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1. Nonlinear Z‐score modeling for improved detection of cognitive abnormality

Author

John Kornak, Julie Fields, Walter Kremers, Sara Farmer, Hilary W. Heuer, Leah Forsberg, Danielle Brushaber, Amy Rindels, Hiroko Dodge, Sandra Weintraub, Lilah Besser, Brian Appleby, Yvette Bordelon, Jessica Bove, Patrick Brannelly, Christina Caso, Giovanni Coppola, Reilly Dever, Christina Dheel, Bradford Dickerson, Susan Dickinson, Sophia Dominguez, Kimiko Domoto‐Reilly, Kelley Faber, Jessica Ferrall, Ann Fishman, Jamie Fong, Tatiana Foroud, Ralitza Gavrilova, Deb Gearhart, Behnaz Ghazanfari, Nupur Ghoshal, Jill Goldman, Jonathan Graff‐Radford, Neill Graff‐Radford, Ian M. Grant, Murray Grossman, Dana Haley, John Hsiao, Robin Hsiung, Edward D. Huey, David Irwin, David Jones, Lynne Jones, Kejal Kantarci, Anna Karydas, Daniel Kaufer, Diana Kerwin, David Knopman, Ruth Kraft, Joel Kramer, Walter Kukull, Maria Lapid, Irene Litvan, Peter Ljubenkov, Diane Lucente, Codrin Lungu, Ian Mackenzie, Miranda Maldonado, Masood Manoochehri, Scott McGinnis, Emily McKinley, Mario Mendez, Bruce Miller, Namita Multani, Chiadi Onyike, Jaya Padmanabhan, Alexander Pantelyat, Rodney Pearlman, Len Petrucelli, Madeline Potter, Rosa Rademakers, Eliana Marisa Ramos, Katherine Rankin, Katya Rascovsky, Erik D. Roberson, Emily Rogalski‐Miller, Pheth Sengdy, Les Shaw, Adam M. Staffaroni, Margaret Sutherland, Jeremy Syrjanen, Carmela Tartaglia, Nadine Tatton, Joanne Taylor, Arthur Toga, John Trojanowski, Ping Wang, Bonnie Wong, Zbigniew Wszolek, Brad Boeve, Adam Boxer, Howard Rosen, and ARTFL/LEFFTDS Consortium

Subjects
Generalized additive models, Heterogenous variance modeling, Neuropsychological testing scores, Nonlinear Z‐score correction, Shape constrained additive models, Neurology. Diseases of the nervous system, RC346-429, Geriatrics, RC952-954.6
Abstract

Abstract Introduction Conventional Z‐scores are generated by subtracting the mean and dividing by the standard deviation. More recent methods linearly correct for age, sex, and education, so that these “adjusted” Z‐scores better represent whether an individual's cognitive performance is abnormal. Extreme negative Z‐scores for individuals relative to this normative distribution are considered indicative of cognitive deficiency. Methods In this article, we consider nonlinear shape constrained additive models accounting for age, sex, and education (correcting for nonlinearity). Additional shape constrained additive models account for varying standard deviation of the cognitive scores with age (correcting for heterogeneity of variance). Results Corrected Z‐scores based on nonlinear shape constrained additive models provide improved adjustment for age, sex, and education, as indicated by higher adjusted‐R2. Discussion Nonlinearly corrected Z‐scores with respect to age, sex, and education with age‐varying residual standard deviation allow for improved detection of non‐normative extreme cognitive scores.

Published
2019
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3. Assessment of executive function declines in presymptomatic and mildly symptomatic familial frontotemporal dementia: NIH-EXAMINER as a potential clinical trial endpoint

