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PubMed2005

Serum proteins profile as an indicator of malignancy: multivariate logistic regression and ROC analyses.

The electrophoretic pattern of serum proteins of 85 patients carrying different types of neoplasia and 85 matched healthy adults were comparatively studied by agarose gel electrophoresis, to find out if there is a specific protein pattern common to different types of cancer. Each protein fraction was analyzed quantitatively by densitometry. Multivariate logistic regression and receiver operating characteristic (ROC) analyses were performed using SPSS software. When total protein and albumin were measured by colorimetric methods, cancer patients, compared to controls, had a decreased concentration of total protein (66.0+/-11.5 g/L vs. 76.4+/-6.8 g/L, p< or =0.0001) and of albumin (39.0+/-8.1 g/L vs. 46.0+/-4.3 g/L, p< or =0.0001). The electrophoretic data of serum proteins showed that the ratio of albumin to globulin (0.92+/-0.30 vs. 1.21+/-0.16, p< or =0.0001), percent of the fractions albumin (46.7+/-8.5% vs. 54.4+/-3.5%, p< or =0.0001) and beta-globulin (11.6+/-4.4% vs. 13.0+/-1.9%, p< or =0.001) were decreased and alpha(1)- (5.3+/-2.5% vs. 2.9+/-0.8%, p< or =0.0001), alpha(2)- (13.5+/-4.8% vs. 11.3+/-2.1%, p< or =0.0001) and gamma-globulins (23.0+/-7.7% vs. 18.3+/-3.1%, p< or =0.0001) were significantly increased in cancer patients relative to controls. Cancer patients also had higher counts of leukocytes (7.98+/-3.11, x10(9) cells/L vs. 6.33+/-1.68 x10(9) cells/L, p< or =0.0001) and erythrocyte sedimentation rate (35.9+/-23.5 mm/h vs. 14.1+/-9.5 mm/h,p< / =0.0001). On the basis of univariate analysis, a protein profile out of the normal ranges was more prevalent in cancer patients than in controls. Analysis of the data using multiple logistic regression indicated that the prevalence of cancer was strongly associated with the serum proteins' profile, and alpha(1)-globulin, erythrocyte sedimentation rate, total protein and the ratio of albumin to globulin were the best parameters to discriminate between malignant and healthy states. The area under the ROC curves were the same for most components of the serum proteins' profile at about 0.75+/-0.09, p< or =0.001. We conclude that the profile of serum proteins indicates high diagnostic values for discriminating between cancer patients and healthy individuals and may be useful as an adjunct diagnosis for detection of malignancy.

Adult↗
PubMed2005

A logistic regression mixture model for interval mapping of genetic trait loci affecting binary phenotypes.

Often in genetic research, presence or absence of a disease is affected by not only the trait locus genotypes but also some covariates. The finite logistic regression mixture models and the methods under the models are developed for detection of a binary trait locus (BTL) through an interval-mapping procedure. The maximum-likelihood estimates (MLEs) of the logistic regression parameters are asymptotically unbiased. The null asymptotic distributions of the likelihood-ratio test (LRT) statistics for detection of a BTL are found to be given by the supremum of a chi2-process. The limiting null distributions are free of the null model parameters and are determined explicitly through only four (backcross case) or nine (intercross case) independent standard normal random variables. Therefore a threshold for detecting a BTL in a flanking marker interval can be approximated easily by using a Monte Carlo method. It is pointed out that use of a threshold incorrectly determined by reading off a chi2-probability table can result in an excessive false BTL detection rate much more severely than many researchers might anticipate. Simulation results show that the BTL detection procedures based on the thresholds determined by the limiting distributions perform quite well when the sample sizes are moderately large.

Algorithms↗
PubMed1997

[Ratio of proportions and the use of the delta method for confidence intervals in logistic regression].

