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Results for “Logistic Models”

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PubMed1997

The relationship of cigarette prices and no-smoking bylaws to the prevalence of smoking in Canada.

OBJECTIVES: The aim of this study was to analyze the association of cigarette prices and no-smoking bylaws with the prevalence of smoking. METHODS: Data on individual smoking status were taken from two national household surveys in Canada. Current cigarette price, the 1-year and 10-year increase in price, and the extent of local restrictions on public smoking were added to the model. Logistic regression was used to estimate the odds of being a smoker. RESULTS: The odds ratio for being a smoker was 1.21 where no-smoking by-laws were relatively infrequent and 1.26 when cigarettes were relatively inexpensive, after adjusting for individual age, sex, education, and marital status. CONCLUSIONS: Both cigarette prices and no-smoking bylaws are effective in controlling smoking; either alone will likely have less impact than the two measures together.

Adult↗

PubMed2005

Pharmacodynamic analysis of the microbiological efficacy of telithromycin in patients with community-acquired pneumonia.

BACKGROUND AND OBJECTIVE: Telithromycin, a ketolide antibacterial, demonstrates concentration-dependent bactericidal activity against the major pathogens causing community-acquired respiratory tract infections. The objective of this study was to explore the relationships between pharmacokinetic/pharmacodynamic predictor variables, such as area under the plasma concentration-time curve (AUC) over minimum inhibitory concentration (MIC) [AUC/MIC], maximum plasma concentration (C(max)) over MIC (C(max)/MIC) and microbiological outcome from telithromycin therapy for community-acquired pneumonia (CAP). PATIENTS AND METHODS: Data were pooled from five phase III studies of oral telithromycin (800 mg once daily for 7-10 days) for the outpatient treatment of adults with CAP. Only subjects with a single pathogen isolated at baseline, a telithromycin MIC determination and at least one plasma pharmacokinetic sample were included. Bacteriologically modified intent-to-treat (bmITT) and bacteriologically evaluable per protocol (PPb) populations were analysed. Individual AUC and C(max) Bayesian estimates were obtained with a population pharmacokinetic model. Logistic regression, nonparametric smoothing, and classification analysis and regression tree (CART) were used to assess the relationship between AUC/MIC and C(max)/MIC and microbiological outcome by pathogen. RESULTS: The bmITT population included 224 patients (Streptococcus pneumoniae in 113, Haemophilus influenzae in 89 and Staphylococcus aureus in 22). Median telithromycin MIC was 0.015 microg/mL for S. pneumoniae, 2.0 microg/mL for H. influenzae and 0.12 microg/mL for S. aureus, with median AUC/MIC of 907.1, 6.9 and 98.4, and median C(max)/MIC of 172.0, 1.3 and 20.4 for the three pathogens, respectively. Both logistic regression and nonparametric smoothing showed the probability of microbiological cure to be consistently greater than 90% over the observed range of predictor variables. No reliable AUC/MIC or C(max)/MIC breakpoints were identified by CART. CONCLUSION: Telithromycin exhibits near-maximal efficacy against three major pathogens causing CAP at a dose of 800 mg once daily.

Adolescent↗

PubMed2003

Patterns of hospital admissions and emergency room visits among patients with scleroderma in South Carolina, USA.

OBJECTIVE: Little research has examined patterns of hospitalization and use of emergency rooms (ER) among patients with systemic sclerosis (SSc). We compared the incidence of hospitalizations and ER visits across 3 race groups (non-Hispanic white, non-Hispanic black, other) and determined predictors of referral to the Medical University of South Carolina (MUSC), a major referral center for patients with SSc residing in the southeastern United States. METHODS: Data were obtained on all South Carolina hospitalizations (1996-2000) for patients who were ever hospitalized for a diagnosis of SSc during that time period. Hospitalization and ER incidence rates were determined in conjunction with corresponding population sizes obtained from the 2000 US Census, and rates were compared across race, sex, and age groups using Poisson regression models. Logistic regression was used to determine predictors of being treated at MUSC. RESULTS: The hospitalization incidence rate was significantly (p < 0.05) higher among blacks compared to whites (rate ratio 1.66; 95% confidence interval 1.41, 1.96), as was the ER incidence rate (rate ratio 1.78; 95% CI 1.50, 2.11). Even after adjusting for sex, age, median household income, primary insurance claim payor, county, and comorbidity, blacks were 60% less likely (p < 0.05) than whites to receive inpatient treatment at MUSC. Similar results were observed when comparing other non-whites to whites. CONCLUSION: The increased hospitalizations and ER visits among non-whites provide additional evidence of greater disease burden among these population groups. Despite this increased burden, non-whites are less likely to receive care at a major SSc referral center.

