Development of a straightforward and sensitive scale for MCI and early AD clinical trials

Huang, Yifan; Ito, Kaori; Billing, Clare B.; Anziano, Richard J.; Initiative, Alzheimer’s Disease Neuroimaging

doi:10.1016/j.jalz.2014.03.008

Cited by 19 publications

(28 citation statements)

References 17 publications

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“…The current research addresses the critical importance of understanding how the individual items or subscales may affect the performances of the overall scale, illustrated by a simple form of two components. Composites with more than two components have also been proposed or are in use in AD studies (Crane et al, 2012;Donohue et al, 2014;Langbaum et al, 2014;Huang et al, 2015). The conclusion from our work that a composite has a greater treatment effect size than the minimal component can be generalized to composites with more than two components (see mathematical proof in supplemental material).…”

Section: Discussionsupporting

confidence: 59%

“…Continuous composites are used in many different therapeutic areas. For example, they are gaining greater interest in Alzheimer's disease (AD) research and development in recent years (Crane et al, 2012;Raghavan et al, 2013;Donohue et al, 2014;Langbaum et al, 2014;Huang et al, 2015). AD is a progressive neurodegenerative disease that impairs patients' cognitive capabilities and subsequently their functioning of daily living.…”

Section: Introductionmentioning

confidence: 99%

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Statistical properties of continuous composite scales and implications for drug development

Liu‐Seifert

Andersen

Case

et al. 2017

Journal of Biopharmaceutical Statistics

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Little research has been conducted on the statistical properties of composite measures comprising linear combinations of continuous component scales. We assessed the quantitative relationship between the composites and their individual components regarding their abilities to detect treatment effects. In particular, we developed the mathematical derivation of the treatment effect size of a continuous composite in relation to the treatment effect sizes of its components and proved multiple properties of the composite. We demonstrated that the treatment effect size of a composite is greater than the minimum treatment effect size of its components and that above certain thresholds of correlations of components and ratios of component effect sizes, the composite may outperform its components. Examples from Alzheimer's disease (AD) clinical studies of solanezumab and donepezil using the composite Integrated AD Rating Scale (iADRS) and its components, the AD Assessment Scale-Cognitive subscale (ADAS-Cog) and AD Cooperative Study-Activities of Daily Living inventory, instrumental items (ADCS-iADL) were consistent with the theoretical statistical properties. The understanding of the quantitative relationships between continuous composites and their components will be useful in clinical trial design and the development of new scales and composites across therapeutic areas.

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Section: Discussionsupporting

confidence: 59%

Section: Introductionmentioning

confidence: 99%

Statistical properties of continuous composite scales and implications for drug development

Liu‐Seifert

Andersen

Case

et al. 2017

Journal of Biopharmaceutical Statistics

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“…14 Mais recentemente, em 2013, Cedarbaum e colaboradores avaliaram o uso do CDR-SOB como medida de desfecho primário em ensaios clínicos, mostrando que as propriedades psicométricas do instrumento parecem adequadas para as pesquisas realizadas nas fases mais precoces da DA. 15 Até a conclusão deste levantamento bibliográfico, os artigos relevantes estavam relacionados ao uso CDR-SOB como parte de um possível instrumento para avaliação no CCL e nos estágios iniciais da DA, 16 ao desenvolvimento de pontos de cortes diferenciado do CDR global e CDR-SOB para pacientes com doença de Parkinson, 17 ao uso do CDR global no CCL 18 e na avaliação da performance de grupos em ensaios clínicos com o uso do CDR-SOB. 19 O CDR no Brasil Apesar de o CDR ser conhecido mundialmente como um instrumento com alta confiabilidade no estagiamento da demência, no Brasil ainda dispomos de poucas publicações referentes ao tema.…”

Section: Resultsunclassified

Trinta anos da escala Clinical Dementia Rating: o que sabemos sobre o CDR?