OBJECTIVE: To present an application of logistic regression modelling to estimate ratios of proportions, such as prevalence ratio or relative risk, and the Delta Method to estimate confidence intervals. METHOD: The Delta Method was used because it is appropriate for the estimation of variance of non-linear functions of random variables. The method is based on Taylor's series expansion and provides a good approximation of variance estimates. A computer program, utilizing the matrix module of SAS, was developed to compute the variance estimates. A practical demonstration is presented with data from a cross-sectional study carried out on a sample of 611 women, to test the hypothesis that the lack of housework sharing is associated with high scores of psychological symptoms as measured by a validated questionnaire. RESULTS: Crude and adjusted prevalence ratio estimated by logistic regression were similar to those estimated by tabular analysis. Also, ranges of the confidence intervals of the prevalence ratio according to the Delta Method were nearly equal to those obtained by the Mantel-Haenszel approach. CONCLUSIONS: The results give support to the use of the Delta Method for the estimation of confidence intervals for ratios of proportions. The method should be seen as an alternative for situations in which the need to control a large number of potential confounders limits the use of stratified analysis.

Confidence Intervals↗
PubMed1995

Measuring the typicality of objects included in environmental scenes: a logistic model for atypicality.

Some empirical studies have stated that people usually categorize scenes according to the suitability of their elements. This paper proposes a method of measuring the typicality of naturalistic objects contained in environmental scenes. 517 subjects gave a score of suitability for 110 object-scene pairs. We used a logistic model for the measurements which enabled us to obtain two indexes, atypicality and discrimination. Analysis showed that the objects could be arranged on a numerical scale according to their typicality in a scene, and from this we concluded that logistic models are a useful and powerful method of measuring typicality.

Adolescent↗
PubMedDate not supplied

Racial/ethnic and educational differences in the estimated odds of recent nitrite use among adult household residents in the United States: an illustration of matching and conditional logistic regression.

This article compares estimates of the relative odds of nitrite use obtained from weighted unconditional logistic regression with estimates obtained from conditional logistic regression after post-stratification and matching of cases with controls by neighborhood of residence. We illustrate these methods by comparing the odds associated with nitrite use among adults of four racial/ethnic groups, with and without a high school education. We used aggregated data from the 1994-B through 1996 National Household Survey on Drug Abuse (NHSDA). Difference between the methods and implications for analysis and inference are discussed.

Administration, Inhalation↗
PubMed2004

Demonstration of the applicability of the Weibull-log-logistic survival model to the isothermal and nonisothermal inactivation of Escherichia coli K-12 MG1655.

Published isothermal semilogarithmic survival curves of Escherichia coli K-12 MG1655, in the range of 49.8 to 60.6 degrees C, all had noticeable downward concavity. They could be described by the model log S(t) = -b(T)t n, where S(t) = N(t)/N0, N(t) and N0 being the momentary and initial number of organisms, respectively; b(T) is a temperature-dependent rate parameter; and n is a constant found to be about 1.5. The temperature dependence of b(T) could be described by the log-logistic model, b(T) = ln[1 + exp[k(T - Tc)]], which had an almost perfect fit, with k = 0.88 degrees C(-1) and Tc = 60.5 degrees C. The constants, n, k, and Tc were considered the organism's survival parameters in the particular medium. They were incorporated into a rate equation on the assumption that in nonisothermal heating, the momentary inactivation rate is the isothermal rate at the momentary temperature at a time that corresponds to the momentary survival ratio. This model's estimates matched the actual survival curves obtained in the same work under two different nonisothermal heating profiles, lending support to the notion that the Weibull-log-logistic model combination can be used not only to describe isothermal inactivation mathematically, but also to predict survival patterns under nonisothermal conditions.

Colony Count, Microbial↗
PubMed1999

Evaluation of regression calibration and SIMEX methods in logistic regression when one of the predictors is subject to additive measurement error.

BACKGROUND: This paper presents an evaluation of two methods of measurement error adjustment based on recently-developed computer routines (RCAL and SIMEX) under logistic regression models, when one of the two predictors is subject to additive measurement error or Berkson error. METHODS: Computer simulations were used to generate data under a variety of conditions and the methods compared in terms of bias, mean squared error and confidence interval coverage of the regression estimates. RESULTS: Based on our investigations, RCAL was shown to perform very well in all situations considered, except in the presence of Berkson error when the predictor variables were highly correlated. CONCLUSIONS: Since measurement error can lead to misleading inference, it is important to adjust for measurement error in the application of logistic regression. Until better measurement error adjustment methods become available, we recommend RCAL on the basis of our simulation results.

