Novel non-linear models for clinical trial analysis with longitudinal data: A tutorial using SAS for both frequentist and Bayesian methods.

Longitudinal data from clinical trials are commonly analyzed using mixed models for repeated measures (MMRM) when the time variable is categorical or linear mixed-effects models (ie, random effects model) when the time variable is continuous. In these models, statistical inference is typically based on the absolute difference in the adjusted mean change (for categorical time) or the rate of change (for continuous time). Previously, we proposed a novel approach: modeling the percentage reduction in disease progression associated with the treatment relative to the placebo decline using proportional models. This concept of proportionality provides an innovative and flexible method for simultaneously modeling different cohorts, multivariate endpoints, and jointly modeling continuous and survival endpoints. Through simulated data, we demonstrate the implementation of these models using SAS procedures in both frequentist and Bayesian approaches. Additionally, we introduce a novel method for implementing MMRM models (ie, analysis of response profile) using the nlmixed procedure.

Statistical considerations when estimating time-saving treatment effects in Alzheimer's disease clinical trials.

INTRODUCTION: Estimating treatment effects as time savings in disease progression may be more easily interpretable than assessing the absolute difference or a percentage reduction. In this study, we investigate the statistical considerations of the existing method for estimating time savings and propose alternative complementary methods. METHODS: We propose five alternative methods to estimate the time savings from different perspectives. These methods are applied to simulated clinical trial data that mimic or modify the Clinical Dementia Rating Sum of Boxes progression trajectories observed in the Clarity AD lecanemab trial. RESULTS: Our study demonstrates that the proposed methods can generate more precise estimates by considering two crucial factors: (1) the absolute difference between treatment arms, and (2) the observed progression rate in the treatment arm. DISCUSSION: Quantifying treatment effects as time savings in disease progression offers distinct advantages. To provide comprehensive estimations, it is important to use various methods. HIGHLIGHTS: We explore the statistical considerations of the current method for estimating time savings. We proposed alternative methods that provide time savings estimations based on the observed absolute differences. By using various methods, a more comprehensive estimation of time savings can be achieved.

Examining amyloid reduction as a surrogate endpoint through latent class analysis using clinical trial data for dominantly inherited Alzheimer's disease.

INTRODUCTION: Increasing evidence suggests that amyloid reduction could serve as a plausible surrogate endpoint for clinical and cognitive efficacy. The double-blind phase 3 DIAN-TU-001 trial tested clinical and cognitive declines with increasing doses of solanezumab or gantenerumab. METHODS: We used latent class (LC) analysis on data from the Dominantly Inherited Alzheimer Network Trials Unit 001 trial to test amyloid positron emission tomography (PET) reduction as a potential surrogate biomarker. RESULTS: LC analysis categorized participants into three classes: amyloid no change, amyloid reduction, and amyloid growth, based on longitudinal amyloid Pittsburgh compound B PET standardized uptake value ratio data. The amyloid-no-change class was at an earlier disease stage for amyloid amounts and dementia. Despite similar baseline characteristics, the amyloid-reduction class exhibited reductions in the annual decline rates compared to the amyloid-growth class across multiple biomarker, clinical, and cognitive outcomes. DISCUSSION: LC analysis indicates that amyloid reduction is associated with improved clinical outcomes and supports its use as a surrogate biomarker in clinical trials. HIGHLIGHTS: We used latent class (LC) analysis to test amyloid reduction as a surrogate biomarker. Despite similar baseline characteristics, the amyloid-reduction class exhibited remarkably better outcomes compared to the amyloid-growth class across multiple measures. LC analysis proves valuable in testing amyloid reduction as a surrogate biomarker in clinical trials lacking significant treatment effects.

Presenilin-1 mutation position influences amyloidosis, small vessel disease, and dementia with disease stage.

