIV-1 RNA level. After controlling for blood HIV-1 RNA level, seminal plasma HIV-1 RNA level was positively associated with interferon (IFN)-γ (p=0.03) and interleukin (IL)-17 (p=0.03) and negatively associated with IL-5 (p=0.0007) in seminal plasma. In addition to blood HIV-1 RNA level, cytokine profiles in the male genital tract are associated with HIV-1 RNA levels in semen. The Th1 and Th17 cytokines IFN-γ and IL-17 are associated with increased seminal plasma HIV-1 RNA, while the Th2 cytokine IL-5 is associated with decreased seminal plasma HIV-1 RNA. These results support the importance of genital tract immunomodulation in HIV-1 transmission. PMID:25209674

Application of LANDSAT to the surveillance and control of lake eutrophication in the Great Lakes basin. [Saginaw Bay, Michigan and Wisconsin

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Computer techniques were developed for mapping water quality parameters from LANDSAT data, using surface samples collected in an ongoing survey of water quality in Saginaw Bay. Chemical and biological parameters were measured on 31 July 1975 at 16 bay stations in concert with the LANDSAT overflight. Application of stepwise linear regression bands to nine of these parameters and corresponding LANDSAT measurements for bands 4 and 5 only resulted in regression correlation coefficients that varied from 0.94 for temperature to 0.73 for Secchi depth. Regression equations expressed with the pair of bands 4 and 5, rather than the ratio band 4/band 5, provided higher correlation coefficients for all the water quality parameters studied (temperature, Secchi depth, chloride, conductivity, total kjeldahl nitrogen, total phosphorus, chlorophyll a, total solids, and suspended solids).

WebDISCO: a web service for distributed cox model learning without patient-level data sharing.

PubMed

Lu, Chia-Lun; Wang, Shuang; Ji, Zhanglong; Wu, Yuan; Xiong, Li; Jiang, Xiaoqian; Ohno-Machado, Lucila

2015-11-01

The Cox proportional hazards model is a widely used method for analyzing survival data. To achieve sufficient statistical power in a survival analysis, it usually requires a large amount of data. Data sharing across institutions could be a potential workaround for providing this added power. The authors develop a web service for distributed Cox model learning (WebDISCO), which focuses on the proof-of-concept and algorithm development for federated survival analysis. The sensitive patient-level data can be processed locally and only the less-sensitive intermediate statistics are exchanged to build a global Cox model. Mathematical derivation shows that the proposed distributed algorithm is identical to the centralized Cox model. The authors evaluated the proposed framework at the University of California, San Diego (UCSD), Emory, and Duke. The experimental results show that both distributed and centralized models result in near-identical model coefficients with differences in the range [Formula: see text] to [Formula: see text]. The results confirm the mathematical derivation and show that the implementation of the distributed model can achieve the same results as the centralized implementation. The proposed method serves as a proof of concept, in which a publicly available dataset was used to evaluate the performance. The authors do not intend to suggest that this method can resolve policy and engineering issues related to the federated use of institutional data, but they should serve as evidence of the technical feasibility of the proposed approach.Conclusions WebDISCO (Web-based Distributed Cox Regression Model; https://webdisco.ucsd-dbmi.org:8443/cox/) provides a proof-of-concept web service that implements a distributed algorithm to conduct distributed survival analysis without sharing patient level data. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Regression of experimentally induced endometriosis with a new selective cyclooxygenase-2 enzyme inhibitor.

PubMed

Kilico, Ismail; Kokcu, Arif; Kefeli, Mehmet; Kandemir, Bedri

2014-01-01

Cyclooxygenase-2 (COX-2) levels increase in women with endometriosis. COX-2, via increasing prostaglandin E2, contributes to an increase in vascular endothelial growth factor. In this way, COX-2 may contribute to the progression and continuity of endometriosis. We investigated the effect of dexketoprofen trometamol, a new selective COX-2 enzyme inhibitor, on experimentally induced endometriotic cysts. Experimental endometriotic cysts were created in 60 adult female Wistar albino rats. The rats were randomized to 2 equal groups, a control (group Con) and a dexketoprofen (group Dex) group. Six weeks later, cyst volumes were measured as in vivo (volume 1). Following volume 1 measurement, for 4 weeks group Con received 0.1 ml distilled water; group Dex received 0.375 mg dexketoprofen trometamol/0.1 ml distilled water, intramuscularly, twice a day. At the end of administration, the cyst volumes were remeasured (volume 2), and the cysts totally excised and weighed. Glandular (GT) and stromal tissues (ST) and natural killer (NK) cell contents in the cyst wall were scored. NK cell content and volume 1 were not different between the 2 groups. Volume 2, cyst weight, and GT and ST contents in group Dex were significantly lower than those in group Con. Dexketoprofen trometamol significantly reduced the development of experimentally induced endometriotic cysts both macroscopically and microscopically.

Rutin inhibits B[a]PDE-induced cyclooxygenase-2 expression by targeting EGFR kinase activity.

PubMed

Choi, Seunghwan; Lim, Tae-Gyu; Hwang, Mun Kyung; Kim, Yoon-A; Kim, Jiyoung; Kang, Nam Joo; Jang, Tae Su; Park, Jun-Seong; Yeom, Myeong Hun; Lee, Ki Won

2013-11-15

Rutin is a well-known flavonoid that exists in various natural sources. Accumulative studies have represented the biological effects of rutin, such as anti-oxidative and anti-inflammatory effects. However, the underlying mechanisms of rutin and its direct targets are not understood. We investigated whether rutin reduced B[a]PDE-induced-COX-2 expression. The transactivation of AP-1 and NF-κB were inhibited by rutin. Rutin also attenuated B[a]PDE-induced Raf/MEK/ERK and Akt activation, but had no effect on the phosphorylation of EGFR. An in vitro kinase assay revealed rutin suppressed EGFR kinase activity. We also confirmed direct binding between rutin and EGFR, and found that the binding was regressed by ATP. The EGFR inhibitor also inhibited the B[a]PDE-induced MEK/ERK and Akt signaling pathways and subsequently, suppressed COX-2 expression and promoter activity, in addition to suppressing the transactivation of AP-1 and NF-κB. In EGFR(-/-)mouse embryonic fibroblast cells, B[a]PDE-induced COX-2 expression was also diminished. Collectively, rutin inhibits B[a]PDE-induced COX-2 expression by suppressing the Raf/MEK/ERK and Akt signaling pathways. EGFR appeared to be the direct target of rutin. Copyright © 2013 Elsevier Inc. All rights reserved.

Models to predict emissions of health-damaging pollutants and global warming contributions of residential fuel/stove combinations in China.

PubMed

Edwards, Rufus D; Smith, Kirk R; Zhang, Junfeng; Ma, Yuqing

2003-01-01

Residential energy use in developing countries has traditionally been associated with combustion devices of poor energy efficiency, which have been shown to produce substantial health-damaging pollution, contributing significantly to the global burden of disease, and greenhouse gas (GHG) emissions. Precision of these estimates in China has been hampered by limited data on stove use and fuel consumption in residences. In addition limited information is available on variability of emissions of pollutants from different stove/fuel combinations in typical use, as measurement of emission factors requires measurement of multiple chemical species in complex burn cycle tests. Such measurements are too costly and time consuming for application in conjunction with national surveys. Emissions of most of the major health-damaging pollutants (HDP) and many of the gases that contribute to GHG emissions from cooking stoves are the result of the significant portion of fuel carbon that is diverted to products of incomplete combustion (PIC) as a result of poor combustion efficiencies. The approximately linear increase in emissions of PIC with decreasing combustion efficiencies allows development of linear models to predict emissions of GHG and HDP intrinsically linked to CO2 and PIC production, and ultimately allows the prediction of global warming contributions from residential stove emissions. A comprehensive emissions database of three burn cycles of 23 typical fuel/stove combinations tested in a simulated village house in China has been used to develop models to predict emissions of HDP and global warming commitment (GWC) from cooking stoves in China, that rely on simple survey information on stove and fuel use that may be incorporated into national surveys. Stepwise regression models predicted 66% of the variance in global warming commitment (CO2, CO, CH4, NOx, TNMHC) per 1 MJ delivered energy due to emissions from these stoves if survey information on fuel type was available. Subsequently if stove type is known, stepwise regression models predicted 73% of the variance. Integrated assessment of policies to change stove or fuel type requires that implications for environmental impacts, energy efficiency, global warming and human exposures to HDP emissions can be evaluated. Frequently, this involves measurement of TSP or CO as the major HDPs. Incorporation of this information into models to predict GWC predicted 79% and 78% of the variance respectively. Clearly, however, the complexity of making multiple measurements in conjunction with a national survey would be both expensive and time consuming. Thus, models to predict HDP using simple survey information, and with measurement of either CO/CO2 or TSP/CO2 to predict emission factors for the other HDP have been derived. Stepwise regression models predicted 65% of the variance in emissions of total suspended particulate as grams of carbon (TSPC) per 1 MJ delivered if survey information on fuel and stove type was available and 74% if the CO/CO2 ratio was measured. Similarly stepwise regression models predicted 76% of the variance in COC emissions per MJ delivered with survey information on stove and fuel type and 85% if the TSPC/CO2 ratio was measured. Ultimately, with international agreements on emissions trading frameworks, similar models based on extensive databases of the fate of fuel carbon during combustion from representative household stoves would provide a mechanism for computing greenhouse credits in the residential sector as part of clean development mechanism frameworks and monitoring compliance to control regimes.

Depression and incident dementia. An 8-year population-based prospective study.

PubMed

Luppa, Melanie; Luck, Tobias; Ritschel, Franziska; Angermeyer, Matthias C; Villringer, Arno; Riedel-Heller, Steffi G

2013-01-01

The aim of the study was to investigate the impact of depression (categorical diagnosis; major depression, MD) and depressive symptoms (dimensional diagnosis and symptom patterns) on incident dementia in the German general population. Within the Leipzig Longitudinal Study of the Aged (LEILA 75+), a representative sample of 1,265 individuals aged 75 years and older were interviewed every 1.5 years over 8 years (mean observation time 4.3 years; mean number of visits 4.2). Cox proportional hazards and binary logistic regressions were used to estimate the effect of baseline depression and depressive symptoms on incident dementia. The incidence of dementia was 48 per 1,000 person-years (95% confidence interval (CI) 45-51). Depressive symptoms (Hazard ratio HR 1.03, 95% CI 1.01-1.05), and in particular mood-related symptoms (HR 1.08, 95% CI 1.03-1.14), showed a significant impact on the incidence of dementia only in univariate analysis, but not after adjustment for cognitive and functional impairment. MD showed only a significant impact on incidence of dementia in Cox proportional hazards regression, but not in binary logistic regression models. The present study using different diagnostic measures of depression on future dementia found no clear significant associations of depression and incident dementia. Further in-depth investigation would help to understand the nature of depression in the context of incident dementia.

