Disease Progression and Pharmacodynamics in Parkinson Disease – Evidence for Functional Protection with Levodopa and Other Treatments

Quantitative comparison of different inhaled corticosteroids in the treatment of asthma in children

BACKGROUND

The GINA recommends inhaled corticosteroids (ICSs) for the treatment of steps 2-3 of childhood asthma. However, the difference in efficacy between these drugs remains unclear. The purpose of this study was to compare the efficacy of different ICS drugs in the treatment of childhood asthma.

METHODS

We searched PubMed and EMBASE for randomized controlled trials of ICSs in the treatment of childhood asthma. Using forced expiratory volume in the first second (FEV₁) as the primary outcome, a time-course model of ICSs was constructed. In addition, the symptom-free days% were analyzed as a secondary outcome.

RESULTS

Six studies involving 2237 children that reported FEV₁ were included. The results showed that the ET50 of ciclesonide (CIC) and budesonide (BUD) was 1.23 and 2.97 weeks, respectively. Compared with them, FP had a higher efficacy. In terms of symptom-free days%, we found that the efficacy of beclometasone dipropionate was lower than that of CIC and fluticasone propionate.

CONCLUSION

In this study, the efficacy of three ICS drugs was quantitatively compared, providing necessary information for the implementation of medication guidelines for steps 2-3 of asthma in children.

IMPACT

This study analyzed the entire time-course of the drug efficacy of Inhaled corticosteroids in the treatment of asthma in children aged 5-12, which found that although the maximum efficacy of both ciclesonide and budesonide was the same, the onset speed of ciclesonide was faster than that of budesonide. The above information provides the necessary quantitative information for the implementation of medication guidelines for steps 2-3 asthma in children.

Whether Immunostimulants Are Effective in Susceptible Children Suffering From Recurrent Respiratory Tract Infections: A Modeling Analysis Based on Literature Aggregate Data

Immunostimulants are gradually being used in the prevention and treatment of recurrent respiratory tract infections in susceptible children, but their drug effects have not been quantified. The purpose of this study was to confirm the efficacy of immunostimulants in the prevention and treatment of recurrent respiratory tract infections in susceptible children. A model-based meta-analysis was used to describe the time course of placebo and immunostimulants in the prevention of respiratory tract infections in children. The cumulative number of respiratory tract infections was used as an indicator of efficacy. A meta-analysis was used to analyze the incidence of drug-related adverse events. Fourteen articles with 2400 pediatric subjects were finally included in the analysis. The results showed that the cumulative number of respiratory tract infections increased linearly with time, with the incidence of respiratory tract infections in the placebo group being 0.65 (95% confidence interval [CI], 0.55-0.75) per month. OM-85 BV and pidotimod reduced the incidence of respiratory tract infections by 0.21 (95%CI, 0.16-0.26) and 0.19 (95%CI, 0.17-0.21) compared to placebo per month, respectively. Pidotimod and OM-85 BV can effectively reduce the incidence of respiratory tract infections in susceptible children, with no significant increase in the incidence of drug-related adverse events when compared with placebo (risk ratio values were 1.07 [95%CI, 0.66-1.71] and 1.31 [95%CI, 0.54-3.19], respectively). This study provides quantitative support for the application of immunostimulants for the prevention of recurrent respiratory tract infections in children.

cLRT-Mod: An efficient methodology for pharmacometric model-based analysis of longitudinal phase II dose finding studies under model uncertainty

Within the challenging context of phase II dose-finding trials, longitudinal analyses may increase drug effect detection power compared to an end-of-treatment analysis. This work proposes cLRT-Mod, a pharmacometric adaptation of the MCP-Mod methodology, which allows the use of nonlinear mixed effect models to first detect a dose-response signal and then identify the doses for the confirmatory phase while accounting for model structure uncertainty. The method was evaluated through extensive clinical trial simulations of a hypothetical phase II dose-finding trial using different scenarios and comparing different methods such as MCP-Mod. The results show an increase in power using cLRT with longitudinal data compared to an EOT multiple contrast tests for scenarios with small sample size and weak drug effect while maintaining pre-specifiability of the models prior to data analysis and the nominal type I error. This work shows how model averaging provides better coverage probability of the drug effect in the prediction step, and avoids under-estimation of the size of the confidence interval. Finally, for illustration purpose cLRT-Mod was applied to the analysis of a real phase II dose-finding trial.

An integrative model of Parkinson's disease treatment including levodopa pharmacokinetics, dopamine kinetics, basal ganglia neurotransmission and motor action throughout disease progression

Levodopa is considered the gold standard treatment of Parkinson's disease. Although very effective in alleviating symptoms at their onset, its chronic use with the progressive neuronal denervation in the basal ganglia leads to a decrease in levodopa's effect duration and to the appearance of motor complications. This evolution challenges the establishment of optimal regimens to manage the symptoms as the disease progresses. Based on up-to-date pathophysiological and pharmacological knowledge, we developed an integrative model for Parkinson's disease to evaluate motor function in response to levodopa treatment as the disease progresses. We combined a pharmacokinetic model of levodopa to a model of dopamine's kinetics and a neurocomputational model of basal ganglia. The parameter values were either measured directly or estimated from human and animal data. The concentrations and behaviors predicted by our model were compared to available information and data. Using this model, we were able to predict levodopa plasma concentration, its related dopamine concentration in the brain and the response performance of a motor task for different stages of disease.

