PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Logistic Model”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7Linked to original sources
PubMed1993

Generalized logistic models for low-dose response data.

We discuss a generalization of the logistic response function of the form Pr(y = 1/x) = [1 + exp(- theta - beta'x)]-alpha, where alpha > 0. This function coincides with the usual logistic response when the shape parameter alpha is equal to one. We describe the use of this model for analysing cancer rates in mice for low-dose exposure to a known carcinogen. When estimating the low-dose responses, the errors associated with extrapolation are reduced when a priori knowledge about the rates among unexposed individuals is incorporated into the fitting procedures.

2-Acetylaminofluorene↗
PubMed2004

A modified logistic model to describe gadolinium kinetics in breast tumors.

A five-parameter modified logistic equation is presented that describes the signal enhancement in magnetic resonance dynamic contrast enhanced imaging (MRI-DCE). In this heuristic model, P(1) approximates the baseline signal, P(2) is related to the magnitude of the peak signal enhancement, P(3) is the approximate time of the maximum rate of increase of signal, P(4) is related to the maximum rate of signal enhancement, and P(5) is the terminal slope of the signal enhancement curve. Six breast tumors were studied that exhibited diverse patterns of signal enhancement, and in each case, estimated model parameters were well identified. Three of the model parameters, P(2), P(4) and P(5) describe attributes of the signal enhancement curve that have previously been shown to have diagnostic value with respect to breast cancer. Procedures for using the primary model parameters to derive a number of secondary parameters that may also have diagnostic value are discussed. Sensitivity analysis shows that the signal enhancement curve is highly sensitive to P(3) in the region of the signal intensity curve associated with rapid uptake of the contrast reagent. Consequently, frequent signal sampling in this time domain is indicated to enable identification of P(3) and sensitive fitting of the signal intensity curve. The advantages of this heuristic model compared to commonly used compartmental modeling approaches are discussed.

Breast Neoplasms↗
PubMed1998

Using a logistic model to predict malignancy of adnexal masses based on menopausal status, ultrasound morphology, and color Doppler findings.

In the present study we aimed to develop a formula for predicting adnexal malignancy based on menopausal status, ultrasound morphology, and color Doppler findings. Logistic regression analysis was performed retrospectively in 79 adnexal masses (59 benign and 20 malignant) in 73 unselected and consecutive patients. All these masses had been preoperatively evaluated using transvaginal color Doppler ultrasonography. In logistic analysis menopausal status (premenopausal vs postmenopausal), color Doppler findings (no flow or lowest resistance index >0.45 vs lowest resistance index </=0.45) and ultrasound morphology (nonsuspicious vs suspicious) were entered as categorical variables. Morphology and color Doppler were found to be independent predictors, whereas menopausal status was not. To assess the validity of the developed mathematical formula, this was applied prospectively in a second series of 58 consecutive and unselected patients diagnosed of adnexal mass and scheduled for surgery. The probability of malignancy was estimated in each case. Overall, 56 of 58 (96.5%) adnexal masses were correctly classified. We conclude that the formula developed in this study is easy to apply and could be useful to predict malignancy or benignity of adnexal masses.

Female↗
PubMed1985

Increasing the sensitivity of caries clinical trials by applying logistic modelling to specific teeth.

An alternative statistical approach is proposed for analysing data from longitudinal clinical trials. Caries increments on those teeth which are known to be particularly susceptible to caries for the population under study are represented by a linear logistic probability model. Expression of the caries increments in the form of a probability model should lead to a better understanding of the relative importance of the various factors which contribute to the caries increment in the population under study. When this model was applied to caries increments on the permanent second molars of children aged 11-13 yr at the baseline of two 3-yr trials, the sensitivity of statistical analysis was up to five times greater than that obtained with traditional statistical methods.

Child↗
PubMed1992

The logistic modeling of sensitivity, specificity, and predictive value of a diagnostic test.