Impact of Pacemaker Lead Characteristics on Pacemaker Related Infection and Heart Perforation: A Nationwide Population-Based Cohort Study.

PubMed

Lin, Yu-Sheng; Chen, Tien-Hsing; Hung, Sheng-Ping; Chen, Dong Yi; Mao, Chun-Tai; Tsai, Ming-Lung; Chang, Shih-Tai; Wang, Chun-Chieh; Wen, Ming-Shien; Chen, Mien-Cheng

2015-01-01

Several risk factors for pacemaker (PM) related complications have been reported. However, no study has investigated the impact of lead characteristics on pacemaker-related complications. Patients who received a new pacemaker implant from January 1997 to December 2011 were selected from the Taiwan National Health Insurance Database. This population was grouped according to the pacemaker lead characteristics in terms of fixation and insulation. The impact of the characteristics of leads on early heart perforation was analyzed by multivariable logistic regression analysis, while the impact of the lead characteristics on early and late infection and late heart perforation over a three-year period were analyzed using Cox regression. This study included 36,104 patients with a mean age of 73.4±12.5 years. In terms of both early and late heart perforations, there were no significant differences between groups across the different types of fixation and insulations. In the multivariable Cox regression analysis, the pacemaker-related infection rate was significantly lower in the active fixation only group compared to either the both fixation (OR, 0.23; 95% CI, 0.07-0.80; P = 0.020) or the passive fixation group (OR, 0.26; 95% CI, 0.08-0.83; P = 0.023). There was no difference in heart perforation between active and passive fixation leads. Active fixation leads were associated with reduced risk of pacemaker-related infection.

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample

PubMed Central

Wang, Ching-Yun; Song, Xiao

2017-01-01

SUMMARY Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women’s Health Initiative. PMID:27546625

Serum Uric Acid Is Associated with Poor Outcome in Black Africans in the Acute Phase of Stroke

PubMed Central

Ayeah, Chia Mark; Ba, H.; Mbahe, Salomon

2017-01-01

Background Prognostic significance of serum uric acid (SUA) in acute stroke still remains controversial. Objectives To determine the prevalence of hyperuricemia and its association with outcome of stroke patients in the Douala General Hospital (DGH). Methods This was a hospital based prospective cohort study which included acute stroke patients with baseline SUA levels and 3-month poststroke follow-up data. Associations between high SUA levels and stroke outcomes were analyzed using multiple logistic regression and survival analysis (Cox regression and Kaplan-Meier). Results A total of 701 acute stroke patients were included and the prevalence of hyperuricemia was 46.6% with a mean SUA level of 68.625 ± 24 mg/l. Elevated SUA after stroke was associated with death (OR = 2.067; 95% CI: 1.449–2.950; p < 0.001) but did not predict this issue. However, an independent association between increasing SUA concentration and mortality was noted in a Cox proportional hazards regression model (adjusted HR = 1.740; 95% CI: 1.305–2.320; p < 0.001). Furthermore, hyperuricemia was an independent predictor of poor functional outcome within 3 months after stroke (OR = 2.482; 95% CI: 1.399–4.404; p = 0.002). Conclusion The prevalence of hyperuricemia in black African stroke patients is quite high and still remains a predictor of poor outcome. PMID:29082062

Quality Reporting of Multivariable Regression Models in Observational Studies: Review of a Representative Sample of Articles Published in Biomedical Journals.

PubMed

Real, Jordi; Forné, Carles; Roso-Llorach, Albert; Martínez-Sánchez, Jose M

2016-05-01

Controlling for confounders is a crucial step in analytical observational studies, and multivariable models are widely used as statistical adjustment techniques. However, the validation of the assumptions of the multivariable regression models (MRMs) should be made clear in scientific reporting. The objective of this study is to review the quality of statistical reporting of the most commonly used MRMs (logistic, linear, and Cox regression) that were applied in analytical observational studies published between 2003 and 2014 by journals indexed in MEDLINE.Review of a representative sample of articles indexed in MEDLINE (n = 428) with observational design and use of MRMs (logistic, linear, and Cox regression). We assessed the quality of reporting about: model assumptions and goodness-of-fit, interactions, sensitivity analysis, crude and adjusted effect estimate, and specification of more than 1 adjusted model.The tests of underlying assumptions or goodness-of-fit of the MRMs used were described in 26.2% (95% CI: 22.0-30.3) of the articles and 18.5% (95% CI: 14.8-22.1) reported the interaction analysis. Reporting of all items assessed was higher in articles published in journals with a higher impact factor.A low percentage of articles indexed in MEDLINE that used multivariable techniques provided information demonstrating rigorous application of the model selected as an adjustment method. Given the importance of these methods to the final results and conclusions of observational studies, greater rigor is required in reporting the use of MRMs in the scientific literature.

Modeling the safety impacts of driving hours and rest breaks on truck drivers considering time-dependent covariates.

PubMed

Chen, Chen; Xie, Yuanchang

2014-12-01

Driving hours and rest breaks are closely related to driver fatigue, which is a major contributor to truck crashes. This study investigates the effects of driving hours and rest breaks on commercial truck driver safety. A discrete-time logistic regression model is used to evaluate the crash odds ratios of driving hours and rest breaks. Driving time is divided into 11 one hour intervals. These intervals and rest breaks are modeled as dummy variables. In addition, a Cox proportional hazards regression model with time-dependent covariates is used to assess the transient effects of rest breaks, which consists of a fixed effect and a variable effect. Data collected from two national truckload carriers in 2009 and 2010 are used. The discrete-time logistic regression result indicates that only the crash odds ratio of the 11th driving hour is statistically significant. Taking one, two, and three rest breaks can reduce drivers' crash odds by 68%, 83%, and 85%, respectively, compared to drivers who did not take any rest breaks. The Cox regression result shows clear transient effects for rest breaks. It also suggests that drivers may need some time to adjust themselves to normal driving tasks after a rest break. Overall, the third rest break's safety benefit is very limited based on the results of both models. The findings of this research can help policy makers better understand the impact of driving time and rest breaks and develop more effective rules to improve commercial truck safety. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.

Are low wages risk factors for hypertension?

PubMed Central

Du, Juan

2012-01-01

Objective: Socio-economic status (SES) is strongly correlated with hypertension. But SES has several components, including income and correlations in cross-sectional data need not imply SES is a risk factor. This study investigates whether wages—the largest category within income—are risk factors. Methods: We analysed longitudinal, nationally representative US data from four waves (1999, 2001, 2003 and 2005) of the Panel Study of Income Dynamics. The overall sample was restricted to employed persons age 25–65 years, n = 17 295. Separate subsamples were constructed of persons within two age groups (25–44 and 45–65 years) and genders. Hypertension incidence was self-reported based on physician diagnosis. Our study was prospective since data from three base years (1999, 2001, 2003) were used to predict newly diagnosed hypertension for three subsequent years (2001, 2003, 2005). In separate analyses, data from the first base year were used to predict time-to-reporting hypertension. Logistic regressions with random effects and Cox proportional hazards regressions were run. Results: Negative and strongly statistically significant correlations between wages and hypertension were found both in logistic and Cox regressions, especially for subsamples containing the younger age group (25–44 years) and women. Correlations were stronger when three health variables—obesity, subjective measures of health and number of co-morbidities—were excluded from regressions. Doubling the wage was associated with 25–30% lower chances of hypertension for persons aged 25–44 years. Conclusions: The strongest evidence for low wages being risk factors for hypertension among working people were for women and persons aged 25–44 years. PMID:22262559

Are low wages risk factors for hypertension?

PubMed

Leigh, J Paul; Du, Juan

2012-12-01

Socio-economic status (SES) is strongly correlated with hypertension. But SES has several components, including income and correlations in cross-sectional data need not imply SES is a risk factor. This study investigates whether wages-the largest category within income-are risk factors. We analysed longitudinal, nationally representative US data from four waves (1999, 2001, 2003 and 2005) of the Panel Study of Income Dynamics. The overall sample was restricted to employed persons age 25-65 years, n = 17 295. Separate subsamples were constructed of persons within two age groups (25-44 and 45-65 years) and genders. Hypertension incidence was self-reported based on physician diagnosis. Our study was prospective since data from three base years (1999, 2001, 2003) were used to predict newly diagnosed hypertension for three subsequent years (2001, 2003, 2005). In separate analyses, data from the first base year were used to predict time-to-reporting hypertension. Logistic regressions with random effects and Cox proportional hazards regressions were run. Negative and strongly statistically significant correlations between wages and hypertension were found both in logistic and Cox regressions, especially for subsamples containing the younger age group (25-44 years) and women. Correlations were stronger when three health variables-obesity, subjective measures of health and number of co-morbidities-were excluded from regressions. Doubling the wage was associated with 25-30% lower chances of hypertension for persons aged 25-44 years. The strongest evidence for low wages being risk factors for hypertension among working people were for women and persons aged 25-44 years.

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

PubMed

Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

2016-01-01

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation. Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models.

Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method

PubMed Central

Zhang, Tingting; Kou, S. C.

2010-01-01

Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure. PMID:21258615

Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method.

PubMed

Zhang, Tingting; Kou, S C

2010-01-01

Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure.

Predictors of survival among hemodialysis patients: effect of perceived family support.

PubMed

Christensen, A J; Wiebe, J S; Smith, T W; Turner, C W

1994-11-01

The authors examined the role of perceived family support and symptoms of depression as predictors of survival in a sample of 78 in-center hemodialysis patients. Cox regression analysis revealed significant effects for family support (p < .005), blood urea nitrogen (p < .01), and age (p < .005). The effect for depression was not significant. The Cox model indicated that a 1-point increase on the family support measure was associated with a 13% reduction in the hazard rate (i.e., mortality). Estimated 5-year mortality rates among low family support patients were approximately 3 times higher than estimated mortality for high support patients. Differences in patient adherence to the dietary and medication regimens failed to explain the significant effect of family support.