Author

Diane Lucente, Sophia Dominguez, Arthur W. Toga, Ann Fishman, Yvette Bordelon, David J. Irwin, Danielle Brushaber, Debra Gearhart, Katya Rascovsky, Mario F. Mendez, Bradford C. Dickerson, John Kornak, Len Petrucelli, Leah K. Forsberg, Kejal Kantarci, Ping Wang, Zbigniew Wszolek, Anna Karydas, Murray Grossman, Fanny M. Elahi, Ian R. Mackenzie, Patrick Brannelly, Walter A. Kukull, Eliana Marisa Ramos, Edward D. Huey, Kelly Faber, John Q. Trojanowski, Kimiko Domoto-Reilly, Behnaz Ghazanfari, Jill Goldman, David S. Knopman, Emily C. McKinley, Nupur Ghoshal, Ging-Yuek Robin Hsiung, Rosa Rademakers, Masood Manoochehri, Hilary W. Heuer, Walter K. Kremers, Erik D. Roberson, Peter A. Ljubenkov, Adam L. Boxer, David T.W. Jones, Tatiana Foroud, Ian Grant, Brad F. Boeve, Bruce L. Miller, Jonathan Graff-Radford, Miranda Maldonado, Nadine Tatton, Ruth Kraft, Adam M. Staffaroni, Neill Graff-Radford, Joel H. Kramer, Joanne Taylor, Reilly Dever, Irene Litvan, Lynn Bajorek, Giovanni Coppola, Jeremy Syrjanen, Kaitlin B. Casaletto, Yann Cobigo, Codrin Lungu, Namita Multani, Howard J. Rosen, Lynne Jones, Katherine P. Rankin, Julie A. Fields, Alexander Pantelyat, Jaya Padmanabhan, Amy Wolf, Leslie M. Shaw, Brian S. Appleby, Chiadi U. Onyike, Jessica Ferrall, Daniel I. Kaufer, Dana Haley, Diana R. Kerwin, Jessica Bove, M. Carmela Tartaglia, Ralitza H. Gavrilova, Christina Dheel, Christina Caso, Emily Rogalski, Sheng-Yang M. Goh, Madeline Potter, Jamie Fong, Susan Dickinson, Pheth Sengdy, Sandra Weintraub, Bonnie Wong, Scott M. McGinnis, Rodney Pearlman, and ARTFL/LEFFTDS consortium

Subjects
Oncology, Male, Epidemiology, Behavioral variant, Neuropsychological Tests, Primary progressive aphasia, Executive Function, 0302 clinical medicine, Cognition, C9orf72, 030212 general & internal medicine, Longitudinal Studies, Nonfluent variant, Inhibition, Health Policy, Frontotemporal lobar degeneration, Middle Aged, Corticobasal syndrome, Magnetic Resonance Imaging, 3. Good health, Psychiatry and Mental health, Frontotemporal Dementia, Disease Progression, Female, Frontotemporal dementia, medicine.medical_specialty, Progranulin, Semantic variant, Clinical Dementia Rating, Article, Progressive supranuclear palsy, 03 medical and health sciences, Cellular and Molecular Neuroscience, Developmental Neuroscience, Genetic, Neuropsychology, Internal medicine, mental disorders, medicine, Humans, C9orf72 Protein, business.industry, Surrogate endpoint, Working memory, nutritional and metabolic diseases, medicine.disease, nervous system diseases, Set-shifting, Mutation, Fluency, Human medicine, Neurology (clinical), Geriatrics and Gerontology, Tau, business, 030217 neurology & neurosurgery, Biomarkers, Executive dysfunction
Abstract

Introduction Identifying clinical measures that track disease in the earliest stages of frontotemporal lobar degeneration (FTLD) is important for clinical trials. Familial FTLD provides a unique paradigm to study early FTLD. Executive dysfunction is a clinically relevant hallmark of FTLD and may be a marker of disease progression. Methods Ninety-three mutation carriers with no symptoms or minimal/questionable symptoms (MAPT, n = 31; GRN, n = 28; C9orf72, n = 34; Clinical Dementia Rating scale plus NACC FTLD Module < 1) and 78 noncarriers enrolled through Advancing Research and Treatment in Frontotemporal Lobar Degeneration/Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects studies completed the Executive Abilities: Measures and Instruments for Neurobehavioral Evaluation and Research (NIH-EXAMINER) and the UDS neuropsychological battery. Linear mixed-effects models were used to identify group differences in cognition at baseline and longitudinally. We examined associations between cognition, clinical functioning, and magnetic resonance imaging volumes. Results NIH-EXAMINER scores detected baseline and differences in slopes between carriers and noncarriers, even in carriers with a baseline Clinical Dementia Rating scale plus NACC FTLD Module = 0. NIH-EXAMINER declines were associated with worsening clinical symptoms and brain volume loss. Discussion The NIH-EXAMINER is sensitive to cognitive changes in presymptomatic familial FTLD and is a promising surrogate endpoint.

