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At least 811 records · Page 45Linked to original sources
PubMed2002

The Mayo Lung Cohort: a regression analysis focusing on lung cancer incidence and mortality.

PURPOSE: The Mayo Lung Project has been interpreted as negative because it failed to demonstrate a significant mortality reduction among those randomized to chest x-ray and cytology. In contrast, survival suggests that screening is highly effective. This report was undertaken to analyze the trial as a closed cohort study, in an effort to identify predictors of lung cancer incidence and mortality, and to determine whether survival or mortality was unbiased. PATIENTS AND METHODS: The Mayo Lung Cohort comprised all 9,192 randomized individuals. Cox proportional hazards regression was used both to determine predictors of incidence and mortality in the population and to identify predictors of mortality among cases. Survival analyses using intent-to-treat principles and measuring survival from randomization were used to evaluate length bias and lead-time bias. Multivariate Cox regression was used to investigate the extent to which the data are consistent with overdiagnosis. RESULTS: Cox regression demonstrates that, in addition to age and smoking, randomization to screening predicted increased lung cancer incidence (hazard ratio, 1.30; 95% confidence interval [CI], 1.06 to 1.60). Predictors of mortality were similar, except randomization to screening was not significant (hazard ratio, 1.06; 95% CI, 0.83 to 1.37). Among cases, survival was significantly superior in the experimental population. Higher incidence in the experimental group accounts for the mortality/survival discrepancy. Both lead-time and length biases can be excluded, because survival from randomization was superior in the experimental population. Overdiagnosis is eliminated because resection was the only significant multivariate predictor of survival. Overall, 50% of resected and 0% of unresected cases were cured. CONCLUSION: Survival was superior in the screened population, and this advantage was not attributable to lead-time bias, length bias, or overdiagnosis bias. Mortality was biased, because incidence differences confounded the ability of mortality to reflect the true effect of screening. Indeed, survival provided an unbiased surrogate for cure in the Mayo Lung Cohort.

Bias↗
PubMed2006

Semi-parametric accelerated failure time regression analysis with application to interval-censored HIV/AIDS data.

This paper demonstrates a way to investigate a potentially non-linear relationship between an interval-censored response variable and a continuously distributed explanatory variable. A potentially non-linear effect of a continuous explanatory variable on the response is incorporated into an accelerated failure time model, forming a partial linear model. A sieve maximum likelihood estimator (MLE) is suggested to simultaneously estimate all the parameters. The sieve MLE is shown to be asymptotically efficient and normally distributed. Simulation studies show that the proposed estimators for the scale and regression parameters are robust and efficient, and the estimator for the non-linear function is able to capture the shape of a variety of smooth non-linear functions. The model is applied to observational HIV data, where the response variable is the time to suppression of HIV viral load after initiation of antiretroviral therapy, and baseline viral load is investigated as a potentially non-linear effect.

Anti-Retroviral Agents↗
PubMed1998

Determinants of four functional tasks among older adults: an exploratory regression analysis.

Functional ability declines in later life. The purpose of this project was to determine if strength, postural control, and joint pain predict performance of four functional tasks among older adults. A sample of 28 older adults completed assessments of strength, postural control, joint pain, and four functional tasks. The duration to complete the functional tasks of: 1) getting out of bed, going to a chair, and then returning to bed; 2) crossing a street and getting onto a bus; 3) exiting the passenger side of a car; and 4) climbing a flight of 27 stairs was recorded. Step-wise regression equations indicated that seated row strength and dynamic postural control were significant predictors of all of the tasks and accounted for the largest proportion of the variance in each equation. These results indicate that measures of physical fitness may be more important predictors of functional tasks among older adults than chronological age.

Activities of Daily Living↗
PubMed1979

A new procedure to derive weighting factors for nonlinear regression analysis applied to enzyme kinetic data.

The experimental variance of enzymic steady-state kinetic experiments depends on velocity as approximated by a power function (Var(v) = K1 . valpha (Askelöf, P., Korsfeldt, M. and Mannervik, B. (1976) Eur. J. Biochem. 69, 61--67). The values of the constants (K1, alpha) can be estimated by making replicate measurements of velocity, and the inverse of the function can then be used as a weighting factor. In order to avoid measurement of a large number of replicates to establish the error structure of a kinetic data set, a different approach was tested. After a preliminary regression using a 'good model', which satisfies reasonable goodness-of-fit criteria, the residuals were taken to represent the experimental error. The neighbouring residuals were grouped together and the sum of their mean squared values was used as a measure of the variance in the neighbourhood of the corresponding measurements. The values of the constants obtained in this way agreed with those obtained by replicates.

