Multivariate functional mixed model with MRI data: An application to Alzheimer's disease.

Alzheimer's Disease (AD) is the leading cause of dementia and impairment in various domains. Recent AD studies, (ie, Alzheimer's Disease Neuroimaging Initiative (ADNI) study), collect multimodal data, including longitudinal neurological assessments and magnetic resonance imaging (MRI) data, to better study the disease progression. Adopting early interventions is essential to slow AD progression for subjects with mild cognitive impairment (MCI). It is of particular interest to develop an AD predictive model that leverages multimodal data and provides accurate personalized predictions. In this article, we propose a multivariate functional mixed model with MRI data (MFMM-MRI) that simultaneously models longitudinal neurological assessments, baseline MRI data, and the survival outcome (ie, dementia onset) for subjects with MCI at baseline. Two functional forms (the random-effects model and instantaneous model) linking the longitudinal and survival process are investigated. We use Markov Chain Monte Carlo (MCMC) method based on No-U-Turn Sampling (NUTS) algorithm to obtain posterior samples. We develop a dynamic prediction framework that provides accurate personalized predictions of longitudinal trajectories and survival probability. We apply MFMM-MRI to the ADNI study and identify significant associations among longitudinal outcomes, MRI data, and the risk of dementia onset. The instantaneous model with voxels from the whole brain has the best prediction performance among all candidate models. The simulation study supports the validity of the estimation and dynamic prediction method.

Dissecting the Domains of Parkinson's Disease: Insights from Longitudinal Item Response Theory Modeling.

BACKGROUND: Longitudinal item response theory (IRT) models previously suggested that the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) motor examination has two salient domains, tremor and nontremor, that progress in time and in response to treatment differently. OBJECTIVE: Apply longitudinal IRT modeling, separating tremor and nontremor domains, to reanalyze outcomes in the previously published clinical trial (Study of Urate Elevation in Parkinson's Disease, Phase 3) that showed no overall treatment effects. METHODS: We applied unidimensional and multidimensional longitudinal IRT models to MDS-UPDRS motor examination items in 298 participants with Parkinson's disease from the Study of Urate Elevation in Parkinson's Disease, Phase 3 (placebo vs. inosine) study. We separated 10 tremor items from 23 nontremor items and used Bayesian inference to estimate progression rates and sensitivity to treatment in overall motor severity and tremor and nontremor domains. RESULTS: The progression rate was faster in the tremor domain than the nontremor domain before levodopa treatment. Inosine treatment had no effect on either domain relative to placebo. Levodopa treatment was associated with greater slowing of progression in the tremor domain than the nontremor domain regardless of inosine exposure. Linear patterns of progression were observed. Despite different domain-specific progression patterns, tremor and nontremor severities at baseline and over time were significantly correlated. CONCLUSIONS: Longitudinal IRT analysis is a novel statistical method addressing limitations of traditional linear regression approaches. It is particularly useful because it can simultaneously monitor changes in different, but related, domains over time and in response to treatment interventions. We suggest that in neurological diseases with distinct impairment domains, clinical or anatomical, this application may identify patterns of change unappreciated by standard statistical methods. © 2022 International Parkinson and Movement Disorder Society.

Bayesian inference and dynamic prediction of multivariate joint model with functional data: An application to Alzheimer's disease.

Alzheimer's disease (AD) is a severe neurodegenerative disorder impairing multiple domains, for example, cognition and behavior. Assessing the risk of AD progression and initiating timely interventions at early stages are critical to improve the quality of life for AD patients. Due to the heterogeneous nature and complex mechanisms of AD, one single longitudinal outcome is insufficient to assess AD severity and disease progression. Therefore, AD studies collect multiple longitudinal outcomes, including cognitive and behavioral measurements, as well as structural brain images such as magnetic resonance imaging (MRI). How to utilize the multivariate longitudinal outcomes and MRI data to make efficient statistical inference and prediction is an open question. In this article, we propose a multivariate joint model with functional data (MJM-FD) framework that relates multiple correlated longitudinal outcomes to a survival outcome, and use the scalar-on-function regression method to include voxel-based whole-brain MRI data as functional predictors in both longitudinal and survival models. We adopt a Bayesian paradigm to make statistical inference and develop a dynamic prediction framework to predict an individual's future longitudinal outcomes and risk of a survival event. We validate the MJM-FD framework through extensive simulation studies and apply it to the motivating Alzheimer's Disease Neuroimaging Initiative (ADNI) study.