Published
2020

4. Comparison of sporadic and familial behavioral variant frontotemporal dementia (FTD) in a North American cohort

Author

Jessica Ferrall, Julie A. Fields, Edward D. Huey, Anna Karydas, Len Petrucelli, John Kornak, Kejal Kantarci, Pei Ning Wang, G-Y Hsiung, Dana Haley, Artfl, Emily C. McKinley, Erik D. Roberson, Masood Manoochehri, Maria Carmela Tartaglia, Brian S. Appleby, Zbigniew Wszolek, Walter K. Kremers, Amy Wolf, Diana R. Kerwin, Bradford C. Dickerson, Murray Grossman, Bruce L. Miller, Ian Grant, Ann Fishman, Jill Goldman, Leah K. Forsberg, Miranda Maldonado, Howard J. Rosen, Ian R. Mackenzie, Patrick Brannelly, Joel H. Kramer, Eliana Marisa Ramos, Behnaz Ghazanfari, Lefftds consortia, Katherine P. Rankin, Katya Rascovsky, Mario F. Mendez, Yvette Bordelon, Leslie M. Shaw, Arthur W. Toga, Chiadikaobi U. Onyike, Irene Litvan, Scott M. McGinnis, Peter A. Ljubenkov, Hilary W. Heuer, Rodney Pearlman, Walter A. Kukull, Nadine Tatton, Adam L. Boxer, Ruth Kraft, David T.W. Jones, Joanne Taylor, Giovanni Coppola, Tatiana Foroud, Debra Gearhart, Jonathan Graff-Radford, B. F. Boeve, Alexander Pantelyat, Danielle Brushaber, Daniel I. Kaufer, Rosa Rademakers, Madeline Potter, Kelly Faber, John Q. Trojanowski, Jamie Fong, Christina Caso, Emily Rogalski, Nupur Ghoshal, Neill Graff-Radford, Jeremy Syrjanen, Susan Dickinson, Pheth Sengdy, Jessica Bove, Sandra Weintraub, Bonnie Wong, Kimiko Domoto-Reilly, David S. Knopman, and David J. Irwin

Subjects
Male, Epidemiology, tau Proteins, Neuropsychological Tests, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Progranulins, Developmental Neuroscience, medicine, Humans, Genetic Predisposition to Disease, 030212 general & internal medicine, Aged, Genetics, C9orf72 Protein, Health Policy, Age Factors, Brain, Mean age, Middle Aged, medicine.disease, Psychiatry and Mental health, Grossman, Frontotemporal Dementia, Mutation, North America, Female, Neurology (clinical), Geriatrics and Gerontology, Psychology, 030217 neurology & neurosurgery, Frontotemporal dementia
Abstract

Author(s): Heuer, Hilary W; Wang, P; Rascovsky, K; Wolf, A; Appleby, B; Bove, J; Bordelon, Y; Brannelly, P; Brushaber, DE; Caso, C; Coppola, G; Dickerson, B; Dickinson, S; Domoto-Reilly, K; Faber, K; Ferrall, J; Fields, J; Fishman, A; Fong, J; Foroud, T; Forsberg, LK; Gearhart, D; Ghazanfari, B; Ghoshal, N; Goldman, J; Graff-Radford, J; Graff-Radford, N; Grant, I; Grossman, M; Haley, D; Hsiung, G-Y; Huey, E; Irwin, D; Jones, D; Kantarci, K; Karydas, A; Kaufer, D; Kerwin, D; Knopman, D; Kornak, J; Kramer, JH; Kraft, R; Kremers, WK; Kukull, W; Litvan, I; Ljubenkov, P; Mackenzie, IR; Maldonado, M; Manoochehri, M; McGinnis, S; McKinley, E; Mendez, MF; Miller, BL; Onyike, C; Pantelyat, A; Pearlman, R; Petrucelli, L; Potter, M; Rademakers, R; Ramos, EM; Rankin, KP; Roberson, ED; Rogalski, E; Sengdy, P; Shaw, L; Syrjanen, J; Tartaglia, MC; Tatton, N; Taylor, J; Toga, A; Trojanowski, J; Weintraub, S; Wong, B; Wszolek, Z; Boeve, BF; Rosen, HJ; Boxer, AL; ARTFL and LEFFTDS consortia | Abstract: IntroductionBehavioral variant frontotemporal dementia (bvFTD) may present sporadically or due to an autosomal dominant mutation. Characterization of both forms will improve understanding of the generalizability of assessments and treatments.MethodsA total of 135 sporadic (s-bvFTD; mean age 63.3 years; 34% female) and 99 familial (f-bvFTD; mean age 59.9; 48% female) bvFTD participants were identified. f-bvFTD cases included 43 with known or presumed chromosome 9 open reading frame 72 (C9orf72) gene expansions, 28 with known or presumed microtubule-associated protein tau (MAPT) mutations, 14 with known progranulin (GRN) mutations, and 14 with a strong family history of FTD but no identified mutation.ResultsParticipants with f-bvFTD were younger and had earlier age at onset. s-bvFTD had higher total Neuropsychiatric Inventory Questionnaire (NPI-Q) scores due to more frequent endorsement of depression and irritability.Discussionf-bvFTD and s-bvFTD cases are clinically similar, suggesting the generalizability of novel biomarkers, therapies, and clinical tools developed in either form to the other.