Dopamine Buffering Capacity Imaging: A Pharmacodynamic fMRI Method for Staging Parkinson Disease

We propose a novel pharmacological fMRI (phMRI) method for objectively quantifying disease severity in Parkinson disease (PD). It is based on the clinical observation that the benefit from a dose of levodopa wears off more quickly as PD progresses. Biologically this has been thought to represent decreased buffering capacity for dopamine as nigrostriatal cells die. Buffering capacity has been modeled based on clinical effects, but clinical measurements are influenced by confounding factors. The new method proposes to measure the effect objectively based on the timing of the known response of several brain regions to exogenous levodopa. Such responses are robust and can be quantified using perfusion MRI. Here we present simulation studies based on published clinical dose-response data and an intravenous levodopa infusion. Standard pharmacokinetic-pharmacodynamic methods were used to model the response. Then the effect site rate constant k e was estimated from simulated response data plus Gaussian noise. Predicted time - effect curves sampled at times consistent with phMRI differ substantially based on clinical severity. Estimated k e from noisy input data was recovered with good accuracy. These simulation results support the feasibility of levodopa phMRI hysteresis mapping to measure the severity of dopamine denervation objectively and simultaneously in all brain regions with a robust imaging response to exogenous levodopa.

Model-based meta-analysis of individual International Prostate Symptom Score trajectories in patients with benign prostatic hyperplasia with moderate or severe symptoms

Aims

International Prostate Symptom Score (IPSS) is a marker of lower urinary tract symptoms (LUTS) deterioration or improvement in benign prostate hyperplasia (BPH). Whereas changes in IPSS relative to baseline have been used as endpoints in clinical trials, little attention has been given to the time course of symptoms. The current investigation aimed to develop a drug‐disease model to describe individual IPSS trajectories in moderate and severe BPH patients.

Methods

A model‐based meta‐analytical approach was used including data from 10 238 patients enrolled into Phase III and IV studies receiving placebo, tamsulosin, dutasteride or combination therapy over a period of up to 4 years. Model predictive performance was assessed using statistical and graphical criteria. Subsequently, simulations were performed to illustrate the implications of treatment with drugs showing symptomatic and disease‐modifying properties in patients with varying disease progression rates.

Results

Improvement and worsening of IPSS could be characterized by a model including a sigmoid function which disentangles drug effects from placebo and varying disease progression rates on IPSS. Mean estimate (95% confidence intervals) for the disease progression rate was 0.319 (0.271–0.411) month⁻¹. Treatment effect on IPSS (DELTA) was found to be 0.0605, 0.0139 and 0.0310 month⁻¹ for placebo, tamsulosin and combination therapy, respectively. In addition, it appears that individual trajectories can be clustered together into different phenotypes describing the underlying disease progression rate (i.e. slow, moderate and fast progressors).

Conclusions

The availability of a drug‐disease model enables the evaluation of interindividual differences in disease progression rate, deterioration of symptoms and treatment effects on LUTS/BPH.

Treatment response and disease progression

This tutorial defines the concepts of disease progression in the context of clinical pharmacology. Disease progression describes the natural history of disease, such as pain, or biomarker of drug response, such as blood pressure. The action of a drug, such as inhibiting an enzyme or activating a receptor, leads to a change in disease status over time. Two main types of drug response can be defined based on the pattern of the time course of disease status. The most common is a symptomatic effect equivalent to a shift up or down of the natural history curve. Less common but quite clinically important is a disease-modifying effect equivalent to a change in the rate of disease progression.

Is It Possible to Conduct a Multi-Arm Multi-Stage Platform Trial in Parkinson's Disease: Lessons Learned from Other Neurodegenerative Disorders and Cancer

Many potential disease modifying therapies have been identified as suitable for clinical evaluation in Parkinson's disease (PD). Currently, the evaluation of compounds in phase II and phase III clinical trials in PD are set up in isolation, a process that is lengthy, costly and lacks efficiency. This review will introduce the concept of a multi-arm, multi-stage (MAMS) trial platform which allows for the assessment of several potential therapies at once, transitioning seamlessly from a phase II safety and efficacy study to a phase III trial by means of an interim analysis. At the interim checkpoint, ineffective arms are dropped and replaced by new treatment arms, thereby allowing for the continuous evaluation of interventions. MAMS trial platforms already exist for prostate, renal and oropharyngeal cancer and are currently being developed for progressive multiple sclerosis (PMS) and motor neuron disease (MND) within the UK. As a MAMS trial will evaluate many potential treatments it is of critical importance that a widely endorsed core protocol is developed which will investigate outcomes and objectives meaningful to patients. This review will discuss the challenges of drug selection, trial design, stratification and outcome measures and will share strategies implemented in the planned MAMS trials for MND and PMS that may be of interest to the PD field.

Quantitative analysis of the placebo response in pharmacotherapy of insomnia and its application in clinical trials

Study Objectives

This study aimed to develop a robust placebo response model for the pharmacotherapy for insomnia to guide drug development and clinical practice.

Methods

PubMed, EMBASE, and Cochrane Library databases were systematically searched for randomized placebo-controlled trials of medications for insomnia dating from the inception dates of the databases to April 18, 2018. Three placebo response models were established to describe the time–course of sleep parameters measured by objective (polysomnography or actigraphy) or subjective methods (sleep diary or questionnaires). The established models were applied to simulate placebo response distribution under different conditions using Monte Carlo simulations.

Results

Fifty-four studies involving 6,416 subjects were included. Placebo response increased over time and reached a plateau at approximately 8 weeks from start of therapy. Established models described the observed data reasonably well based on various diagnostic plots. Baseline sleep parameters affected the placebo response. There were significant positive correlations with placebo response and the severity of sleep latency, wake after sleep onset, and total sleep time at baseline. In addition, placebo response, assessed by subjective and objective methods, was consistent after correcting the baseline levels.

Conclusions

The established placebo response models can serve as a tool to predict placebo response at different baseline levels, which can provide valuable reference for clinical trial design, decision-making in drug development, and clinical practice.

Item Response Model Adaptation for Analyzing Data from Different Versions of Parkinson's Disease Rating Scales

Purpose

The aim of this work was to allow combination of information from recent and historical trials in Parkinson’s Disease (PD) by developing bridging methodology between two versions of the clinical endpoint.

