Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU): Trial Satisfaction and Attitudes towards Future Clinical Trials.

BACKGROUND: Clinical trial satisfaction is increasingly important for future trial designs and is associated with treatment adherence and willingness to enroll in future research studies or to recommend trial participation. In this post-trial survey, we examined participant satisfaction and attitudes toward future clinical trials in the Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU). METHODS: We developed an anonymous, participant satisfaction survey tailored to participants enrolled in the DIAN-TU-001 double-blind clinical trial of solanezumab or gantenerumab and requested that all study sites share the survey with their trial participants. A total of 194 participants enrolled in the trial at 24 study sites. We utilized regression analysis to explore the link between participants' clinical trial experiences, their satisfaction, and their willingness to participate in upcoming trials. RESULTS: Survey responses were received over a sixteen-month window during 2020-2021 from 58 participants representing 15 study sites. Notably, 96.5% of the survey respondents expressed high levels of satisfaction with the trial, 91.4% would recommend trial participation, and 96.5% were willing to enroll again. Age, gender, and education did not influence satisfaction levels. Participants reported enhanced medical care (70.7%) and pride in contributing to the DIAN-TU trial (84.5%). Satisfaction with personnel and procedures was high (98.3%). Respondents had a mean age of 48.7 years, with most being from North America and Western Europe, matching the trial's demographic distribution. Participants' decisions to learn their genetic status increased during the trial, and most participants endorsed considering future trial participation regardless of the DIAN-TU-001 trial outcome. CONCLUSION: Results suggest that DIAN-TU-001 participants who responded to the survey exhibited high motivation to participate in research, overall satisfaction with the clinical trial, and willingness to participate in research in the future, despite a long trial duration of 4-7 years with detailed annual clinical, cognitive, PET, MRI, and lumbar puncture assessments. Implementation of features that alleviate barriers and challenges to trial participation is like to have a high impact on trial satisfaction and reduce participant burden.

Clinical Correlates of the PET-based Braak Staging Framework in Alzheimer's Disease.

In vivo Alzheimer's disease diagnosis and staging is traditionally based on clinical features. However, the agreement between clinical and pathological Alzheimer's disease diagnosis, whose diagnosis assessment includes amyloid and Braak histopathological tau staging, is not completely convergent. The development of positron emission tomography (PET) tracers targeting neurofibrillary tangles offers prospects for advancing the staging of Alzheimer's disease from both biological and clinical perspectives. Recent advances in radiochemistry made it possible to apply the postmortem Braak staging framework to tau-PET images obtained in vivo. Here, our aim is to provide a narrative review of the current literature on the relationship between Alzheimer's disease clinical features and the PET-based Braak staging framework. Overall, the available studies support the stepwise increase in disease severity following the advance of PET-based Braak stages, with later stages being associated with worse cognitive and clinical symptoms. In line with this, there is a trend for unimpaired cognition, mild cognitive impairment, and Alzheimer's disease dementia to be compatible with early, intermediate, and late patterns of tau deposition based on PET-based Braak stages. Moreover, neuropsychiatric symptom severity seems to be linked to the extent of tau-PET signal across Braak areas. In sum, this framework seems to correspond well with the clinical progression of Alzheimer's disease, which is an indication of its potential utility in research and clinical practice, especially for detecting preclinical tau levels in individuals without symptoms. However, further research is needed to improve the generalizability of these findings and to better understand the applications of this staging framework.

CTAD Task Force Paper: Neuropsychiatric Symptoms in AD: Clinical Trials Targeting Mild Behavioral Impairment: A Report from the International CTAD Task Force.