Econometric models of road use, accidents, and road investment decisions. Volume 2 : an econometric model of car ownership, road use, accidents, and their severity (Essay 3)

DOT National Transportation Integrated Search

1999-11-01

Using a fairly large cross-section/time-series data base, covering all provinces of Norway and all months between January 1973 and December 1994, we estimate non-linear (Box-Cox) regression equations explaining aggregate car ownership, road use, seat...

Improving Your Data Transformations: Applying the Box-Cox Transformation

ERIC Educational Resources Information Center

Osborne, Jason W.

2010-01-01

Many of us in the social sciences deal with data that do not conform to assumptions of normality and/or homoscedasticity/homogeneity of variance. Some research has shown that parametric tests (e.g., multiple regression, ANOVA) can be robust to modest violations of these assumptions. Yet the reality is that almost all analyses (even nonparametric…

The Transfer Velocity Project: A Comprehensive Look at the Transfer Function

ERIC Educational Resources Information Center

Hayward, Craig

2011-01-01

The 1999-2000 Transfer Velocity Project (TVP) cohort of 147,207 community college students is used to develop both a college-level endogenous model, appropriate for applied research and guidance for campus action, and a student-level model. Survival analysis (Cox regression) is employed to evaluate the relative contribution of 53 student-level…

Faster Remission of Chronic Depression with Combined Psychotherapy and Medication than with Each Therapy Alone

ERIC Educational Resources Information Center

Manber, Rachel; Kraemer, Helena C.; Arnow, Bruce A.; Trivedi, Madhukar H.; Rush, A. John; Thase, Michael E.; Rothbaum, Barbara O.; Klein, Daniel N.; Kocsis, James H.; Gelenberg, Alan J.; Keller, Martin E.

2008-01-01

The main aim of the present novel reanalysis of archival data was to compare the time to remission during 12 weeks of treatment of chronic depression following antidepressant medication (n = 218), psychotherapy (n = 216), and their combination (n = 222). Cox regression survival analyses revealed that the combination of medication and psychotherapy…

Dual oxidase 1: A predictive tool for the prognosis of hepatocellular carcinoma patients.

PubMed

Chen, Shengsen; Ling, Qingxia; Yu, Kangkang; Huang, Chong; Li, Ning; Zheng, Jianming; Bao, Suxia; Cheng, Qi; Zhu, Mengqi; Chen, Mingquan

2016-06-01

Dual oxidase 1 (DUOX1), which is the main source of reactive oxygen species (ROS) production in the airway, can be silenced in human lung cancer and hepatocellular carcinomas. However, the prognostic value of DUOX1 expression in hepatocellular carcinoma patients is still unclear. We investigated the prognostic value of DUOX1 expression in liver cancer patients. DUOX1 mRNA expression was determined in tumor tissues and non-tumor tissues by real‑time PCR. For evaluation of the prognostic value of DUOX1 expression, Kaplan-Meier method and Cox's proportional hazards model (univariate analysis and multivariate analysis) were employed. A simple risk score was devised by using significant variables obtained from the Cox's regression analysis to further predict the HCC patient prognosis. We observed a reduced DUOX1 mRNA level in the cancer tissues in comparison to the non‑cancer tissues. More importantly, Kaplan-Meier analysis showed that patients with high DUOX1 expression had longer disease-free survival and overall survival compared with those with low expression of DUOX1. Cox's regression analysis indicated that DUOX1 expression, age, and intrahepatic metastasis may be significant prognostic factors for disease-free survival and overall survival. Finally, we found that patients with total scores of >2 and >1 were more likely to relapse and succumb to the disease than patients whose total scores were ≤2 and ≤1. In conclusion, DUOX1 expression in liver tumors is a potential prognostic tool for patients. The risk scoring system is useful for predicting the survival of liver cancer patients after tumor resection.

Computer Mapping of Water Quality in Saginaw Bay with LANDSAT Digital Data

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator); Shah, N. J.; Smith, V. E.; Mckeon, J. B.

1976-01-01

The author has identified the following significant results. LANDSAT digital data and ground truth measurements for Saginaw Bay (Lake Huron), Michigan, for 31 July 1975 were correlated by stepwise linear regression and the resulting equations used to estimate invisible water quality parameters in nonsampled areas. Chloride, conductivity, total Kjeldahl nitrogen, total phosphorus, and chlorophyll a were best correlated with the ratio of LANDSAT Band 4 to Band 5. Temperature and Secchi depth correlate best with Band 5.

Analysis of flight data from a High-Incidence Research Model by system identification methods

NASA Technical Reports Server (NTRS)

Batterson, James G.; Klein, Vladislav

1989-01-01

Data partitioning and modified stepwise regression were applied to recorded flight data from a Royal Aerospace Establishment high incidence research model. An aerodynamic model structure and corresponding stability and control derivatives were determined for angles of attack between 18 and 30 deg. Several nonlinearities in angles of attack and sideslip as well as a unique roll-dominated set of lateral modes were found. All flight estimated values were compared to available wind tunnel measurements.

Polymorphism in COX-2 modifies the inverse association between Helicobacter pylori seropositivity and esophageal squamous cell carcinoma risk in Taiwan: a case control study

PubMed Central

2009-01-01

Background Overexpression of Cyclooxygenase-2 (COX-2) was observed in many types of cancers, including esophageal squamous cell carcinoma (ESCC). One functional SNP, COX-2 -1195G/A, has been reported to mediate susceptibility of ESCC in Chinese populations. In our previous study, the presence of Helicobacter pylori (H. pylori) was found to play a protective role in development of ESCC. The interaction of COX-2 and H. pylori in gastric cancer was well investigated. However, literature on their interaction in ESCC risk is scarce. The purpose of this study was to evaluate the association and interaction between COX-2 single nucleotide polymorphism (SNP), H. pylori infection and the risk of developing ESCC. Methods One hundred and eighty patients with ESCC and 194 controls were enrolled in this study. Personal data regarding related risk factors, including alcohol consumption, smoking habits and betel quid chewing, were collected via questionnaire. Genotypes of the COX-2 -1195 polymorphism were determined by PCR-based restriction fragment length polymorphism. H. pylori seropositivity was defined by immunochromatographic screening test. Data was analyzed by chi-squared tests and polytomous logistics regression. Results In analysis adjusting for the covariates and confounders, H. pylori seropositivity was found to be inversely association with the ESCC development (adjusted OR: 0.5, 95% CI: 0.3 – 0.9). COX-2 -1195 AA homozygous was associated with an increased risk of contracting ESCC in comparison with the non-AA group, especially among patients with H. pylori seronegative (adjusted OR ratio: 2.9, 95% CI: 1.2 – 7.3). The effect was strengthened among patients with lower third ESCC (adjusted OR ratio: 6.9, 95% CI 2.1 – 22.5). Besides, H. pylori seropositivity conveyed a notably inverse effect among patients with COX-2 AA polymorphism (AOR ratio: 0.3, 95% CI: 0.1 – 0.9), and the effect was observed to be enhanced for the lower third ESCC patients (AOR ratio: 0.09, 95% CI: 0.02 – 0.47, p for multiplicative interaction 0.008) Conclusion H. pylori seropositivity is inversely associated with the risk of ESCC in Taiwan, and COX-2 -1195 polymorphism plays a role in modifying the influence between H. pylori and ESCC, especially in lower third esophagus. PMID:19463183

Polymorphism in COX-2 modifies the inverse association between Helicobacter pylori seropositivity and esophageal squamous cell carcinoma risk in Taiwan: a case control study.

PubMed

Hu, Huang-Ming; Kuo, Chao-Hung; Lee, Chien-Hung; Wu, I-Chen; Lee, Ka-Wo; Lee, Jang-Ming; Goan, Yih-Gang; Chou, Shah-Hwa; Kao, Ein-Long; Wu, Ming-Tsang; Wu, Deng-Chyang

2009-05-23

Overexpression of Cyclooxygenase-2 (COX-2) was observed in many types of cancers, including esophageal squamous cell carcinoma (ESCC). One functional SNP, COX-2 -1195G/A, has been reported to mediate susceptibility of ESCC in Chinese populations. In our previous study, the presence of Helicobacter pylori (H. pylori) was found to play a protective role in development of ESCC. The interaction of COX-2 and H. pylori in gastric cancer was well investigated. However, literature on their interaction in ESCC risk is scarce. The purpose of this study was to evaluate the association and interaction between COX-2 single nucleotide polymorphism (SNP), H. pylori infection and the risk of developing ESCC. One hundred and eighty patients with ESCC and 194 controls were enrolled in this study. Personal data regarding related risk factors, including alcohol consumption, smoking habits and betel quid chewing, were collected via questionnaire. Genotypes of the COX-2 -1195 polymorphism were determined by PCR-based restriction fragment length polymorphism. H. pylori seropositivity was defined by immunochromatographic screening test. Data was analyzed by chi-squared tests and polytomous logistics regression. In analysis adjusting for the covariates and confounders, H. pylori seropositivity was found to be inversely association with the ESCC development (adjusted OR: 0.5, 95% CI: 0.3 - 0.9). COX-2 -1195 AA homozygous was associated with an increased risk of contracting ESCC in comparison with the non-AA group, especially among patients with H. pylori seronegative (adjusted OR ratio: 2.9, 95% CI: 1.2 - 7.3). The effect was strengthened among patients with lower third ESCC (adjusted OR ratio: 6.9, 95% CI 2.1 - 22.5). Besides, H. pylori seropositivity conveyed a notably inverse effect among patients with COX-2 AA polymorphism (AOR ratio: 0.3, 95% CI: 0.1 - 0.9), and the effect was observed to be enhanced for the lower third ESCC patients (AOR ratio: 0.09, 95% CI: 0.02 - 0.47, p for multiplicative interaction 0.008) H. pylori seropositivity is inversely associated with the risk of ESCC in Taiwan, and COX-2 -1195 polymorphism plays a role in modifying the influence between H. pylori and ESCC, especially in lower third esophagus.

Validation of a heteroscedastic hazards regression model.

PubMed

Wu, Hong-Dar Isaac; Hsieh, Fushing; Chen, Chen-Hsin

2002-03-01

A Cox-type regression model accommodating heteroscedasticity, with a power factor of the baseline cumulative hazard, is investigated for analyzing data with crossing hazards behavior. Since the approach of partial likelihood cannot eliminate the baseline hazard, an overidentified estimating equation (OEE) approach is introduced in the estimation procedure. It by-product, a model checking statistic, is presented to test for the overall adequacy of the heteroscedastic model. Further, under the heteroscedastic model setting, we propose two statistics to test the proportional hazards assumption. Implementation of this model is illustrated in a data analysis of a cancer clinical trial.