Methods

A previously developed Item Response Model (IRM), that described longitudinal changes in Movement Disorder Society (MDS) sponsored revision of Unified Parkinson’s Disease Rating Scale (UPDRS) [MDS–UPDRS] data from the De Novo PD cohort in Parkinson’s Progression Markers Initiative, was first adapted to describe baseline UPDRS data from two clinical trials, one in subjects with early PD and another in subjects with advanced PD. Assuming similar IRM structure, items of the UPDRS version were mapped to those in the MDS-UPDRS version. Subsequently, the longitudinal changes in the placebo arm of the advanced PD study were characterized.

Results

The parameters reflecting differences in the shared items between endpoints were successfully estimated, and the model diagnostics indicated that mapping was better for early PD subjects (closer to De Novo cohort) than for advanced PD subjects. Disease progression for placebo in advanced PD patients was relatively shallow.

Conclusion

An IRM able to handle two variants of clinical PD endpoints was developed; it can improve the utilization of data from diverse sources and diverse disease populations.

Electronic supplementary material

The online version of this article (10.1007/s11095-019-2668-6) contains supplementary material, which is available to authorized users.

Impact of disease progression on individual IPSS trajectories and consequences of immediate versus delayed start of treatment in patients with moderate or severe LUTS associated with BPH

Purpose

Despite superiority of tamsulosin–dutasteride combination therapy versus monotherapy for lower urinary tract symptoms due to benign prostatic hyperplasia (LUTS/BPH), patients at risk of disease progression are often initiated on α-blockers. This study evaluated the impact of initiating tamsulosin monotherapy prior to switching to tamsulosin–dutasteride combination therapy versus immediate combination therapy using a longitudinal model describing International Prostate Symptom Score (IPSS) trajectories in moderate/severe LUTS/BPH patients at risk of disease progression.

Methods

Clinical trial simulations (CTS) were performed using data from 10,238 patients from Phase III/IV dutasteride trials. The effect of varying disease progression rates was explored by comparing profiles on- and off-treatment. CTS scenarios were investigated, including a reference (immediate combination therapy) and six alternative virtual treatment arms (delayed combination therapy of 1–24 months). Clinical response (≥ 25% IPSS reduction relative to baseline) was analysed using log-rank test. Differences in IPSS relative to baseline at various on-treatment time points were assessed by t tests.

Results

Delayed combination therapy initiation led to significant (p < 0.01) decreases in clinical response. At month 48, clinical response rate was 79.7% versus 74.1%, 70.3% and 71.0% and IPSS was 6.3 versus 7.6, 8.1 and 8.0 (switchers from tamsulosin monotherapy after 6, 12 and 24 months, respectively) with immediate combination therapy. More patients transitioned from severe/moderate to mild severity scores by month 48.

Conclusions

CTS allows systematic evaluation of immediate versus delayed combination therapy. Immediate response to α-blockers is not predictive of long-term symptom improvement. Observed IPSS differences between immediate and delayed combination therapy (6–24 months) are statistically significant.

Electronic supplementary material

The online version of this article (10.1007/s00345-019-02783-x) contains supplementary material, which is available to authorized users.

Developing and validating Parkinson's disease subtypes and their motor and cognitive progression

OBJECTIVES

To use a data-driven approach to determine the existence and natural history of subtypes of Parkinson's disease (PD) using two large independent cohorts of patients newly diagnosed with this condition.

METHODS

1601 and 944 patients with idiopathic PD, from Tracking Parkinson's and Discovery cohorts, respectively, were evaluated in motor, cognitive and non-motor domains at the baseline assessment. Patients were recently diagnosed at entry (within 3.5 years of diagnosis) and were followed up every 18 months. We used a factor analysis followed by a k-means cluster analysis, while prognosis was measured using random slope and intercept models.

RESULTS

We identified four clusters: (1)  fast motor progression with symmetrical motor disease, poor olfaction, cognition and postural hypotension; (2) mild motor and non-motor disease with intermediate motor progression; (3) severe motor disease, poor psychological well-being and  poor sleep with an intermediate motor progression; (4) slow motor progression with tremor-dominant, unilateral disease. Clusters were moderately to substantially stable across the two cohorts (kappa 0.58). Cluster 1 had the fastest motor progression in Tracking Parkinson's at 3.2 (95% CI 2.8 to 3.6) UPDRS III points per year while cluster 4 had the slowest at 0.6 (0.1-1.1). In Tracking Parkinson's, cluster 2 had the largest response to levodopa 36.3% and cluster 4 the lowest 28.8%.

CONCLUSIONS

We have found four novel clusters that replicated well across two independent early PD cohorts and were associated with levodopa response and motor progression rates. This has potential implications for better understanding disease pathophysiology and the relevance of patient stratification in future clinical trials.

Pharmacokinetics of Rytary®, An Extended-Release Capsule Formulation of Carbidopa-Levodopa

Parkinson's disease (PD) is a chronic progressive neurological disorder characterized by resting tremor, rigidity, bradykinesia, gait disturbance, and postural instability. Levodopa, the precursor to dopamine, coadministered with carbidopa or benserazide, aromatic amino acid decarboxylase inhibitors, is the most effective and widely used therapeutic agent in the treatment of PD. With continued levodopa treatment, a majority of patients develop motor complications such as dyskinesia and motor 'on-off' fluctuations, which are, in part, related to the fluctuations in plasma concentrations of levodopa. A new extended-release (ER) carbidopa-levodopa capsule product (also referred to as IPX066) was developed and approved in the US as Rytary^® and in the EU as Numient^®. The capsule formulation is designed to provide an initial rapid absorption of levodopa comparable to immediate-release (IR) carbidopa-levodopa, and to subsequently provide stable levodopa concentrations with reduced peak-to-trough excursions in plasma concentrations in order to reduce motor fluctuations associated with pulsatile stimulation of dopamine receptors and to minimize dyskinesia. Phase III studies of this ER carbidopa-levodopa capsule formulation in patients with PD have shown a significant reduction in 'off' time compared with IR carbidopa-levodopa and carbidopa-levodopa-entacapone. We present a review of the clinical pharmacokinetics and pharmacodynamics of this ER product of carbidopa-levodopa in healthy subjects and in patients with PD.