The International CTAD Task Force (TF) addressed challenges related to designing clinical trials for agitation in dementia, presenting accomplishments from the two previous TFs on neuropsychiatric symptoms (NPS). In addition, this TF proposed a paradigm shift in NPS assessment and management, presenting Mild Behavioral Impairment (MBI) as a clinical syndrome. MBI is marked by later-life emergent and persistent NPS in dementia-free older persons (ranging from cognitively unimpaired to subjective cognitive decline to mild cognitive impairment), which facilitates earlier detection and better prognostication of Alzheimer's disease (AD). The TF has made the following recommendations for incorporation of NPS into AD preventative trials: (1) clinical trials targeting improvement in MBI symptoms should be undertaken; (2) treatment trials for MBI should be disease specific and confirm the diagnosis of participants using biomarkers; trials should include measures sensitive to cognitive changes in preclinical AD, which can serve as outcome measures, in addition to changes in biomarker levels; (3) as a first step, pharmacotherapeutic trials should address the full MBI complex as well as the specific symptoms/domains that constitute MBI; (4) clinical trials using problem-adaptation psychotherapy to target affective MBI should be considered; and (5) MBI should be considered in AD trials of disease modifying therapies. The well-validated and widely-used MBI Checklist (MBI-C) is an appropriate symptom rating scale for these studies, as it was developed specifically to identify and measure MBI in dementia-free persons. Other scales such as the Neuropsychiatric Inventory (NPI) may be used, although administration at two timepoints may be necessary to operationalize the MBI criterion of symptom persistence.

Viewpoint: Clinicians' Perspectives on How Disease Modifying Drugs for Alzheimer's Disease Impact Specialty Care.

Clinicians specialized in the diagnosis and management of persons living with early-stage Alzheimer's disease need to enable access, for those meeting criteria, to the new class of disease modifying drugs (DMDs). These drugs act on amyloid ß42 and delay progression of symptoms. Thus, there will be interest from patients and families. Over the short term, the use of antibodies administered intravenously with serial MRIs to detect amyloid-related imaging abnormalities (ARIA) may require participation in structured phase 4 studies or in registries with third party funding for support staff and MRI scans. In the mid term, the availability of oral anti-amyloid therapy, likely with lower risk of ARIA, may transform clinical practice to a model of screening suitable patients using plasma biomarkers, with a subsequent rapid referral to a specialized memory clinic. Eventually, the biological profile of patients for amyloid, tau, and inflammation will determine which type of DMD to use. We are optimistic that clinicians will gain confidence with the use DMDs and answer the increasing needs of our aging population.

Adding the Topographical Information from Tau-PET to the A/T/(N) Framework: Steps Towards Staging AD in Vivo.

Biomarkers have revolutionized the study and clinical diagnosis of Alzheimer's disease (AD). While amyloid-ß accumulation begins decades before the onset of clinical dementia in AD, tau pathology is more closely associated in both space and time to neurodegeneration and to clinical dysfunction. Correspondingly, tau-PET may prove useful in determining the severity of AD. Building on the biological research framework for AD, we review here methods and rationale to stage the severity of AD in vivo using the topographical distribution of tau-PET. We discuss how tau-PET can be used to detect early and subthreshold tau accumulation in medial temporal cortices prior to the onset of cognitive symptoms. Furthermore, tau-PET can be used to monitor the severity of AD as tau-PET spreads to association cortices and finally primary sensory cortices. We discuss the utility of tau-PET to monitor the progression of AD, the flexibility of potential approaches, and applications for clinical trials. In this regard, topographical information from tau-PET is a useful addition to the A/T/(N) framework.

White Matter Hyperintensity as a Vascular Contribution to the AT(N) Framework.

