Optimal design for model discrimination and parameter estimation for itraconazole population pharmacokinetics in cystic fibrosis patients

Optimal sampling times are found for a study in which one of the primary purposes is to develop a model of the pharmacokinetics of itraconazole in patients with cystic fibrosis for both capsule and solution doses. The optimal design is expected to produce reliable estimates of population parameters for two different structural PK models. Data collected at these sampling times are also expected to provide the researchers with sufficient information to reasonably discriminate between the two competing structural models.

Binocular interaction:Contrast matching and contrast discrimination are predicted by the same model

How do signals from the 2 eyes combine and interact? Our recent work has challenged earlier schemes in which monocular contrast signals are subject to square-law transduction followed by summation across eyes and binocular gain control. Much more successful was a new 'two-stage' model in which the initial transducer was almost linear and contrast gain control occurred both pre- and post-binocular summation. Here we extend that work by: (i) exploring the two-dimensional stimulus space (defined by left- and right-eye contrasts) more thoroughly, and (ii) performing contrast discrimination and contrast matching tasks for the same stimuli. Twenty-five base-stimuli made from 1 c/deg patches of horizontal grating, were defined by the factorial combination of 5 contrasts for the left eye (0.3-32%) with five contrasts for the right eye (0.3-32%). Other than in contrast, the gratings in the two eyes were identical. In a 2IFC discrimination task, the base-stimuli were masks (pedestals), where the contrast increment was presented to one eye only. In a matching task, the base-stimuli were standards to which observers matched the contrast of either a monocular or binocular test grating. In the model, discrimination depends on the local gradient of the observer's internal contrast-response function, while matching equates the magnitude (rather than gradient) of response to the test and standard. With all model parameters fixed by previous work, the two-stage model successfully predicted both the discrimination and the matching data and was much more successful than linear or quadratic binocular summation models. These results show that performance measures and perception (contrast discrimination and contrast matching) can be understood in the same theoretical framework for binocular contrast vision. © 2007 VSP.

Myocardial Perfusion Imaging Is a Strong Predictor of Death in Women

OBJECTIVES We sought to assess the prognostic value and risk classification improvement using contemporary single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI) to predict all-cause mortality. BACKGROUND Myocardial perfusion is a strong estimator of prognosis. Evidence published to date has not established the added prognostic value of SPECT-MPI nor defined an approach to detect improve classification of risk in women from a developing nation. METHODS A total of 2,225 women referred for SPECT-MPI were followed by a mean period of 3.7 +/- 1.4 years. SPECT-MPI results were classified as abnormal on the presence of any perfusion defect. Abnormal scans were further classified as with mild/moderate reversible, severe reversible, partial reversible, or fixed perfusion defects. Risk estimates for incident mortality were categorized as <1%/year, 1% to 2%/year, and >2%/year using Cox proportional hazard models. Risk-adjusted models incorporated clinical risk factors, left ventricular ejection fraction (LVEF), and perfusion variables. RESULTS All-cause death occurred in 139 patients. SPECT-MPI significantly risk stratified the population; patients with abnormal scans had significantly higher death rates compared with patients with normal scans, 13.1% versus 4.0%, respectively (p < 0.001). Cox analysis demonstrated that after adjusting for clinical risk factors and LVEF, SPECT-MPI improved the model discrimination (integrated discrimination index = 0.009; p = 0.02), added significant incremental prognostic information (global chi-square increased from 87.7 to 127.1; p < 0.0001), and improved risk prediction (net reclassification improvement = 0.12; p = 0.005). CONCLUSIONS SPECT-MPI added significant incremental prognostic information to clinical and left ventricular functional variables while enhancing the ability to classify this Brazilian female population into low-and high-risk categories of all-cause mortality. (J Am Coll Cardiol Img 2011;4:880-8) (C) 2011 by the American College of Cardiology Foundation

Inflammatory markers and incident heart failure risk in older adults: the Health ABC (Health, Aging, and Body Composition) study.

OBJECTIVES: The purpose of this study was to evaluate the association between inflammation and heart failure (HF) risk in older adults. BACKGROUND: Inflammation is associated with HF risk factors and also directly affects myocardial function. METHODS: The association of baseline serum concentrations of interleukin (IL)-6, tumor necrosis factor-alpha, and C-reactive protein (CRP) with incident HF was assessed with Cox models among 2,610 older persons without prevalent HF enrolled in the Health ABC (Health, Aging, and Body Composition) study (age 73.6 +/- 2.9 years; 48.3% men; 59.6% white). RESULTS: During follow-up (median 9.4 years), HF developed in 311 (11.9%) participants. In models controlling for clinical characteristics, ankle-arm index, and incident coronary heart disease, doubling of IL-6, tumor necrosis factor-alpha, and CRP concentrations was associated with 29% (95% confidence interval: 13% to 47%; p < 0.001), 46% (95% confidence interval: 17% to 84%; p = 0.001), and 9% (95% confidence interval: -1% to 24%; p = 0.087) increase in HF risk, respectively. In models including all 3 markers, IL-6, and tumor necrosis factor-alpha, but not CRP, remained significant. These associations were similar across sex and race and persisted in models accounting for death as a competing event. Post-HF ejection fraction was available in 239 (76.8%) cases; inflammatory markers had stronger association with HF with preserved ejection fraction. Repeat IL-6 and CRP determinations at 1-year follow-up did not provide incremental information. Addition of IL-6 to the clinical Health ABC HF model improved model discrimination (C index from 0.717 to 0.734; p = 0.001) and fit (decreased Bayes information criterion by 17.8; p < 0.001). CONCLUSIONS: Inflammatory markers are associated with HF risk among older adults and may improve HF risk stratification.