Can Interactions Between α-Synuclein, Dopamine and Calcium Explain Selective Neurodegeneration in Parkinson's Disease?

Several lines of evidence place alpha-synuclein (aSyn) at the center of Parkinson's disease (PD) etiology, but it is still unclear why overexpression or mutated forms of this protein affect some neuronal populations more than others. Susceptible neuronal populations in PD, dopaminergic neurons of the substantia nigra pars compacta (SNpc) and the locus coeruleus (LC), are distinguished by relatively high cytoplasmic concentrations of dopamine and calcium ions. Here we review the evidence for the multi-hit hypothesis of neurodegeneration, including recent papers that demonstrate synergistic interactions between aSyn, calcium ions and dopamine that may lead to imbalanced protein turnover and selective susceptibility of these neurons. We conclude that decreasing the levels of any one of these toxicity mediators can be beneficial for the survival of SNpc and LC neurons, providing multiple opportunities for targeted drug interventions aimed at modifying the course of PD.

Parkinson's Disease Severity at 3 Years Can Be Predicted from Non-Motor Symptoms at Baseline

Objective

The aim of this study is to present a predictive model of Parkinson’s disease (PD) global severity, measured with the Clinical Impression of Severity Index for Parkinson’s Disease (CISI-PD).

Methods

This is an observational, longitudinal study with annual follow-up assessments over 3 years (four time points). A multilevel analysis and multiple imputation techniques were performed to generate a predictive model that estimates changes in the CISI-PD at 1, 2, and 3 years.

Results

The clinical state of patients (CISI-PD) significantly worsened in the 3-year follow-up. However, this change was of small magnitude (effect size: 0.44). The following baseline variables were significant predictors of the global severity change: baseline global severity of disease, levodopa equivalent dose, depression and anxiety symptoms, autonomic dysfunction, and cognitive state. The goodness-of-fit of the model was adequate, and the sensitive analysis showed that the data imputation method applied was suitable.

Conclusion

Disease progression depends more on the individual’s baseline characteristics than on the 3-year time period. Results may contribute to a better understanding of the evolution of PD including the non-motor manifestations of the disease.

Progression of MDS-UPDRS Scores Over Five Years in De Novo Parkinson Disease from the Parkinson's Progression Markers Initiative Cohort

Background

The Movement Disorder Society Unified Parkinson Disease Rating Scale (MDS-UDPRS) is a commonly used tool to measure Parkinson disease (PD) progression. Longitudinal changes in MDS-UPDRS scores in de novo PD have not been established.

Objective

Determine progression rates of MDS-UPDRS scores in de novo PD.

Methods

362 participants from the Parkinson's Progression Markers Initiative, a multicenter longitudinal cohort study of de novo PD, were included. Longitudinal progression of MDS-UPDRS total and subscale scores were modeled using mixed model regression.

Results

MDS-UPDRS scores increased in a linear fashion over five years in de novo PD. MDS-UPDRS total score increased an estimated 4.0 points/year, Part I 0.25 points/year, Part II 1.0 points/year, and Part III 2.4 points/year.

Conclusions

The expected average progression of MDS-UPDRS scores in de novo PD from this study can assist in clinical monitoring and provide comparative data for detection of disease modification in treatment trials.

Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson's Disease Patients

PURPOSE

This manuscript aims to precisely describe the natural disease progression of Parkinson's disease (PD) patients and evaluate approaches to increase the drug effect detection power.

METHODS

An item response theory (IRT) longitudinal model was built to describe the natural disease progression of 423 de novo PD patients followed during 48 months while taking into account the heterogeneous nature of the MDS-UPDRS. Clinical trial simulations were then used to compare drug effect detection power from IRT and sum of item scores based analysis under different analysis endpoints and drug effects.

RESULTS

The IRT longitudinal model accurately describes the evolution of patients with and without PD medications while estimating different progression rates for the subscales. When comparing analysis methods, the IRT-based one consistently provided the highest power.

CONCLUSION

IRT is a powerful tool which enables to capture the heterogeneous nature of the MDS-UPDRS.

Quantitative analysis of efficacy and associated factors of calcium intake on bone mineral density in postmenopausal women

A model-based meta-analysis method was performed to quantitatively analyze the efficacy characteristics of calcium intake in BMD increase among postmenopausal women. We found that age and calcium intake dose were key factors affecting the efficiency and onset of BMD change, and daily 1200 mg calcium was suggested to be a beneficial dosage.

INTRODUCTION

This paper aims to quantify the efficacy of calcium intake in preventing bone mineral density (BMD) decrease among postmenopausal women and to investigate the factors that may affect the efficacy.

METHODS

Comprehensive literature search was conducted in PubMed and EMBASE from January 2016. Placebo-controlled or no-treatment controlled randomized trials focused on calcium intake for the management of osteoporosis in postmenopausal women were included. The clinical and demographic characteristics of participants and efficacy data, defined as the mean percentage change of spine BMD (L2-L4) at each observation time point compared with that of baseline, were extracted from the studies. Model-based meta-analysis (MBMA) was used to describe the time course of BMD change by calcium intake and identify the related factors.

RESULTS

This study includes 17 trials involving 2537 subjects. The results showed that a classic pharmacodynamic maximal effect (E _max) model could describe the time course of BMD change by calcium intake. Using this model, we found that age and calcium intake dose were key factors affecting the efficiency and onset of BMD change. A 60-year-old woman administered with 800 mg/day calcium can achieve a maximum BMD increasing rate of 2.38%, and the time to reach 50% of this maximum (known as onset time) was 9.44 months. An increase of 0.0817% per year was noted in the maximal effect value for women aged between 50 and 83 years. For calcium dose interval from 250 to 2000 mg/day, the onset time was expressed as 9.44 × (dose/800)^-1.33 months. Two-year calcium intake of 700, 1200, and 2000 mg/day resulted in a maximum efficacy of BMD of 68.0, 81.3, and 89.6%, respectively. This indicates that the final efficacy had already reached the plateau (>80% E _max) under the 1200-mg/day dose.