Validating new symptom emergence as a patient-centric outcome measure for PD clinical trials.

INTRODUCTION: Tracking of emergent symptoms (ES) in de novo Parkinson Disease (PD) patients using Parts Ib and II of the MDS-UPDRS rating scale has been proposed as an outcome measure for PD clinical trials, based on observations in the Safety, Tolerability and Efficacy Assessment of Isradipine for PD (STEADY-PD3) clinical trial. METHODS: Individual item-level data was extracted from the SURE-PD3 study (coded as "PD-1018" in the C-path pooled dataset). We sought to confirm the observations made in the STEADY-PD3 dataset by analyzing data from a different Phase 3 clinical trial, the Phase 3 Study of Urate Elevation in Parkinson Disease (SURE-PD3), in which MDS-UPDRS was assessed more frequently than the 12-month intervals in STEADY-PD3, using similar methodology. RESULTS: We were able to broadly validate results that demonstrated the frequency of ES, lack of impact of the introduction of symptomatic medications, and in the reduction in sample size required to demonstrate slowing of disease progression at a group level compared with the traditional total MDS-UPDRS summed score scoring methods. Counts of ES generally correlated modestly with summed MDS-UPRDS scores, both for the various sub-parts and for the overall scale as well. However, instability of individual item responses, especially during the first 6 months of observation complicated the assessment of the temporal evolution and stability of ES over time in the course of the SURE-PD3 study. CONCLUSION: Further validation using data sets with frequent administration of MDS-UPDRS is necessary to assess value of this approach as an outcome measure in PD clinical trials.

Increasing Sensitivity in Patient-Reported MDS-UPDRS Items for Predicting Medication Initiation in Early PD.

BACKGROUND: The MDS-UPDRS Parts IB and II are self-reported items providing a direct patient voice to the experiences of PD. OBJECTIVE: To determine the most sensitive combination of MDS-UPDRS Parts IB and II items that accurately predicted the clinically relevant target of dopaminergic therapy initiation. METHODS: Utilizing a longitudinal cohort of de novo non-treated PD patients, we applied item response theory (IRT) and survival analysis to assess the relationship between baseline patient-reported symptoms and the later initiation of dopaminergic therapy. The 20 MDS-UPDRS Parts IB and II items were analyzed for their relationship to PD severity (discrimination) and the amount of information they provided in this determination (information). These parameters were used to develop models of predictive accuracy for initiation of dopaminergic therapy. RESULTS: A six-item version showed a significantly higher C-index as compared to the full 20 item model (P = 0.001). This shortened version of the MDS-UPDRS contained only Part II items and provided a predictive accuracy for initiation of dopaminergic therapy better than the total combined scale score or any other combination. CONCLUSIONS: A six-item "Baseline Outcome Voice" version of patient-reported MDS-UPDRS items significantly increases the sensitivity of predicting the key future clinical outcome of starting dopaminergic treatment in early PD. This study also demonstrates how IRT modeling can provide information useful to refining existing measures to identify the most sensitive combination of items honoring the voice of the patient in determining key clinically pertinent decisions. Further research is needed to validate these findings in underrepresented populations.

Assessing tilavonemab efficacy in early Alzheimer's disease via longitudinal item response theory modeling.