Algorithms↗
PubMedDate not supplied

Use of the logistic organ dysfunction system to study mortality in an Indian intensive care unit.

BACKGROUND: Mortality in Indian intensive care units has not been well studied. Scoring systems are used to predict mortality of patients admitted to such units. Some scoring systems predict hospital mortality while others predict mortality in intensive care units. We used the logistic organ dysfunction system to study the hospital and intensive care unit mortalities in our intensive care unit. METHODS: We prospectively studied 527 consecutively admitted patients in 1997 to the medical intensive care unit in St John's Medical College Hospital, Bangalore. The outcomes studied were death in hospital and death in the intensive care unit. Using standardized mortality ratios, we compared our observed hospital and intensive care unit mortalities with the hospital mortality predicted by the logistic organ dysfunction system. RESULTS: The standardized mortality ratios for hospital deaths was 1.3 with a confidence interval of 1.17-1.49 and for intensive care unit deaths it was 1.0 with a confidence interval of 0.89-1.18. The hospital mortality rates in our setting are significantly higher (p < 0.05) than the predicted hospital mortality rates of the published western model for intensive care unit patients. The intensive care unit mortality rates are not significantly different from the predicted hospital mortality rates of the published western model for intensive care unit patients. CONCLUSION: Our intensive care unit mortality rate is comparable to the western hospital mortality rate. However, after transfer of patients out of the unit, the hospital mortality is higher.

Adolescent↗
PubMedDate not supplied

A multiphasic approach for describing serial height data of Fels children: a hexaphasic-logistic-additive growth model.

In this paper, we reported the results obtained from fitting a new growth model to serial height data of 80 Fels children. The model assumed that human height growth curves are due to the combined effects of six macroscopic logistic growth processes, each reaching the same asymptotic height value. It was named the Walker and Walker-Hexaphasic-Logistic-Additive (WWHLA) growth model. An advantage to using this model is that it allowed us to easily fit entire growth curves with 14 biologically interpretable parameters. We tested the model using a computerized nonlinear least squares technique. The results showed that the new model worked extremely well. The fits resulted in high R, R2, and adjusted R2 values, large F values, relatively low residual mean squares, Durbin-Watson statistics that were very close to 2, and relatively small standard error estimates for the model parameters. In addition, the normality and constant variance test passed for more than 95 percent of the children, and the graphs of the residuals essentially showed no model bias. The new model identified the six growth components or processes in both male and female growth curves. The processes were named according to when they reached their peak height velocity: neonatal, infantile, early-childhood, middle-childhood, late-childhood, and pubertal. Preliminary results suggest that the WWHLA model appears to be the best that is currently available at this time for describing the human growth curve.

Body Height↗
PubMed2000

Models to predict cardiovascular risk: comparison of CART, multilayer perceptron and logistic regression.

The estimate of a multivariate risk is now required in guidelines for cardiovascular prevention. Limitations of existing statistical risk models lead to explore machine-learning methods. This study evaluates the implementation and performance of a decision tree (CART) and a multilayer perceptron (MLP) to predict cardiovascular risk from real data. The study population was randomly splitted in a learning set (n = 10,296) and a test set (n = 5,148). CART and the MLP were implemented at their best performance on the learning set and applied on the test set and compared to a logistic model. Implementation, explicative and discriminative performance criteria are considered, based on ROC analysis. Areas under ROC curves and their 95% confidence interval are 0.78 (0.75-0.81), 0.78 (0.75-0.80) and 0.76 (0.73-0.79) respectively for logistic regression, MLP and CART. Given their implementation and explicative characteristics, these methods can complement existing statistical models and contribute to the interpretation of risk.

Artificial Intelligence↗
PubMedDate not supplied

[Unconditioned logistic regression and sample size: a bibliographic review].

Unconditioned logistic regression is a highly useful risk prediction method in epidemiology. This article reviews the different solutions provided by different authors concerning the interface between the calculation of the sample size and the use of logistics regression. Based on the knowledge of the information initially provided, a review is made of the customized regression and predictive constriction phenomenon, the design of an ordinal exposition with a binary output, the event of interest per variable concept, the indicator variables, the classic Freeman equation, etc. Some skeptical ideas regarding this subject are also included.