Published
2020

5. Clinical and volumetric changes with increasing functional impairment in familial frontotemporal lobar degeneration

Author

Zbigniew Wszolek, Ping Wang, Ann Fishman, Jill Goldman, Sandra Weintraub, Bonnie Wong, Debra Gearhart, Peter A. Ljubenkov, Ruth Kraft, Maria I. Lapid, Ging-Yuek Robin Hsiung, Len Petrucelli, Jamie Fong, Rosa Rademakers, Brad F. Boeve, Madeleine Potter, Adam L. Boxer, David T.W. Jones, Sheng-Yang M. Goh, Yvette Bordelon, Kimiko Domoto-Reilly, Arthur W. Toga, Kejal Kantarci, Meredith Bock, David S. Knopman, Emily C. McKinley, Walter K. Kremers, Erik D. Roberson, Bradford C. Dickerson, Amelia Wolf, Kelly Faber, John Q. Trojanowski, Murray Grossman, Julie A. Fields, Walter A. Kukull, Elise Ong, Masood Manoochehri, Scott M. McGinnis, Jessica Bove, Rodney Pearlman, Anna Karydas, Eliana Marisa Ramos, Bruce L. Miller, Behnaz Ghazanfari, Lynn Bajorek, Ian Grant, Ian R. Mackenzie, Patrick Brannelly, M. Carmela Tartaglia, Joanne Taylor, Miranda Maldonado, Giovanni Coppola, Danielle Brushaber, Kevin Chiang, Adam M. Staffaroni, Howard J. Rosen, Reilly Dever, Tatiana Foroud, Alexander Pantelyat, Irene Litvan, Jonathan Graff-Radford, Daniel I. Kaufer, Dana Haley, Edward D. Huey, Diana R. Kerwin, Christine Caso, Joel H. Kramer, Emily Rogalski, Brian S. Appleby, Chiadi U. Onyike, Jessica Ferrall, Katya Rascovsky, Mario F. Mendez, Hilary W. Heuer, Nadine Tatton, Leslie M. Shaw, Susan Dickinson, Pheth Sengdy, Nicholas T. Olney, Leah K. Forsberg, John Kornak, Neill Graff-Radford, Jeremy Syrjanen, David J. Irwin, Nupur Ghoshal, Katherine P. Rankin, Yann Cobigo, and ARTFL and LEFFTDS consortia

Subjects
Male, medicine.medical_specialty, Epidemiology, Trail Making Test, C9ORF72, tau Proteins, Neuropsychological Tests, Audiology, Frontotemporal lobar degeneration, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, Familial, Progranulins, 0302 clinical medicine, Atrophy, Genetic, Developmental Neuroscience, C9orf72, mental disorders, MAPT, Image Processing, Computer-Assisted, medicine, Humans, Dementia, Genetic Predisposition to Disease, Longitudinal Studies, 030212 general & internal medicine, Effects of sleep deprivation on cognitive performance, Biology, C9orf72 Protein, business.industry, Health Policy, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Temporal Lobe, Psychiatry and Mental health, Female, Neurology (clinical), Human medicine, Geriatrics and Gerontology, business, Asymptomatic carrier, GRN, 030217 neurology & neurosurgery, Frontotemporal dementia
Abstract

Introduction The Advancing Research and Treatment in Frontotemporal Lobar Degeneration and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects longitudinal studies were designed to describe the natural history of familial-frontotemporal lobar degeneration due to autosomal dominant mutations. Methods We examined cognitive performance, behavioral ratings, and brain volumes from the first time point in 320 MAPT, GRN, and C9orf72 family members, including 102 non–mutation carriers, 103 asymptomatic carriers, 43 mildly/questionably symptomatic carriers, and 72 carriers with dementia. Results Asymptomatic carriers showed similar scores on all clinical measures compared with noncarriers but reduced frontal and temporal volumes. Those with mild/questionable impairment showed decreased verbal recall, fluency, and Trail Making Test performance and impaired mood and self-monitoring. Dementia was associated with impairment in all measures. All MAPT carriers with dementia showed temporal atrophy, but otherwise, there was no single cognitive test or brain region that was abnormal in all subjects. Discussion Imaging changes appear to precede clinical changes in familial-frontotemporal lobar degeneration, but specific early clinical and imaging changes vary across individuals.