INTRODUCTION: Amyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin-1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre-/postcodon 200) influences these pathologic features and dementia at different stages. METHODS: Individuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross-sectionally evaluated regional Pittsburgh compound B-positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging-based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition. RESULTS: Postcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures. DISCUSSION: We demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials. HIGHLIGHTS: Mutation position influences Aß burden, SVD, and dementia. PSEN1 pre-200 group had stronger associations between Aß burden and disease stage. PSEN1 post-200 group had stronger associations between SVD markers and disease stage. PSEN1 post-200 group had worse dementia score than pre-200 in late disease stage. Diffusion tensor imaging-based SVD markers mediated mutation position effects on dementia in the late stage.

T1 and FLAIR signal intensities are related to tau pathology in dominantly inherited Alzheimer disease.

Carriers of mutations responsible for dominantly inherited Alzheimer disease provide a unique opportunity to study potential imaging biomarkers. Biomarkers based on routinely acquired clinical MR images, could supplement the extant invasive or logistically challenging) biomarker studies. We used 1104 longitudinal MR, 324 amyloid beta, and 87 tau positron emission tomography imaging sessions from 525 participants enrolled in the Dominantly Inherited Alzheimer Network Observational Study to extract novel imaging metrics representing the mean (µ) and standard deviation (σ) of standardized image intensities of T1-weighted and Fluid attenuated inversion recovery (FLAIR) MR scans. There was an exponential decrease in FLAIR-µ in mutation carriers and an increase in FLAIR and T1 signal heterogeneity (T1-σ and FLAIR-σ) as participants approached the symptom onset in both supramarginal, the right postcentral and right superior temporal gyri as well as both caudate nuclei, putamina, thalami, and amygdalae. After controlling for the effect of regional atrophy, FLAIR-µ decreased and T1-σ and FLAIR-σ increased with increasing amyloid beta and tau deposition in numerous cortical regions. In symptomatic mutation carriers and independent of the effect of regional atrophy, tau pathology demonstrated a stronger relationship with image intensity metrics, compared with amyloid pathology. We propose novel MR imaging intensity-based metrics using standard clinical T1 and FLAIR images which strongly associates with the progression of pathology in dominantly inherited Alzheimer disease. We suggest that tau pathology may be a key driver of the observed changes in this cohort of patients.

Amyloid-Related Imaging Abnormalities in the DIAN-TU-001 Trial of Gantenerumab and Solanezumab: Lessons from a Trial in Dominantly Inherited Alzheimer Disease.

OBJECTIVE: To determine the characteristics of participants with amyloid-related imaging abnormalities (ARIA) in a trial of gantenerumab or solanezumab in dominantly inherited Alzheimer disease (DIAD). METHODS: 142 DIAD mutation carriers received either gantenerumab SC (n = 52), solanezumab IV (n = 50), or placebo (n = 40). Participants underwent assessments with the Clinical Dementia Rating® (CDR®), neuropsychological testing, CSF biomarkers, ß-amyloid positron emission tomography (PET), and magnetic resonance imaging (MRI) to monitor ARIA. Cross-sectional and longitudinal analyses evaluated potential ARIA-related risk factors. RESULTS: Eleven participants developed ARIA-E, including 3 with mild symptoms. No ARIA-E was reported under solanezumab while gantenerumab was associated with ARIA-E compared to placebo (odds ratio [OR] = 9.1, confidence interval [CI][1.2, 412.3]; p = 0.021). Under gantenerumab, APOE-ɛ4 carriers were more likely to develop ARIA-E (OR = 5.0, CI[1.0, 30.4]; p = 0.055), as were individuals with microhemorrhage at baseline (OR = 13.7, CI[1.2, 163.2]; p = 0.039). No ARIA-E was observed at the initial 225 mg/month gantenerumab dose, and most cases were observed at doses >675 mg. At first ARIA-E occurrence, all ARIA-E participants were amyloid-PET+, 60% were CDR >0, 60% were past their estimated year to symptom onset, and 60% had also incident ARIA-H. Most ARIA-E radiologically resolved after dose adjustment and developing ARIA-E did not significantly increase odds of trial discontinuation. ARIA-E was more frequently observed in the occipital lobe (90%). ARIA-E severity was associated with age at time of ARIA-E. INTERPRETATION: In DIAD, solanezumab was not associated with ARIA. Gantenerumab dose over 225 mg increased ARIA-E risk, with additional risk for individuals APOE-ɛ4(+) or with microhemorrhage. ARIA-E was reversible on MRI in most cases, generally asymptomatic, without additional risk for trial discontinuation. ANN NEUROL 2022;92:729-744.