The AT(N) framework enables the classification of an individual within the biological Alzheimer's disease (AD) continuum by pairing the cognitive stage with the biomarker status of amyloid-beta (Aß, A), tau (T) and neurodegeneration (N). AD is a multifactorial disease that may involve different pathogenic mechanisms such as cerebrovascular disease (CVD). Therefore, biomarkers of these mechanisms can be added to the AT(N) framework to enhance the biomarker characterization of individuals within the AD continuum. In AD, white matter hyperintensities (WMH) which are postulated to develop as a result of chronic ischemia from small vessel CVD are shown to play a role in the aetiology. However, the interplay of WMH with Aß and tau pathophysiology in AD remains unclear. In this review, we summarized the studies that evaluated the associations between WMH and AD pathophysiology (Aß and tau). We found that the evidence supporting the association of WMH with Aß was mixed, and this may be explained by the relative contributions of WMH due to its differential load and anatomical distribution. More studies are also needed to determine the association of WMH with tau pathology. Future longitudinal studies with harmonized methodologies to quantify WMH and account for the anatomical differences of WMH are required to validate the relationship between WMH and AT(N) biomarkers. This will allow a clearer understanding of the utility of WMH as a vascular biomarker in the AT(N) framework. Novel CVD biomarkers will also have the potential to further elucidate the contributions of CVD to the AD pathophysiology.

Neuroinflammation Biomarkers in the AT(N) Framework Across the Alzheimer's Disease Continuum.

In the past years, neuroinflammation has been widely investigated in Alzheimer's disease (AD). Evidence from animal, in vivo and post-mortem studies has shown that inflammatory changes are a common feature of the disease, apparently happening in response to amyloid-beta and tau accumulation. Progress in imaging and fluid biomarkers now allows for identifying surrogate markers of neuroinflammation in living individuals, which may offer unprecedented opportunities to better understand AD pathogenesis and progression. In this context, inflammatory mediators and glial proteins (mainly derived from microglial cells and astrocytes) seem to be the most promising biomarkers. Here, we discuss the biological basis of neuroinflammation in AD, revise the proposed neuroinflammation biomarkers, describe what we have learned from anti-inflammatory drug trials, and critically discuss the potential addition of these biomarkers in the AT(N) framework.

Can We Use Blood Biomarkers as Entry Criteria and for Monitoring Drug Treatment Effects in Clinical Trials? A Report from the EU/US CTAD Task Force.

In randomized clinical trials (RCTs) for Alzheimer's Disease (AD), cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers are currently used for the detection and monitoring of AD pathological features. The use of less resource-intensive plasma biomarkers could decrease the burden to study volunteers and limit costs and time for study enrollment. Blood-based markers (BBMs) could thus play an important role in improving the design and the conduct of RCTs on AD. It remains to be determined if the data available on BBMs are strong enough to replace CSF and PET biomarkers as entry criteria and monitoring tools in RCTs.

Evaluation of the Statistical Detection of Change Algorithm for Screening Patients with MS with New Lesion Activity on Longitudinal Brain MRI.

BACKGROUND AND PURPOSE: Identification of new MS lesions on longitudinal MR imaging by human readers is time-consuming and prone to error. Our objective was to evaluate the improvement in the performance of subject-level detection by readers when assisted by the automated statistical detection of change algorithm. MATERIALS AND METHODS: A total of 200 patients with MS with a mean interscan interval of 13.2 (SD, 2.4) months were included. Statistical detection of change was applied to the baseline and follow-up FLAIR images to detect potential new lesions for confirmation by readers (Reader + statistical detection of change method). This method was compared with readers operating in the clinical workflow (Reader method) for a subject-level detection of new lesions. RESULTS: Reader + statistical detection of change found 30 subjects (15.0%) with at least 1 new lesion, while Reader detected 16 subjects (8.0%). As a subject-level screening tool, statistical detection of change achieved a perfect sensitivity of 1.00 (95% CI, 0.88-1.00) and a moderate specificity of 0.67 (95% CI, 0.59-0.74). The agreement on a subject level was 0.91 (95% CI, 0.87-0.95) between Reader + statistical detection of change and Reader, and 0.72 (95% CI, 0.66-0.78) between Reader + statistical detection of change and statistical detection of change. CONCLUSIONS: The statistical detection of change algorithm can serve as a time-saving screening tool to assist human readers in verifying 3D FLAIR images of patients with MS with suspected new lesions. Our promising results warrant further evaluation of statistical detection of change in prospective multireader clinical studies.