Academic Medical Centers↗

PubMedDate not supplied

Dialysis choice in the context of an early referral policy: there is room for self care.

BACKGROUND: Predialysis care is vital for the patient and is crucial for dialysis choice: empowered, early referred patients tend to prefer out-of-hospital and self-care treatment; despite these claims, early referral remains too often a program more than a reality. Aim of the study was to evaluate the pattern and reasons for RRT choice in patients treated in a long-standing outpatient network, presently following 850 chronic patients (about 80% diabetics), working with an early referral policy and offering a wide set of dialysis options (home hemo and PD; self care and limited care hemodialysis; hospital hemodialysis). METHODS: Prospective historical study. All patients who started RRT in January 2001-December 2003 were considered. Correlations between demographical (sex, age, educational level) or clinical variables (pre-RRT follow-up, comorbidity, SGA and Karnofsky) and treatment choice have been tested by univariate (chi-square, Kruskal-Wallis) and multivariate models (logistic regression), both considering all choices and dichotomising choice into "hospital" versus "out of hospital dialysis". RESULTS: Hospital dialysis was chosen by 32.6% of patients; out of hospital in 67.4% (PD 26.5%, limited-care 18.4%, home hemodialysis 4.1%, self-care 18.4%). Hospital dialysis and PD were chosen by elderly patients (median age: 67.5 and 70 years respectively) with multiple comorbidities (75% and 92.3%); no difference for age, comorbidity, Karnofsky, SGA and educational level. 6/13 PD patients needed the help of a partner. Self-care/home hemodialysis patients were younger (median age 52), had higher educational level (p = 0.014) and lower prevalence of comorbidity (63.6% vs 94.7% in the other dialysis patients, p = 0.006). In the context of a long follow-up period (3.9 years) a statistically significant difference was found comparing hospital dialysis (3.3 years) vs out of hospital dialysis (4.9 years) (p = 0.035). In a logistic regression model, only pre-RRT follow-up was correlated with dialysis "hospital vs "out of hospital" choice (p = 0.014). CONCLUSION: Early nephrological follow-up may enhance self and home-based dialysis care.

Adult↗

PubMed2005

Interventions that increase or decrease the likelihood of a meaningful improvement in physical health in patients with sciatica.

BACKGROUND AND PURPOSE: The purpose of our study was to determine whether physical therapy interventions predicted meaningful short-term improvement in physical health for patients diagnosed with sciatica. SUBJECTS: We examined data from 1,804 patients (age: mean=52.1 years, SD=15.6 years; 65.7% female, 34.3% male) who had been diagnosed with sciatica and who had completed an episode of outpatient physical therapy. METHODS: Principal components factor analysis was used to define intervention categories from specific treatments applied during the plan of care. A nested-model logistic regression analysis identified intervention categories that predicted meaningful improvement in physical health. Meaningful improvement was defined as a change of 14 or more points on the Physical Component Scale-12 (PCS-12) summary score. RESULTS: Twenty-six percent (n=473) of patients had a meaningful improvement in physical health. Improvement was more likely in patients receiving joint mobility interventions (odds ratio [OR]=2.5, 95% confidence interval [CI]=1.5-4.4) or general exercise (OR=1.5, 95% CI=1.2-2.0). Patients who received spasm reduction interventions were less likely to improve (OR=0.77, 95% CI=0.60-0.98). DISCUSSION AND CONCLUSION: Physical therapists should emphasize the use of joint mobility interventions and exercise when treating patients with sciatica, whereas interventions for spasm reduction should be avoided.