Longitudinal head-to-head comparison of 11C-PiB and 18F-florbetapir PET in a Phase 2/3 clinical trial of anti-amyloid-ß monoclonal antibodies in dominantly inherited Alzheimer's disease.

PURPOSE: Pittsburgh Compound-B (11C-PiB) and 18F-florbetapir are amyloid-ß (Aß) positron emission tomography (PET) radiotracers that have been used as endpoints in Alzheimer's disease (AD) clinical trials to evaluate the efficacy of anti-Aß monoclonal antibodies. However, comparing drug effects between and within trials may become complicated if different Aß radiotracers were used. To study the consequences of using different Aß radiotracers to measure Aß clearance, we performed a head-to-head comparison of 11C-PiB and 18F-florbetapir in a Phase 2/3 clinical trial of anti-Aß monoclonal antibodies. METHODS: Sixty-six mutation-positive participants enrolled in the gantenerumab and placebo arms of the first Dominantly Inherited Alzheimer Network Trials Unit clinical trial (DIAN-TU-001) underwent both 11C-PiB and 18F-florbetapir PET imaging at baseline and during at least one follow-up visit. For each PET scan, regional standardized uptake value ratios (SUVRs), regional Centiloids, a global cortical SUVR, and a global cortical Centiloid value were calculated. Longitudinal changes in SUVRs and Centiloids were estimated using linear mixed models. Differences in longitudinal change between PET radiotracers and between drug arms were estimated using paired and Welch two sample t-tests, respectively. Simulated clinical trials were conducted to evaluate the consequences of some research sites using 11C-PiB while other sites use 18F-florbetapir for Aß PET imaging. RESULTS: In the placebo arm, the absolute rate of longitudinal change measured by global cortical 11C-PiB SUVRs did not differ from that of global cortical 18F-florbetapir SUVRs. In the gantenerumab arm, global cortical 11C-PiB SUVRs decreased more rapidly than global cortical 18F-florbetapir SUVRs. Drug effects were statistically significant across both Aß radiotracers. In contrast, the rates of longitudinal change measured in global cortical Centiloids did not differ between Aß radiotracers in either the placebo or gantenerumab arms, and drug effects remained statistically significant. Regional analyses largely recapitulated these global cortical analyses. Across simulated clinical trials, type I error was higher in trials where both Aß radiotracers were used versus trials where only one Aß radiotracer was used. Power was lower in trials where 18F-florbetapir was primarily used versus trials where 11C-PiB was primarily used. CONCLUSION: Gantenerumab treatment induces longitudinal changes in Aß PET, and the absolute rates of these longitudinal changes differ significantly between Aß radiotracers. These differences were not seen in the placebo arm, suggesting that Aß-clearing treatments may pose unique challenges when attempting to compare longitudinal results across different Aß radiotracers. Our results suggest converting Aß PET SUVR measurements to Centiloids (both globally and regionally) can harmonize these differences without losing sensitivity to drug effects. Nonetheless, until consensus is achieved on how to harmonize drug effects across radiotracers, and since using multiple radiotracers in the same trial may increase type I error, multisite studies should consider potential variability due to different radiotracers when interpreting Aß PET biomarker data and, if feasible, use a single radiotracer for the best results. TRIAL REGISTRATION: ClinicalTrials.gov NCT01760005. Registered 31 December 2012. Retrospectively registered.

