Competing Risks Analysis of the Finnish Diabetes Prevention Study.

Clinical studies often observe one interesting event in the presence of other competing events. When both types of events can occur at any time but are only observed at clinical visits (i.e.

Limited Sampling Strategies to Predict Mycophenolic Acid and Tacrolimus Area Under the Concentration-Time Curve in Steroid-Free Kidney Transplant Patients.

This study aimed to develop limited sampling strategies to predict oral mycophenolic acid (MPA) exposure from one to three blood samples in stable steroid-free kidney-transplanted patients and assess if the same scheme could predict tacrolimus exposure. Additionally, we aimed to validate existing strategies, and to describe the pharmacokinetics of MPA and its inactive metabolite, MPA-glucuronide (MPAG), in our cohort. We analysed data from dense pharmacokinetic sampling from 15 steroid-free kidney-transplanted patients, which were prospectively enrolled as part of larger cohort.

A Combined Model-Based Meta-Analysis of Aggregated and Individual FEV1 Data From Randomized COPD Trials.

Model-based meta-analysis allows integration of aggregated-level data (AD) from different clinical trials in one model to assess population efficacy/safety. However, AD is limited in individual-level information, while individual-patient-level data (IPD) are hard to obtain. Combined modeling may take advantage of both sources.

Modeling of Disease Progression of Type 2 Diabetes Using Real-World Data: Quantifying Competing Risks of Morbidity and Mortality.

Type 2 diabetes (T2D) is a progressive metabolic disorder that could be an underlying cause of long-term complications that increase mortality. The assessment of the probability of such events could be essential for mortality risk management. This work aimed to establish a framework for risk predictions of macrovascular complications (MVC) and diabetic kidney disease (DKD) in patients with T2D, using real-world data from the Swedish National Diabetes Registry (NDR), in the presence of mortality as a competing risk.

Item response theory analysis of daytime sleepiness as a symptom of obstructive sleep apnea.

Obstructive sleep apnea (OSA) is a sleep disorder which is linked to many health risks. The gold standard to evaluate OSA in clinical trials is the Apnea-Hypopnea Index (AHI). However, it is time-consuming, costly, and disregards aspects such as quality of life.

Evaluation of covariate effects in item response theory models.

Item response theory (IRT) models are usually the best way to analyze composite or rating scale data. Standard methods to evaluate covariate or treatment effects in IRT models do not allow to identify item-specific effects. Finding subgroups of patients who respond differently to certain items could be very important when designing inclusion or exclusion criteria for clinical trials, and aid in understanding different treatment responses in varying disease manifestations.

Evaluation of postprandial total triglycerides within the TIGG model for characterizing postprandial response of glucose, insulin, and GLP-1.

The TIGG model is the first model to integrate glucose and insulin regulation, incretin effect, and triglyceride (TG) response in the lipoprotein subclasses of chylomicrons and VLDL-V6. This model described the response following a high-fat meal in individuals who are lean, obese, and very obese and provided insights into the possible regulation of glucose homeostasis in the extended period following a meal. Often, total TGs are analyzed within clinical studies, instead of lipoprotein subclasses.

Optimal dosing of gliclazide-A model-based approach.

Gliclazide was approved as a treatment for type 2 diabetes in an era before model-based drug development, and consequently, the recommended doses were not optimised with modern methods. To investigate various dosing regimens of gliclazide, we used publicly available data to characterise the dose-response relationship using pharmacometric models. A literature search identified 21 published gliclazide pharmacokinetic (PK) studies with full profiles.

Altered glucose-dependent secretion of glucagon and ACTH is associated with insulin resistance, assessed by population analysis.

This study aimed to characterize how the dysregulation of counter-regulatory hormones can contribute to insulin resistance and potentially to diabetes. Therefore, we investigated the association between insulin sensitivity and the glucose- and insulin-dependent secretion of glucagon, adrenocorticotropic hormone (ACTH), and cortisol in non-diabetic individuals using a population model analysis. Data, from hyperinsulinemic-hypoglycemic clamps, were pooled for analysis, including 52 individuals with a wide range of insulin resistance (reflected by glucose infusion rate 20-60 min; GIR20-60min).

Pharmacometric modeling of drug adverse effects: an application of mixture models in schizophrenia spectrum disorder patients treated with clozapine.

Clozapine has superior efficacy to other antipsychotics yet is underutilized due to its adverse effects, such as neutropenia, weight gain, and tachycardia. The current investigation aimed to introduce a pharmacometric approach to simultaneously model drug adverse effects, with examples from schizophrenia spectrum patients receiving clozapine. The adverse drug effects were represented as a function of time by incorporating a mixture model to describe individual susceptibility to the adverse effects.

Optimization of trial duration to predict long-term HbA1c change with therapy: A pharmacometrics simulation-based evaluation.

Glycated hemoglobin (HbA1c) is the main biomarker of diabetes drug development. However, because of its delayed turnover, trial duration is rarely shorter than 12 weeks, and being able to predict long-term HbA1c with precision using data from shorter studies would be beneficial. The feasibility of reducing study duration was therefore investigated in this study, assuming a model-based analysis.