A method is described for modeling the sensitivity, specificity, and positive and negative predictive values of a diagnostic test. To model sensitivity and specificity, the dependent variable (Y) is defined to be the dichotomous results of the screening test, and the presence or absence of disease, as defined by the "gold standard", is included as a binary explanatory variable (X1), along with variables used to define the subgroups of interest. The sensitivity of the screening test may then be estimated using logistic regression procedures. Modeled estimates of the specificity and predictive values of the screening test may be similarly derived. Using data from a population-based study of peripheral arterial disease, the authors demonstrated empirically that this method may be useful for obtaining smoothed estimates of sensitivity, specificity, and predictive values. As an extension of this method, an approach to the modeling of the relative sensitivity of two screening tests is described, using data from a study of screening procedures for colorectal disease as an example.

Arterial Occlusive Diseases↗
PubMed2004

Functional mapping of quantitative trait loci underlying growth trajectories using a transform-both-sides logistic model.

The incorporation of developmental control mechanisms of growth has proven to be a powerful tool in mapping quantitative trait loci (QTL) underlying growth trajectories. A theoretical framework for implementing a QTL mapping strategy with growth laws has been established. This framework can be generalized to an arbitrary number of time points, where growth is measured, and becomes computationally more tractable, when the assumption of variance stationarity is made. In practice, however, this assumption is likely to be violated for age-specific growth traits due to a scale effect. In this article, we present a new statistical model for mapping growth QTL, which also addresses the problem of variance stationarity, by using a transform-both-sides (TBS) model advocated by Carroll and Ruppert (1984, Journal of the American Statistical Association 79, 321-328). The TBS-based model for mapping growth QTL cannot only maintain the original biological properties of a growth model, but also can increase the accuracy and precision of parameter estimation and the power to detect a QTL responsible for growth differentiation. Using the TBS-based model, we successfully map a QTL governing growth trajectories to a linkage group in an example of forest trees. The statistical and biological properties of the estimates of this growth QTL position and effect are investigated using Monte Carlo simulation studies. The implications of our model for understanding the genetic architecture of growth are discussed.

Biometry↗
PubMed2005

A novel logistic model based on clinicopathological features predicts microsatellite instability in colorectal carcinomas.

High-frequency microsatellite instability has been reported to be associated with good prognosis in colorectal adenocarcinoma. However, methods to assess microsatellite instability (MIN) are based on genetic assays and are not ideally suited to most histopathology laboratories. The aim of the present study was to develop a model for prediction of MIN status in colorectal cancer based on phenotypic characteristics. Clinicopathological features of a cohort of 204 patients with primary colon cancer were retrospectively reviewed following predetermined criteria. Genetic assessment of MIN status was performed on DNA extracted from sections of formalin-fixed, paraffin-embedded specimens by testing a panel of 11 microsatellite markers. Logistic regression analysis generated a mathematical tool capable of identifying colorectal tumors displaying MIN status with a sensitivity of 77.8% and a specificity of 96.8%. Features associated with instability included the proximal location of the lesions, occurrence of solid and/or mucinous differentiation, absence of cribriform structures, presence of peritumoral Crohn-like reaction, expansive growth pattern, high Ki67 proliferative index, and p53-negative phenotype. This approach predicts microsatellite instability in colorectal carcinoma with an overall assigned accuracy of 95.1% and a negative predictive value of 97.8%. Implementation of this tool to routine histopathological studies could improve the management of patients with colorectal cancer, especially those presenting with stage II and III of the disease. It will also assist in identifying a subset of patients likely to benefit from adjuvant chemotherapy.

Aged↗
PubMedDate not supplied

Estimation of probability of malignancy using a logistic model combining color Doppler ultrasonography, serum CA125 level in women with a pelvic mass.