INTRODUCTION: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by declines in cognitive and functional severities. This research utilized the Clinical Dementia Rating (CDR) to assess the influence of tilavonemab on these deteriorations. METHODS: Longitudinal Item Response Theory (IRT) models were employed to analyze CDR domains in early-stage AD patients. Both unidimensional and multidimensional models were contrasted to elucidate the trajectories of cognitive and functional severities. RESULTS: We observed significant temporal increases in both cognitive and functional severities, with the cognitive severity deteriorating at a quicker rate. Tilavonemab did not demonstrate a statistically significant effect on the progression in either severity. Furthermore, a significant positive association was identified between the baselines and progression rates of both severities. DISCUSSION: While tilavonemab failed to mitigate impairment progression, our multidimensional IRT analysis illuminated the interconnected progression of cognitive and functional declines in AD, suggesting a comprehensive perspective on disease trajectories. Highlights: Utilized longitudinal Item Response Theory (IRT) models to analyze the Clinical Dementia Rating (CDR) domains in early-stage Alzheimer's disease (AD) patients, comparing unidimensional and multidimensional models.Observed significant temporal increases in both cognitive and functional severities, with cognitive severity deteriorating at a faster rate, while tilavonemab showed no statistically significant effect on either domain's progression.Found a significant positive association between the baseline severities and their progression rates, indicating interconnected progression patterns of cognitive and functional declines in AD.Introduced the application of multidimensional longitudinal IRT models to provide a comprehensive perspective on the trajectories of cognitive and functional severities in early AD, suggesting new avenues for future research including the inclusion of time-dependent random effects and data-driven IRT models.

Clinical efficacy of CDK4/6 inhibitor plus endocrine therapy in HR-positive/HER2-0 and HER2-low-positive metastatic breast cancer: a secondary analysis of PALOMA-2 and PALOMA-3 trials.

BACKGROUND: Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors in combination with traditional endocrine therapy (ET) are now the recommended first-line treatment for hormone receptor (HR)-positive and HER2-negative metastatic breast cancer (MBC). However, the benefits of adding CDK4/6 inhibitors to ET in HER2-low-positive and HER2-0 subgroups remain unclear. We aimed to assess the effectiveness of CDK4/6 inhibitors in combination with ET in patients with HR-positive, HER2-low-positive and HER2-0 MBC. METHODS: This secondary analysis assessed progression-free survival (PFS) among HER2-low-positive and HER2-0 patients enrolled in the double-blind, placebo-controlled randomised clinical trials PALOMA-2 and PALOMA-3. The study included 1186 HER2-negative, HR-positive female patients, with available immunohistochemistry (IHC) and/or in situ hybridization (ISH) results, across 17 countries enrolled between February 2013 and August 2014. HER2-low-positive status was defined by IHC 1+ or 2+ with negative ISH, and HER2-zero by IHC 0. Data analyses were conducted between March and May 2023. In the PALOMA-2 trial, patients were randomly assigned to receive either palbociclib or placebo, in combination with letrozole in the first-line treatment for HR-positive MBC. Patients in the PALOMA-3 study, who had progression or relapse during previous ET, were randomly allocated to receive either palbociclib plus fulvestrant or placebo plus fulvestrant. The primary endpoint was investigator-assessed PFS. Kaplan-Meier approach and Cox proportional hazards model were applied to estimate the association of treatment strategies with PFS among HER2-0 and HER2-low-positive populations. The two trials are registered with ClinicalTrials.gov, number NCT01740427 and NCT01942135. FINDINGS: Of the 666 patients with MBC from the PALOMA-2 study, there were 153 HER2-0 and 513 HER2-low-positive patients. In the HER2-0 population, no significant difference in PFS was observed between the palbociclib-letrozole and placebo-letrozole groups (hazard ratio = 0.79, 95% confidence interval [CI] 0.48-1.30, p = 0.34). In the HER2-low-positive population, palbociclib-letrozole demonstrated a significantly lower risk of PFS than placebo-letrozole group (hazard ratio = 0.52, 95% CI 0.41-0.66, p < 0.0001). The PALOMA-3 study analysed 520 patients with MBC. Within the 153 HER2-0 patients, the palbociclib-fulvestrant group showed a significantly longer PFS than the placebo-fulvestrant group (hazard ratio = 0.54, 95% CI 0.30-0.95, p = 0.034). Among the 367 HER2-low-positive patients, palbociclib-fulvestrant improved PFS (hazard ratio = 0.39, 95% CI 0.28-0.54, p < 0.0001). INTERPRETATION: The combination of a CDK4/6 inhibitor with ET significantly improved PFS in HER2-low-positive patients, while for HER2-0 patients, benefits were primarily observed in patients who had progressed on previous ET. Furthermore, HER2-0 patients may derive limited benefits from first-line CDK4/6 inhibitor treatment. Further work is needed to validate these findings and to delineate patient subsets that are most likely to benefit from the combination of CDK4/6 inhibitors and ET as first-line treatments. FUNDING: None.