Published
2020

6. Individualized atrophy scores predict dementia onset in familial frontotemporal lobar degeneration

Author

Zbigniew Wszolek, Masood Manoochehri, John Kornak, Bradford C. Dickerson, Jill Goldman, Murray Grossman, Ian Grant, Jessica Bove, Walter K. Kremers, Tatiana Foroud, Dana Haley, Len Petrucelli, Madeline Potter, Jamie Fong, Kelly Faber, Debra Gearhart, Eliana Marisa Ramos, Jonathan Graff-Radford, Hilary W. Heuer, Behnaz Ghazanfari, John Q. Trojanowski, Scott M. McGinnis, Edward D. Huey, Sophia Dominguez, Ann Fishman, Brad F. Boeve, Rodney Pearlman, Diana R. Kerwin, Arthur W. Toga, Nadine Tatton, Leah K. Forsberg, Anna Karydas, Susan Dickinson, Peter A. Ljubenkov, Kimiko Domoto-Reilly, Pheth Sengdy, Adam L. Boxer, David T.W. Jones, Ruth Kraft, Leslie M. Shaw, Walter A. Kukull, David S. Knopman, Namita Multani, Jaya Padmanabhan, Sandra Weintraub, Bonnie Wong, Lynne Jones, Lynn Bajorek, Ping Wang, Katherine P. Rankin, Diane Lucente, M. Carmela Tartaglia, Miranda Maldonado, Reilly Dever, Ging-Yuek Robin Hsiung, Yvette Bordelon, Katya Rascovsky, Mario F. Mendez, Howard J. Rosen, Danielle Brushaber, Kevin Chiang, Adam M. Staffaroni, Ralitza H. Gavrilova, Irene Litvan, Ian R. Mackenzie, Patrick Brannelly, Sheng-Yang M. Goh, Nupur Ghoshal, Neill Graff-Radford, Jeremy Syrjanen, Joanne Taylor, Giovanni Coppola, Christina Dheel, Alexander Pantelyat, Yann Cobigo, Daniel I. Kaufer, Rosa Rademakers, Christina Caso, David J. Irwin, Emily Rogalski, Codrin Lungu, Bruce L. Miller, Joel H. Kramer, Chiadi U. Onyike, Jessica Ferrall, Brian S. Appleby, Kejal Kantarci, Emily C. McKinley, Erik D. Roberson, and Julie A. Fields

Subjects
Male, medicine.medical_specialty, Epidemiology, TDP-43, Separation (statistics), tau Proteins, Neuropsychological Tests, Logistic regression, Asymptomatic, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Atrophy, Progranulins, Developmental Neuroscience, Internal medicine, Image Processing, Computer-Assisted, Genetics, Medicine, Dementia, Humans, Genetic Predisposition to Disease, 030212 general & internal medicine, Magnetic resonance imaging (MRI), Framingham Risk Score, C9orf72 Protein, business.industry, Health Policy, Brain, Frontotemporal lobar degeneration, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Psychiatry and Mental health, Frontotemporal Dementia, Mutation, Female, Neurology (clinical), Geriatrics and Gerontology, medicine.symptom, Tau, business, 030217 neurology & neurosurgery, Frontotemporal dementia
Abstract

Introduction Some models of therapy for neurodegenerative diseases envision starting treatment before symptoms develop. Demonstrating that such treatments are effective requires accurate knowledge of when symptoms would have started without treatment. Familial frontotemporal lobar degeneration offers a unique opportunity to develop predictors of symptom onset. Methods We created dementia risk scores in 268 familial frontotemporal lobar degeneration family members by entering covariate-adjusted standardized estimates of brain atrophy into a logistic regression to classify asymptomatic versus demented participants. The score's predictive value was tested in a separate group who were followed up longitudinally (stable vs. converted to dementia) using Cox proportional regressions with dementia risk score as the predictor. Results Cross-validated logistic regression achieved good separation of asymptomatic versus demented (accuracy = 90%, SE = 0.06). Atrophy scores predicted conversion from asymptomatic or mildly/questionably symptomatic to dementia (HR = 1.51, 95% CI: [1.16,1.98]). Discussion Individualized quantification of baseline brain atrophy is a promising predictor of progression in asymptomatic familial frontotemporal lobar degeneration mutation carriers.