Oral Tau Aggregation Inhibitor for Alzheimer's Disease: Design, Progress and Basis for Selection of the 16 mg/day Dose in a Phase 3, Randomized, Placebo-Controlled Trial of Hydromethylthionine Mesylate.

BACKGROUND: Hydromethylthionine mesylate is a tau aggregation inhibitor shown to have exposure-dependent pharmacological activity on cognitive decline and brain atrophy in two completed Phase 3 trials in mild/moderate Alzheimer's disease (AD). OBJECTIVES: The present report summarises the basis for selection of 16 mg/day as monotherapy as the optimal treatment regime and the design rationale of a confirmatory Phase 3 trial (LUCIDITY). DESIGN: The trial comprises a 12-month double-blind, placebo-controlled phase followed by a 12-month modified delayed-start open-label treatment phase. SETTING: 76 clinical research sites in North America and Europe. PARTICIPANTS: 545 patients with probable AD or MCI-AD in the final version of the protocol. INTERVENTION: Participants were assigned randomly to receive hydromethylthione mesylate at doses of 16 mg/day, 8 mg/day or placebo at a 4:1:4 ratio during the double-blind phase. All participants in the open-label phase receive the 16 mg/day dose. MEASUREMENTS: Co-primary clinical outcomes are the 11-item Alzheimer's Disease Assessment Scale (ADAS-cog11) and the 23-item Alzheimer's Disease Cooperative Study - Activities of Daily Living (ADCS-ADL23). Secondary biomarker measures include whole-brain atrophy and temporal lobe 18F-fluorodeoxyglucose positron emission tomography. RESULTS: 446 participants are expected to complete the 12-month placebo-controlled phase in March 2022. CONCLUSIONS: If the primary end points are met, the data will provide confirmatory evidence of the clinical and biomarker benefits of hydromethylthionine mesylate in minimal to moderate AD. As low-dose oral hydromethylthionine mesylate is simple to use clinically, does not cause amyloid-related imaging abnormalities and has a benign safety profile, it would likely improve AD management.

Prediction of Cognitive Decline for Enrichment of Alzheimer's Disease Clinical Trials.

BACKGROUND: A key issue to Alzheimer's disease clinical trial failures is poor participant selection. Participants have heterogeneous cognitive trajectories and many do not decline during trials, which reduces a study's power to detect treatment effects. Trials need enrichment strategies to enroll individuals who are more likely to decline. OBJECTIVES: To develop machine learning models to predict cognitive trajectories in participants with early Alzheimer's disease and presymptomatic individuals over 24 and 48 months respectively. DESIGN: Prognostic machine learning models were trained from a combination of demographics, cognitive tests, APOE genotype, and brain imaging data. SETTING: Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), National Alzheimer's Coordinating Center (NACC), Open Access Series of Imaging Studies (OASIS-3), PharmaCog, and a Phase 3 clinical trial in early Alzheimer's disease were used for this study. PARTICIPANTS: A total of 2098 participants who had demographics, cognitive tests, APOE genotype, and brain imaging data, as well as follow-up visits for 24-48 months were included. MEASUREMENTS: Baseline magnetic resonance imaging, cognitive tests, demographics, and APOE genotype were used to separate decliners, defined as individuals whose CDR-Sum of Boxes scores increased during a predefined time window, from stable individuals. A prognostic model to predict decline at 24 months in early Alzheimer's disease was trained on 1151 individuals who had baseline diagnoses of mild cognitive impairment and Alzheimer's dementia from ADNI and NACC. This model was validated on 115 individuals from a placebo arm of a Phase 3 clinical trial and 76 individuals from the PharmaCog dataset. A second prognostic model to predict decline at 48 months in presymptomatic populations was trained on 628 individuals from ADNI and NACC who were cognitively unimpaired at baseline. This model was validated on 128 individuals from OASIS-3. RESULTS: The models achieved up to 79% area under the curve (cross-validated and out-of-sample). Power analyses showed that using prognostic models to recruit enriched cohorts of predicted decliners can reduce clinical trial sample sizes by as much as 51% while maintaining the same detection power. CONCLUSIONS: Prognostic tools for predicting cognitive decline and enriching clinical trials with participants at the highest risk of decline can improve trial quality, derisk endpoint failures, and accelerate therapeutic development in Alzheimer's disease.