CONCLUSION

Calcium intake can effectively postpone the tendency of BMD decrease in postmenopausal women. An increased calcium dose contributes to the shortening of the onset time. Considering the drug-acting rate and safety into account, menopausal women can be administered with a rational dose of 1200 mg/day to reduce bone loss.

Modeling a Composite Score in Parkinson's Disease Using Item Response Theory

In the current work, we present the methodology for development of an Item Response Theory model within a non-linear mixed effects framework to characterize the longitudinal changes of the Movement Disorder Society (sponsored revision) of Unified Parkinson's Disease Rating Scale (MDS-UPDRS) endpoint in Parkinson's disease (PD). The data were obtained from Parkinson's Progression Markers Initiative database and included 163,070 observations up to 48 months from 430 subjects belonging to De Novo PD cohort. The probability of obtaining a score, reported for each of the items in the questionnaire, was modeled as a function of the subject's disability. Initially, a single latent variable model was explored to characterize the disease progression over time. However, based on the understanding of the questionnaire set-up and the results of a residuals-based diagnostic tool, a three latent variable model with a mixture implementation was able to adequately describe longitudinal changes not only at the total score level but also at each individual item level. The linear progression rates obtained for the patient-reported items and the non-sided items were similar, each of which roughly take about 50 months for a typical subject to progress linearly from the baseline by one standard deviation. However for the sided items, it was found that the better side deteriorates quicker than the disabled side. This study presents a framework for analyzing MDS-UPDRS data, which can be adapted to more traditional UPDRS data collected in PD clinical trials and result in more efficient designs and analyses of such studies.

Disease Progression Modeling: Key Concepts and Recent Developments

Disease modeling involves the use of mathematical functions to describe quantitatively the time course of disease progression. In order to characterize the natural progression of disease, these models generally incorporate longitudinal data for some biomarker(s) of disease severity or can incorporate more direct measures of disease severity. Disease models are also often linked to pharmacokinetic-pharmacodynamic models so that the influence of drug treatment on disease progression can be quantified and evaluated. Regulatory agencies have embraced disease progression models as powerful tools that can be used to improve drug development productivity. This article provides a brief overview of key concepts in disease progression modeling followed by illustrative examples from models for Alzheimer's disease. Finally, recent novel applications in which disease progression models have been linked to cost-effectiveness analysis and genomic analysis are described.

Dose-Response Analysis of the Effect of Carbidopa-Levodopa Extended-Release Capsules (IPX066) in Levodopa-Naive Patients With Parkinson Disease

Parkinson disease is an age-related disorder of the central nervous system principally due to loss of dopamine-producing cells in the midbrain. Levodopa, in combination with carbidopa, is widely regarded as an effective treatment for the symptoms of Parkinson disease. A dose-response relationship is established for carbidopa-levodopa extended-release capsules (IPX066) in levodopa-naive Parkinson disease patients using a disease progression model. Unified Parkinson Disease Rating Scale (UPDRS) part II plus part III scores from 171 North American patients treated with placebo or IPX066 for approximately 30 weeks from a double-blind, parallel-group, dose-ranging study were used to develop the pharmacodynamic model. The model comprised 3 components: a linear function describing disease progression, a component describing placebo (or nonlevodopa) effects, and a component to describe the effect of levodopa. Natural disease progression in early Parkinson disease as measured by UPDRS was 11.6 units/year and faster in patients with more severe disease (Hoehn-Yahr stage 3). Maximum placebo/nonlevodopa response was 23.0% of baseline UPDRS. Maximum levodopa effect from IPX066 was 76.7% of baseline UPDRS, and the ED50 was 450 mg levodopa. Equilibration half-life for the effect compartment was 62.8 days. Increasing age increased and being female decreased equilibration half-life. The quantitative model allowed description of the entire time course of response to clinical trial intervention.

A review of disease progression models of Parkinson's disease and applications in clinical trials

Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including "Parkinson disease," "progression," and "model." For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease-modifying treatment effects, and to demonstrate how model-based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model-based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. © 2016 International Parkinson and Movement Disorder Society.

The Natural Progression of Parkinson's Disease in a Small Cohort with 15 Drug-naïve Patients

BACKGROUND

The studies of the natural progression of Parkinson's disease (PD) in Chinese populations have been lacking. To address this issue and obtain a preliminary data, we conducted a PD progression assessment in 15 adults with de novo PD from a nutritional intervention trial (NIT) cohort in Lin County China.

METHODS

Using the Copiah County screening questionnaire and United Kingdom Parkinson's Disease Society Brain Bank diagnostic criteria, we surveyed the available NIT cohort members in 2000 and diagnosed 86 patients as PD. In 2010, we resurveyed all PD patients and confirmed definite PD diagnosis in 15 cases with the rest of them being dead (54); having probable (10) PD or vascular Parkinsonism (3); refusing to participate (2); or being away (2). In both surveys, we used Hoehn and Yahr (HY) scale and assessed the disease progression. Unified Parkinson's Disease Rating Scale (UPDRS) was added to the second survey.

RESULTS

In 2010, the average disease duration for 15 definite PD patients was 13.6 ± 7.3 years. Over a 10-year time span, 9 out of 15 patients remained at the same HY stage while the remaining 6 progressed. Rigidity (47% vs. 100%; P = 0.002) and postural instability (7% vs. 47%; P = 0.005) worsened significantly. The mean UPDRS motor scores in 2010 were 39.4 ± 23.7.

CONCLUSIONS

Overall worsening of motor function in PD seems to be the rule in this untreated cohort, and their rate of progression seemed to be slower than those reported in the western populations.