Enzymes↗
PubMed2004

Avoiding regression analysis pitfalls when calibrating white blood cell differential counters.

Method comparison and calibration are important for clinical hematologists and for manufacturers of new methods and instruments. Automation of the white blood cell (WBC) differential count poses unique problems in this regard because the reference method is a microscopic manual cell count of 200 WBCs. A highly variable reference method can obscure the true relation between the reference and the test methods and reduce sensitivity to miscalibration. A computer model based on published cell distributions and on the statistical properties of proportions was created to enable testing of alternative approaches to calibration. Ordinary linear regression (OLR) and standard Deming regression (SDR) were applied to a comparison of the results obtained with a virtual cell counter (counting 2,000 WBCs) and that obtained with a virtual 200-cell reference method for monocytes (mean population percentage of 7.1%) and lymphocytes (mean population percentage of 29%). Both regression approaches can misrepresent the known mathematical relation between the methods. This problem almost always occurs when OLR is used and the proportion of the cell of interest is low, as in the case of monocytes (7.1% of the total count). OLR comparisons, however, introduce significant error even for cell counts of 29%. SDR performed much better for both cell types.

Automation↗
PubMed1996

Relationship between total mortality and cholesterol reduction as found by meta-regression analysis of randomized cholesterol-lowering trials.

All randomized trials of cholesterol lowering except those without information on total mortality or cholesterol reduction were included in this meta-analysis. Its purpose was to review the relationship between log odds ratio of total mortality in active vs. control group and degree of cholesterol reduction, adjusting for appropriate covariates such as type of trial (single or multifactor), risk level in the control group, and type of treatment. Analysis revealed that risk level in the control group was particularly important to adjust for because it correlated both to degree of cholesterol reduction (r = 0.48) and to log OR of total mortality (r = -0.38, single-factor trials) and thus confounded the cholesterol mortality association. After adjustment, a borderline significant association was found between degree of absolute cholesterol reduction and total mortality log OR. Type of treatments also seemed to be associated with log OR, mostly through excess risk in hormone-treated patients. There was no statistically significant indication that fibrate trials had inferior results as compared to other drug trials. Meta-analysis estimates of global treatment effects can be misleading in the guidance for creating appropriate recommendations regarding cholesterol reduction. More emphasis must be put on how cholesterol is reduced and how much.

Anticholesteremic Agents↗
PubMed1986

Logistic curve fitting and parameter estimation using nonlinear noniterative least-squares regression analysis.

A microcomputer program has been developed for the fitting of the logistic curve to biological, medical, and other experimental data. In addition to supplying estimates for all of the logistic curve parameters, the program provides the fitted result for each input datum thus allowing for the immediate assessment of the logistic curve and detection of possible outliers.

Biometry↗
PubMed2003

Regression analysis of incomplete medical cost data.

The accumulation of medical cost over time for each subject is an increasing stochastic process defined up to the instant of death. The stochastic structure of this process is complex. In most applications, the process can only be observed at a limited number of time points. Furthermore, the process is subject to right censoring so that it is unobservable after the censoring time. These special features of the medical cost data, especially the presence of death and censoring, pose major challenges in the construction of plausible statistical models and the development of the corresponding inference procedures. In this paper, we propose several classes of regression models which formulate the effects of possibly time-dependent covariates on the marginal mean of cost accumulation in the presence of death or on the conditional means of cost accumulation given specific survival patterns. We then develop estimating equations for these models by combining the approach of generalized estimating equations for longitudinal data with the inverse probability of censoring weighting technique. The resultant estimators are shown to be consistent and asymptotically normal with simple variance estimators. Simulation studies indicate that the proposed inference procedures behave well in practical situations. An application to data taken from a large cancer study reveals that the Medicare enrollees who are diagnosed with less aggressive ovarian cancer tend to accumulate medical cost at lower rates than those with more aggressive disease, but tend to have higher lifetime costs because they live longer.