Logistic Models↗
PubMed2003

[Usefulness of logistic regression model to predict the endometrial carcinoma based on blood flow indices measured wit the of three-dimensional Doppler sonography].

AIM: Construction and prospective verification of predictive model permitting to rate individual probability of existence of endometrial carcinoma with use of three-dimensional Doppler Doppler sonography. MATERIAL AND METHODS: We analyzed the results of 3D sonography of 123 women (mean age 53.8 +/- 10.6; mean BMI--28.2 +/- 5.4). We estimated: endometrial thickness and volume, blood flow indices. All ultrasound measurements were verified by histology. In aim of finding the best combination of features essentially affect on endometrial cancer's risk and for estimate individual probability of endometrial cancer we use a logistic regression analysis. The obtained model was verified on 20 new cases. RESULTS: There were 24 women with endometrial cancer, 59 women with endometrial hyperplasia and 40 women without endometrial changes. We affirmed that only three variables had statistical significant influence on the constructed predictive model. Probability of endometrial carcinoma was: P(X) = 1/(1 + e-z), where "e" is mathematical constant and z = 0.12 x age + 0.16 x endometrial thickness + 0.47 x VI -11.3. The best sensitivity and specificity were 70.8% and 98.9%. The sensitivity and specificity in 20 new cases was adequately 75% and 91.6%. CONCLUSION: The usefulness of a predictive model built with the help of logistic regression analysis increase sonographic diagnostic precision. The usefulness of endometrial blood flow indices permit to estimate the individual risk of endometrial cancer in women examined with three-dimensional sonography.

Adult↗
PubMed2004

[Logistic regression analysis of factors influencing clinical therapeutic effect on acute tetramine poisoning].

OBJECTIVE: To investigate the factors affecting clinical therapeutic effect on acute tetramine poisoning. METHODS: Using Logistic regression to analyze the relationships among the degree of tetramine poisoning, time of onset, time of admission, exposure history, sex, age, unithol, gastric lavage, etc with the death of poisonded patients. RESULTS: The fatality rate of patient with tetramine poisoning who got gastric lavage was less than that who did not (5.85% vs 38.00%, P < 0.01). In patients who got gastric lavage, the fatality rates were increased with the degree of tetramine poisoning (control: 0%, mild poisoning: 3.07%, severe poisoning: 9.14%, P < 0.05). There was no significant difference in fatality between using unithol and not using patients (7.22% vs 8.25%, P > 0.05). CONCLUSION: Unithol has no significant influence of clinical therapeutic effect on tetramine poisoning patients and dose not reduce the fatality rate of patient with tetramine poisoning, but gastric lavage and the degree of tetramine poisoning do. Logistic regression analysis showed that gastric lavage is the main factor affecting the therapeutic effect on tetramine poisoning.

Acute Disease↗
PubMed2005

[Comparison of multiple prediction models for hypertension (Neural networks, logistic regression and flexible discriminant analyses)].

OBJECTIVE: In this study, we compared performances of logistic regression analysis (LR), flexible discriminant analysis (EAA) and neural networks (SA) in prediction of primary hypertension. METHODS: Predictor variables were family history, lipoprotein A, triglyceride, smoking and body mass index. The data were collected from Cardiology Clinic of Trakya University Medical Faculty in Turkey, 2001. Logistic regression analysis, flexible discriminant analysis and neural networks were used for prediction of control and hypertension groups. Comparison of the performance of all models was done using receiver operating characteristic (ROC) curve analysis. RESULTS: All models had areas under the ROC curve in the range of 0.793-0.984 and SA had sensitivity, specificity, and accuracy greater than 90% at ideal threshold. ROC curve areas of SA and LR, and SA and EAA were statistically different (p<0.001 and p<0.001 respectively), while ROC curve areas of EAA and LR did not differ (p>0.05). CONCLUSION: We concluded that family history, lipoprotein A, triglyceride, smoking and body mass index variables can be used for prediction of control and hypertension groups with statistically better performance of SA over LR and EAA.

Body Mass Index↗
PubMed1992

[A correlation study of psychologic stress factors and cancer by stepwise and logistic regression analyses].