Early versus delayed initiation of pharmacotherapy in Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease and pathologically is characterised by a progressive loss of dopaminergic cells of the nigrostriatal pathway. Clinically, PD is mainly defined by the presence of the motor symptoms of bradykinesia, rigidity, rest tremor and postural instability, but non-motor symptoms such as depression, dementia and autonomic disturbances are recognised as integral parts of the disease. Although pharmacotherapy for PD was introduced almost 50 years ago, and has improved significantly over the intervening period, the timing of initiation of treatment in newly diagnosed PD remains controversial. While some physicians favour an early start of pharmacotherapy at or soon after diagnosis, others prefer to delay pharmacological treatment until a certain degree of disability has developed. This article aims to discuss the advantages and disadvantages of both strategies by exploring their effects on symptoms, disease progression and quality of life. Although the data on putative disease-modifying effects of early pharmacological intervention in PD are still inconclusive, we believe that the most important indication for an early initiation of anti-parkinsonian treatment should be to maintain the quality of life of PD patients and to secure their socioeconomic status as long as possible.

Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model

Although advantages of physiologically based pharmacokinetic models (PBPK) are now well established, PBPK models that are linked to pharmacodynamic (PD) models to predict pharmacokinetics (PK), PD, and efficacy of monoclonal antibodies (mAbs) in humans are uncommon. The aim of this study was to develop a PD model that could be linked to a physiologically based mechanistic FcRn model to predict PK, PD, and efficacy of efalizumab. The mechanistic FcRn model for mAbs with target-mediated drug disposition within the Simcyp population-based simulator was used to simulate the pharmacokinetic profiles for three different single doses and two multiple doses of efalizumab administered to virtual Caucasian healthy volunteers. The elimination of efalizumab was modeled with both a target-mediated component (specific) and catabolism in the endosome (non-specific). This model accounted for the binding between neonatal Fc receptor (FcRn) and efalizumab (protective against elimination) and for changes in CD11a target concentration. An integrated response model was then developed to predict the changes in mean Psoriasis Area and Severity Index (PASI) scores that were measured in a clinical study as an efficacy marker for efalizumab treatment. PASI scores were approximated as continuous and following a first-order asymptotic progression model. The reported steady state asymptote (Y ss) and baseline score [Y (0)] was applied and parameter estimation was used to determine the half-life of progression (T p) of psoriasis. Results suggested that simulations using this model were able to recover the changes in PASI scores (indicating efficacy) observed during clinical studies. Simulations of both single dose and multiple doses of efalizumab concentration-time profiles as well as suppression of CD11a concentrations recovered clinical data reasonably well. It can be concluded that the developed PBPK FcRn model linked to a PD model adequately predicted PK, PD, and efficacy of efalizumab.

Clinical pharmacology = disease progression + drug action

Clinical pharmacology is concerned with understanding how to use medicines to treat disease. Pharmacokinetics and pharmacodynamics have provided powerful methodologies for describing the time course of concentration and effect in individuals and in populations. This population approach may also be applied to describing the progression of disease and the action of drugs to change disease progress. Quantitative models for symptomatic and disease-modifying effects of drugs are valuable not only for describing drugs and diseases but also for identifying criteria to distinguish between types of drug actions, with implications for regulatory decisions and long-term patient care.

A time to event tutorial for pharmacometricians

Models for time to event provide the link between standard pharmacokinetic–dynamic models disease progression, and clinical outcome events. The biological basis for events may be expressed quantitatively in terms of a hazard function. This tutorial explains hazards and how doses can be linked to events predicted from hazard functions.

CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e43; doi:10.1038/psp.2013.18; advance online publication 15 May 2013

Comparisons of Analysis Methods for Proof-of-Concept Trials

Drug development struggles with high costs and time consuming processes. Hence, a need for new strategies has been accentuated by many stakeholders in drug development. This study proposes the use of pharmacometric models to rationalize drug development. Two simulated examples, within the therapeutic areas of acute stroke and type 2 diabetes, are utilized to compare a pharmacometric model-based analysis to a t-test with respect to study power of proof-of-concept (POC) trials. In all investigated examples and scenarios, the conventional statistical analysis resulted in several fold larger study sizes to achieve 80% power. For a scenario with a parallel design of one placebo group and one active dose arm, the difference between the conventional and pharmacometric approach was 4.3- and 8.4-fold, for the stroke and diabetes example, respectively. Although the model-based power depend on the model assumptions, in these scenarios, the pharmacometric model-based approach was demonstrated to permit drastic streamlining of POC trials.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e23; doi:10.1038/psp.2012.24; advance online publication 16 January 2013.

Progression of motor and nonmotor features of Parkinson's disease and their response to treatment

AIMS

(i) To describe the progression of the cardinal features of Parkinson's disease (PD); (ii) to investigate whether baseline PD subtypes explain disease progression; and (iii) to quantify the symptomatic and disease-modifying effects of anti-parkinsonian treatments.

METHODS

Data were available for 795 PD subjects, initially untreated, followed for up to 8 years. Cardinal features [tremor, rigidity, bradykinesia, and postural instability and gait disorder (PIGD)] were derived from the total unified Parkinson's disease rating scale (total UPDRS), cognitive status from the mini-mental status exam score (MMSE) and depression status from the Hamilton depression scale (HAM-D). Analysis was performed using a nonlinear mixed effects approach with an asymptotic model for natural disease progression. Treatment effects (i.e. symptomatic and disease modifying) were evaluated by describing changes in the natural history model parameters.

RESULTS

Tremor progressed more slowly (half-time of 3.9 years) than all other motor features (half-time 2-3 years). The MMSE progression was negligible, while HAM-D progressed with a half-time of 5 years. Levodopa had marked symptomatic effects on all features, but low potency for effect on PIGD (ED₅₀ of 1237 mg day⁻¹ compared with 7-24 mg day⁻¹ for other motor and nonmotor features). Other anti-parkinsonian treatments had much smaller symptomatic effects. All treatments had disease-modifying effects on the cardinal features of PD. Baseline PD subtypes only explained small differences in disease progression.