Therapeutic Targets for Alzheimer's Disease: Amyloid Vs. Non-Amyloid. Where Does Consensus Lie Today? An CTAD Task Force Report.

There was consensus that both amyloid and tau pathologies should be targeted in Alzheimer's disease, as well as additional pathophysiological mechanisms such as neuroinflammation. The selection of one or both of these targets may depend upon a personalized approach that takes into account the genetic and acquired factors that cause AD in any given person as well as their stage of disease as reflected in a biomarker profile. The validation of this therapeutic approach will be made possible by new methodologies for subdividing into predominant pathology, by efficient methods for identifying people in the earliest stages of disease, and by combination studies.

[Pelvic fracture and urogenital dysfunction in women: A literature review]. / Fracture du pelvis et conséquences urogénitales chez la femme : revue de la littérature.

INTRODUCTION: The consequences of a pelvic fracture on pelvic statics and sexuality in women are often overlooked and relegated to secondary care. OBJECTIVE: To carry out a state of knowledge on disorders of pelvic statics and sexuality in patients with a history of pelvic fracture: incidence, risk factors, management. METHODS: Literature review on the Pubmed, Medline, Embase and Cochrane database using the following keywords and MeSH terms: pelvis floor dysfunction, urinary dysfunction, sexual dysfunction, pelvic organ prolapse, in association with the terms pelvic fracture, pelvic trauma. RESULTS: Among the 270 initial articles, 21 were selected. Finally, one retrospective cohort study has evaluated the impact of pelvic fracture on the onset of a genital prolapse, 2 comparative retrospective studies and one prospective study focused on the impact of pelvic fracture on lower urinary tract symptoms. One comprehensive review studied pelvic fracture and sexuality outcomes. The incidence of prolapse following pelvic fracture could not be identified. The incidence of lower urinary tract symptoms varies between 21 and 67% with a significant difference for urinary urgency without leakage (P=0.016) and SUI (P=0.004). The incidence of sexual disorders varies between 21 and 62% with a predominance of dyspareunia. The mechanism of the trauma is thought to be a contributing factor, as well as the damage of the pubic symphysis (RR 4.8 95% CI 2.0-11.2). CONCLUSION: The evaluation of urogenital, sexual and anorectal dysfunctions following trauma to the pelvis has so far been little explored in the literature. Future prospective studies are to be carried out to improve patient care.

Pain intensity and imaging at the initial phase of acute pyelonephritis.

OBJECTIVE: To identify predictive factors of urological complication on imaging findings in women with pyelonephritis aged 18 to 65 years. METHODS: We performed an observational, retrospective, single-center study. The medical charts of women diagnosed with pyelonephritis at the emergency department from 2010 to 2015 were reviewed. Only patients who underwent an imaging study at the emergency department and with microbiologically confirmed pyelonephritis were included for analysis. The primary endpoint was the presence of urological complications on imaging findings. The secondary endpoint was treatment changes after imaging diagnosis. RESULTS: Of the 193 women enrolled, 88 (45.6%) had urological complication(s) on imaging findings. The multivariate analysis revealed that history of urolithiasis (OR=2.41; P=0.01) and pain requiring morphine use (OR=5.29; P=0.009) were predictive of urological complications on imaging findings. Of the 120 women with uncomplicated pyelonephritis who underwent imaging studies, 45% had urological complication, resulting in a treatment change in 36.7% of patients. The multivariate analysis revealed that age>40 years (OR=4.58; P=0.02) and pain requiring morphine use (OR=3.78; P=0.02) were predictive of urological complication(s) on imaging findings and of treatment change based on imaging findings (OR=6.76; P=0.005 and OR=4.19; P=0.01 respectively) in this subgroup. CONCLUSIONS: Pain requiring morphine use, age, and history of urolithiasis are independent predictors of urological complications on imaging findings in patients with acute pyelonephritis.

