Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's disease
Abstract Introduction Clinical trials for sporadic Alzheimer's disease generally use mixed models for repeated measures (MMRM) or, to a lesser degree, constrained longitudinal data analysis models (cLDA) as the analysis model with time since baseline as a categorical variable. Inferences using...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Alzheimer’s & Dementia: Translational Research & Clinical Interventions |
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| Online Access: | https://doi.org/10.1002/trc2.12286 |
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| author | Guoqiao Wang Lei Liu Yan Li Andrew J. Aschenbrenner Randall J. Bateman Paul Delmar Lon S. Schneider Richard E. Kennedy Gary R. Cutter Chengjie Xiong |
| author_facet | Guoqiao Wang Lei Liu Yan Li Andrew J. Aschenbrenner Randall J. Bateman Paul Delmar Lon S. Schneider Richard E. Kennedy Gary R. Cutter Chengjie Xiong |
| author_sort | Guoqiao Wang |
| collection | DOAJ |
| description | Abstract Introduction Clinical trials for sporadic Alzheimer's disease generally use mixed models for repeated measures (MMRM) or, to a lesser degree, constrained longitudinal data analysis models (cLDA) as the analysis model with time since baseline as a categorical variable. Inferences using MMRM/cLDA focus on the between‐group contrast at the pre‐determined, end‐of‐study assessments, thus are less efficient (eg, less power). Methods The proportional cLDA (PcLDA) and proportional MMRM (pMMRM) with time as a categorical variable are proposed to use all the post‐baseline data without the linearity assumption on disease progression. Results Compared with the traditional cLDA/MMRM models, PcLDA or pMMRM lead to greater gain in power (up to 20% to 30%) while maintaining type I error control. Discussion The PcLDA framework offers a variety of possibilities to model longitudinal data such as proportional MMRM (pMMRM) and two‐part pMMRM which can model heterogeneous cohorts more efficiently and model co‐primary endpoints simultaneously. |
| format | Article |
| id | doaj-art-156b39a76da5402b9763580e7d3ca7c6 |
| institution | DOAJ |
| issn | 2352-8737 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Alzheimer’s & Dementia: Translational Research & Clinical Interventions |
| spelling | doaj-art-156b39a76da5402b9763580e7d3ca7c62025-08-20T02:50:40ZengWileyAlzheimer’s & Dementia: Translational Research & Clinical Interventions2352-87372022-01-0181n/an/a10.1002/trc2.12286Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's diseaseGuoqiao Wang0Lei Liu1Yan Li2Andrew J. Aschenbrenner3Randall J. Bateman4Paul Delmar5Lon S. Schneider6Richard E. Kennedy7Gary R. Cutter8Chengjie Xiong9Division of Biostatistics Washington University School of Medicine St. Louis Missouri USADivision of Biostatistics Washington University School of Medicine St. Louis Missouri USADepartment of Neurology Washington University School of Medicine St. Louis Missouri USADepartment of Neurology Washington University School of Medicine St. Louis Missouri USADepartment of Neurology Washington University School of Medicine St. Louis Missouri USAF. Hoffmann‐La Roche Ltd. Basel SwitzerlandDepartment of Psychiatry and The Behavioral Sciences Department of Neurology Keck School of Medicine University of Southern California Los Angeles USADepartment of Medicine University of Alabama at Birmingham Birmingham USADepartment of Biostatistics University of Alabama at Birmingham Birmingham USADivision of Biostatistics Washington University School of Medicine St. Louis Missouri USAAbstract Introduction Clinical trials for sporadic Alzheimer's disease generally use mixed models for repeated measures (MMRM) or, to a lesser degree, constrained longitudinal data analysis models (cLDA) as the analysis model with time since baseline as a categorical variable. Inferences using MMRM/cLDA focus on the between‐group contrast at the pre‐determined, end‐of‐study assessments, thus are less efficient (eg, less power). Methods The proportional cLDA (PcLDA) and proportional MMRM (pMMRM) with time as a categorical variable are proposed to use all the post‐baseline data without the linearity assumption on disease progression. Results Compared with the traditional cLDA/MMRM models, PcLDA or pMMRM lead to greater gain in power (up to 20% to 30%) while maintaining type I error control. Discussion The PcLDA framework offers a variety of possibilities to model longitudinal data such as proportional MMRM (pMMRM) and two‐part pMMRM which can model heterogeneous cohorts more efficiently and model co‐primary endpoints simultaneously.https://doi.org/10.1002/trc2.12286Alzheimer's diseaseproportional constrained longitudinal data analysis model (PcLDA)MMRMproportional MMRM (pMMRM)proportional treatment effect |
| spellingShingle | Guoqiao Wang Lei Liu Yan Li Andrew J. Aschenbrenner Randall J. Bateman Paul Delmar Lon S. Schneider Richard E. Kennedy Gary R. Cutter Chengjie Xiong Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's disease Alzheimer’s & Dementia: Translational Research & Clinical Interventions Alzheimer's disease proportional constrained longitudinal data analysis model (PcLDA) MMRM proportional MMRM (pMMRM) proportional treatment effect |
| title | Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's disease |
| title_full | Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's disease |
| title_fullStr | Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's disease |
| title_full_unstemmed | Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's disease |
| title_short | Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's disease |
| title_sort | proportional constrained longitudinal data analysis models for clinical trials in sporadic alzheimer s disease |
| topic | Alzheimer's disease proportional constrained longitudinal data analysis model (PcLDA) MMRM proportional MMRM (pMMRM) proportional treatment effect |
| url | https://doi.org/10.1002/trc2.12286 |
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