Published
2019

7. Nonlinear Z‐score modeling for improved detection of cognitive abnormality

Author

Edward D. Huey, Bradford C. Dickerson, Murray Grossman, Hiroko H. Dodge, Chiadi U. Onyike, Diane Lucente, David J. Irwin, Neill R. Graff-Radford, Jessica Ferrall, Dana Haley, Leah K. Forsberg, Eliana Marisa Ramos, Jill Goldman, Behnaz Ghazanfari, Ian R. A. Mackenzie, Brad F. Boeve, John Kornak, Kimiko Domoto-Reilly, Madeline Potter, Susan Dickinson, Emily Rogalski-Miller, Sara A. Farmer, Adam L. Boxer, David T.W. Jones, Diana R. Kerwin, Tatiana Foroud, Pheth Sengdy, Len Petrucelli, Jamie Fong, Rosa Rademakers, Julie A. Fields, Bruce L. Miller, Joel H. Kramer, Sandra Weintraub, Bonnie Wong, Christina Dheel, Carmela Tartaglia, Christina Caso, Joanne Taylor, Codrin Lungu, John Q. Trojanowski, Zbigniew K. Wszolek, Jeremy Syrjanen, Giovanni Coppola, Peter A. Ljubenkov, Walter A. Kukull, Miranda Maldonado, Masood Manoochehri, Reilly Dever, Alexander Pantelyat, Jonathan Graff-Radford, Ruth Kraft, Katherine P. Rankin, Daniel I. Kaufer, Amy Rindels, Adam M. Staffaroni, Sophia Dominguez, Arthur W. Toga, Kejal Kantarci, Howard J. Rosen, Margaret Sutherland, Maria I. Lapid, Ian Grant, Katya Rascovsky, Jessica Bove, Ann Fishman, Artfl, Irene Litvan, Brian S. Appleby, Les Shaw, Hilary W. Heuer, Nadine Tatton, Patrick Brannelly, Mario F. Mendez, Emily C. McKinley, Erik D. Roberson, Nupur Ghoshal, John K. Hsiao, Scott M. McGinnis, Rodney Pearlman, Danielle Brushaber, Yvette Bordelon, Ralitza H. Gavrilova, Anna Karydas, Deb Gearhart, David S. Knopman, Namita Multani, Jaya Padmanabhan, Walter K. Kremers, Lynne Jones, Kelley Faber, Ping Wang, Lilah M. Besser, Robin Hsiung, and ARTFL/LEFFTDS Consortium

Subjects
lcsh:Geriatrics, Standard score, Generalized additive models, lcsh:RC346-429, Standard deviation, Shape constrained additive models, 03 medical and health sciences, 0302 clinical medicine, Nonlinear Z‐score correction, Statistics, Effects of sleep deprivation on cognitive performance, 10. No inequality, Additive model, Biology, lcsh:Neurology. Diseases of the nervous system, 030304 developmental biology, Mathematics, 0303 health sciences, Neuropsychological testing scores, Generalized additive model, Cognition, Variance (accounting), lcsh:RC952-954.6, Psychiatry and Mental health, Nonlinear system, Cognitive & Behavioral Assessment, Neurology (clinical), Human medicine, 030217 neurology & neurosurgery, Heterogenous variance modeling, Nonlinear Z-score correction
Abstract

Introduction Conventional Z-scores are generated by subtracting the mean and dividing by the standard deviation. More recent methods linearly correct for age, sex, and education, so that these “adjusted” Z-scores better represent whether an individual's cognitive performance is abnormal. Extreme negative Z-scores for individuals relative to this normative distribution are considered indicative of cognitive deficiency. Methods In this article, we consider nonlinear shape constrained additive models accounting for age, sex, and education (correcting for nonlinearity). Additional shape constrained additive models account for varying standard deviation of the cognitive scores with age (correcting for heterogeneity of variance). Results Corrected Z-scores based on nonlinear shape constrained additive models provide improved adjustment for age, sex, and education, as indicated by higher adjusted-R2. Discussion Nonlinearly corrected Z-scores with respect to age, sex, and education with age-varying residual standard deviation allow for improved detection of non-normative extreme cognitive scores.

Published
2019

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