Activities of Daily Living↗

PubMed1993

The analysis of case-control studies under validation subsampling.

In case-control studies, one often finds that covariates are missing or measured with error in the entire sample, whereas complete or exact covariate information is available only in a subsample. This paper discusses the analysis of case-control studies under a double-sampling scheme, where at the first stage covariates are measured with error or missing, and at the second stage are validated in a subsample. The method proposed combines the risk information from both samples by assuming that (1) the disease incidence model is logistic, (2) the partial or proxy information takes on finitely many values, and (3) the error is non-differential. The estimator is obtained by jointly fitting logistic models to the first and second stage data, a variance formula is presented. Parameters can be estimated by use of standard packages for dose-response data. Data from an ongoing case-control study on lung cancer serve as an example.

Aged↗

PubMedDate not supplied

Evaluation of a multivariate prostate-specific antigen and percentage of free prostate-specific antigen logistic regression model in the diagnosis of prostate cancer.

The use of prostate-specific antigen (PSA) in the diagnosis of prostate cancer is controversial due to false-positive results caused by benign prostatic hyperplasia. Several groups have suggested the usefulness of the percentage of free PSA (%fPSA) in patients with PSA levels between 4 and 10 microg/l. Based on previously obtained results, biopsy is carried out in our hospital if the PSA is greater than 10 microg/l or if the %fPSA is lower than 20% and PSA is between 4-10 microg/l. In this study, we have compared these results with those obtained with a logistic regression model based on the determination of PSA and %fPSA. The diagnostic efficacy of the logistic regression model is greater than that of the currently used model. The posterior construction of a nomogram based on the data obtained greatly facilitates the application of the logistic regression model.

Aged↗

PubMed1987

Fitting models of carcinogenesis to a case-control study of breast cancer.

Data from a case-control study of breast cancer in 441 cases and matched controls aged less than or equal to 38 in Los Angeles is fitted to two models of carcinogenesis: the two-stage model of Moolgavkar and Knudson; and a multistage adaptation of the log/log model proposed by Pike et al. In the two-stage model, risk factors (here age at menarche, age at first pregnancy, abortion, regularity of cycling, benign breast disease, and use of oral contraceptives (OCs] are postulated to act either by increasing the rate of mutation of normal to intermediate or of intermediate to malignant stage cells, or by increasing the proliferation rates of such cells. In the multistage model, it is postulated that all transition rates are equally determined by the rate of cell turnover, which is in turn influenced by risk factors. In both models, positive family history is modelled in two ways: (1) all cells may have started in an intermediate stage at birth, with probability depending on the number and degree of affected family members; or (2) as an event rate modifier in the same way as other covariates. With only menarche or menarche and family history included, the multistage and two-stage models both produced likelihoods very similar to those from a simple logistic model, though both fit better than the logistic model as more covariates were added to the model. The two stage models offer greater flexibility in modelling the time at which each factor is most effective. We found irregular menstrual cycling to reduce the rate of proliferation of normal cells or their mutation rate to intermediate cells by 50% (p less than 0.025) and use of OCs to increase these rates by 3.25 fold (p less than 0.01). Having completed a pregnancy of more than 26 weeks gestation appeared to reduce the rate of intermediate cell proliferation by 5% (p less than 0.05) relative to a baseline rate of 14% per year. Benign breast disease was associated with a 1.60 fold increased rate of the second mutation (p less than 0.025). In all models, family history was by far the strongest risk factor (RR = 4.44 from the logistic model, p less than 0.0001). Covariates showed similar effects in the multistage model, though their magnitudes were slightly different.

Adult↗

PubMed1998

Empirical comparisons of proportional hazards, poisson, and logistic regression modeling of occupational cohort data.

