Disease progression model anchored around clinical diagnosis in longitudinal cohorts: example of Alzheimer's disease and related dementia.

BACKGROUND: Alzheimer's disease and related dementia (ADRD) are characterized by multiple and progressive anatomo-clinical changes including accumulation of abnormal proteins in the brain, brain atrophy and severe cognitive impairment. Understanding the sequence and timing of these changes is of primary importance to gain insight into the disease natural history and ultimately allow earlier diagnosis. Yet, modeling changes over disease course from cohort data is challenging as the usual timescales (time since inclusion, chronological age) are inappropriate and time-to-clinical diagnosis is available on small subsamples of participants with short follow-up durations prior to diagnosis. One solution to circumvent this challenge is to define the disease time as a latent variable. METHODS: We developed a multivariate mixed model approach that realigns individual trajectories into the latent disease time to describe disease progression. In contrast with the existing literature, our methodology exploits the clinical diagnosis information as a partially observed and approximate reference to guide the estimation of the latent disease time. The model estimation was carried out in the Bayesian Framework using Stan. We applied the methodology to the MEMENTO study, a French multicentric clinic-based cohort of 2186 participants with 5-year intensive follow-up. Repeated measures of 12 ADRD markers stemmed from cerebrospinal fluid (CSF), brain imaging and cognitive tests were analyzed. RESULTS: The estimated latent disease time spanned over twenty years before the clinical diagnosis. Considering the profile of a woman aged 70 with a high level of education and APOE4 carrier (the main genetic risk factor for ADRD), CSF markers of tau proteins accumulation preceded markers of brain atrophy by 5 years and cognitive decline by 10 years. However we observed that individual characteristics could substantially modify the sequence and timing of these changes, in particular for CSF level of A[Formula: see text]. CONCLUSION: By leveraging the available clinical diagnosis timing information, our disease progression model does not only realign trajectories into the most homogeneous way. It accounts for the inherent residual inter-individual variability in dementia progression to describe the long-term anatomo-clinical degradations according to the years preceding clinical diagnosis, and to provide clinically meaningful information on the sequence of events. TRIAL REGISTRATION: clinicaltrials.gov, NCT01926249. Registered on 16 August 2013.

Malignant hypercalcemia revealing a diffuse large B-cell lymphoma in a patient with a previous diagnosis of chronic myelomonocytic leukemia: An uncommon hematological coexistence.

A 76-year-old patient previously admitted to the cardiology department for replacement of a right ventricular lead on a double-chamber pacemaker was admitted to the internal medicine department 15 days after for bronchopneumopathy. His past medical history was relevant for Type 2 diabetes mellitus, heart failure due to dilated hypokinetic heart disease, transcatheter aortic valve implantation (TAVI), and chronic myelomonocytic leukemia (CMML-0) diagnosed in 2021. Twenty-four hours after admission, the patient's general condition deteriorated abruptly, with the onset of drowsiness and psychomotor retardation. Laboratory exams revealed hypercalcemia at 4.18 mmol/L. Intensive hydration, calcitonin, and zoledronic acid were initiated and the patient was transferred to the nephrology intensive care unit where he underwent two sessions of hemodialysis to normalize serum calcium levels before readmission to internal medicine. Laboratory exams revealed low parathyroid hormone, normal 1-25-OH vitamin D, and increased parathyroid hormone-related peptide. Thoracoabdominal and positron emission tomography (PET) scan showed diffuse abdominopelvic peritoneal carcinosis associated with low-grade pleural effusion and multiple supra- and sub-diaphragmatic adenopathies, leading to a search for a solid tumor. The patient's clinical condition worsened leading to a transfer to the intensive care unit. The biopsy of a peritoneal carcinosis nodule confirmed the diagnosis of diffuse large B-cell lymphoma. Specific treatments were unsuccessful and the patient expired.

Associations among hypertension, dementia biomarkers, and cognition: The MEMENTO cohort.

INTRODUCTION: Approximately 40% of dementia cases could be delayed or prevented acting on modifiable risk factors including hypertension. However, the mechanisms underlying the hypertension-dementia association are still poorly understood. METHODS: We conducted a cross-sectional analysis in 2048 patients from the MEMENTO cohort, a French multicenter clinic-based study of outpatients with either isolated cognitive complaints or mild cognitive impairment. Exposure to hypertension was defined as a combination of high blood pressure (BP) status and antihypertensive treatment intake. Pathway associations were examined through structural equation modeling integrating extensive collection of neuroimaging biomarkers and clinical data. RESULTS: Participants treated with high BP had significantly lower cognition compared to the others. This association was mediated by higher neurodegeneration and higher white matter hyperintensities load but not by Alzheimer's disease (AD) biomarkers. DISCUSSION: These results highlight the importance of controlling hypertension for prevention of cognitive decline and offer new insights on mechanisms underlying the hypertension-dementia association. HIGHLIGHTS: Paths of hypertension-cognition association were assessed by structural equation models. The hypertension-cognition association is not mediated by Alzheimer's disease biomarkers. The hypertension-cognition association is mediated by neurodegeneration and leukoaraiosis. Lower cognition was limited to participants treated with uncontrolled blood pressure. Blood pressure control could contribute to promote healthier brain aging.