Accelerated longitudinal changes and ordering of Alzheimer disease biomarkers across the adult lifespan.

The temporal evolutions and relative orderings of Alzheimer disease biomarkers, including CSF amyloid-ß42 (Aß42), Aß40, total tau (Tau) and phosphorylated tau181 (pTau181), standardized uptake value ratio (SUVR) from the molecular imaging of cerebral fibrillar amyloid-ß with PET using the 11C-Pittsburgh Compound-B (PiB), MRI-based hippocampal volume and cortical thickness and cognition have been hypothesized but not yet fully tested with longitudinal data for all major biomarker modalities among cognitively normal individuals across the adult lifespan starting from 18 years. By leveraging a large harmonized database from 8 biomarker studies with longitudinal data from 2609 participants in cognition, 873 in MRI biomarkers, 519 in PET PiB imaging and 475 in CSF biomarkers for a median follow-up of 5-6 years, we estimated the longitudinal trajectories of all major Alzheimer disease biomarkers as functions of baseline age that spanned from 18 to 103 years, located the baseline age window at which the longitudinal rates of change accelerated and further examined possible modifying effects of apolipoprotein E (APOE) genotype. We observed that participants 18-45 years at baseline exhibited learning effects on cognition and unexpected directions of change on CSF and PiB biomarkers. The earliest acceleration of longitudinal change occurred for CSF Aß42 and Aß42/Aß40 ratio (with an increase) and for Tau, and pTau181 (with a decrease) at the next baseline age interval of 45-50 years, followed by an accelerated increase for PiB SUVR at the baseline age of 50-55 years and an accelerated decrease for hippocampal volume at the baseline age of 55-60 years and finally by an accelerated decline for cortical thickness and cognition at the baseline age of 65-70 years. Another acceleration in the rate of change occurred at the baseline age of 65-70 years for Aß42/Aß40 ratio, Tau, pTau181, PiB SUVR and hippocampal volume. Accelerated declines in hippocampal volume and cognition continued after 70 years. For participants 18-45 years at baseline, significant increases in Aß42 and Aß42/Aß40 ratio and decreases in PiB SUVR occurred in APOE ɛ4 non-carriers but not carriers. After age 45 years, APOE ɛ4 carriers had greater magnitudes than non-carriers in the rates of change for all CSF biomarkers, PiB SUVR and cognition. Our results characterize the temporal evolutions and relative orderings of Alzheimer disease biomarkers across the adult lifespan and the modification effect of APOE ɛ4. These findings may better inform the design of prevention trials on Alzheimer disease.

Comparing statistical methods in assessing the prognostic effect of biomarker variability on time-to-event clinical outcomes.

BACKGROUND: In recent years there is increasing interest in modeling the effect of early longitudinal biomarker data on future time-to-event or other outcomes. Sometimes investigators are also interested in knowing whether the variability of biomarkers is independently predictive of clinical outcomes. This question in most applications is addressed via a two-stage approach where summary statistics such as variance are calculated in the first stage and then used in models as covariates to predict clinical outcome in the second stage. The objective of this study is to compare the relative performance of various methods in estimating the effect of biomarker variability. METHODS: A joint model and 4 different two-stage approaches (naïve, landmark analysis, time-dependent Cox model, and regression calibration) were illustrated using data from a large multi-center randomized phase III trial, the Ocular Hypertension Treatment Study (OHTS), regarding the association between the variability of intraocular pressure (IOP) and the development of primary open-angle glaucoma (POAG). The model performance was also evaluated in terms of bias using simulated data from the joint model of longitudinal IOP and time to POAG. The parameters for simulation were chosen after OHTS data, and the association between longitudinal and survival data was introduced via underlying, unobserved, and error-free parameters including subject-specific variance. RESULTS: In the OHTS data, joint modeling and two-stage methods reached consistent conclusion that IOP variability showed no significant association with the risk of POAG. In the simulated data with no association between IOP variability and time-to-POAG, all the two-stage methods (except the naïve approach) provided a reliable estimation. When a moderate effect of IOP variability on POAG was imposed, all the two-stage methods underestimated the true association as compared with the joint modeling while the model-based two-stage method (regression calibration) resulted in the least bias. CONCLUSION: Regression calibration and joint modelling are the preferred methods in assessing the effect of biomarker variability. Two-stage methods with sample-based measures should be used with caution unless there exists a relatively long series of longitudinal measurements and/or strong effect size (NCT00000125).