Comparison of clinical and angiographic prognostic risk scores in elderly patients presenting with acute coronary syndrome and referred for percutaneous coronary intervention.

BACKGROUND: Multiple risk prediction models have been validated in all-age patients presenting with acute coronary syndrome (ACS) and treated with percutaneous coronary intervention (PCI); however, they have not been validated specifically in the elderly. METHODS: We calculated the GRACE (Global Registry of Acute Coronary Events) score, the logistic EuroSCORE, the AMIS (Acute Myocardial Infarction Swiss registry) score, and the SYNTAX (Synergy between Percutaneous Coronary Intervention with TAXUS and Cardiac Surgery) score in a consecutive series of 114 patients ≥75 years presenting with ACS and treated with PCI within 24 hours of hospital admission. Patients were stratified according to score tertiles and analysed retrospectively by comparing the lower/mid tertiles as an aggregate group with the higher tertile group. The primary endpoint was 30-day mortality. Secondary endpoints were the composite of death and major adverse cardiovascular events (MACE) at 30 days, and 1-year MACE-free survival. Model discrimination ability was assessed using the area under receiver operating characteristic curve (AUC). RESULTS: Thirty-day mortality was higher in the upper tertile compared with the aggregate lower/mid tertiles according to the logistic EuroSCORE (42% vs 5%; odds ratio [OR] = 14, 95% confidence interval [CI] = 4-48; p <0.001; AUC = 0.79), the GRACE score (40% vs 4%; OR = 17, 95% CI = 4-64; p <0.001; AUC = 0.80), the AMIS score (40% vs 4%; OR = 16, 95% CI = 4-63; p <0.001; AUC = 0.80), and the SYNTAX score (37% vs 5%; OR = 11, 95% CI = 3-37; p <0.001; AUC = 0.77). CONCLUSIONS: In elderly patients presenting with ACS and referred to PCI within 24 hours of admission, the GRACE score, the EuroSCORE, the AMIS score, and the SYNTAX score predicted 30 day mortality. The predictive value of clinical scores was improved by using them in combination.

Assessing the improved discriminatory power of a new biomarker in prognostic models

Although the area under the receiver operating characteristic (AUC) is the most popular measure of the performance of prediction models, it has limitations, especially when it is used to evaluate the added discrimination of a new biomarker in the model. Pencina et al. (2008) proposed two indices, the net reclassification improvement (NRI) and integrated discrimination improvement (IDI), to supplement the improvement in the AUC (IAUC). Their NRI and IDI are based on binary outcomes in case-control settings, which do not involve time-to-event outcome. However, many disease outcomes are time-dependent and the onset time can be censored. Measuring discrimination potential of a prognostic marker without considering time to event can lead to biased estimates. In this dissertation, we have extended the NRI and IDI to survival analysis settings and derived the corresponding sample estimators and asymptotic tests. Simulation studies were conducted to compare the performance of the time-dependent NRI and IDI with Pencina’s NRI and IDI. For illustration, we have applied the proposed method to a breast cancer study.^ Key words: Prognostic model, Discrimination, Time-dependent NRI and IDI ^

Design strategies for controlling the molecular weight and rate using reversible addition-fragmentation chain transfer mediated living radical polymerization

Living radical polymerization has allowed complex polymer architectures to be synthesized in bulk, solution, and water. The most versatile of these techniques is reversible addition-fragmentation chain transfer (RAFT), which allows a wide range of functional and nonfunctional polymers to be made with predictable molecular weight distributions (MWDs), ranging from very narrow to quite broad. The great complexity of the RAFT mechanism and how the kinetic parameters affect the rate of polymerization and MWD are not obvious. Therefore, the aim of this article is to provide useful insights into the important kinetic parameters that control the rate of polymerization and the evolution of the MWD with conversion. We discuss how a change in the chain-transfer constant can affect the evolution of the MWD. It is shown how we can, in principle, use only one RAFT agent to obtain a poly-mer with any MWD. Retardation and inhibition are discussed in terms of (1) the leaving R group reactivity and (2) the intermediate radical termination model versus the slow fragmentation model. (c) 2005 Wiley Periodicals, Inc.