Prognostic significance of microvessel density and mast cell density for the survival of Thai patients with primary colorectal cancer.

PubMed

Yodavudh, Sirisanpang; Tangjitgamol, Siriwan; Puangsa-art, Supalarp

2008-05-01

Angiogenesis has been found to be a reliable prognostic indicator for several types of malignancies. In colorectal cancer, however there has been controversy as to whether there is a correlation between this feature and the tumors' behavior. Determine the correlation between microvessel density (MVD) and mast cell density (MCD) in order to evaluate these factors in terms of their prognostic relevance for primary colorectal carcinoma in Thai patients. One hundred and thirty colorectal carcinoma patients diagnosed between January 2002 and December 2004 were identified. Eleven patients were excluded from the present study due to recurrence of colorectal carcinoma in eight cases whereas pathologic blocks were not found in three cases. One hundred and nineteen patients met all inclusion criteria and were included in the present study. Representative paraffin sections obtained by the tissue micro-array technique (9 x 5 arrays per slide) from areas of highest vascular density (hot spots) were prepared. Sections were immuno-stained by monoclonal anti CD 31 for microvessel and antibody mast cell tryptase for mast cell detections, respectively. Three readings at different periods of time under a microscopic examination of high power magnification were examined by a pathologist who was blinded to clinical data. The highest microvessel and mast cell counts were recorded as MVD and MCD. Patients were then divided into groups of high and low MVD and high and low MCD by median values (20.5 and 14.5, respectively). Overall survival of the patients in each group was estimated by the Kaplan-Meier Method while a multivariate Cox regression backward stepwise analysis was employed to find out independent prognostic factors. Significant positive correlation was found to exist between MVD and MCD in the hot spots (R = 0.697, p < 0.0001). Regarding their prognostic role, patients with tumors of low MVD (hypovascular) and low MCD (low mast cell counts) had significantly longer survival rates than those with hypervascular and high mast cell counts (p < 0.0001). The Multivariate Cox hazard showed that MVD and distance metastasis of cancer were independent poor prognostic factors to survival (p = 0.036 and p = 0.024, respectively). The patients with high MVD (hypervascular) tumors and with presence of distant metastasis had 1.9 and 2.5 times higher death rates than the corresponding hypovascular and non-metastatic groups, respectively during the period from January 2002 to September 2007. Assessment of microvessel density in the invasive front of primary colorectal carcinoma could serve as useful prognosis tool of primary colorectal carcinoma in Thai patients.

All-cause mortality of elderly Australian veterans using COX-2 selective or non-selective NSAIDs: a longitudinal study

PubMed Central

Kerr, Stephen J; Rowett, Debra S; Sayer, Geoffrey P; Whicker, Susan D; Saltman, Deborah C; Mant, Andrea

2011-01-01

AIM To determine hazard ratios for all-cause mortality in elderly Australian veterans taking COX-2 selective and non-selective NSAIDs. METHODS Patient cohorts were constructed from claims databases (1997 to 2007) for veterans and dependants with full treatment entitlement irrespective of military service. Patients were grouped by initial exposure: celecoxib, rofecoxib, meloxicam, diclofenac, non-selective NSAID. A reference group was constructed of patients receiving glaucoma/hypothyroid medications and none of the study medications. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated for each exposure group against each of the reference group. The final model was adjusted for age, gender and co-prescription as a surrogate for cardiovascular risk. Patients were censored if the gap in supply of study prescription exceeded 30 days or if another study medication was initiated. The outcome measure in all analyses was death. RESULTS Hazard ratios and 95% CIs, adjusted for age, gender and cardiovascular risk, for each group relative to the reference group were: celecoxib 1.39 (1.25, 1.55), diclofenac 1.44 (1.28, 1.62), meloxicam 1.49 (1.25, 1.78), rofecoxib 1.58 (1.39, 1.79), non-selective NSAIDs 1.76 (1.59, 1.94). CONCLUSIONS In this large cohort of Australian veterans exposed to COX-2 selective and non-selective NSAIDs, there was a significant increased mortality risk for those exposed to either COX-2-selective or non-selective NSAIDs relative to those exposed to unrelated (glaucoma/hypothyroid) medications. PMID:21276041

Prognostic factors in multiple myeloma: selection using Cox's proportional hazard model.

PubMed

Pasqualetti, P; Collacciani, A; Maccarone, C; Casale, R

1996-01-01

The pretreatment characteristics of 210 patients with multiple myeloma, observed between 1980 and 1994, were evaluated as potential prognostic factors for survival. Multivariate analysis according to Cox's proportional hazard model identified in the 160 dead patients with myeloma, among 26 different single prognostic variables, the following factors in order of importance: beta 2-microglobulin; bone marrow plasma cell percentage, hemoglobinemia, degree of lytic bone lesions, serum creatinine, and serum albumin. By analysis of these variables a prognostic index (PI), that considers the regression coefficients derived by Cox's model of all significant factors, was obtained. Using this it was possible to separate the whole patient group into three stages: stage I (PI < 1.485, 67 patients), stage II (PI: 1.485-2.090, 76 patients), and stage III (PI > 2.090, 67 patients), with a median survivals of 68, 36 and 13 months (P < 0.0001), respectively. Also the responses to therapy (P < 0.0001) and the survival curves (P < 0.00001) presented significant differences among the three subgroups. Knowledge of these factors could be of value in predicting prognosis and in planning therapy in patients with multiple myeloma.

Subjective Global Assessment-Dialysis Malnutrition Score and cardiovascular risk in hemodialysis patients: an observational cohort study.

PubMed

Spatola, Leonardo; Finazzi, Silvia; Calvetta, Albania; Reggiani, Francesco; Morenghi, Emanuela; Santostasi, Silvia; Angelini, Claudio; Badalamenti, Salvatore; Mugnai, Giacomo

2018-06-23

Malnutrition is an important risk factor for cardiovascular mortality in hemodialysis (HD) patients. However, current malnutrition biomarkers seem unable to accurately estimate the role of malnutrition in predicting cardiovascular risk. Our aim was to investigate the role of the Subjective Global Assessment-Dialysis Malnutrition Score (SGA-DMS) compared to two well-recognized comorbidity scores-Charlson Comorbidity Index (CCI) and modified CCI (excluding age-factor) (mCCI)-in predicting cardiovascular events in HD patients. In 86 maintenance HD patients followed from June 2015 to June 2017, we analyzed biohumoral data and clinical scores as risk factors for cardiovascular events (acute heart failure, acute coronary syndrome and stroke). Their impact on outcome was investigated by linear regression, Cox regression models and ROC analysis. Cardiovascular events occurred in 26/86 (30%) patients during the 2-year follow-up. Linear regression showed only age and dialysis vintage to be positively related to SGA-DMS: B 0.21 (95% CI 0.01; 0.30) p 0.05, and B 0.24 (0.09; 0.34) p 0.02, respectively, while serum albumin, normalized protein catabolic rate (nPCR) and dialysis dose (Kt/V) were negatively related to SGA-DMS: B - 1.29 (- 3.29; - 0.81) p 0.02; B - 0.08 (- 1.52; - 0.35) p 0.04 and B - 2.63 (- 5.25; - 0.22) p 0.03, respectively. At Cox regression analysis, SGA-DMS was not a risk predictor for cardiovascular events: HR 1.09 (0.9; 1.22), while both CCI and mCCI were significant predictors: HR 1.43 (1.13; 1.87) and HR 1.57 (1.20; 2.06) also in Cox adjusted models. ROC analysis reported similar AUCs for CCI and mCCI: 0.72 (0.60; 0.89) p 0.00 and 0.70 (0.58; 0.82) p 0.00, respectively, compared to SGA-DMS 0.56 (0.49; 0.72) p 0.14. SGA-DMS is not a superior and significant prognostic tool compared to CCI and mCCI in assessing cardiovascular risk in HD patients, even it allows to appraise both malnutrition and comorbidity status.

Cognition and Incident Coronary Heart Disease in Late Midlife: The Whitehall II Study

ERIC Educational Resources Information Center

Singh-Manoux, Archana; Sabia, Severine; Kivimaki, Mika; Shipley, Martin J.; Ferrie, Jane E.; Marmot, Michael G.

2009-01-01

The purpose of this study was to investigate whether cognitive function in midlife predicts incident coronary heart disease (CHD), followed up over 6 years. Data on 5292 (28% women, mean age 55) individuals free from CHD at baseline were drawn from the British Whitehall II study. We used Cox regression to model the association between cognition…

The Role of Inhibitory Control in the Development of Human Figure Drawing in Young Children

ERIC Educational Resources Information Center

Riggs, Kevin J.; Jolley, Richard P.; Simpson, Andrew

2013-01-01

We investigated the role of inhibitory control in young children's human figure drawing. We used the Bear-Dragon task as a measure of inhibitory control and used the classification system devised by Cox and Parkin to measure the development of human figure drawing. We tested 50 children aged between 40 and 64 months. Regression analysis showed…

A Case for Transforming the Criterion of a Predictive Validity Study

ERIC Educational Resources Information Center

Patterson, Brian F.; Kobrin, Jennifer L.

2011-01-01

This study presents a case for applying a transformation (Box and Cox, 1964) of the criterion used in predictive validity studies. The goals of the transformation were to better meet the assumptions of the linear regression model and to reduce the residual variance of fitted (i.e., predicted) values. Using data for the 2008 cohort of first-time,…

The Association of Administrative Segregation Placement and Other Risk Factors with the Self-Injury-Free Time of Male Prisoners

ERIC Educational Resources Information Center

Lanes, Eric

2009-01-01

The current study examined the relationship between risk factors for prisoner self-injurious behavior (SIB) and the amount of time male prisoners function without engaging in SIB (SIB-free time), and obtained estimates of SIB-free time for selected SIB prisoner subgroups dependent on their housing status. Conditional Cox regression analysis…

Development and validation of prognostic models in metastatic breast cancer: a GOCS study.