Impact of Obesity on Postprandial Triglyceride Contribution to Glucose Homeostasis, Assessed with a Semimechanistic Model.

The integrated glucose-insulin model is a semimechanistic model describing glucose and insulin after a glucose challenge. Similarly, a semiphysiologic model of the postprandial triglyceride (TG) response in chylomicrons and VLDL-V6 was recently published. We have developed the triglyceride-insulin-glucose-GLP-1 (TIGG) model by integrating these models and active GLP-1.

Linking categorical models for prediction of pleasantness score using individual predictions of sweetness and creaminess: An advancement of categorical modeling.

The aim of this work was to develop and evaluate approaches of linked categorical models using individual predictions of probability. A model was developed using data from a study which assessed the perception of sweetness, creaminess, and pleasantness in dairy solutions containing variable concentrations of sugar and fat. Ordered categorical models were used to predict the individual sweetness and creaminess scores and these individual predictions were used as covariates in the model of pleasantness response.

An Item Response Theory-Informed Strategy to Model Total Score Data from Composite Scales.

Composite scale data is widely used in many therapeutic areas and consists of several categorical questions/items that are usually summarized into a total score (TS). Such data is discrete and bounded by nature. The gold standard to analyse composite scale data is item response theory (IRT) models.

Postprandial triglyceride reduction following acute treatment of a selective 5-hydroxytryptamine-2c agonist and characterization using a semi-physiological model.

Aim: To investigate the tolerability, pharmacokinetics (PK) and postprandial triglyceride (TG) response of single, escalating oral doses of a selective 5-hydroxytryptamine-2c (5-HT ) agonist in subjects with overweight/obesity and apply mechanistic population pharmacokinetic-pharmacodynamic modelling to identify a plausible drug mechanism of action.

Materials And Methods: This phase 1, single-centre, double-blind, randomized, placebo-controlled, four-period, two-alternating cohorts study evaluated single escalating oral doses ranging from 5 to 130 mg of LY2140112 (LY) in subjects with overweight/obesity (body mass index: 27-39 kg/m ). Postprandial TG response (total TG, chylomicrons and very low-density lipoprotein particles [VLDL]-V6) following a high-fat meal were assessed for 11 h postmeal for each dose level.

Comparison of Precision and Accuracy of Five Methods to Analyse Total Score Data.

Total score (TS) data is generated from composite scales consisting of several questions/items, such as the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). The analysis method that most fully uses the information gathered is item response theory (IRT) models, but these are complex and require item-level data which may not be available. Therefore, the TS is commonly analysed with standard continuous variable (CV) models, which do not respect the bounded nature of data.

Sweet/Fat Preference Taste in Subjects Who are Lean, Obese and Very Obese.

Purpose: This study assessed the perception of sweetness, creaminess, and pleasantness from a sweet/fat preference test in subjects who are lean (BMI: 19-25), obese (BMI: 30-33) or very obese (BMI: 34-40) using categorical modeling.

Methods: Subjects tasted 16 dairy solutions consisting of 0%, 3.5%, 11.

A Time-to-Event Model Relating Integrated Craving to Risk of Smoking Relapse Across Different Nicotine Replacement Therapy Formulations.

Smoking increases the risk of cancer and other diseases, causing an estimated 7 million deaths per year. Nicotine replacement therapy (NRT) reduces craving for smoking, therefore, increasing an individual's probability to remain abstinent. In this work, we for the first time quantitatively described the relationship between craving and smoking abstinence, using retrospectively collected data from 19 studies, including 3 NRT formulations (inhaler, mouth spray, and patch) and a combination of inhaler and patch.

Optimal Designs for Model-Based Assessment of Insulin Sensitivity and Glucose Effectiveness.

The integrated minimal model allows assessment of clinical diagnosis indices, for example, insulin sensitivity (S ) and glucose effectiveness (S ), from data of the insulin-modified intravenous glucose tolerance test (IVGTT), which is laborious with an intense sampling schedule, up to 32 samples. The aim of this study was to propose a more informative, although less laborious, IVGTT design to be used for model-based assessment of S and S . The IVGTT design was optimized simultaneously for all design variables: glucose and insulin infusion doses, time of glucose dose and start of insulin infusion, insulin infusion duration, sampling times, and number of samples.

Correction to: Evidence-Based Design of Fixed-Dose Combinations: Principles and Application to Pediatric Anti-Tuberculosis Therapy.

In the online supplementary.

Relating Nicotine Plasma Concentration to Momentary Craving Across Four Nicotine Replacement Therapy Formulations.

Tobacco use is a major health concern. To assist smoking cessation, nicotine replacement therapy (NRT) is used to reduce nicotine craving. We quantitatively described the relationship between nicotine pharmacokinetics (PKs) from NRTs and momentary craving, linking two different pharmacodynamic (PD) scales for measuring craving.

A Bounded Integer Model for Rating and Composite Scale Data.

Rating and composite scales are commonly used to assess treatment efficacy. The two main strategies for modelling such endpoints are to treat them as a continuous or an ordered categorical variable (CV or OC). Both strategies have disadvantages, including making assumptions that violate the integer nature of the data (CV) and requiring many parameters for scales with many response categories (OC).