Modelling the distribution of cognitive outcomes for early-stage neurocognitive disorders: a model comparison approach
Background: Cognitive assessments for patients with neurocognitive disorders are mostly measured by the Montreal Cognitive Assessment (MoCA) and Visual Cognitive Assessment Test (VCAT) as screening tools. These cognitive scores are usually left-skewed and the results of the association analysis migh...
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sg-ntu-dr.10356-1784782024-06-30T15:39:16Z Modelling the distribution of cognitive outcomes for early-stage neurocognitive disorders: a model comparison approach Saffari, Seyed Ehsan Soo, See Ann Mohammadi, Raziyeh Ng, Kok Pin Greene, William Kandiah, Negaenderan Lee Kong Chian School of Medicine (LKCMedicine) Duke-NUS Medical School Dementia Research Centre Medicine, Health and Life Sciences Cognitive impairment Cognitive screening tool Background: Cognitive assessments for patients with neurocognitive disorders are mostly measured by the Montreal Cognitive Assessment (MoCA) and Visual Cognitive Assessment Test (VCAT) as screening tools. These cognitive scores are usually left-skewed and the results of the association analysis might not be robust. This study aims to study the distribution of the cognitive outcomes and to discuss potential solutions. Materials and Methods: In this retrospective cohort study of individuals with subjective cognitive decline or mild cognitive impairment, the inverse-transformed cognitive outcomes are modelled using different statistical distributions. The robustness of the proposed models are checked under different scenarios: with intercept-only, models with covariates, and with and without bootstrapping. Results: The main results were based on the VCAT score and validated via the MoCA score. The findings suggested that the inverse transformation method improved the modelling the cognitive scores compared to the conventional methods using the original cognitive scores. The association of the baseline characteristics (age, gender, and years of education) and the cognitive outcomes were reported as estimates and 95% confidence intervals. Bootstrap methods improved the estimate precision and the bootstrapped standard errors of the estimates were more robust. Cognitive outcomes were widely analysed using linear regression models with the default normal distribution as a conventional method. We compared the results of our suggested models with the normal distribution under various scenarios. Goodness-of-fit measurements were compared between the proposed models and conventional methods. Conclusions: The findings support the use of the inverse transformation method to model the cognitive outcomes instead of the original cognitive scores for early-stage neurocognitive disorders where the cognitive outcomes are left-skewed. Ministry of Education (MOE) National Medical Research Council (NMRC) Published version This research is supported by the Ministry of Education, Singapore, under its MOE AcRF Tier 3 Award MOE2017-T3-1-002, National Medical Research Council (NMRC), Singapore, under its Clinician Scientist Award (MOH-CSAINV18nov-0007), National Neuroscience Institute-Health Research Endowment Fund, Singapore (NNI-HREF 991016), and National Medical Research Council (NMRC), Singapore, under its Clinician Scientist Award (CNIG22jul-0004). 2024-06-24T00:58:22Z 2024-06-24T00:58:22Z 2024 Journal Article Saffari, S. E., Soo, S. A., Mohammadi, R., Ng, K. P., Greene, W. & Kandiah, N. (2024). Modelling the distribution of cognitive outcomes for early-stage neurocognitive disorders: a model comparison approach. Biomedicines, 12(2), 393-. https://dx.doi.org/10.3390/biomedicines12020393 2227-9059 https://hdl.handle.net/10356/178478 10.3390/biomedicines12020393 38397995 2-s2.0-85187248310 2 12 393 en MOE2017-T3-1-002 MOH-CSAINV18nov-0007 NNI-HREF 991016 CNIG22jul-0004 Biomedicines © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf |
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Medicine, Health and Life Sciences Cognitive impairment Cognitive screening tool Saffari, Seyed Ehsan Soo, See Ann Mohammadi, Raziyeh Ng, Kok Pin Greene, William Kandiah, Negaenderan Modelling the distribution of cognitive outcomes for early-stage neurocognitive disorders: a model comparison approach |
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Background: Cognitive assessments for patients with neurocognitive disorders are mostly measured by the Montreal Cognitive Assessment (MoCA) and Visual Cognitive Assessment Test (VCAT) as screening tools. These cognitive scores are usually left-skewed and the results of the association analysis might not be robust. This study aims to study the distribution of the cognitive outcomes and to discuss potential solutions. Materials and Methods: In this retrospective cohort study of individuals with subjective cognitive decline or mild cognitive impairment, the inverse-transformed cognitive outcomes are modelled using different statistical distributions. The robustness of the proposed models are checked under different scenarios: with intercept-only, models with covariates, and with and without bootstrapping. Results: The main results were based on the VCAT score and validated via the MoCA score. The findings suggested that the inverse transformation method improved the modelling the cognitive scores compared to the conventional methods using the original cognitive scores. The association of the baseline characteristics (age, gender, and years of education) and the cognitive outcomes were reported as estimates and 95% confidence intervals. Bootstrap methods improved the estimate precision and the bootstrapped standard errors of the estimates were more robust. Cognitive outcomes were widely analysed using linear regression models with the default normal distribution as a conventional method. We compared the results of our suggested models with the normal distribution under various scenarios. Goodness-of-fit measurements were compared between the proposed models and conventional methods. Conclusions: The findings support the use of the inverse transformation method to model the cognitive outcomes instead of the original cognitive scores for early-stage neurocognitive disorders where the cognitive outcomes are left-skewed. |
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Lee Kong Chian School of Medicine (LKCMedicine) |
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Lee Kong Chian School of Medicine (LKCMedicine) Saffari, Seyed Ehsan Soo, See Ann Mohammadi, Raziyeh Ng, Kok Pin Greene, William Kandiah, Negaenderan |
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Article |
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Saffari, Seyed Ehsan Soo, See Ann Mohammadi, Raziyeh Ng, Kok Pin Greene, William Kandiah, Negaenderan |
author_sort |
Saffari, Seyed Ehsan |
title |
Modelling the distribution of cognitive outcomes for early-stage neurocognitive disorders: a model comparison approach |
title_short |
Modelling the distribution of cognitive outcomes for early-stage neurocognitive disorders: a model comparison approach |
title_full |
Modelling the distribution of cognitive outcomes for early-stage neurocognitive disorders: a model comparison approach |
title_fullStr |
Modelling the distribution of cognitive outcomes for early-stage neurocognitive disorders: a model comparison approach |
title_full_unstemmed |
Modelling the distribution of cognitive outcomes for early-stage neurocognitive disorders: a model comparison approach |
title_sort |
modelling the distribution of cognitive outcomes for early-stage neurocognitive disorders: a model comparison approach |
publishDate |
2024 |
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https://hdl.handle.net/10356/178478 |
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1814047035427389440 |