PubMed

Rabinovich, M; Vallejo, C; Bianco, A; Perez, J; Machiavelli, M; Leone, B; Romero, A; Rodriguez, R; Cuevas, M; Dansky, C

1992-01-01

The significance of several prognostic factors and the magnitude of their influence on response rate and survival were assessed by means of uni- and multivariate analyses in 362 patients with stage IV (UICC) breast carcinoma receiving combination chemotherapy as first systemic treatment over an 8-year period. Univariate analyses identified performance status and prior adjuvant radiotherapy as predictors of objective regression (OR), whereas the performance status, prior chemotherapy and radiotherapy (adjuvants), white blood cells count, SGOT and SGPT levels, and metastatic pattern were significantly correlated to survival. In multivariate analyses favorable characteristics associated to OR were prior adjuvant radiotherapy, no prior chemotherapy and postmenopausal status. Regarding survival, the performance status and visceral involvement were selected by the Cox model. The predictive accuracy of the logistic and the proportional hazards models was retrospectively tested in the training sample, and prospectively in a new population of 126 patients also receiving combined chemotherapy as first treatment for metastatic breast cancer. A certain overfitting to data in the training sample was observed with the regression model for response. However, the discriminative ability of the Cox model for survival was clearly confirmed.

Kawasaki Disease Increases the Incidence of Myopia.

PubMed

Kung, Yung-Jen; Wei, Chang-Ching; Chen, Liuh An; Chen, Jiin Yi; Chang, Ching-Yao; Lin, Chao-Jen; Lim, Yun-Ping; Tien, Peng-Tai; Chen, Hsuan-Ju; Huang, Yong-San; Lin, Hui-Ju; Wan, Lei

2017-01-01

The prevalence of myopia has rapidly increased in recent decades and has led to a considerable global public health concern. In this study, we elucidate the relationship between Kawasaki disease (KD) and the incidence of myopia. We used Taiwan's National Health Insurance Research Database to conduct a population-based cohort study. We identified patients diagnosed with KD and individuals without KD who were selected by frequency matched based on sex, age, and the index year. The Cox proportional hazards regression model was used to estimate the hazard ratio and 95% confidence intervals for the comparison of the 2 cohorts. The log-rank test was used to test the incidence of myopia in the 2 cohorts. A total of 532 patients were included in the KD cohort and 2128 in the non-KD cohort. The risk of myopia (hazard ratio, 1.31; 95% confidence interval, 1.08-1.58; P < 0.01) was higher among patients with KD than among those in the non-KD cohort. The Cox proportional hazards regression model showed that irrespective of age, gender, and urbanization, Kawasaki disease was an independent risk factor for myopia. Patients with Kawasaki disease exhibited a substantially higher risk for developing myopia.

Prognostic significance of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with stage III and IV colorectal cancer

PubMed Central

Kim, Jae Hyun; Lee, Jun Yeop; Kim, Hae Koo; Lee, Jin Wook; Jung, Sung Gyu; Jung, Kyoungwon; Kim, Sung Eun; Moon, Won; Park, Moo In; Park, Seun Ja

2017-01-01

AIM To evaluate the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in patients with colorectal cancer (CRC). METHODS Between April 1996 and December 2010, medical records from a total of 1868 patients with CRC were retrospectively reviewed. The values of simple inflammatory markers including NLR and PLR in predicting the long-term outcomes of these patients were evaluated using Kaplan-Meier curves and Cox regression models. RESULTS The median follow-up duration was 46 mo (interquartile range, 22-73). The estimation of NLR and PLR was based on the time of diagnosis. In multivariate Cox regression analysis, high NLR (≥ 3.0) and high PLR (≥ 160) were independent risk factors predicting poor long-term outcomes in patients with stage III and IV CRC. However, high NLR and high PLR were not prognostic factors in patients with stage I and II CRC. CONCLUSION In this study, we identified that high NLR (≥ 3.0) and high PLR (≥ 160) are useful prognostic factors to predict long-term outcomes in patients with stage III and IV CRC. PMID:28210087

Aspergillus Colonization of the Lung Allograft is a Risk Factor for Bronchiolitis Obliterans Syndrome

PubMed Central

Weigt, S. Samuel; Elashoff, Robert M.; Huang, Cathy; Ardehali, Abbas; Gregson, Aric L.; Kubak, Bernard; Fishbein, Michael C.; Saggar, Rajeev; Keane, Michael P.; Saggar, Rajan; Lynch, Joseph P.; Zisman, David A.; Ross, David J.; Belperio, John A.

2014-01-01

Multiple infections have been linked with the development of bronchiolitis obliterans syndrome (BOS) post-lung transplantation. Lung allograft airway colonization by Aspergillus species is common among lung transplant recipients. We hypothesized that Aspergillus colonization may promote the development of BOS and may decrease survival post-lung transplantation. We reviewed all lung transplant recipients transplanted in our center between 1/2000 and 6/2006. Bronchoscopy was performed according to a surveillance protocol and when clinically indicated. Aspergillus colonization was defined as a positive culture from bronchoalveolar lavage or two sputum cultures positive for the same Aspergillus species, in the absence of invasive pulmonary Aspergillosis. We found that Aspergillus colonization was strongly associated with BOS and BOS related mortality in Cox regression analyses. Aspergillus colonization typically preceded the development of BOS by a median of 261 days (95% CI 87 to 520). Furthermore, in a multivariate Cox regression model, Aspergillus colonization was a distinct risk factor for BOS, independent of acute rejection. These data suggest a potential causative role for Aspergillus colonization in the development of BOS post-lung transplantation and raise the possibility that strategies aimed to prevent Aspergillus colonization may help delay or reduce the incidence of BOS. PMID:19459819

Prognostic value of inflammation-based scores in patients with osteosarcoma

PubMed Central

Liu, Bangjian; Huang, Yujing; Sun, Yuanjue; Zhang, Jianjun; Yao, Yang; Shen, Zan; Xiang, Dongxi; He, Aina

2016-01-01

Systemic inflammation responses have been associated with cancer development and progression. C-reactive protein (CRP), Glasgow prognostic score (GPS), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and neutrophil-platelet score (NPS) have been shown to be independent risk factors in various types of malignant tumors. This retrospective analysis of 162 osteosarcoma cases was performed to estimate their predictive value of survival in osteosarcoma. All statistical analyses were performed by SPSS statistical software. Receiver operating characteristic (ROC) analysis was generated to set optimal thresholds; area under the curve (AUC) was used to show the discriminatory abilities of inflammation-based scores; Kaplan-Meier analysis was performed to plot the survival curve; cox regression models were employed to determine the independent prognostic factors. The optimal cut-off points of NLR, PLR, and LMR were 2.57, 123.5 and 4.73, respectively. GPS and NLR had a markedly larger AUC than CRP, PLR and LMR. High levels of CRP, GPS, NLR, PLR, and low level of LMR were significantly associated with adverse prognosis (P < 0.05). Multivariate Cox regression analyses revealed that GPS, NLR, and occurrence of metastasis were top risk factors associated with death of osteosarcoma patients. PMID:28008988

Disadvantage of survival outcomes in widowed patients with colorectal neuroendocrine neoplasm: an analysis of surveillance, epidemiology and end results database.

PubMed

Li, Jing; Wang, Ying; Han, Fang; Wang, Zhu; Xu, Lichun; Tong, Jiandong

2016-12-13

Marital status correlates with health. Our goal was to examine the impact of marital status on the survival outcomes of patients with colorectal neuroendocrine neoplasms (NENs). The Surveillance, Epidemiology and End Results program was used to identify 1,289 eligible patients diagnosed between 2004 and 2010 with colorectal NENs. Statistical analyses were performed using Chi-square, Kaplan-Meier, and Cox regression proportional hazards methods. Patients in the widowed group had the highest proportion of larger tumor (>2cm), and higher ratio of poor grade (Grade III and IV) and more tumors at advanced stage (P<0.05). The 5-year cause specific survival (CSS) was 76% in the married group, 51% in the widowed group, 73% in the single group, and 72% in the divorced/separated group, which manifest statistically significant difference in the univariate log-rank test and Cox regression model (P<0.05). Furthermore, marital status was an independent prognostic factor only in Distant stage (P<0.001). In conclusion, patients in widowed group were at greater risk of cancer specific mortality from colorectal NENs and social support may lead to improved outcomes for patients with NENs.

Randomized Trial of Intensive Housing Placement and Community Transition Services for Episodic and Recidivist Homeless Families

PubMed Central

Mitchell, Kristen; Pareti, Lauren; DeGenova, Joe; Heller, Anne; Hannigan, Anthony; Gholston, Jennifer

2013-01-01

Objectives. We compared Home to Stay, a pilot of intensive housing placement and community transition services for episodic and recidivist homeless families, with a standard services approach. Methods. Using intention-to-treat analyses, we conducted a modified randomized trial of 138 Home to Stay client families and a control group of 192 client families receiving standard shelter services. Results. Home to Stay clients exited shelter more quickly than clients in the control group (Cox regression, P < .001), more commonly exited shelter with housing subsidies (75% vs 56%), stayed out of shelter longer (Cox regression, P = .011), and spent fewer total days in shelter (376 days vs 449 days). Home to Stay performed best with clients who entered shelter within 180 days of the pilot’s start date and had less impact on clients entering shelter before that time. Conclusions. Relative to standard services, Home to Stay services can accelerate exit from shelter and reduce return to shelter and total sheltered days for episodic and recidivist homeless families. Standard shelter services may be able to narrow this performance gap by incentivizing work with all episodic and recidivist homeless families. PMID:24148053

Misspecification of Cox regression models with composite endpoints

PubMed Central

Wu, Longyang; Cook, Richard J

2012-01-01

Researchers routinely adopt composite endpoints in multicenter randomized trials designed to evaluate the effect of experimental interventions in cardiovascular disease, diabetes, and cancer. Despite their widespread use, relatively little attention has been paid to the statistical properties of estimators of treatment effect based on composite endpoints. We consider this here in the context of multivariate models for time to event data in which copula functions link marginal distributions with a proportional hazards structure. We then examine the asymptotic and empirical properties of the estimator of treatment effect arising from a Cox regression model for the time to the first event. We point out that even when the treatment effect is the same for the component events, the limiting value of the estimator based on the composite endpoint is usually inconsistent for this common value. We find that in this context the limiting value is determined by the degree of association between the events, the stochastic ordering of events, and the censoring distribution. Within the framework adopted, marginal methods for the analysis of multivariate failure time data yield consistent estimators of treatment effect and are therefore preferred. We illustrate the methods by application to a recent asthma study. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22736519

Adverse Clinical Outcome Associated With Mutations That Typify African American Colorectal Cancers.

