A PAUC-based Estimation Technique for Disease Classification and Biomarker Selection.

The partial area under the receiver operating characteristic curve (PAUC) is a well-established performance measure to evaluate biomarker combinations for disease classification. Because the PAUC is defined as the area under the ROC curve within a restricted interval of false positive rates, it enables practitioners to quantify sensitivity rates within pre-specified specificity ranges. This issue is of considerable importance for the development of medical screening tests. Although many authors have highlighted the importance of PAUC, there exist only few methods that use the PAUC as an objective function for finding optimal combinations of biomarkers. In this paper, we introduce a boosting method for deriving marker combinations that is explicitly based on the PAUC criterion. The proposed method can be applied in high-dimensional settings where the number of biomarkers exceeds the number of observations. Additionally, the proposed method incorporates a recently proposed variable selection technique (stability selection) that results in sparse prediction rules incorporating only those biomarkers that make relevant contributions to predicting the outcome of interest. Using both simulated data and real data, we demonstrate that our method performs well with respect to both variable selection and prediction accuracy. Specifically, if the focus is on a limited range of specificity values, the new method results in better predictions than other established techniques for disease classification

A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments

In this study we propose a deformation-based framework to jointly model the influence of aging and Alzheimer's disease (AD) on the brain morphological evolution. Our approach combines a spatio-temporal description of both processes into a generative model. A reference morphology is deformed along specific trajectories to match subject specific morphologies. It is used to define two imaging progression markers: 1) a morphological age and 2) a disease score. These markers can be computed locally in any brain region. The approach is evaluated on brain structural magnetic resonance images (MRI) from the ADNI database. The generative model is first estimated on a control population, then, for each subject, the markers are computed for each acquisition. The longitudinal evolution of these markers is then studied in relation with the clinical diagnosis of the subjects and used to generate possible morphological evolution. In the model, the morphological changes associated with normal aging are mainly found around the ventricles, while the Alzheimer's disease specific changes are more located in the temporal lobe and the hippocampal area. The statistical analysis of these markers highlights differences between clinical conditions even though the inter-subject variability is quiet high. In this context, the model can be used to generate plausible morphological trajectories associated with the disease. Our method gives two interpretable scalar imaging biomarkers assessing the effects of aging and disease on brain morphology at the individual and population level. These markers confirm an acceleration of apparent aging for Alzheimer's subjects and can help discriminate clinical conditions even in prodromal stages. More generally, the joint modeling of normal and pathological evolutions shows promising results to describe age-related brain diseases over long time scales.Comment: NeuroImage, Elsevier, In pres

Estimating prognosis in patients with acute myocardial infarction using personalized computational heart models

Biomechanical computational models have potential prognostic utility in patients after an acute ST-segment–elevation myocardial infarction (STEMI). In a proof-of-concept study, we defined two groups (1) an acute STEMI group (n = 6, 83% male, age 54 ± 12 years) complicated by left ventricular (LV) systolic dysfunction; (2) an age- and sex- matched hyper-control group (n = 6, 83% male, age 46 ± 14 years), no prior history of cardiovascular disease and normal systolic blood pressure (SBP < 130 mmHg). Cardiac MRI was performed in the patients (2 days & 6 months post-STEMI) and the volunteers, and biomechanical heart models were synthesized for each subject. The candidate parameters included normalized active tension (ATnorm) and active tension at the resting sarcomere length (Treq, reflecting required contractility). Myocardial contractility was inversely determined from personalized heart models by matching CMR-imaged LV dynamics. Compared with controls, patients with recent STEMI exhibited increased LV wall active tension when normalized by SBP. We observed a linear relationship between Treq 2 days post-MI and global longitudinal strain 6 months later (r = 0.86; p = 0.03). Treq may be associated with changes in LV function in the longer term in STEMI patients complicated by LV dysfunction. Further studies seem warranted