One hundred forty three pairs of cancer patients and healthy controls were enrolled in this study. Thirty four psychologic stress factors were analyzed by stepwise and logistic regressions to identify risk factors for cancer. At the level of significance of alpha = 0.05, F(10,120) = 1.91 and alpha = 0.01, F(10,120) = 2.47, 15 and 13 risk factors were entered into stepwise regression equation, respectively. By conditioned logistic regression analysis, the following five major correlated factors were revealed: introversive personality, family accidents, the ten-year turmoil, repeated mishaps and death of children. The results indicate that, among all the psychological stress factors studied, introversive personality is the most important predisposing factor in the causation of cancer. This study suggests that psychologic stress might play important part in the etiopathogenesis of human malignancies.

Case-Control Studies↗
PubMed1992

[Logistic model for predicting the prognosis in patients with intra-abdominal infection based on the APACHE II index].

BACKGROUND: The APACHE II method has been widely used to classify patients according to disease severity. The high mortality and the lack of reliable prognostic parameters justify the study and application of indexes of severity (IS) and prognostic indexes (PI) in patients with intraabdominal sepsis. METHODS: A prospective study is presented concerning 100 patients with intraabdominal sepsis in whom a prognostic index derived from the APACHE II method by means of a logistic regression model was applied. In this model the APACHE II score is used as the only independent variable with the aim of predicting the outcome (mortality or survival) at the time of hospital admission. RESULTS: The predictive values obtained, with a 70% probability of mortality taken as the cut-off point, were: sensitivity 100%, specificity 87.7% and total predictive capacity 91%. CONCLUSIONS: It was concluded that the logistic prediction model of prognosis shows a high correlation with patient outcome and the application of the APACHE II score is useful in patients with intraabdominal infection.

Abdomen↗
PubMed2005

Factors influencing outcome after hepatic portoenterostomy for biliary atresia: a logistic regression analysis.

BACKGROUND/OBJECTIVE: The association of many factors with the outcome in Biliary atresia (BA) after hepatic portoenterostomy has drawn the attention of many pediatric hepatologists and hepatobiliary surgeons. Understanding these factors will become an important subject in prediction of the postoperative status and in indicating further proper management. MATERIAL AND METHOD: During the last 9 years, 159 BA babies were treated by hepatic portoenterostomy. The authors reviewed the following factors and how they related to outcome: age at operation, total bilirubin (TB) level, type of BA, postoperative bile drainage, hepatic histological features at operation, preoperative and postoperative cholangitis. A multiple logistic regression analysis was used to indicate the factors which significantly influenced the outcome. RESULTS: Of the 159 BA babies, clearing of jaundice confirmed by the color of stool and postoperative serum bilirubin level less than 2 mg % was observed in 54 patients (Group A). Bile drainage with mild jaundice (TB 2-5 mg %) was detected in 65 patients (Group B). The operation failed to create bile flow clinically and biochemically in 40 patients (Group C). Some patients in the last group died during follow-up due to hepatic disease. The multiple logistic regression analysis revealed that the age at operation (> 8 weeks of age), and the presence of portal and parenchymal inflammation at operation significantly related to the failure of portoenterostomy which was followed by portal hypertension with or without esophageal varices. The presence of cholangitis was also significantly related to a poor outcome. CONCLUSION: The age at operation, portal and parenchymal inflammation and the presence of cholangitis are significant factors which relate to the poor prognosis of BA. Recognition of these will lead to proper long-term management.

Age Factors↗
PubMed1991

[A case-control study on HBV infection in families of hepatocellular carcinoma-application of conditional logistic regression model].

To assess the risk of HBV infection in families of hepatocellular carcinoma (HCC), methods of case-control study and conditional logistic regression model were applied. The total infection rate of HBV was 88.89% in cases and 55.56% in controls, showing a statistically significant difference (P less than 0.01). Analysis of logistic model showed that the variable interaction of HBsAg and anti-HBc in pointer group and the variable five-HBV-marker in siblings group were the most important risk factors in these families. However, no significant difference was found in each marker of HBV between two spouse-groups (P greater than 0.05). This study indicates a familial clustering of HBV infection in HCC families.

Adult↗