Relative efficiency of equal versus unequal cluster sizes in cluster randomized trials with a small number of clusters.

To calculate sample sizes in cluster randomized trials (CRTs), the cluster sizes are usually assumed to be identical across all clusters for simplicity. However, equal cluster sizes are not guaranteed in practice, especially when the number of clusters is limited. Therefore, it is important to understand the relative efficiency (RE) of equal versus unequal cluster sizes when designing CRTs with a limited number of clusters. In this paper, we are interested in the RE of two bias-corrected sandwich estimators of the treatment effect in the Generalized Estimating Equation (GEE) models for CRTs with a small number of clusters. Specifically, we derive the RE of two bias-corrected sandwich estimators for binary, continuous, or count data in CRTs under the assumption of an exchangeable working correlation structure. We consider different scenarios of cluster size distributions and investigate RE performance through simulation studies. We conclude that the number of clusters could be increased by as much as 42% to compensate for efficiency loss due to unequal cluster sizes. Finally, we propose an algorithm of increasing the number of clusters when the coefficient of variation of cluster sizes is known and unknown.

Tau PET in autosomal dominant Alzheimer's disease: relationship with cognition, dementia and other biomarkers.

Tauopathy is a hallmark pathology of Alzheimer's disease with a strong relationship with cognitive impairment. As such, understanding tau may be a key to clinical interventions. In vivo tauopathy has been measured using cerebrospinal fluid assays, but these do not provide information about where pathology is in the brain. The introduction of PET ligands that bind to paired helical filaments provides the ability to measure the amount and distribution of tau pathology. The heritability of the age of dementia onset tied to the specific mutations found in autosomal dominant Alzheimer's disease families provides an elegant model to study the spread of tau across the course of the disease as well as the cross-modal relationship between tau and other biomarkers. To better understand the pathobiology of Alzheimer's disease we measured levels of tau PET binding in individuals with dominantly inherited Alzheimer's disease using data from the Dominantly Inherited Alzheimer Network (DIAN). We examined cross-sectional measures of amyloid-ß, tau, glucose metabolism, and grey matter degeneration in 15 cognitively normal mutation non-carriers, 20 asymptomatic carriers, and 15 symptomatic mutation carriers. Linear models examined the association of pathology with group, estimated years to symptom onset, as well as cross-modal relationships. For comparison, tau PET was acquired on 17 older adults with sporadic, late onset Alzheimer disease. Tau PET binding was starkly elevated in symptomatic DIAN individuals throughout the cortex. The brain areas demonstrating elevated tau PET binding overlapped with those seen in sporadic Alzheimer's disease, but with a greater cortical involvement and greater levels of binding despite similar cognitive impairment. Tau PET binding was elevated in the temporal lobe, but the most prominent loci of pathology were in the precuneus and lateral parietal regions. Symptomatic mutation carriers also demonstrated elevated tau PET binding in the basal ganglia, consistent with prior work with amyloid-ß. The degree of tau tracer binding in symptomatic individuals was correlated to other biomarkers, particularly markers of neurodegeneration. In addition to the differences seen with tau, amyloid-ß was increased in both asymptomatic and symptomatic groups relative to non-carriers. Glucose metabolism showed decline primarily in the symptomatic group. MRI indicated structural degeneration in both asymptomatic and symptomatic cohorts. We demonstrate that tau PET binding is elevated in symptomatic individuals with dominantly inherited Alzheimer's disease. Tau PET uptake was tied to the onset of cognitive dysfunction, and there was a higher amount, and different regional pattern of binding compared to late onset, non-familial Alzheimer's disease.