Challenges in the Pharmacokinetics of Therapeutic Proteins

Due to the complex structure and complicated disposition pattern of therapeutic macromolecules, their pharmacokinetic interpretation has many challenges. Two of these challenges were investigated in this dissertation: 1) the error of classical bioavailability assessment observed during subcutaneous (SC) administration of therapeutic macromolecules that undergo target-mediated drug disposition (TMDD) and 2) the ontogeny of the neonatal Fc receptor (FcRn) expression along with its effect on the pharmacokinetics of monoclonal antibodies (mAbs) during development. TMDD often well describes the pharmacokinetics of therapeutic proteins that have high specificity and affinity of binding to their target receptors. The target receptors can be saturated by therapeutic proteins under therapeutic concentration due to their limited expression and availability in the body. Consequently, clearance through this pathway will reach its maximum and nonlinear pharmacokinetics will be observed upon further increasing dose if TMDD is a major elimination process. This, in turn, will impact the bioavailability estimation. Bioavailability estimations based on the classic AUC approach can be erroneous in this situation, mainly due to the incorrect assumption of dose-independent constant clearance that cannot be applied to therapeutic proteins that undergo TMDD. To shed light on this issue, a simulation study was performed with two model drugs: filgrastim and denosumab. Their published structural pharmacokinetic models and model parameters were employed in the simulations of plasma concentration-time profiles at different IV and SC doses. The bioavailability was calculated as the ratio of dose-normalized AUC after SC administration to that after IV administration. The overestimation was extreme when high SC and low IV doses of both protein drugs were used for the estimations, whereas excessive underestimation was observed with the combination of low SC and high IV doses. These biases in the bioavailability estimation resulted from the transition from low plasma concentration (at low doses) to high plasma concentration (at high doses), which shifted the major elimination pathway from TMDD to the unspecific linear clearance pathway. The changes in clearance resulted in parallel changes in dosenormalized AUCs and were very dynamic in the dose range of 0.1 – 5 µg/kg for filgrastim and below 60 mg for denosumab; thus caution is necessary when bioavailability of these two therapeutic proteins is estimated in these dose ranges using conventional method. To minimize the error of conventional bioavailability estimation of protein drugs that undergo TMDD, the bioavailability should be estimated at similar IV and SC doses or the assessment should be performed in dose ranges that yield constant dose-normalized AUCs (0.01 – 0.1 µg/kg or 5 – 10000 µg/kg for filgrastim, and 60 – 210 mg for denosumab). Moreover, an alternative estimation method could be applied, which determines the ratio of IV and SC doses that generate equally shaped concentration-time profile by applying a variable rate IV infusion, thereby resulting in equal AUCs as suggested by others. FcRn has been evidenced as a salvage pathway from lysosomal clearance for mAbs and Fc conjugated proteins; thus it can prolong the existence of these protein drugs in systemic circulation. The ontogeny of FcRn expression and its effect on the pharmacokinetics of mAbs should be of special concern if therapeutic mAbs are used in both pediatrics and adults. The down-regulation of FcRn during the development may shortened the half-life of therapeutic mAbs observed in adults. To address this problem, FcRn expression was quantified in various organs of C57BL/6J mice from postnatal days 2 through 70, the pharmacokinetics of AMG589 were studied in different age groups of C57BL/6J mice, and the correlation between the FcRn expression levels and the pharmacokinetics of AMG589 at various developmental stages of mice were explored using a nonlinear-mixed effects modeling-based population pharmacokinetic approach. FcRn showed ontogenetic changes in liver, lungs, and kidneys. Two-fold increases in FcRn expression were observed in liver and lungs of 10-day-old mice, whereas FcRn expression in the kidneys was doubled in 10- and 42-day-old mice. However, the ontogeny of FcRn expression could not be correlated to the prolonged persistence of AMG589 observed in 42 day old mice. A population pharmacokinetic approach revealed that after accounting for the effect of body weight by allometric scaling, age and FcRn expression in skin influenced the pharmacokinetics of AMG589 in different age groups of mice. Decreasing volume of distribution of AMG589 was observed during development. Interestingly, clearance of AMG589 was negatively correlated with the expression of FcRn in the skin, even though FcRn expression in skin did not show any ontogeny. These results suggest that body weight, age, and FcRn expression in skin could affect the pharmacokinetics of fully-human mAbs. However, regardless of the species difference in physiology, body weight should be considered during dosage regimen design, especially for pediatric patients who show a highly dynamic change in body size at early age. In summary, the findings in this dissertation have pointed out the weakness of the classical bioavailability estimation for protein drugs that undergo TMDD and have determined the factors that should be considered for dose adjustments of therapeutic mAbs in different-aged populations