Aged↗
PubMed1985

Estimation of the initial velocity of enzyme-catalysed reactions by non-linear regression analysis of progress curves.

Most methods for studying the kinetic properties of an enzyme involve the determination of initial velocities. When the reaction progress curve shows significant curvature due to depletion of the substrate, accumulation of inhibitory products or instability of the enzyme, estimation of the initial velocity is a subjective and inexact process. Two methods have been suggested [Cornish-Bowden (1975) Biochem. J. 144, 305-312; Boeker (1982) Biochem J. 203, 117-123] that attempt to eliminate this subjective element. The present study offers a third alternative, which is based on fitting a reparameterized form of the integrated Michaelis-Menten equation to the progress curves by non-linear regression. This method yields estimates and standard errors of the initial velocity and of the time to reach 50% reaction. No prior knowledge of the apparent product concentration at zero time or infinite time is required, since both of these quantities are also estimated from the data. It is shown that this method yields reliable estimates of the initial velocity under a wide range of circumstances, including those where the two previously published methods perform poorly.

Enzyme Activation↗
PubMed1993

Pooled time series regression analysis in longitudinal studies.

Many longitudinal studies attempt to examine changes in outcome measures over time in groups of patients. Applying conventional analytic techniques, such as a single classical linear regression model, to these data will often not result in minimum variance estimates, and may affect the results of tests of significance. Pooled time series regression analyses comprise a set of techniques that may be used in these instances to model changes in outcome measures over time. Pooling of time series data from many individuals may be done using two types of models: fixed effect models, which specify differences among individuals in separate intercept terms, and random effects models, which allow for differences among individuals by including an additional error component in the model. The choice between these alternative model specifications is guided by both theoretical and statistical considerations. This paper describes the use of pooled time series analysis, contrasts these methods with two classical linear regression approaches, and demonstrates these differences using two examples: a hypothetical study of serum glucose measurements in patients with diabetic ketoacidosis, and a longitudinal study of the development of functional disability in a cohort of patients with rheumatoid arthritis. These methods may be applicable to the study of outcomes in many chronic illnesses.

Humans↗
PubMed2006

Regression analysis of mean quality-adjusted lifetime with censored data.

In clinical trials of chronic diseases such as acquired immunodeficiency syndrome, cancer, or cardiovascular diseases, the concept of quality-adjusted lifetime (QAL) has received more and more attention. In this paper, we consider the problem of how the covariates affect the mean QAL when the data are subject to right censoring. We allow a very general form for the mean model as a function of covariates. Using the idea of inverse probability weighting, we first construct a simple weighted estimating equation for the parameters in our mean model. We then find the form of the most efficient estimating equation, which yields the most efficient estimator for the regression parameters. Since the most efficient estimator depends on the distribution of the health history processes, and thus cannot be estimated nonparametrically, we consider different approaches for improving the efficiency of the simple weighted estimating equation using observed data. The applicability of these methods is demonstrated by both simulation experiments and a data example from a breast cancer clinical trial study.

Breast Neoplasms↗
PubMed1992

Assessing influence in regression analysis with censored data.

In this paper we show how to evaluate the effect that perturbations to the model, data, or case weights have on maximum likelihood estimates from censored survival data. The ideas and methods also apply to other nonlinear estimation problems. We review the ideas behind using log-likelihood displacement and local influence methods. We describe new interpretations for some local influence statistics and show how these statistics extend and complement traditional case deletion influence statistics for linear least squares. These statistics identify individual and combinations of cases that have important influence on estimates of parameters and functions of these parameters. We illustrate the methods by reanalyzing the Stanford Heart Transplant data with a parametric regression model.

Age Factors↗
PubMed2005

Differential effects of MDMA, cocaine, and cannabis use severity on distinctive components of the executive functions in polysubstance users: a multiple regression analysis.

Executive functioning impairments have been demonstrated following consumption of drugs of abuse. These executive impairments could play an important role on the development of the addictive process and rehabilitation of substance abusers. Recent neuropsychological models of executive functioning assume a multicomponent organization of these processes, suggesting different functions could contribute differentially to performance on executive tasks. The aim of this study was to analyze the relationship between severity of consumption of different drugs and neuropsychological performance on tasks sensitive to impairment in the executive subprocesses of working memory, response inhibition, cognitive flexibility, and abstract reasoning. Instruments sensitive to impairment in these four components were administered to 38 polysubstance abusers along with a severity of drug consumption interview. Multiple regression analyses were used. Results showed a differential impact of severity of MDMA abuse on working memory and abstract reasoning indices, of cocaine severity on an inhibitory control index and of cannabis on a cognitive flexibility index. Metabolic reorganization of monoamine frontal-subcortical pathways after drug exposure are proposed as possible explanations for these impairments.