Awareness of genetic risk in the Dominantly Inherited Alzheimer Network (DIAN).

INTRODUCTION: Although some members of families with autosomal dominant Alzheimer's disease mutations learn their mutation status, most do not. How knowledge of mutation status affects clinical disease progression is unknown. This study quantifies the influence of mutation awareness on clinical symptoms, cognition, and biomarkers. METHODS: Mutation carriers and non-carriers from the Dominantly Inherited Alzheimer Network (DIAN) were stratified based on knowledge of mutation status. Rates of change on standard clinical, cognitive, and neuroimaging outcomes were examined. RESULTS: Mutation knowledge had no associations with cognitive decline, clinical progression, amyloid deposition, hippocampal volume, or depression in either carriers or non-carriers. Carriers who learned their status mid-study had slightly higher levels of depression and lower cognitive scores. DISCUSSION: Knowledge of mutation status does not affect rates of change on any measured outcome. Learning of status mid-study may confer short-term changes in cognitive functioning, or changes in cognition may influence the determination of mutation status.

Lanthanum-doped activated carbon derived from municipal sludge for enhanced defluoridation: characteristics and mechanism.

The sewage sludge production has been increasing along with the ever-growing populations and wastewater treatment rate. Lanthanum-doped activated carbon (AC-La) was derived from municipal sludge via chemical activation and utilized for fluoride removal. Batch experiments were conducted to discuss the effect of lanthanum dosage, time and pH on the adsorption process. The results showed that 4 g/L AC-La exhibited a fluoride removal rate of 80.9% with 10 mg/L initial fluoride concentration, and the optimal pH range for adsorption was 3-10. X-ray fluorescence, scanning electron microscopy with energy-dispersive X-ray spectroscopy, Brunauer-Emmett-Teller, X-ray diffraction, Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy analyses were conducted to analyze the microstructure and chemical properties of sludge, unmodified activated carbon (AC) and AC-La. The results showed that with initial lanthanum dosage of 15 wt%, the final loading amount of La in AC-La was 13.8 wt%. After modification, the specific surface area of AC-La increased from 1.8 m2/g (sludge) to 133.0 m2/g. The removal mechanism of fluoride onto AC-La was mainly the inner-sphere complexation between lanthanum and fluoride, facilitated by exchange interaction with hydroxyls. A stability study showed that AC-La maintained a quite small dissolution and was safe in waters (La dissolution rate < 0.2‰).

Staging biomarkers in preclinical autosomal dominant Alzheimer's disease by estimated years to symptom onset.

INTRODUCTION: Staging preclinical Alzheimer disease (AD) by the expected years to symptom onset (EYO) in autosomal dominant AD (ADAD) through biomarker correlations is important. METHODS: We estimated the correlation matrix between EYO/cognition and imaging/CSF biomarkers, and searched for the EYO cutoff where a change in the correlations occurred before and after the cutoff among the asymptomatic mutation carriers of ADAD. We then estimated the longitudinal rate of change for biomarkers/cognition within each preclinical stage defined by the EYO. RESULTS: Based on the change in the correlations, the preclinical ADAD was divided by EYOs -7 and -13 years. Mutation carriers demonstrated a temporal ordering of biomarker/cognition changes across the three preclinical stages. DISCUSSION: Duration of each preclinical stage can be estimated in ADAD, facilitating better planning of prevention trials with the EYO cutoffs under the recently released FDA guidance. The generalization of these results to sporadic AD warrants further investigation.

Emerging cerebrospinal fluid biomarkers in autosomal dominant Alzheimer's disease.