How Selection Over Time Contributes to the Inconsistency of the Association Between Sex/Gender and Cognitive Decline Across Cognitive Aging Cohorts.

The association between sex/gender and aging-related cognitive decline remains poorly understood because of inconsistencies in findings. Such heterogeneity could be attributable to the cognitive functions studied and study population characteristics, but also to differential selection by dropout and death between men and women. We aimed to evaluate the impact of selection by dropout and death on the association between sex/gender and cognitive decline. We first compared the statistical methods most frequently used for longitudinal data, targeting either population estimands (marginal models fitted by generalized estimating equations) or subject-specific estimands (mixed/joint models fitted by likelihood maximization) in 8 studies of aging: 6 population-based studies (the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) Study (1996-2009), Personnes Âgées QUID (PAQUID; 1988-2014), the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study (2003-2016), the Three-City Study (Bordeaux only; 1999-2016), the Washington Heights-Inwood Community Aging Project (WHICAP; 1992-2017), and the Whitehall II Study (2007-2016)) and 2 clinic-based studies (the Alzheimer's Disease Neuroimaging Initiative (ADNI; 2004-2017) and a nationwide French cohort study, MEMENTO (2011-2016)). We illustrate differences in the estimands of the association between sex/gender and cognitive decline in selected examples and highlight the critical role of differential selection by dropout and death. Using the same estimand, we then contrast the sex/gender-cognitive decline associations across cohorts and cognitive measures suggesting a residual differential sex/gender association depending on the targeted cognitive measure (memory or animal fluency) and the initial cohort selection. We recommend focusing on subject-specific estimands in the living population for assessing sex/gender differences while handling differential selection over time.

Personalized prediction of progression in pre-dementia patients based on individual biomarker profile: A development and validation study.

INTRODUCTION: The prognosis of patients at the pre-dementia stage is difficult to define. The aim of this study is to develop and validate a biomarker-based continuous model for predicting the individual cognitive level at any future moment. In addition to personalized prognosis, such a model could reduce trial sample size requirements by allowing inclusion of a homogenous patient population. METHODS: Disease-progression modeling of longitudinal cognitive scores of pre-dementia patients (baseline Clinical Dementia Rating ≤ 0.5) was used to derive a biomarker profile that was predictive of patient's cognitive progression along the dementia continuum. The biomarker profile model was developed and validated in the MEMENTO cohort and externally validated in the Alzheimer's Disease Neuroimaging Initiative. RESULTS: Of nine candidate biomarkers in the development analysis, three cerebrospinal fluid and two magnetic resonance imaging measures were selected to form the final biomarker profile. The model-based prognosis of individual future cognitive deficit was shown to significantly improve when incorporating biomarker information on top of cognition and demographic data. In trial power calculations, adjusting the primary analysis for the baseline biomarker profile reduced sample size requirements by ≈10%. Compared to conventional cognitive cut-offs, inclusion criteria based on biomarker-profile cut-offs resulted in up to 28% reduced sample size requirements due to increased homogeneity in progression patterns. DISCUSSION: The biomarker profile allows prediction of personalized trajectories of future cognitive progression. This enables accurate personalized prognosis in clinical care and better selection of patient populations for clinical trials. A web-based application for prediction of patients' future cognitive progression is available online.

Cost comparison of reusable and disposable air/water syringe tips in a large French teaching hospital

Air/water syringe (AWS) tips can be used in any type of dental care. They may be disposable (plastic) or reusable (stainless steel or plastic). We assessed the costs of using both sorts of tips in a French teaching hospital. A systematic use of one AWS tip per dental consultation was considered. Consultations performed with reusable AWS (stainless steel) tips give rise to costs linked to initial purchase of tips, their sterilisation, and replacement. Consultation costs of disposable AWS tips were calculated at their current purchase price. Replacing reusable tips was evaluat-ed in two different situations: annual replacement or replacement in case of visual deterioration. Results showed that the number of consultations must lie beyond a certain threshold in order to make reusable tips more economical in use than disposable counterparts. If the reusable tips are replaced every year, this threshold is higher (e.g.: 1,366consultations at the University of Bordeaux) than under a rule of tip replacement in case of visual deterioration (e.g. at the Bordeaux University: 1,267consultations in case of an annual replacement rate of 10%, or 1,289 with a re-placement rate of 30%). This is the first study regarding the costs of disposable versus reusable AWS tips. We suggest that disposable tips might be more cost-effective than reusable tips, not-ably because of their reduced risk of crosscontamination. The choice of the use of one or an-other AWS tip crucially depends on the number of consultations, as well as on their practical utilisation and on infection control issues.