Adult↗
PubMed2007

Cancer mortality trends in the Umbria region of Italy 1978-2004: a joinpoint regression analysis.

BACKGROUND: The aim of the present paper was to analyse cancer mortality in the Umbria region, from 1978 to 2004. Mortality trends depend on a number of factors including exposures, health system interventions, and possibly artefact (e.g. classification change, variations of data completeness). Descriptive data on mortality only allow for generation of hypotheses to explain observed trends. Some clues on the respective role of possible mortality determinants may be found comparing mortality with incidence and survival data. METHODS: Mortality data for the periods 1978-1993 and 1994-2004 were supplied by the National Institute of Statistics (ISTAT) and the Regional Causes of Death Registry (ReNCaM) respectively. Sex and site-specific mortality time trends were analysed by the "joinpoint regression" method. RESULTS: For all sites combined, in both sexes, the standardised rate was first increasing before the end of the eighties and decreasing thereafter. Gastric cancer mortality showed a different trend by gender; that is the rate constantly decreased over the period among females while, for males, it was first increasing up to 1985 and decreasing thereafter. Liver cancer trend showed a pattern similar to gastric cancer. Large bowel cancer showed a gender specific trend, that is it was increasing among males and stable among females. Also lung cancer mortality varied by gender: it started to decline after 1989 among males but was steadily increasing over the study period among women. A decreasing trend for female breast cancer mortality began in 1994. Prostate cancer mortality trend is the only one showing two significant joinpoints: mortality decreased up to 1990, then it increased up to 1998 and, finally, was decreasing. CONCLUSION: Overall cancer mortality was decreasing in both sexes in Umbria and this favourable trend will probably continue and further improve since population screening against breast, cervix, and large bowel cancers were recently introduced. Besides gastric cancer, tobacco-related cancers and prostate cancer mainly contributed to mortality reduction in males, whereas breast cancer mainly contributed to declining mortality in females.

Breast Neoplasms↗
PubMed2000

[Correlation-regression analysis of morphometric parameters of the tibial bone following osteotomy with experimental local infection].

Dynamics of morphometric parameters of ischemic disease and bone reparative regeneration were determined experimentally in 43 rats subjected to tibia resection with following infection with pathogenic S. aureus at terms from 3 to 60 days. On 1st posttraumatic day mean parameters of ischemic in bones of rats alterations subjected to the operation in aseptic condition exceed that of rats from infected group; on later terms mean parameters of reactive and reparative changes in rats from infected group exceed that of rats from aseptic group; qualitative and quantitative differences in rats from both groups were reflected in differences of structure and intensity of correlation links and types of regression correlation between certain morphometric parameters of bone lesion.

Animals↗
PubMed1979

A computer program for life table regression analysis with time dependent covariates.

This paper presents a computer program for analyzing time-dependent covariables in survival studies by the life table regression model described by Holford [3]. Basically, life table regression incorporates the elements of regression and the life table into a single model. Regression parameters are estimated by the method of maximum likelihood using the Newton-Raphson iterative procedure. The program provides two methods for testing hypotheses concerning regression coefficients, namely the standard normal deviate test and a Wald statistic based on the first and second derivatives of the log likelihood. Residual plots are provided to assess the fit of the model to the data.

Actuarial Analysis↗
PubMed1992

Simultaneous and iterative weighted regression analysis of toxicity tests using a microplate reader.

A system is described for determination of LC50 or IC50 by an iterative process based on data obtained from a plate reader using a marine unicellular alga as a target species. The esterase activity of Tetraselmis suesica on fluorescein diacetate as a substrate was measured using a fluorescence titerplate. Simultaneous analysis of results was performed using an iterative process adopting the sigmoid function Y = y/1 (dose of toxicant/IC50)slope for dose-response relationships. IC50 (+/- SEM) was estimated (P less than 0.05). An application with phosalone as a toxicant is presented.

Cholinesterase Inhibitors↗