INTRODUCTION: Four less well-studied but promising "emerging" cerebrospinal fluid (CSF) biomarkers are elevated in late-onset Alzheimer disease (AD): neurogranin, synaptosomal-associated protein-25 (SNAP-25), visinin-like protein 1 (VILIP-1), and chitinase-3-like protein 1 (YKL-40). METHODS: CSF neurogranin, SNAP-25, VILIP-1, and YKL-40 were measured in families carrying autosomal-dominant AD mutations. RESULTS: The four emerging CSF biomarkers were significantly elevated in the mutation carriers (n = 235) versus noncarriers (n = 145). CSF SNAP-25, VILIP-1, and YKL-40 were altered very early in the AD time course, approximately 15-19 years before estimated symptom onset. All CSF biomarkers predicted important AD-related outcomes including performance on a cognitive composite, brain amyloid burden as measured by amyloid positron emission tomography, and the estimated years from symptom onset. DISCUSSION: Early abnormalities in CSF tTau, pTau, SNAP-25, VILIP-1, and YKL-40 suggest that synaptic damage, neuronal injury, and neuroinflammation begin shortly after the commencement of brain amyloid accumulation.

A novel cognitive disease progression model for clinical trials in autosomal-dominant Alzheimer's disease.

Clinical trial outcomes for Alzheimer's disease are typically analyzed by using the mixed model for repeated measures (MMRM) or similar models that compare an efficacy scale change from baseline between treatment arms with or without participants' disease stage as a covariate. The MMRM focuses on a single-point fixed follow-up duration regardless of the exposure for each participant. In contrast to these typical models, we have developed a novel semiparametric cognitive disease progression model (DPM) for autosomal dominant Alzheimer's disease based on the Dominantly Inherited Alzheimer Network (DIAN) observational study. This model includes 3 novel features, in which the DPM (1) aligns and compares participants by disease stage, (2) uses a proportional treatment effect similar to the concept of the Cox proportional hazard ratio, and (3) incorporates extended follow-up data from participants with different follow-up durations using all data until last participant visit. We present the DPM model developed by using the DIAN observational study data and demonstrate through simulation that the cognitive DPM used in hypothetical intervention clinical trials produces substantial gains in power compared with the MMRM.

Baseline EDSS proportions in MS clinical trials affect the overall outcome and power: A cautionary note.

BACKGROUND: In randomized clinical trials, when treatments do not work equally effectively across stratifications of participants, observed event rates may differ from those hypothesized leading to deviations in estimated power. OBJECTIVES: To investigate the effect of distributions of baseline Expanded Disability Status Scale (EDSS) proportions in relapsing-remitting multiple sclerosis (RRMS) on the trial outcome, confirmed disability progression rate (CDPR), and power. METHODS: We reported CDPRs in the CombiRx trial by baseline EDSS and by groups (1st (0, 1), 2nd (1.5, 2), 3rd (2.5, 3), and 4th (⩾3.5)) and investigated the effect of different combinations of baseline EDSS proportions on the trial outcome and power. RESULTS: There were 244 (25.4%) participants in the 1st group, 368 (38.4%) in the 2nd group, 223 (23.3%) in the 3rd group, and 124 (12.9%) in the 4th group with CDPRs of 40.1%, 13.9%, 11.2%, and 16.9%, respectively. Both CDPR and power increased when the proportion of the 1st group increased in hypothetical trials with equal sample sizes in each arm, and a 10% increase in the 1st group led to a 5% increase in power. CONCLUSION: Various baseline EDSS proportions yielded different CDPRs and power, suggesting caution in interpretation of treatment effects across trials that enrolled participants with different proportions of baseline EDSS.

Challenging Assumptions About African American Participation in Alzheimer Disease Trials.