PubMed

Wang, Zhenghe; Li, Li; Guda, Kishore; Chen, Zhengyi; Barnholtz-Sloan, Jill; Park, Young Soo; Markowitz, Sanford D; Willis, Joseph

2016-12-01

African Americans have the highest incidence and mortality from colorectal cancer (CRC) of any US racial group. We recently described a panel of 15 genes that are statistically significantly more likely to be mutated in CRCs from African Americans than in Caucasians (AA-CRC genes). The current study investigated the outcomes associated with these mutations in African American CRCs (AA-CRCs). In a cohort of 66 patients with stage I-III CRCs, eight of 27 CRCs with AA-CRC gene mutations (Mut+) developed metastatic disease vs only four of 39 mutation-negative (Mut-) cases (P = .03, Cox regression model with two-sided Wald test). Moreover, among stage III cases (n = 33), Mut+ cancers were nearly three times more likely to relapse as Mut- cases (7 of 15 Mut+ vs 3 of 18 Mut-; P = .03, Cox regression model with two-sided Wald test). AA-CRC mutations may thus define a high-risk subset of CRCs that contributes to the overall disparity in CRC outcomes observed in African Americans. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Low Survival Rates of Oral and Oropharyngeal Squamous Cell Carcinoma

PubMed Central

da Silva Júnior, Francisco Feliciano; dos Santos, Karine de Cássia Batista; Ferreira, Stefania Jeronimo

2017-01-01

Aim To assess the epidemiological and clinical factors that influence the prognosis of oral and oropharyngeal squamous cell carcinoma (SCC). Methods One hundred and twenty-one cases of oral and oropharyngeal SCC were selected. The survival curves for each variable were estimated using the Kaplan-Meier method. The Cox regression model was applied to assess the effect of the variables on survival. Results Cancers at an advanced stage were observed in 103 patients (85.1%). Cancers on the tongue were more frequent (23.1%). The survival analysis was 59.9% in one year, 40.7% in two years, and 27.8% in 5 years. There was a significant low survival rate linked to alcohol intake (p = 0.038), advanced cancer staging (p = 0.003), and procedures without surgery (p < 0.001). When these variables were included in the Cox regression model only surgery procedures (p = 0.005) demonstrated a significant effect on survival. Conclusion The findings suggest that patients who underwent surgery had a greater survival rate compared with those that did not. The low survival rates and the high percentage of patients diagnosed at advanced stages demonstrate that oral and oropharyngeal cancer patients should receive more attention. PMID:28638410

[Negative prognostic impact of female gender on oncological outcomes following radical cystectomy].

PubMed

Dabi, Y; Rouscoff, Y; Delongchamps, N B; Sibony, M; Saighi, D; Zerbib, M; Peyraumore, M; Xylinas, E

2016-02-01

To confirm gender specific differences in pathologic factors and survival rates of urothelial bladder cancer patients treated with radical cystectomy. We conducted a retrospective monocentric study on 701 patients treated with radical cystectomy and pelvic lymphadenectomy for muscle invasive bladder cancer. Impact of gender on recurrence rate, specific and non-specific mortality rate were evaluated using Cox regression models in univariate and multivariate analysis. We collected data on 553 males (78.9%) and 148 females (21.1%) between 1998 and 2011. Both groups were comparable at inclusion regarding age, pathologic stage, nodal status and lymphovascular invasion. Mean follow-up time was 45 months (interquartile 23-73) and by that time, 163 patients (23.3%) had recurrence of their tumor and 127 (18.1%) died from their disease. In multivariable Cox regression analyses, female gender was independently associated with disease recurrence (RR: 1.73; 95% CI 1.22-2.47; P=0.02) and cancer-specific mortality (RR=2.50, 95% CI=1.71-3.68; P<0.001). We confirmed female gender to be an independent negative prognosis factor for patients following a radical cystectomy and lymphadenectomy for an invasive muscle bladder cancer. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Perceived Social Support, Self-Esteem, and Internet Addiction Among Students of Al-Zahra University, Tehran, Iran.

PubMed

Naseri, Laila; Mohamadi, Jalal; Sayehmiri, Koroush; Azizpoor, Yosra

2015-09-01

Internet addiction is a global phenomenon that causes serious problems in mental health and social communication. Students form a vulnerable group, since they have free, easy, and daily access to the internet. The current study aimed to investigate perceived social support, self-esteem, and internet addiction among Al-Zahra University students. In the current descriptive research, the statistical sample consisted of 101 female students residing at AL-Zahra University dormitory, Tehran, Iran. Participants were randomly selected and their identities were classified. Then, they completed the Multidimensional Scale of Perceived Social Support, Rosenberg's Self-esteem Scale, and Yang Internet Addiction Test. After completion of the questionnaires, the data were analyzed using the correlation test and stepwise regression. The Pearson correlation coefficient indicated significant relationships between self-esteem and internet addiction (P < 0.05, r = -0.345), perceived social support (r = 0.224, P < 0.05), and the subscale of family (r = 0.311, P < 0.05). The findings also demonstrated a significant relationship between internet addiction and perceived social support (r = -0.332, P < 0.05), the subscale of family (P < 0.05, r = -0.402), and the other subscales (P < 0.05, r = -0.287). Results of the stepwise regression showed that the scale of internet addiction and the family subscale were predicative variables for self-esteem (r = 0.137, P < 0.01, F2, 96 = 77.7). Findings of the current study showed that persons with low self-esteem were more vulnerable to internet addiction.

Health related quality of life and influencing factors among welders.

PubMed

Qin, Jingxiang; Liu, Wuzhong; Zhu, Jun; Weng, Wei; Xu, Jiaming; Ai, Zisheng

2014-01-01

Occupational exposure to welding fumes is a serious occupational health problem all over the world. Welders are exposed to many occupational hazards; these hazards might cause some occupational diseases. The aim of the study was to assess the health related quality of life (HRQL) of electric welders in Shanghai China and explore influencing factors to HRQL of welders. 301 male welders (without pneumoconiosis) and 305 non-dust male workers in Shanghai were enrolled in this study. Short Form-36 (SF-36) health survey questionnaires were applied in this cross-sectional study. Socio-demographic, working and health factors were also collected. Multiple stepwise regress analysis was used to identify significant factors related to the eight dimension scores. Six dimensions including role-physical (RP), bodily pain (BP), general health (GH), validity (VT), social function (SF), and mental health (MH) were significantly worse in welders compared to non-dust workers. Multiple stepwise regress analysis results show that native place, monthly income, quantity of children, drinking, sleep time, welding type, use of personal protective equipment (PPE), great events in life, and some symptoms including dizziness, discomfort of cervical vertebra, low back pain, cough and insomnia may be influencing factors for HRQL of welders. Among these factors, only sleep time and the use of PPE were salutary. Some dimensions of HRQL of these welders have been affected. Enterprises which employ welders should take measures to protect the health of these people and improve their HRQL.

Correlation between increased urinary sodium excretion and decreased left ventricular diastolic function in patients with type 2 diabetes mellitus.

PubMed

Kagiyama, Shuntaro; Koga, Tokushi; Kaseda, Shigeru; Ishihara, Shiro; Kawazoe, Nobuyuki; Sadoshima, Seizo; Matsumura, Kiyoshi; Takata, Yutaka; Tsuchihashi, Takuya; Iida, Mitsuo

2009-10-01

Increased salt intake may induce hypertension, lead to cardiac hypertrophy, and exacerbate heart failure. When elderly patients develop heart failure, diastolic dysfunction is often observed, although the ejection fraction has decreased. Diabetes mellitus (DM) is an established risk factor for heart failure. However, little is known about the relationship between cardiac function and urinary sodium excretion (U-Na) in patients with DM. We measured 24-hour U-Na; cardiac function was evaluated directly during coronary catheterization in type 2 DM (n = 46) or non-DM (n = 55) patients with preserved cardiac systolic function (ejection fraction > or = 60%). Cardiac diastolic and systolic function was evaluated as - dp/dt and + dp/dt, respectively. The average of U-Na was 166.6 +/- 61.2 mEq/24 hour (mean +/- SD). In all patients, stepwise multivariate regression analysis revealed that - dp/dt had a negative correlation with serum B-type natriuretic peptide (BNP; beta = - 0.23, P = .021) and U-Na (beta = - 0.24, P = .013). On the other hand, + dp/dt negatively correlated with BNP (beta = - 0.30, P < .001), but did not relate to U-Na. In the DM-patients, stepwise multivariate regression analysis showed that - dp/dt still had a negative correlation with U-Na (beta = - 0.33, P = .025). The results indicated that increased urinary sodium excretion is associated with an impairment of cardiac diastolic function, especially in patients with DM, suggesting that a reduction of salt intake may improve cardiac diastolic function.

The rate of adherence to urate-lowering therapy and associated factors in Chinese gout patients: a cross-sectional study.

PubMed

Yin, Rulan; Cao, Haixia; Fu, Ting; Zhang, Qiuxiang; Zhang, Lijuan; Li, Liren; Gu, Zhifeng

2017-07-01

The aim of this study was to assess adherence rate and predictors of non-adherence with urate-lowering therapy (ULT) in Chinese gout patients. A cross-sectional study was administered to 125 gout patients using the Compliance Questionnaire on Rheumatology (CQR) for adherence to ULT. Patients were asked to complete the Treatment Satisfaction Questionnaire for Medication version II, Health Assessment Questionnaire, Confidence in Gout Treatment Questionnaire, Gout Knowledge Questionnaire, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and 36-Item Short Form Health Survey. Data were analyzed by independent sample t test, rank sum test, Chi-square analysis as well as binary stepwise logistic regression modeling. The data showed that the rate of adherence (CQR ≥80%) to ULT was 9.6% in our investigated gout patients. Adherence was associated with functional capacity, gout-related knowledge, satisfaction with medication, confidence in gout treatment and mental components summary. Multivariable analysis of binary stepwise logistic regression identified gout-related knowledge and satisfaction of effectiveness with medication was the independent risk factors of medication non-adherence. Patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication, were more likely not to adhere to ULT. Non-adherence to ULT among gout patients is exceedingly common, particularly in patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication. These findings could help medical personnel develop useful interventions to improve gout patients' medication adherence.