BAYESIAN INFERENCE AND DYNAMIC PREDICTION FOR MULTIVARIATE LONGITUDINAL AND SURVIVAL DATA.

Alzheimer's disease (AD) is a complex neurological disorder impairing multiple domains such as cognition and daily functions. To better understand the disease and its progression, many AD research studies collect multiple longitudinal outcomes that are strongly predictive of the onset of AD dementia. We propose a joint model based on a multivariate functional mixed model framework (referred to as MFMM-JM) that simultaneously models the multiple longitudinal outcomes and the time to dementia onset. We develop six functional forms to fully investigate the complex association between longitudinal outcomes and dementia onset. Moreover, we use the Bayesian methods for statistical inference and develop a dynamic prediction framework that provides accurate personalized predictions of disease progressions based on new subject-specific data. We apply the proposed MFMM-JM to two large ongoing AD studies: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and National Alzheimer's Coordinating Center (NACC), and identify the functional forms with the best predictive performance. our method is also validated by extensive simulation studies with five settings.

Detection of Simulated In Vitro Digestion Products of Fucoxanthin and Their Photodamage Alleviation Effect in Retinal Müller Cells Induced by Ultraviolet B Irradiation: A Proteomics Analysis.

Our previous study reported that the marine dietary bioactive compound fucoxanthin (FX) has the potential to reduce the level of oxidation in retinal Müller cells (RMCs) induced by ultraviolet B (UVB) irradiation. However, the gastrointestinal environment can inhibit the bioavailability and absorption of FX in the cell systems. In the current study, FX was initially digested in a simulated in vitro gastrointestinal fluid. Nine main digestive products were identified, and the photoprotective activities of FX simulated in vitro gastrointestinal digestion products (FX-ID) were assessed in the same RMC model. FX-ID significantly reduced intracellular ROS and alleviated apoptosis. Western blot assays showed that FX-ID inhibited phosphorylated proteins in the MAPK and NF-κB signaling pathways. Our proteomics analysis revealed that the differentially expressed proteins were linked to biological networks associated with antioxidation and metabolic processes. The data may provide insight into the photoprotective mechanisms of FX-ID and promote the development of various functional foods to prevent retinal disorders.

Seaweed Slurry Improved Gel Properties and Enhanced Protein Structure of Silver Carp (Hypophthalmichthys molitrix) Surimi.

In order to improve the gel quality of silver carp (Hypophthalmichthys molitrix) surimi, the texture and rheological properties and microstructure of silver carp surimi gel products were analyzed by adding Laminaria japonica (LJ), Undaria pinnatifida (UP) and Sargassum fusiforme (SF) slurries. After adding kelp slurry (KS), the gel strength reached the highest level of 1047.26 ± 85.04 (g·mm). The carbonyl content and surface hydrophobicity of surimi protein increased, while the free amino groups, total sulfhydryl groups, and fluorescence intensity decreased significantly. The results of transform infrared spectroscopy (FT-IR), circular dichroic (CD), and Raman spectra showed that the KS promoted the change of the secondary structure of protein. Scanning electron microscopy (SEM) images revealed that kelp slurry had a more compact gel microstructure. In conclusion, the kelp slurry could significantly increase the gel strength, improve the quality of surimi products, enrich the nutrition of silver carp surimi, and have great significance for expanding the application range of seaweed.