OBJECTIVE: The authors investigated potential effects of increased African American participation in Alzheimer disease (AD) and mild cognitive impairment (MCI) clinical trials by examining differences in comorbid conditions and treatment outcome affecting trial design. METHODS: Using a meta-database of 18 studies from the Alzheimer's Disease Cooperative Study and the Alzheimer's Disease Neuroimaging Initiative, a cohort of 5,164 subjects were included for whom there were baseline demographic data and information on comorbid disorders, grouped by organ system. Meta-analysis was used to compare prevalence of comorbidities, dropouts, and rates of change on the cognitive subscale of the Alzheimer's Disease Assessment Scale by race. Clinical trial scenarios similar to recent therapeutic trials were simulated to determine effects of increased African American participation on statistical power. RESULTS: Approximately 7% of AD, 4% of MCI, and 11% of normal participants were African American. African American subjects had higher prevalence of cardiovascular disorders (odds ratio: 2.10; 95% confidence interval [CI]: 1.71-2.57) and higher rate of dropouts (odds ratio: 1.60; 95% CI: 1.15-2.21) compared with whites but lower rates of other disorders. There were no significant differences in rate of progression (-0.862 points/year; 95% CI: -1.89 to 0.162) by race and little effect on power in simulated trials with sample sizes similar to current AD trial designs. CONCLUSION: Increasing African American participation in AD clinical trials will require adaptation of trial protocols to address comorbidities and dropouts. However, increased diversity is unlikely to negatively affect trial outcomes and should be encouraged to promote generalizability of trial results.

Continuous Electroencephalography (cEEG) Monitoring and Outcomes of Critically Ill Patients.

BACKGROUND It is not clear whether performing continuous EEG (cEEG) in critically ill patients during intensive care unit (ICU) treatment affects outcomes at discharge. MATERIAL AND METHODS We prospectively matched 234 patients who received cEEG (cases) by admission diagnosis and sex to 234 patients who did not receive cEEG (controls) and followed them until discharge. Patients admitted due to seizures were excluded. The primary measures of outcome were Glasgow Coma Scale at Discharge (GCSD) and disposition at discharge, and the secondary measures of outcome were AED modifications, Glasgow Outcomes Scale, and Modified-Rankin Scale. These outcomes were compared between the cases and controls. RESULTS Some differences in primary outcome measures between the groups emerged on univariate analyses, but these differences were small and not significant after controlling for covariates. Cases had longer ICU stays (p=0.002) and lower admission GCS (p=0.01) but similar GCSD (p=0.10). Of the secondary outcome measures, the mean (SD) number of AED modifications for cases was 2.2±3.1 compared to 0.4±0.8 for controls (p<0.0001); 170 (72.6%) cases had at least 1 AED modification compared to only 56 (24.1%) of the controls (p<0.0001). CONCLUSIONS Performing cEEG did not improve discharge outcome but it significantly influenced AED prescription patterns. Further studies assessing long-term outcomes are needed to better define the role of cEEG in this patient population.

The DIAN-TU Next Generation Alzheimer's prevention trial: Adaptive design and disease progression model.

INTRODUCTION: The Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) trial is an adaptive platform trial testing multiple drugs to slow or prevent the progression of Alzheimer's disease in autosomal dominant Alzheimer's disease (ADAD) families. With completion of enrollment of the first two drug arms, the DIAN-TU now plans to add new drugs to the platform, designated as the Next Generation (NexGen) prevention trial. METHODS: In collaboration with ADAD families, philanthropic organizations, academic leaders, the DIAN-TU Pharma Consortium, the National Institutes of Health, and regulatory colleagues, the DIAN-TU developed innovative clinical study designs for the DIAN-TU NexGen prevention trial. RESULTS: Our expanded trial toolbox consists of a disease progression model for ADAD, primary end point DIAN-TU cognitive performance composite, biomarker development, self-administered cognitive assessments, adaptive dose adjustments, and blinded data collection through the last participant completion. CONCLUSION: These steps represent elements to improve efficacy of the adaptive platform trial and a continued effort to optimize prevention and treatment trials in ADAD.