CONCLUSIONS

This analysis indicates that tremor progresses more slowly than other cardinal features and that PIGD is less treatment responsive in early PD patients. There was no evidence of baseline PD subtypes as a clinically useful predictor of disease progression rate. Anti-parkinsonian treatments have symptomatic and disease-modifying effects on all major features of PD.

Disease progress and response to treatment as predictors of survival, disability, cognitive impairment and depression in Parkinson's disease

AIM

To describe the time to clinical events (death, disability, cognitive impairment and depression) in Parkinson's disease using the time course of disease status and treatment as explanatory variables.

METHODS

Disease status based on the Unified Parkinson's Disease Rating Scale (UPDRS) and the time to clinical outcome events were obtained from 800 patients who initially had early Parkinson's disease. Parametric hazard models were used to describe the time to the events of interest.

RESULTS

Time course of disease status (severity) was an important predictor of clinical outcome events. There was an increased hazard ratio for death 1.4 (95% CI 1.31, 149), disability 2.75 (95% CI 2.30, 3.28), cognitive impairment 4.35 (95% CI 1.94, 9.74), and depressive state 1.43 (95% CI 1.26, 1.63) with each 10 unit increase of UPDRS. Age at study entry increased the hazard with hazard ratios of 49.1 (95% CI 8.7, 278) for death, 4.76 (95% CI 1.10, 20.6) for disability and 90.0 (95% CI 63.3-128) for cognitive impairment at age 60 years. Selegiline treatment had independent effects as a predictor of death at 8 year follow-up with a hazard ratio of 2.54 (95% CI 1.51, 4.25) but had beneficial effects on disability with a hazard ratio of 0.363 (95% CI 0.132, 0.533) and depression with a hazard ratio of 0.372 (95% CI 0.12, 0.552).

CONCLUSIONS

Our findings show that the time course of disease status based on UPDRS is a much better predictor of future clinical events than any baseline disease characteristic. Continued selegiline treatment appears to increase the hazard of death.

Influence of methotrexate on infliximab pharmacokinetics and pharmacodynamics in ankylosing spondylitis

AIMS

Infliximab, an anti-tumour necrosis factor α monoclonal antibody, has profoundly modified the treatment of several inflammatory diseases. The objective was to assess the influence of methotrexate on the variability of infliximab pharmacokinetics and concentration-effect relationship in axial ankylosing spondylitis (AAS) patients.

METHODS

Twenty-six patients with AAS were included in a prospective study. They were treated by infliximab 5 mg kg⁻¹ infusions at weeks 0, 2, 6, 12 and 18. Infliximab concentrations were measured before, and 2 and 4 h after each infusion, and at each intermediate visit (weeks 1, 3, 4, 5, 8, 10 and 14). Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) was measured at each visit. Infliximab pharmacokinetics was described using a two-compartment model with first-order distribution and elimination constants. A population approach was used. Infliximab pharmacodynamics was described using the area under the BASDAI curve.

RESULTS

A total of 507 blood samples and 329 BASDAI measurements were collected. The following pharmacokinetic parameters were obtained (interindividual coefficient of variation): volumes of distribution for the central compartment = 2.4 l (9.6%) and peripheral compartment = 1.8 l (26%), systemic clearance = 0.23 l day⁻¹ (22%) and intercompartment clearance = 2.3 l day⁻¹. Methotrexate influenced neither pharmacokinetic nor BASDAI variability.

CONCLUSIONS

Using the present dosage, the clinical efficacy of infliximab is only weakly influenced by its serum concentrations. The results do not support the combination of methotrexate with infliximab in ankylosing spondylitis.

Modelling and simulation in the pharmaceutical industry--some reflections

Modelling and simulation (M&S) is increasingly being applied in (clinical) drug development. It provides an opportune area for the community of pharmaceutical statisticians to pursue. In this article, we highlight useful principles behind the application of M&S. We claim that M&S should be focussed on decisions, tailored to its purpose and based in applied sciences, not relying entirely on data-driven statistical analysis. Further, M&S should be a continuous process making use of diverse information sources and applying Bayesian and frequentist methodology, as appropriate. In addition to forming a basis for analysing decision options, M&S provides a framework that can facilitate communication between stakeholders. Besides the discussion on modelling philosophy, we also describe how standard simulation practice can be ineffective and how simulation efficiency can often be greatly improved.

Bayesian quantitative disease-drug-trial models for Parkinson's disease to guide early drug development

The problem we have faced in drug development is in its efficiency. Almost a half of registration trials are reported to fail mainly because pharmaceutical companies employ one-size-fits-all development strategies. Our own experience at the regulatory agency suggests that failure to utilize prior experience or knowledge from previous trials also accounts for trial failure. Prior knowledge refers to both drug-specific and nonspecific information such as placebo effect and the disease course. The information generated across drug development can be systematically compiled to guide future drug development. Quantitative disease-drug-trial models are mathematical representations of the time course of biomarker and clinical outcomes, placebo effects, a drug's pharmacologic effects, and trial execution characteristics for both the desired and undesired responses. Applying disease-drug-trial model paradigms to design a future trial has been proposed to overcome current problems in drug development. Parkinson's disease is a progressive neurodegenerative disorder characterized by bradykinesia, rigidity, tremor, and postural instability. A symptomatic effect of drug treatments as well as natural rate of disease progression determines the rate of disease deterioration. Currently, there is no approved drug which claims disease modification. Regulatory agency has been asked to comment on the trial design and statistical analysis methodology. In this work, we aim to show how disease-drug-trial model paradigm can help in drug development and how prior knowledge from previous studies can be incorporated into a current trial using Parkinson's disease model as an example. We took full Bayesian methodology which can allow one to translate prior information into probability distribution.