This research was conducted to examine the effect of model choice on the epidemiologic interpretation of occupational cohort data. Three multiplicative models commonly employed in the analysis of occupational cohort studies--proportional hazards. Poisson, and logistic regression--were used to analyze data from an historical cohort study of workers exposed to formaldehyde. Samples were taken from this dataset to create a number of predetermined scenarios for comparing the models, varying study size, outcome frequency, strength of risk factors, and follow-up length. The Poisson and proportional hazards models yielded nearly identical relative risk estimates and confidence intervals in all situations except when confounding by age could not be closely controlled in the Poisson analysis. Logistic regression findings were more variable, with risk estimates differing most from the proportional hazards results when there was a common outcome or strong relative risk. The logistic model also provided less precise estimates than the other two. Thus, although logistic was the easiest model to implement, it should be used only in occupational cohort studies when the outcome is rare (5% or less), and the relative risk is less than approximately 2. Even then, the proportional hazards and Poisson models are better choices. Selecting between these two can be based on convenience in most circumstances.

Cohort Studies↗

PubMed2006

The kinetics of Lagenidium giganteum growth in liquid and solid cultures.

AIMS: Production of the mosquito biolarvacide Lagenidium giganteum in solid culture has been proposed as an economic alternative to production in liquid culture because of observations of improved shelf life and efficacy upon storage. Understanding the differences between these production systems and estimating growth rate in solid culture are important for commercialization. In order to address these needs a logistic model was developed to describe the growth kinetics of L. giganteum produced in solid and liquid cultures. METHODS AND RESULTS: Kinetic parameters in the logistic model were estimated by nonlinear regression of CO2 evolution rate (CER) and biomass data from solid and liquid cultivation experiments. Lagenidium giganteum biomass was measured using DNA extracted directly from samples. The logistic model was fit to experimental biomass and CER data with low standard errors for parameter estimates. The model was validated in two independent experiments by examining prediction of biomass using on-line CER measurements. CONCLUSIONS: There were significant differences between maximum biomass density, maintenance coefficients, and specific growth rates for liquid and solid cultures. The maximum biomass density (mg dw ml-1) was 11 times greater for solid cultivation compared with liquid cultivation of L. giganteum; however, the maintenance coefficient (mg CO2 h-1 (mg dw)-1) was six times greater for liquid cultivation than in solid cultivation. The specific growth rate at 30 degrees C was approximately 30% greater in liquid cultivation compared with solid cultivation. Slower depletion of substrate and lower endogenous metabolism may explain the longer shelf life of L. giganteum produced in solid culture. SIGNIFICANCE AND IMPACT OF THE STUDY: A simple logistic model was developed which allows real-time estimation of L. giganteum biomass from on-line CER measurements. Parameter estimates for liquid and solid cultivation models also elucidated observations of longer shelf life for production in solid culture.

Biomass↗

PubMed2006

Switchgrass (Panicum vigratum, L.) delivery to a biorefinery using integrated biomass supply analysis and logistics (IBSAL) model.

This study develops cost, energy input and carbon emissions for a number of switchgrass supply options. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model developed at Oak Ridge National Laboratory is used to evaluate the delivery systems. Three biomass collection systems: baling, loafing and ensiling are evaluated. The number and operational performance of equipment are specified to complete collection operations within 120 days of harvest after August 1. Bales are stacked and tarped on the farm side. The transport of biomass from the farm side to a biorefinery takes place over a full year cycle, i.e. 365 days. Supply quantities range from 454 to 4540 dry tonnes/day (500-5000 dry tons/day). Delivered costs to a biorefinery with capacity of 1814 dry tonnes/day (2000 dry tons/day) are: 44-47 dollars/dry tonne for delivered bales (round and square); 37 dollars/dry tonne for delivered loafs (size 2.4 m x 3.6 m x 6 m); 40 dollars/dry tonne for chopped biomass; and 48 dollars/dry tonne for ensiled chops. These costs do not include any payment to the farmers or switchgrass farming cost. Based on the data from literature, the switchgrass farming cost can range from 30 to 36 dollars/dry tonne. These costs would be additional to the switchgrass collection and transportation cost. Switchgrass collection is generally less expensive than collection of straw or corn stover because of the assumed high yield of 11 dry tonnes/ha and a denser biomass. Energy consumption for delivery systems at this capacity ranges from 4.8% to 6.3% of the energy content of switchgrass. Additional 1% of the energy content of switchgrass is consumed in its farming. At 1814 dry tonnes/day (2000 dry tons/day) capacity, greenhouse gas emissions ranges from 75 to 100 kg of CO2/dry tonne of switchgrass delivered.