The goal of this study was to develop a scoring system using combination of Doppler characterization of pelvic/ovarian lesions and serum CA125 level. Our purpose was to maximize the preoperative discrimination between benign and malignant entities. In a prospective study, a total of 101 patients were evaluated preoperatively using a standard transvaginal ultrasound and color Doppler imaging with pulse spectral analysis and serum CA125 level within a week prior to surgery. The variables that were analyzed by the multivariate logistic regression method are as follows: tumor structure, ascites, presence of septum, the peak systolic velocity (PSV), the resistance index (RI), and serum CA125 level. Of the 101 patients qualified for the study, 48 patients were diagnosed with benign (47.5%) and 53 (52.5%) with malignant tumors. Each criterion used alone provides statistically significant discrimination between benign and malignant tumors. Four criteria could be combined in a malignancy score which is calculated using the product of the serum CA125 level (1 if CA125 > or =40 U/mL and 0 if CA125 <40 U/mL), the result of sonography for presence of septum in tumor (1 if there was septum > or =3 mm, 0 if there was no septum or <3 mm), result of Doppler flow imaging as RI (1 if RI < or =0.5 and 0 if RI >0.5) and the PSV (1 if PSV > or =40 cm/s and 0 if PSV <40 cm/s). This scoring system devised was statistically more effective discriminator between cancer and benign lesions than formal methods. Using malignancy score cutoff level of two, the sensitivity was 98% (CI 88.62-99.9.), the specificity was 85% (CI 71.62-93.45), the positive predictive value was 87.5%, and the negative predictive value was 97.6%. Area under curve of receiver operative characteristic curves was 0.987 (CI 0.971-1.004). These values were statistically more significant than those obtained from the independent use of RI, PSV, or serum CA125 level at their optimum decision values (P < 0.05). There is a need for a prospective evaluation of this score using a larger sample of patients.

Adolescent↗
PubMed2002

Logistic model analysis of neurological findings in Minamata disease and the predicting index.

OBJECTIVE: To establish a statistical diagnostic method to identify patients with Minamata disease (MD) considering factors of aging and sex, we analyzed the neurological findings in MD patients, inhabitants in a methylmercury polluted (MP) area, and inhabitants in a non-MP area. MATERIALS AND METHODS: We compared the neurological findings in MD patients and inhabitants aged more than 40 years in the non-MP area. Based on the different frequencies of the neurological signs in the two groups, we devised the following formula to calculate the predicting index for MD: predicting index = 1/(1+e(-x)) x 100 (The value of x was calculated using the regression coefficients of each neurological finding obtained from logistic analysis. The index 100 indicated MD, and 0, non-MD). RESULTS: Using this method, we found that 100% of male and 98% of female patients with MD (95 cases) gave predicting indices higher than 95. Five percent of the aged inhabitants in the MP area (598 inhabitants) and 0.2% of those in the non-MP area (558 inhabitants) gave predicting indices of 50 or higher. CONCLUSION: Our statistical diagnostic method for MD was useful in distinguishing MD patients from healthy elders based on their neurological findings.

Adult↗
PubMed2006

Combining logistic models with multivariate methods for the rapid biological assessment of rivers using macroinvertebrates.

This work represents an attempt to define a simple method to classify the relative degree of disturbance of sites in lotic systems on the basis of comparison of their faunistic composition with reference sites. Two ecotypes were selected in northern Portugal where benthic invertebrates were sampled in reaches with different levels of contamination. As a first stage, previous Geographic Information System information was used to define reference sites in each ecotype. Afterwards, multivariate techniques and non linear estimation models were combined to assess biological quality. This method allowed us to quantify sites according to increasing levels of contamination, after the probabilities of occurrence of taxa along a gradient of contamination taking into account the reference condition. The results suggest that this method is sensitive to organic pollution, easy to interpret, namely the species tolerance, and could be a good framework to establish regional rankings depending on the ecological impact of river sites.

Altitude↗
PubMed2001

Extinction and quasi-stationarity in the Verhulst logistic model.

We formulate and analyse a stochastic version of the Verhulst deterministic model for density-dependent growth of a single population. Three parameter regions with qualitatively different behaviours are identified. Explicit approximations of the quasi-stationary distribution and of the expected time to extinction are presented in each of these regions. The quasi-stationary distribution is approximately normal, and the time to extinction is long, in one of these regions. Another region has a short time to extinction and a quasi-stationary distribution that is approximately truncated geometric. A third region is a transition region between these two. Here the time to extinction is moderately long and the quasi-stationary distribution has a more complicated behaviour. Numerical illustrations are given.

Animals↗
PubMed1986

Background factors of ectopic pregnancy. II. Risk estimation by means of a logistic model.

Based on the frequency distribution in a previous case-control study of ectopic pregnancy in Sweden, the prognostic value of a number of risk factors was analysed. A logistic procedure was applied in a stepwise manner, resulting in a risk-scoring model in which the probability of ectopic pregnancy can be determined on the basis of four background factors.

Abdomen↗