The use of decision-analytic models in Parkinson's disease: a systematic review and critical appraisal

The aims of this review were to review decision-analytic models used to evaluate interventions in idiopathic Parkinson's disease (PD), and to consider the future directions for development of methods to model the progression of PD over time. A systematic search of the healthcare literature up to June 2010 identified model-based economic evaluations in PD. The modelling methods used in the identified studies were appraised using good practice guidelines for decision-analytic modelling. The review identified 18 model-based evaluations of interventions in PD. All models evaluated treatments targeted towards the motor symptoms of PD or the motor complications of PD treatment. There were no models identified that evaluated interventions targeted towards the non-motor symptoms of PD, such as neuropsychiatric problems or autonomic dysfunction. Consequently, models characterized disease progression in PD using clinical measures of motor functioning. Most studies (n = 13) evaluated medications, three evaluated diagnostic technologies and two examined surgical procedures. Overall, the models reported structural components and data inputs appropriately and clearly, although limited evidence was provided to support choices made on the structures used in the models or the data synthesis reported. Models did not adequately consider structural uncertainty or internal/external consistency. Modelling methods used to date do not capture the full impact of PD. The emphasis in the current literature is on the motor symptoms of PD, characterizing the clinical nature of disease progression, largely neglecting the important impacts of non-motor symptoms. Modelling methods reported for the motor symptoms of PD may not be suitable for future interventions targeted towards modifying disease progression in PD across the entire spectrum of PD. More comprehensive models of disease progression, including both motor and non-motor symptoms will be needed where it is important to capture the effects of interventions more broadly.

Efficacy, safety, and patient preference of monoamine oxidase B inhibitors in the treatment of Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disease and the most treatable. Treatment of PD is symptomatic and generally focuses on the replacement or augmentation of levodopa. A number of options are available for treatment, both in monotherapy of early PD and to treat complications of advanced PD. This review focuses on rasagiline and selegiline, two medications that belong to a class of antiparkinsonian drugs called monoamine oxidase B (MAO-B) inhibitors. Topics covered in the review include mechanism of action, efficacy in early and advanced PD, effects on disability, the controversy regarding disease modification, safety, and patient preference for MAO-B inhibitors.

Estimating transformations for repeated measures modeling of continuous bounded outcome data

Continuous bounded outcome data are unlikely to meet the usual assumptions for mixed-effects models of normally distributed and independent subject-specific and residual random effects. Additionally, overly complicated model structures might be necessary to account adequately for non-drug (time-dependent) and drug treatment effects. A transformation strategy with a likelihood component for censoring is developed to promote the simplicity of model structures and to improve the plausibility of assumptions on the random effects. The approach is motivated by Health Assessment Questionnaire Disability Index (HAQ-DI) data from a study in subjects with rheumatoid arthritis and is evaluated using a simulation study.

Targeting the progression of Parkinson's disease

By the time a patient first presents with symptoms of Parkinson's disease at the clinic, a significant proportion (50-70%) of the cells in the substantia nigra (SN) has already been destroyed. This degeneration progresses until, within a few years, most of the cells have died. Except for rare cases of familial PD, the initial trigger for cell loss is unknown. However, we do have some clues as to why the damage, once initiated, progresses unabated. It would represent a major advance in therapy to arrest cell loss at the stage when the patient first presents at the clinic. Current therapies for Parkinson's disease focus on relieving the motor symptoms of the disease, these unfortunately lose their effectiveness as the neurodegeneration and symptoms progress. Many experimental approaches are currently being investigated attempting to alter the progression of the disease. These range from replacement of the lost neurons to neuroprotective therapies; each of these will be briefly discussed in this review. The main thrust of this review is to explore the interactions between dopamine, alpha synuclein and redox-active metals. There is abundant evidence suggesting that destruction of SN cells occurs as a result of a self-propagating series of reactions involving dopamine, alpha synuclein and redox-active metals. A potent reducing agent, the neurotransmitter dopamine has a central role in this scheme, acting through redox metallo-chemistry to catalyze the formation of toxic oligomers of alpha-synuclein and neurotoxic metabolites including 6-hydroxydopamine. It has been hypothesized that these feed the cycle of neurodegeneration by generating further oxidative stress. The goal of dissecting and understanding the observed pathological changes is to identify therapeutic targets to mitigate the progression of this debilitating disease.

Early addition of selegiline to L-Dopa treatment is beneficial for patients with Parkinson disease

OBJECTIVES

To evaluate the clinical outcome of Parkinson disease (PD) patients treated with selegiline (with L-Dopa/decarboxylase inhibitor) in the early stage of the disease in comparison with that of late-stage use of selegiline.

METHODS

The study and the reference groups were extracted from a large database of the registry of all selegiline users (4692) between year 1998 and 2003 according to the defined criteria. The study group consisted of 106 PD patients who received selegiline within 5 years from the onset of the disease and were followed up for 7 years in average. The reference group consisted of 585 PD patients with comparable disease duration who received selegiline for 16 weeks from 9 to 11 years (mean [SD], 9.9 [0.7]) after the onset of the disease, and the evaluation was made before and after the treatment with selegiline.

RESULTS

The sum of the Unified Parkinson's Disease Rating Scale (UPDRS) scores of 6 major motor symptoms of the study group was significantly lower than that of the reference group (mean [SD], 7.78 [4.30] vs 11.41 [3.88]; P < 0.0001) when compared at a point with the same disease duration (9.8 [1.7] vs 9.9 [0.7] years). The mean UPDRS score of the reference group after 4 months' treatment with selegiline did not reach that of the study group (mean [SD], 9.40 [3.76] vs 7.78 [4.30]; P = 0.0002).

CONCLUSIONS

The clinical outcome as evaluated by the selected UPDRS motor scores was better for L-Dopa-treated patients who received selegiline within 5 years from the onset compared with those who received selegiline approximately 10 years from the onset.