Air Pollution↗

PubMed1998

Joint estimation of Down syndrome risk and ascertainment rates: a meta-analysis of nine published data sets.

In this paper we present an analysis of nine data sets in which ascertainment and maternal age risk of Down syndrome are estimated jointly using maximum likelihood. We include data on 4825 Down syndrome cases from nine previously published data sets. These include data from studies carried out before the introduction of prenatal screening and from recent studies involving women who had not received prenatal testing. Our results show that, allowing for under-ascertainment, there is a good degree of consistency between the different data sets. We compare the three- and five-parameter constant plus exponential model with a three-parameter logistic model for maternal age-specific risk. We show that the three-parameter logistic model provides a good fit to the data and compare rates from this model with those derived from published studies of uncertain completeness (Cuckle et al., 1987) and those from data sets believed to be complete (Halliday et al., 1995; Hecht and Hook, 1994, 1996). In general, our results agree closely with those of the latter, but achieve greater precision because of the inclusion of additional data. Our derived rates are considerably higher than those of Cuckle et al. (1987), which are embedded in many computer systems for generating risks.

Down Syndrome↗

PubMed1997

Early diagnosis of acute myocardial infarction by either electrocardiogram or a logistic regression model: portability of a predictive instrument of acute cardiac ischemia to a small rural coronary care unit.

OBJECTIVE: To test the ability of a logistic regression model (LRM) that predicts acute cardiac ischemia to make an early diagnosis of acute myocardial infarction (AMI); the ability of the LRM to predict AMI was also compared with the presenting electrocardiogram (ECG). SETTING: A small rural Irish coronary care unit. METHODS: Clinical and ECG data required by the LRM to predict acute coronary ischemia were recorded in 600 consecutive patients admitted with suspected AMI. Estimates of the LRM were ranked into equal deciles in declining probability of acute cardiac ischemia (pACI), and presenting ECGs were placed into one of seven categories. RESULTS: At presentation 50% of AMI patients were in the two LRM deciles with the highest pACI, and 49% of AMI patients had ECGs with greater than 2 mm ST elevation associated with reciprocal changes. ECG categories had a 76% sensitivity for the early diagnosis of AMI and the LRM had an 84% sensitivity. The specificity, accuracy and positive predictive value for the ECG categories were 92%, 84% and 85%, respectively. The specificity, accuracy and positive predictive value of the LRM were 84%, 84% and 75%, respectively. The areas under the receiver operating characteristic curve of the LRM and ECG categories were almost identical (91% and 90%, respectively). CONCLUSION: AMI can be diagnosed early with comparable accuracy either by placing presenting ECGs into one of seven categories, or by the LRM. The best method and 'cut-off' point for the diagnosis of AMI varies according to clinical circumstances. Categorizing ECGs requires more skill in ECG interpretation, but takes less time. The previously reported performances of the LRM were replicated, confirming portability of its use into different clinical settings and patient populations.

Acute Disease↗

PubMed1989

Limitations of a conventional logistic regression model based on left ventricular ejection fraction in predicting coronary events after myocardial infarction.