Pinto

Perez

2018

Revista HUPE

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Introdução: Há uma crescente demanda por instrumentos padronizados, tanto para o rastreio quanto para o diagnóstico de demência, em ambientes de assistência e de pesquisa. A escala Clinical Dementia Rating (CDR) foi desenvolvida há 30 anos, permite uma avaliação global cognitiva e funcional, e foi submetida a adaptações ao longo dos anos. Objetivos: Detalhar o desenvolvimento do CDR, com ênfase na cronologia das principais publicações e nas validações disponíveis no Brasil. Método: Revisão narrativa por meio de busca eletrônica no Pubmed e em referências bibliográficas dos artigos identificados. Foram selecionados 23 artigos. Resultados: O CDR foi desenvolvido por Hughes no Memory Aging Project, da Universidade de Washington, em 1977, e publicado no Bristish Journal of Psychiatry, em 1982. É composto por um questionário estruturado e uma escala que avaliam seis domínios cognitivos: memória, orientação, julgamento e resolução de problemas, assuntos da comunidade, casa e lazer e autocuidado. Os indivíduos são classificados em quatro categorias: 0 = ausência de demência; 0.5 = demência questionável; 1 = demência leve; 2 = demência moderada; e 3 = demência avançada. Em 2008, uma simplificação da pontuação foi proposta e validada, usando a soma de cada domínio, chamada Sum of Box (CDR-SOB). No Brasil, foram identificados dois estudos de validação do CDR e um estudo do uso do CDR-SOB. Conclusões: O CDR é um instrumento útil com alta confiabilidade na avaliação das demências, com duas validações disponíveis no Brasil. As versões mais recentes parecem possibilitar uma melhor avaliação dos estágios iniciais dos quadros demenciais.Descritores: Clinical Dementia Rating; Validação; Demência.

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“…Those included ADAS‐cog, MMSE, CDR, Functional Assessment Questionnaire (FAQ), Clock Drawing Test, Rey Auditory Verbal Learning Test, Logical Memory Test, Digit Span Test, Category Fluency Test, Trail Making Test, Digit Symbol Substitution Test, and Boston Naming Test. In MCI populations enriched by APOE ‐ε4 allele, hippocampal volume, and CSF Aβ, the best composite score was Word Recall + Delayed Word Recall + Orientation + CDR‐SB + FAQ, which was more sensitive than ADAS‐cog or CDR‐SB alone . A combined framework of item response theory and pharmacometric modeling of ADAS‐cog has also been investigated in an MCI plus mild AD population, demonstrating a significantly higher power to detect drug effect compared with the traditional method of analysis; in particular, 71% and 23% trial size reduction when compared with a least square means and a traditional pharmacometric analysis, respectively …”

Section: Selection Of End Pointsmentioning

confidence: 99%

“…61 Another study evaluated possible combinations of clinical end points (both total scores and individual item scores) available in ADNI-1 and ADNI-GO. 62 Those included ADAS-cog, MMSE, CDR, Functional Assessment Questionnaire (FAQ), Clock Drawing Test, Rey Auditory Verbal Learning Test, Logical Memory Test, Digit Span Test, Category Fluency Test, Trail Making Test, Digit Symbol Substitution Test, and Boston Naming Test. In MCI populations enriched by APOE-ε4 allele, hippocampal volume, and CSF Aβ, the best composite score was Word Recall + Delayed Word Recall + Orientation + CDR-SB + FAQ, which was more sensitive than ADAS-cog or CDR-SB alone.…”

Section: Modeling and Simulation Aid: Model-informed Composite End Pomentioning

confidence: 99%

Challenges in Alzheimer's Disease Drug Discovery and Development: The Role of Modeling, Simulation, and Open Data

Conrado¹,

Duvvuri

Geerts

et al. 2020

Clin Pharma and Therapeutics

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Alzheimer’s disease (AD) is the leading cause of dementia worldwide. With 35 million people over 60 years of age with dementia, there is an urgent need to develop new treatments for AD. To streamline this process, it is imperative to apply insights and learnings from past failures to future drug development programs. In the present work, we focus on how modeling and simulation tools can leverage open data to address drug development challenges in AD.

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Development of a straightforward and sensitive scale for MCI and early AD clinical trials

Abstract: The proposed composite score derived from the existing clinical endpoints demonstrated higher sensitivity in the MCI population and is easy to implement and standardize across studies.

Cited by 19 publications

References 17 publications

Statistical properties of continuous composite scales and implications for drug development

Statistical properties of continuous composite scales and implications for drug development

Trinta anos da escala Clinical Dementia Rating: o que sabemos sobre o CDR?

Challenges in Alzheimer's Disease Drug Discovery and Development: The Role of Modeling, Simulation, and Open Data

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