Stigma Resistance in Stable Schizophrenia: The Relative Contributions of Stereotype Endorsement, Self-Reflection, Self-Esteem, and Coping Styles

PubMed Central

Kao, Yu-Chen; Chang, Hsin-An; Tzeng, Nian-Sheng; Yeh, Chin-Bin; Loh, Ching-Hui

2017-01-01

Objective: Stigma resistance (SR) has recently emerged as a prominent aspect of research on recovery from schizophrenia, partly because studies have suggested that the development of stigma-resisting beliefs may help individuals lead a fulfilling life and recover from their mental illness. The present study assessed the relationship between personal SR ability and prediction variables such as self-stigma, self-esteem, self-reflection, coping styles, and psychotic symptomatology. Method: We performed an exploratory cross-sectional study of 170 community-dwelling patients with schizophrenia. Self-stigma, self-esteem, self-reflection, coping skills, and SR were assessed through self-report. Psychotic symptom severity was rated by the interviewers. Factors showing significant association in univariate analyses were included in a stepwise backward regression model. Results: Stepwise regressions revealed that acceptance of stereotypes of mental illness, self-esteem, self-reflection, and only 2 adaptive coping strategies (positive reinterpretation and religious coping) were significant predictors of SR. The prediction model accounted for 27.1% of the variance in the SR subscale score in our sample. Conclusions: Greater reflective capacity, greater self-esteem, greater preferences for positive reinterpretation and religious coping, and fewer endorsements of the stereotypes of mental illness may be key factors that relate to higher levels of SR. These factors are potentially modifiable in tailored interventions, and such modification may produce considerable improvements in the SR of the investigated population. This study has implications for psychosocial rehabilitation and emerging views of recovery from mental illness. PMID:28884606

Relationships between temperaments, occupational stress, and insomnia among Japanese workers.

PubMed

Deguchi, Yasuhiko; Iwasaki, Shinichi; Ishimoto, Hideyuki; Ogawa, Koichiro; Fukuda, Yuichi; Nitta, Tomoko; Mitake, Tomoe; Nogi, Yukako; Inoue, Koki

2017-01-01

Insomnia among workers reduces the quality of life, contributes toward the economic burden of healthcare costs and losses in work performance. The relationship between occupational stress and insomnia has been reported in previous studies, but there has been little attention to temperament in occupational safety and health research. The aim of this study was to clarify the relationships between temperament, occupational stress, and insomnia. The subjects were 133 Japanese daytime local government employees. Temperament was assessed using the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Auto questionnaire (TEMPS-A). Occupational stress was assessed using the Generic Job Stress Questionnaire (GJSQ). Insomnia was assessed using the Athens Insomnia Scale (AIS). Stepwise multiple logistic regression analyses were conducted. In a stepwise multivariate logistic regression analysis, it was found that the higher subdivided stress group by "role conflict" (OR = 5.29, 95% CI, 1.61-17.32) and anxious temperament score (OR = 1.33; 95% CI, 1.19-1.49) was associated with the presence of insomnia using an adjusted model, whereas other factors were excluded from the model. The study limitations were the sample size and the fact that only Japanese local government employees were surveyed. This study demonstrated the relationships between workers' anxious temperament, role conflict, and insomnia. Recognizing one's own anxious temperament would lead to self-insight, and the recognition of anxious temperament and reduction of role conflict by their supervisors or coworkers would reduce the prevalence of insomnia among workers in the workplace.

Job stress, achievement motivation and occupational burnout among male nurses.

PubMed

Hsu, Hsiu-Yueh; Chen, Sheng-Hwang; Yu, Hsing-Yi; Lou, Jiunn-Horng

2010-07-01

This paper is a report of an exploration of job stress, achievement motivation and occupational burnout in male nurses and to identify predictors of occupational burnout. Since the Nightingale era, the nursing profession has been recognized as 'women's work'. The data indicate that there are more female nurses than male nurses in Taiwan. However, the turnover rate for male nurses is twice that of female nurses. Understanding the factors that affect occupational burnout of male nurses may help researchers find ways to reduce the likelihood that they will quit. A survey was conducted in Taiwan in 2008 using a cross-sectional design. A total of 121 male nurses participated in the study. Mailed questionnaires were used to collect data, which were analysed using descriptive statistics and stepwise multiple regression. The job stress of male nurses was strongly correlated with occupational burnout (r = 0.64, P < 0.001). Stepwise multiple regression analyses indicated that job stress was the only factor to have a statistically significant direct influence on occupational burnout, accounting for 45.8% of the variance in this. Job stress was comprised of three dimensions, of which role conflict accounted for 40.8% of the variance in occupational burnout. The contribution of job stress to occupational burnout of male nurses was confirmed. As occupational burnout may influence the quality of care by these nurses, nurse managers should strive to decrease male nurses' job stress as this should lead to a reduction of negative outcomes of occupational burnout.

Factors Predicting Recovery of Oral Intake in Stroke Survivors with Dysphagia in a Convalescent Rehabilitation Ward.

PubMed

Ikenaga, Yasunori; Nakayama, Sayaka; Taniguchi, Hiroki; Ohori, Isao; Komatsu, Nahoko; Nishimura, Hitoshi; Katsuki, Yasuo

2017-05-01

Percutaneous endoscopic gastrostomy may be performed in dysphagic stroke patients. However, some patients regain complete oral intake without gastrostomy. This study aimed to investigate the predictive factors of intake, thereby determining gastrostomy indications. Stroke survivors admitted to our convalescent rehabilitation ward who underwent gastrostomy or nasogastric tube placement from 2009 to 2015 were divided into 2 groups based on intake status at discharge. Demographic data and Functional Independence Measure (FIM), Dysphagia Severity Scale (DSS), National Institutes of Health Stroke Scale, and Glasgow Coma Scale (GCS) scores on admission were compared between groups. We evaluated the factors predicting intake using a stepwise logistic regression analysis. Thirty-four patients recovered intake, whereas 38 achieved incomplete intake. Mean age was lower, mean body mass index (BMI) was higher, and mean time from stroke onset to admission was shorter in the complete intake group. The complete intake group had less impairment in terms of GCS, FIM, and DSS scores. In the stepwise logistic regression analysis, BMI, FIM-cognitive score, and DSS score were significant independent factors predicting intake. The formula of BMI × .26 + FIM cognitive score × .19 + DSS score × 1.60 predicted recovery of complete intake with a sensitivity of 88.2% and a specificity of 84.2%. Stroke survivors with dysphagia with a high BMI and FIM-cognitive and DSS scores tended to recover oral intake. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Stigma Resistance in Stable Schizophrenia: The Relative Contributions of Stereotype Endorsement, Self-Reflection, Self-Esteem, and Coping Styles.

PubMed

Kao, Yu-Chen; Lien, Yin-Ju; Chang, Hsin-An; Tzeng, Nian-Sheng; Yeh, Chin-Bin; Loh, Ching-Hui

2017-10-01

Stigma resistance (SR) has recently emerged as a prominent aspect of research on recovery from schizophrenia, partly because studies have suggested that the development of stigma-resisting beliefs may help individuals lead a fulfilling life and recover from their mental illness. The present study assessed the relationship between personal SR ability and prediction variables such as self-stigma, self-esteem, self-reflection, coping styles, and psychotic symptomatology. We performed an exploratory cross-sectional study of 170 community-dwelling patients with schizophrenia. Self-stigma, self-esteem, self-reflection, coping skills, and SR were assessed through self-report. Psychotic symptom severity was rated by the interviewers. Factors showing significant association in univariate analyses were included in a stepwise backward regression model. Stepwise regressions revealed that acceptance of stereotypes of mental illness, self-esteem, self-reflection, and only 2 adaptive coping strategies (positive reinterpretation and religious coping) were significant predictors of SR. The prediction model accounted for 27.1% of the variance in the SR subscale score in our sample. Greater reflective capacity, greater self-esteem, greater preferences for positive reinterpretation and religious coping, and fewer endorsements of the stereotypes of mental illness may be key factors that relate to higher levels of SR. These factors are potentially modifiable in tailored interventions, and such modification may produce considerable improvements in the SR of the investigated population. This study has implications for psychosocial rehabilitation and emerging views of recovery from mental illness.

Prediction of reported consumption of selected fat-containing foods.

PubMed

Tuorila, H; Pangborn, R M

1988-10-01

A total of 100 American females (mean age = 20.8 years) completed a questionnaire, in which their beliefs, evaluations, liking and consumption (frequency, consumption compared to others, intention to consume) of milk, cheese, ice cream, chocolate and "high-fat foods" were measured. For the design and analysis, the basic frame of reference was the Fishbein-Ajzen model of reasoned action, but the final analyses were carried out with stepwise multiple regression analysis. In addition to the components of the Fishbein-Ajzen model, beliefs and evaluations were used as independent variables. On the average, subjects reported liking all the products but not "high-fat foods", and thought that milk and cheese were "good for you" whereas the remaining items were "bad for you". Principal component analysis for beliefs revealed factors related to pleasantness/benefit aspects, to health and weight concern and to the "functionality" of the foods. In stepwise multiple regression analyses, liking was the predominant predictor of reported consumption for all the foods, but various belief factors, particularly those related to concern with weight, also significantly predicted consumption. Social factors played only a minor role. The multiple R's of the predictive functions varied from 0.49 to 0.74. The fact that all four foods studied elicited individual sets of beliefs and belief structures, and that none of them was rated similar to the generic "high-fat foods", emphasizes that consumers attach meaning to integrated food entities rather than to ingredients.

Behavioral activation: Is it the expectation or achievement, of mastery or pleasure that contributes to improvement in depression?

PubMed

Furukawa, Toshi A; Imai, Hissei; Horikoshi, Masaru; Shimodera, Shinji; Hiroe, Takahiro; Funayama, Tadashi; Akechi, Tatsuo

2018-06-06

Behavioral activation (BA) is receiving renewed interest as a stand-alone or as a component of cognitive-behavior therapy (CBT) for depression. However, few studies have examined which aspects of BA are most contributory to its efficacy. This is a secondary analysis of a 9-week randomized controlled trial of smartphone CBT for patients with major depression. Depression severity was measured at baseline and at end of treatment by the Patient Health Questionnaire-9. All aspects of behavioral activation tasks that the participants had engaged in, including their expected mastery and pleasure and obtained mastery and pleasure, were recorded in the web server. We examined their contribution to improvement in depression as simple correlations and in stepwise multivariable linear regression. Among the 78 patients who completed at least one behavioral experiment, all aspects of expected or achieved mastery or pleasure correlated with change in depression severity. Discrepancy between the expectation and achievement, representing unexpected gain in mastery or pleasure, was not correlated. In stepwise regression, expected mastery and pleasure, especially the maximum level of the latter, emerged as the strongest contributing factors. The study is observational and cannot deduce cause-effect relationships. It may be the expected and continued sense of pleasure in planning activities that are most meaningful and rewarding to individuals, and not the simple level or amount of obtained pleasure, that contributes to the efficacy of BA. Copyright © 2018. Published by Elsevier B.V.