Improving the mapping of condition-specific health-related quality of life onto SF-6D score

Background This study sought to improve the predictive performance and goodness-of-fit of mapping models, as part of indirect valuation, by introducing cubic spline smoothing to map a group of health-related quality of life (HRQOL) measures onto a preference-based measure. Methods This study was a secondary analysis of a cross-sectional health survey data assessing the HRQOL for patients with colorectal neoplasms. Mapping functions of condition-specific functional assessment of cancer therapy—colorectal (FACT-C) onto preference-based SF-6D measure were developed using a dataset of 553 Chinese subjects with different stages of colorectal neoplasm. The missing values of FACT-C were imputed using multiple imputation. Then three widely applicable models (ordinary least square (OLS), Tobit and two-part models) were employed for the mapping function after applying the cubic spline smoothing on the data. For the evaluation of the effectiveness of cubic spline smoothing and multiple imputation, the goodness-of-fit and prediction performance of each model were compared. Results Analyses showed that the models fitted with transformed data from cubic spline smoothing offered better performance in goodness-of-fit and prediction than the models fitted with the original data. The values of $R^2$ were improved by over 10 %, and the root mean square error and the mean absolute error were both reduced. The best goodness-of-fit and performance were achieved by OLS model using transformed data from cubic spline smoothing. Conclusions Cubic spline smoothing and multiple imputation were recommended for the mapping of HRQOL measures onto the preference-based measure. Among the three mapping models, the simple-to-use OLS model had the best performance.postprin

Explorations into Appendicular Ontogeny using a Cross-Sectional, Contemporary U.S. Sample

Investigations into the subadult skeleton have been restricted by sample availability in biological anthropology. Alternatively, the same source of longitudinal data has been repeatedly used, which does not reflect the variability of growth and development (i.e., ontogeny) or the United States (U.S.) population. Small and/or homogenous samples have often resulted in limited or inappropriate modeling choices to investigate the growth and development and variation of the subadult skeleton. Recent technological advancements have made virtual anthropology possible. The use of computed tomography (CT) scans has opened the doors to increasing sample sizes of minority groups and in turn increasing the variation of skeletal information. One repository, the Subadult Virtual Anthropology Database (SVAD), has focused on increasing and diversifying subadult skeletal data to increase the possibilities of subadult research in biological anthropology. The articles in this (non)dissertation collection use the SVAD (M=610, F=416) and the Forensic Anthropology Data Bank (FDB; M=285, F=161) to evaluate three different perspectives of appendicular (i.e., long bone) ontogeny: absolute, relative, and index. First, relative long bone lengths and nonlinear modeling are used as the first-ever evaluation of long bone growth through adult stabilization. Second, the brachial and crural indices are used to explore the chronological ontogenetic trajectories of each index and their ecogeographic patterns. Third, absolute long bone breadth and length measurements are used to create linear and nonlinear equations for estimating subadult stature for forensic application. In doing so, this is the first comprehensive collection of studies that explore three distinct perspectives of long bone ontogeny and variation from the same source of subadult skeletal data, demonstrating the need for additional contemporary subadult samples and novel modeling approaches