Bayesian population pharmacokinetic analysis of sirolimus

Objective: It is usual that data collected from routine clinical care is sparse and unable to support the more complex pharmacokinetic (PK) models that may have been reported in previous rich data studies. Informative priors may be a pre-requisite for model development. The aim of this study was to estimate the population PK parameters of sirolimus using a fully Bayesian approach with informative priors. Methods: Informative priors including prior mean and precision of the prior mean were elicited from previous published studies using a meta-analytic technique. Precision of between-subject variability was determined by simulations from a Wishart distribution using MATLAB (version 6.5). Concentration-time data of sirolimus retrospectively collected from kidney transplant patients were analysed using WinBUGS (version 1.3). The candidate models were either one- or two-compartment with first order absorption and first order elimination. Model discrimination was based on computation of the posterior odds supporting the model. Results: A total of 315 concentration-time points were obtained from 25 patients. Most data were clustered at trough concentrations with range of 1.6 to 77 hours post-dose. Using informative priors, either a one- or two-compartment model could be used to describe the data. When a one-compartment model was applied, information was gained from the data for the value of apparent clearance (CL/F = 18.5 L/h), and apparent volume of distribution (V/F = 1406 L) but no information was gained about the absorption rate constant (ka). When a two-compartment model was fitted to the data, the data were informative about CL/F, apparent inter-compartmental clearance, and apparent volume of distribution of the peripheral compartment (13.2 L/h, 20.8 L/h, and 579 L, respectively). The posterior distribution of the volume distribution of central compartment and ka were the same as priors. The posterior odds for the two-compartment model was 8.1, indicating the data supported the two-compartment model. Conclusion: The use of informative priors supported the choice of a more complex and informative model that would otherwise have not been supported by the sparse data.

A model of gender prejudice, power, and discrimination: How hierarchy-enhancing factors predominate over hierarchy-attenuating factors

Gender inequalities remain an issue in our society and particularly in the workplace. Several factors can explain this gender difference in top-level managerial positions such as career ambitions but also biases against women. In our chapter, we propose a model explaining why gender inequalities and particularly discrimination against women is still present in our societies despite social norms and existing legislation on gender equality. To this purpose, we review research on discrimination through two different approaches, (a) a prejudice approach through the justification-suppression model developed by Crandall and Eshleman (2003) and (b) a power approach through the social dominance theory (Pratto, Sidanius, Stallworth, & Malle, 1994; Sidanius & Pratto, 1999). In our work, we integrate these two approaches and propose a model of gender prejudice, power and discrimination. The integration of these two approaches contributes to a better understanding of how discrimination against women is formed and maintained over time.

¿Puede un modelo educativo intercultural combatir la discriminación y la xenofobia? = Can an intercultural education model combat discrimination and xenophobia?

In this article we present a qualitative study conducted with six indigenous and six mestizos from Intercultural University of Chiapas. The aim of the study is to exemplify the mutual perception between different ethno-linguistic groups, as well as the possible change occurred after the admission to the University. That is, opinions about the other group after and before entering the University. We conclude that a higher education intercultural model can promote mutual understanding and relationship between indigenous and mestizos and thus combat prejudices and stereotypes

¿Puede un modelo educativo intercultural combatir la discriminación y la xenofobia? = Can an intercultural education model combat discrimination and xenophobia?

In this article we present a qualitative study conducted with six indigenous and six mestizos from Intercultural University of Chiapas. The aim of the study is to exemplify the mutual perception between different ethno-linguistic groups, as well as the possible change occurred after the admission to the University. That is, opinions about the other group after and before entering the University. We conclude that a higher education intercultural model can promote mutual understanding and relationship between indigenous and mestizos and thus combat prejudices and stereotypes

Discrimination of production environments of specialty coffees by means of stable isotopes and discriminant model

The south of Minas Gerais, Brazil stands out among various regions through its capacity for production of specialty coffees. Its potential, manifested through being one of the most award-winning Brazilian regions in recent years, has been recognized by the Cup of Excellence (COE). With the evident relationship between product quality and the environment in mind, the need arises for scientific studies to provide a foundation for discrimination of product origin, creating new methods for combating possible fraud. The aim of this study was to evaluate the use of carbon and nitrogen isotopes in discrimination of production environments of specialty coffees from the Serra da Mantiqueira of Minas Gerais by means of the discriminant model. Coffee samples were composed of ripe yellow and red fruits collected manually at altitudes below 1,000 m, from 1,000 to 1,200 m and above 1,200 m. The yellow and red fruits were subjected to dry processing and wet processing, with five replications. A total of 119 samples were used for discrimination of specialty coffee production environments by means of stable isotopes and statistical modeling. The model generated had an accuracy rate of 89% in discrimination of environments and was composed of the isotope variables of δ15N, δ13C, %C, %N, δD, δ18O (meteoric water) and sensory analysis scores. In addition, for the first time, discrimination of environments on a local geographic scale, within a single municipality, was proposed and successfully concluded. This shows that isotope analysis is an effective method in verifying geographic origin for specialty coffees.