Association between red blood cell distribution width (RDW) and carotid artery atherosclerosis (CAS) in patients with primary ischemic stroke.

PubMed

Jia, He; Li, Huimian; Zhang, Yan; Li, Che; Hu, Yingyun; Xia, Chunfang

2015-01-01

The present study aimed to explore the association between RDW and CAS in patients with ischemic stroke, expecting to find a new and significant diagnosis index for clinical practice. This cross-sectional study involves 432 consecutive patients with primary ischemic stroke (within 72 h). All subjects were confirmed by magnetic resonance imaging, and underwent physical examination, laboratory tests and carotid ultrasonography check. Finally, 392 patients were included according to the exclusion criteria. The odds ratios of independent variables were calculated using stepwise multiple logistic regression. Carotid intimal-medial thickness (IMT) and RDW are both significantly different between CAS group and control group. Univariate analyses show that high-sensitive C-reactive protein (Hs-CRP) and RDW (r=0.436) are both in significantly positive association with IMT. Stepwise multiple logistic regression shows that RDW is an independent protective factor of CAS in patients with ischemic stroke. Compared with the lowest quartile, the second to fourth quartiles are 1.13 (95% CI: 1.13-3.05), 2.02 (95% CI: 1.66-4.67), and 3.10 (95% CI: 2.46-7.65), respectively. The present study suggested that RDW level were higher than non-CAS in patients with primary ischemic stroke. Our results facilitated a bridge to connect RDW with ischemic stroke and further confirmed the role of RDW in the progression of the ischemic stroke. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Relationships between temperaments, occupational stress, and insomnia among Japanese workers

PubMed Central

Ishimoto, Hideyuki; Ogawa, Koichiro; Fukuda, Yuichi; Nitta, Tomoko; Mitake, Tomoe; Nogi, Yukako; Inoue, Koki

2017-01-01

Insomnia among workers reduces the quality of life, contributes toward the economic burden of healthcare costs and losses in work performance. The relationship between occupational stress and insomnia has been reported in previous studies, but there has been little attention to temperament in occupational safety and health research. The aim of this study was to clarify the relationships between temperament, occupational stress, and insomnia. The subjects were 133 Japanese daytime local government employees. Temperament was assessed using the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Auto questionnaire (TEMPS-A). Occupational stress was assessed using the Generic Job Stress Questionnaire (GJSQ). Insomnia was assessed using the Athens Insomnia Scale (AIS). Stepwise multiple logistic regression analyses were conducted. In a stepwise multivariate logistic regression analysis, it was found that the higher subdivided stress group by “role conflict” (OR = 5.29, 95% CI, 1.61–17.32) and anxious temperament score (OR = 1.33; 95% CI, 1.19–1.49) was associated with the presence of insomnia using an adjusted model, whereas other factors were excluded from the model. The study limitations were the sample size and the fact that only Japanese local government employees were surveyed. This study demonstrated the relationships between workers’ anxious temperament, role conflict, and insomnia. Recognizing one’s own anxious temperament would lead to self-insight, and the recognition of anxious temperament and reduction of role conflict by their supervisors or coworkers would reduce the prevalence of insomnia among workers in the workplace. PMID:28407025

Is patriarchy the source of men's higher mortality?

PubMed Central

Stanistreet, D; Bambra, C; Scott-Samuel, A

2005-01-01

Objective: To examine the relation between levels of patriarchy and male health by comparing female homicide rates with male mortality within countries. Hypothesis: High levels of patriarchy in a society are associated with increased mortality among men. Design: Cross sectional ecological study design. Setting: 51 countries from four continents were represented in the data—America, Europe, Australasia, and Asia. No data were available for Africa. Results: A multivariate stepwise linear regression model was used. Main outcome measure was age standardised male mortality rates for 51 countries for the year 1995. Age standardised female homicide rates and GDP per capita ranking were the explanatory variables in the model. Results were also adjusted for the effects of general rates of homicide. Age standardised female homicide rates and ranking of GDP were strongly correlated with age standardised male mortality rates (Pearson's r = 0.699 and Spearman's 0.744 respectively) and both correlations achieved significance (p<0.005). Both factors were subsequently included in the stepwise regression model. Female homicide rates explained 48.8% of the variance in male mortality, and GDP a further 13.6% showing that the higher the rate of female homicide, and hence the greater the indicator of patriarchy, the higher is the rate of mortality among men. Conclusion: These data suggest that oppression and exploitation harm the oppressors as well as those they oppress, and that men's higher mortality is a preventable social condition, which could be tackled through global social policy measures. PMID:16166362

Relationship between Spiritual Health and Quality of Life in Patients with Cancer.

PubMed

Mohebbifar, Rafat; Pakpour, Amir H; Nahvijou, Azin; Sadeghi, Atefeh

2015-01-01

As the essence of health in humans, spiritual health is a fundamental concept for discussing chronic diseases such as cancer and a major approach for improving quality of life in patients is through creating meaningfulness and purpose. The present descriptive analytical study was conducted to assess the relationship between spiritual health and quality of life in 210 patients with cancer admitted to the Cancer Institute of Iran, selected through convenience sampling in 2014. Data were collected using Spiritual Health Questionnaire and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC-QLQ). Patients' performance was assessed through the Karnofsky Performance Status Indicator and their cognitive status through the Mini-Mental State Examination (MMSE). Data were analyzed in SPSS-16 using descriptive statistics and stepwise linear regression. The results obtained reported the mean and standard deviation of the patients' spiritual health scoreas 78.4±16.1and the mean and standard deviation of their quality of life score as 58.1±18.7. The stepwise linear regression analysis confirmed a positive and significant relationship between spiritual health and quality of life in patients with cancer (β=0.688 and r=0.00). The results of the study show that spiritual health should be more emphasized and reinforced as a factor involved in improving quality of life in patients with cancer. Designing care therapies and spiritual interventions is a priority in the treatment of these patients.

The investigation of the relationship between probability of suicide and reasons for living in psychiatric inpatients

PubMed Central

Eskiyurt, Reyhan; Ozkan, Birgul

2017-01-01

Aim: This study was carried out to determine the reasons of the suicide probability and reasons for living of the inpatients hospitalized at the psychiatry clinic and to analyze the relationship between them. Materials and Methods: The sample of the study consisted of 192 patients who were hospitalized in psychiatric clinics between February and May 2016 and who agreed to participate in the study. In collecting data, personal information form, suicide probability scale (SPS), reasons for living inventory (RFL), and Beck's depression inventory (BDI) were used. Stepwise regression method was used to determine the factors that predict suicide probability. Results: In the study, as a result of analyses made, the median score on the SPS was found 76.0, the median score on the RFL was found 137.0, the median score on the BDI of the patients was found 13.5, and it was found that patients with a high probability of suicide had less reasons for living and that their depression levels were very high. As a result of stepwise regression analysis, it was determined that suicidal ideation, reasons for living, maltreatment, education level, age, and income status were the predictors of suicide probability (F = 61.125; P < 0.001). Discussion: It was found that the patients who hospitalized in the psychiatric clinic have high suicide probability and the reasons of living are strong predictors of suicide probability in accordance with the literature. PMID:29497185

QSPR models for half-wave reduction potential of steroids: a comparative study between feature selection and feature extraction from subsets of or entire set of descriptors.

PubMed

Hemmateenejad, Bahram; Yazdani, Mahdieh

2009-02-16

Steroids are widely distributed in nature and are found in plants, animals, and fungi in abundance. A data set consists of a diverse set of steroids have been used to develop quantitative structure-electrochemistry relationship (QSER) models for their half-wave reduction potential. Modeling was established by means of multiple linear regression (MLR) and principle component regression (PCR) analyses. In MLR analysis, the QSPR models were constructed by first grouping descriptors and then stepwise selection of variables from each group (MLR1) and stepwise selection of predictor variables from the pool of all calculated descriptors (MLR2). Similar procedure was used in PCR analysis so that the principal components (or features) were extracted from different group of descriptors (PCR1) and from entire set of descriptors (PCR2). The resulted models were evaluated using cross-validation, chance correlation, application to prediction reduction potential of some test samples and accessing applicability domain. Both MLR approaches represented accurate results however the QSPR model found by MLR1 was statistically more significant. PCR1 approach produced a model as accurate as MLR approaches whereas less accurate results were obtained by PCR2 approach. In overall, the correlation coefficients of cross-validation and prediction of the QSPR models resulted from MLR1, MLR2 and PCR1 approaches were higher than 90%, which show the high ability of the models to predict reduction potential of the studied steroids.

Functional form diagnostics for Cox's proportional hazards model.

PubMed

León, Larry F; Tsai, Chih-Ling

2004-03-01

We propose a new type of residual and an easily computed functional form test for the Cox proportional hazards model. The proposed test is a modification of the omnibus test for testing the overall fit of a parametric regression model, developed by Stute, González Manteiga, and Presedo Quindimil (1998, Journal of the American Statistical Association93, 141-149), and is based on what we call censoring consistent residuals. In addition, we develop residual plots that can be used to identify the correct functional forms of covariates. We compare our test with the functional form test of Lin, Wei, and Ying (1993, Biometrika80, 557-572) in a simulation study. The practical application of the proposed residuals and functional form test is illustrated using both a simulated data set and a real data set.

Use of the Box-Cox Transformation in Detecting Changepoints in Daily Precipitation Data Series

NASA Astrophysics Data System (ADS)

Wang, X. L.; Chen, H.; Wu, Y.; Pu, Q.

2009-04-01

This study integrates a Box-Cox power transformation procedure into two statistical tests for detecting changepoints in Gaussian data series, to make the changepoint detection methods applicable to non-Gaussian data series, such as daily precipitation amounts. The detection power aspects of transformed methods in a common trend two-phase regression setting are assessed by Monte Carlo simulations for data of a log-normal or Gamma distribution. The results show that the transformed methods have increased the power of detection, in comparison with the corresponding original (untransformed) methods. The transformed data much better approximate to a Gaussian distribution. As an example of application, the new methods are applied to a series of daily precipitation amounts recorded at a station in Canada, showing satisfactory detection power.