The clinical utility of conventional logistic regression models based on left ventricular ejection fraction (LVEF) for the prediction of cardiac events (death or recurrent infarction) was assessed in 646 postinfarction patients undergoing radionuclide ventriculography at rest and during exercise. The discriminant power of 2 different models (LVEF at rest alone vs LVEF at rest plus LVEF at peak exercise) was quantified in terms of the area under receiver-operating characteristic curves based on knowledge of patient outcome in the year after testing and the logistic probability of that outcome. Although LVEF at rest provided a significant amount of prognostic information (receiver-operating characteristic curve area = 62 +/- 4%, p less than 0.001), several limitations were observed: (1) powerful predictors of risk were uncommon (32% of patients with an LVEF at rest less than 0.20 had a cardiac event, but only 3% of the population had such extreme values); (2) the accuracy of predictions for high risk patients was less than for low risk patients (28 vs 98%, p less than 0.001); (3) addition of exercise LVEF to the model did not improve the accuracy of prediction (receiver-operating characteristic curve area = 68 +/- 4%, p = 0.11); and (4) predictions for individual patients were very imprecise (the 95% confidence interval of percent risk for an LVEF at rest of 0.20 [11 to 36%] overlapped that for an LVEF at rest of 0.60 [0 to 14%]).(ABSTRACT TRUNCATED AT 250 WORDS)

Death, Sudden↗

PubMed2005

Long-range trends in adult mortality: models and projection methods.

In the study reported here, I had two objectives: (1) to test a new version of the logistic model for the pattern of change over time in age-specific adult mortality rates and (2) to develop a new method for projecting future trends in adult mortality. A test of the goodness of fit of the logistic model for the force of mortality indicated that its slope parameter is nearly constant over time. This finding suggests a variant of the model that is called the shifting logistic model. A new projection method, based on the shifting mortality model, is proposed and compared with the widely used Lee-Carter procedure.

Adult↗

PubMed1996

Univariate analysis of dichotomous or ordinal data from twin pairs: a simulation study comparing structural equation modeling and logistic regression.

The univariate analysis of categorical twin data can be performed using either structural equation modeling (SEM) or logistic regression. This paper presents a comparison between these two methods using a simulation study. Dichotomous and ordinal (three category) twin data are simulated under two different sample sizes (1,000 and 2,000 twin pairs) and according to different additive genetic and common environmental models of phenotypic variation. The two methods are found to be generally comparable in their ability to detect a "correct" model under the specifications of the simulation. Both methods lack power to detect the right model for dichotomous data when the additive genetic effect is low (between 10 and 20%) or medium (between 30 and 40%); the ordinal data simulations produce similar results except for the additive genetic model with medium or high heritability. Neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large and the sample size included 2,000 twin pairs. The SEM method was found to have better power than logistic regression when there is a medium (30%) or high (50%) additive genetic effect and a modest common environmental effect. Conversely, logistic regression performed better than SEM in correctly detecting additive genetic effects with simulated ordinal data (for both 1,000 and 2,000 pairs) that did not contain modest common environmental effects; in this case the SEM method incorrectly detected a common environmental effect that was not present.

Analysis of Variance↗

PubMed1984

Methodological issues in case-control studies IV: Validity and efficiency of various analysis strategies for continuous variables using the unconditional logistic regression model.

Computer simulation has been used to evaluate the performance of the unconditional logistic regression model when used to analyse continuous data from case-control studies. The size of the bias in the odds ratio estimate introduced by small sample sizes and by the use of the incorrect analysis model has been estimated for various underlying population conditions, together with the power as a measure of efficiency. It is concluded that the model is robust over a wide range of exposures to the risk factor, in the sense that both small sample sizes and use of the incorrect model introduced relatively small biases. The power of the test is again little altered by use of the incorrect analysis model.

Aged↗

PubMed1996

Early diagnosis of acute myocardial infarction using clinical and electrocardiographic data at presentation: derivation and evaluation of logistic regression models.

The aim of this study was to determine which, and how many, data items are required to construct a decision support algorithm for early diagnosis of acute myocardial infarction using clinical and electrocardiographic data available at presentation. Logistic regression models were derived using data items from 600 consecutive patients at one centre (Edinburgh), then tested prospectively on 510 cases from the same centre and 662 consecutive cases from another centre (Sheffield). Although performance of the models increased with progressive addition of data inputs when applied to training data, a simple six-factor model was the most effective on test data, yielding accuracies of 84.3 and 83.6% on the two test sets. A model constructed solely of electrocardiographic data performed nearly as well as those incorporating clinical data. Previously published logistic regression models did not perform so well as the models derived from data collected for this study.

Adolescent↗