Utility of enhanced CT for patients with suspected uncomplicated renal colic and no acute findings on non-enhanced CT.

AIM: To evaluate the utility of contrast-enhanced computed tomography (CECT) for patients with suspected uncomplicated renal colic (URC) and no abnormalities on non-enhanced computed tomography (NECT). MATERIALS AND METHODS: The hospital institutional review board and ethics committee approved this retrospective study with a waiver of informed consent. Between January 2016 and April 2017, all consecutive adult patients who consulted at the adult Emergency Department (ED) with suspected URC and who had undergone both NECT and CECT were included retrospectively. The primary endpoint was prevalence of CECT-only diagnosis without acute findings on NECT. The risk factors for an acute finding were identified by logistic regression analysis. RESULTS: Among 126 patients with suspected URC, 12 were excluded. Among the 76 patients with no acute findings on NECT, CECT led to find acute lesions in 14/76 (18%) cases, but only 2/76 (3%) resulted in a change of management. Predictive factors of abnormal finding on CECT were: low renal clearance and high leukocyte count with OR 0.96 (95% confidence interval [CI]: 0.93-0.99), p=0.0189 and OR 5.79 (95% CI: 1.55-21.64), p=0.0091, respectively. CONCLUSIONS: In most cases, NECT is sufficient for screening patients with suspected URC. If leucocytosis and low renal function are present, stronger consideration may be given to CECT.

Rostral-Caudal Hippocampal Functional Convergence Is Reduced Across the Alzheimer's Disease Spectrum.

Beginning in the early stages of Alzheimer's disease (AD), the hippocampus reduces its functional connections to other cortical regions due to synaptic depletion. However, little is known regarding connectivity abnormalities within the hippocampus. Here, we describe rostral-caudal hippocampal convergence (rcHC), a metric of the overlap between the rostral and caudal hippocampal functional networks, across the clinical spectrum of AD. We predicted a decline in rostral-caudal hippocampal convergence in the early stages of the disease. Using fMRI, we generated resting-state hippocampal functional networks across 56 controls, 48 early MCI (EMCI), 35 late MCI (LMCI), and 31 AD patients from the Alzheimer's Disease Neuroimaging Initiative cohort. For each diagnostic group, we performed a conjunction analysis and compared the rostral and caudal hippocampal network changes using a mixed effects linear model to estimate the convergence and differences between these networks, respectively. The conjunction analysis showed a reduction of rostral-caudal hippocampal convergence strength from early MCI to AD, independent of hippocampal atrophy. Our results demonstrate a parallel between the functional convergence within the hippocampus and disease stage, which is independent of brain atrophy. These findings support the concept that network convergence might contribute as a biomarker for connectivity dysfunction in early stages of AD.

Combination Therapy for Alzheimer's Disease: Perspectives of the EU/US CTAD Task Force.

Combination therapy is expected to play an important role for the treatment of Alzheimer's disease (AD). In October 2018, the European Union-North American Clinical Trials in Alzheimer's Disease Task Force (EU/US CTAD Task Force) met to discuss scientific, regulatory, and logistical challenges to the development of combination therapy for AD and current efforts to address these challenges. Task Force members unanimously agreed that successful treatment of AD will likely require combination therapy approaches that target multiple mechanisms and pathways. They further agreed on the need for global collaboration and sharing of data and resources to accelerate development of such approaches.