Application of longitudinal item response theory models to modeling Parkinson's disease progression.

The Movement Disorder Society revised version of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) parts 2 and 3 reflect patient-reported functional impact and clinician-reported severity of motor signs of Parkinson's disease (PD), respectively. Total scores are common clinical outcomes but may obscure important time-based changes in items. We aim to analyze longitudinal disease progression based on MDS-UPRDS parts 2 and 3 item-level responses over time and as functions of Hoehn & Yahr (H&Y) stages 1 and 2 for subjects with early PD. The longitudinal item response theory (IRT) modeling is a novel statistical method addressing limitations in traditional linear regression approaches, such as ignoring varying item sensitivities and the sum score balancing out improvements and declines. We utilized a harmonized dataset consisting of six studies with 3573 subjects with early PD and 14,904 visits, and mean follow-up time of 2.5 years (±1.57). We applied both a unidimensional (each part separately) and multidimensional (both parts combined) longitudinal IRT models. We assessed the progression rates for both parts, anchored to baseline H&Y stages 1 and 2. Both the uni- and multidimensional longitudinal IRT models indicate significant worsening time effects in both parts 2 and 3. Baseline H&Y stage 2 was associated with significantly higher baseline severities, but slower progression rates in both parts, as compared with stage 1. Patients with baseline H&Y stage 1 demonstrated slower progression in part 2 severity compared to part 3, whereas patients with baseline H&Y stage 2 progressed faster in part 2 than part 3. The multidimensional model had a superior fit compared to the unidimensional models and it had excellent model performance.

Novel Approach to Movement Disorder Society-Unified Parkinson's Disease Rating Scale Monitoring in Clinical Trials: Longitudinal Item Response Theory Models.

BACKGROUND: Although nontremor and tremor Part 3 Movement Disorder Society-Unified Parkinson's Disease Rating Scale items measure different impairment domains, their distinct progression and drug responsivity remain unstudied longitudinally. The total score may obscure important time-based and treatment-based changes occurring in the individual domains. OBJECTIVE: Using the unique advantages of item response theory (IRT), we developed novel longitudinal unidimensional and multidimensional models to investigate nontremor and tremor changes occurring in an interventional Parkinson's disease (PD) study. METHOD: With unidimensional longitudinal IRT, we assessed the 33 Part 3 item data (22 nontremor and 10 tremor items) of 336 patients with early PD from the STEADY-PD III (Safety, Tolerability, and Efficacy Assessment of Isradipine for PD, placebo vs. isradipine) study. With multidimensional longitudinal IRT, we assessed the progression rates over time and treatment (in overall motor severity, nontremor, and tremor domains) using Markov Chain Monte Carlo implemented in Stan. RESULTS: Regardless of treatment, patients showed significant but different time-based deterioration rates for total motor, nontremor, and tremor scores. Isradipine was associated with additional significant deterioration over placebo in total score and nontremor scores, but not in tremor score. Further highlighting the 2 separate latent domains, nontremor and tremor severity changes were positively but weakly correlated (correlation coefficient, 0.108). CONCLUSIONS: Longitudinal IRT analysis is a novel statistical method highly applicable to PD clinical trials. It addresses limitations of traditional linear regression approaches and previous IRT investigations that either applied cross-sectional IRT models to longitudinal data or failed to estimate all parameters simultaneously. It is particularly useful because it can separate nontremor and tremor changes both over time and in response to treatment interventions.