Hostname: page-component-848d4c4894-8bljj Total loading time: 0 Render date: 2024-07-02T15:33:26.709Z Has data issue: false hasContentIssue false
  • English
  • Français

Predicting Progression to Parkinson’s Disease Dementia Using Multivariate Normative Comparisons

Published online by Cambridge University Press:  14 May 2019

J.A. Agelink van Rentergem ,
N.R. de Vent ,
H.M. Huizenga ,
J.M.J. Murre ,
B.A. Schmand  and
ANDI consortium
J.A. Agelink van Rentergem
Affiliation:
Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
N.R. de Vent*
Affiliation:
Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
H.M. Huizenga
Affiliation:
Department of Psychology, University of Amsterdam, Amsterdam, Netherlands Amsterdam Brain and Cognition Center, University of Amsterdam, Amsterdam, Netherlands Research Priority Area Yield, University of Amsterdam, Amsterdam, Netherlands
J.M.J. Murre
Affiliation:
Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
B.A. Schmand
Affiliation:
Department of Psychology, University of Amsterdam, Amsterdam, Netherlands Department of Medical Psychology, Academic Medical Center, Amsterdam, Netherlands
ANDI consortium
Affiliation:
See full list of consortium members onwww.andi.nl/
*
Correspondence and reprint requests to: N.R. de Vent, Postbus 15916, 1001 NK Amsterdam, The Netherlands. E-mail: n.r.devent@uva.nl
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective: Parkinson’s disease with mild cognitive impairment (PD-MCI) is a risk factor for progression to PD dementia (PDD) at a later stage of the disease. The consensus criteria of PD-MCI use a traditional test-by-test normative comparison. The aim of this study was to investigate whether a new multivariate statistical method provides a more sensitive tool for predicting dementia status at 3- and 5-year follow-ups. This method allows a formal evaluation of a patient’s profile of test scores given a large aggregated database with regression-based norms. Method: The cognitive test results of 123 newly diagnosed PD patients from a previously published longitudinal study were analyzed with three different methods. First, the PD-MCI criteria were applied in the traditional way. Second, the PD-MCI criteria were applied using the large aggregated normative database. Last, multivariate normative comparisons (MNCs) were made using the same aggregated normative database. The outcome variable was progression to dementia within 3 and 5 years. Results: The MNC was characterized by higher sensitivity and higher specificity in predicting progression to PDD at follow-up than the two PD-MCI criteria methods, although the difference in classification accuracy did not reach statistical significance. Conclusion: We conclude that MNCs could allow for a more accurate prediction of PDD than the traditional PD-MCI criteria, because there are encouraging trends in both increased sensitivity and increased specificity. (JINS, 2019, 25, 678–687)

Keywords

Mild cognitive impairmentneuropsychological diagnosticsnormative dataregression-based normsmultivariate normative comparisonaggregated databaseANDI
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 25 , Issue 7 , August 2019 , pp. 678 - 687
Copyright
Copyright © INS. Published by Cambridge University Press, 2019. 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

†

Denotes shared first authorship

References

REFERENCES

Aarsland, D., Andersen, K., Larsen, J.P., Lolk, A., Nielsen, H., & Kragh–Sørensen, P. (2001). Risk of dementia in Parkinson’s disease: A community-based, prospective study. Neurology, 56(6), 730–736. doi: 10.1212/WNL.56.6.730.CrossRefGoogle ScholarPubMed
Aarsland, D., Brønnick, K., Larsen, J.P., Tysnes, O.B., Alves, G., & Norwegian ParkWest Study Group. (2009). Cognitive impairment in incident, untreated Parkinson disease: The Norwegian ParkWest Study. Neurology, 72(13), 1121–1126.CrossRefGoogle ScholarPubMed
Agelink van Rentergem, J.A., de Vent, N.R., Schmand, B.A., Murre, J.M.J., & Huizenga, H.M. (2017a). Multivariate normative comparisons for neuropsychological assessment by a multilevel factor structure or multiple imputation approach. Psychological Assessment. Advance online publication.CrossRefGoogle Scholar
Agelink van Rentergem, J.A., Murre, J.M.J., & Huizenga, H.M. (2017b). Multivariate normative comparisons using an aggregated database. PLoS ONE, 12, 1–18.CrossRefGoogle ScholarPubMed
Agresti, A. & Coull, B.A. (1998). Approximate is better than “exact” for interval estimation of binomial proportions. The American Statistician, 52(2), 119–126.Google Scholar
Benton, A.L. & Hamsher, K. (1983). Multilingual Aphasia Examination. Iowa City: AJA Associates.Google Scholar
Benton, A.L., Hamsher, K., Varney, N., & Spreen, O. (1983). Contributions to Neuropsychological Assessment – A Clinical Manual. New York: Oxford University Press.Google Scholar
Binder, L.M., Iverson, G.L., & Brooks, B.L. (2009). To err is human: “Abnormal” neuropsychological scores and variability are common in healthy adults. Archives of Clinical Neuropsychology, 24(1), 31–46. doi: 10.1093/arclin/acn001.CrossRefGoogle Scholar
Broeders, M., De Bie, R.M.A., Velseboer, D.C., Speelman, J.D., Muslimovic, D., & Schmand, B. (2013). Evolution of mild cognitive impairment in Parkinson disease. Neurology, 81(4), 346–352.CrossRefGoogle ScholarPubMed
Carley, S., Dosman, S., Jones, S.R., & Harrison, M. (2005). Simple nomograms to calculate sample size in diagnostic studies. Emergency Medicine Journal, 22(3), 180–181.CrossRefGoogle ScholarPubMed
Caviness, J.N., Driver-Dunckley, E., Connor, D.J., Sabbagh, M.N., Hentz, J.G., Noble, B., Evidente, V.G.H., Shill, H.A., & Adler, C.H. (2007). Defining mild cognitive impairment in Parkinson’s disease. Movement Disorders, 22(9), 1272–1277. doi: 10.1002/mds.21453.CrossRefGoogle ScholarPubMed
Collin, C., Wade, D.T., Davies, S., & Horne, V. (1988). The Barthel ADL Index: A reliability study. International Disability Studies, 10(2), 61–63. doi: 10.3109/09638288809164103CrossRefGoogle ScholarPubMed
Crawford, J.R. & Garthwaite, P.H. (2002). Investigation of the single case in neuropsychology: Confidence limits on the abnormality of test scores and test score differences. Neuropsychologia, 40, 1196–1208. doi: 10.1016/S00283932(01)00224-X.CrossRefGoogle Scholar
Culbertson, W.C. & Zillmer, E.A. (1998). The Tower of London DX: A standardized approach to assessing executive functioning in children. Archives of Clinical Neuropsychology, 13(3), 285–301. doi: 10.1016/S0887-6177(97)00033-4.CrossRefGoogle Scholar
de Vent, N.R., Agelink van Rentergem, J.A., Schmand, B.A., & Murre, J.M.J., ANDI Consortium, & Huizenga, H.M. (2016) Advanced Neuropsychological Diagnostics Infrastructure (ANDI): A normative database created from control datasets. Frontiers in Psychology, 7(1601), 1–10. doi: 10.3389/fpsyg.CrossRefGoogle ScholarPubMed
Domellöf, M.E., Ekman, U., Forsgren, L. & Elgh, E. (2015). Cognitive function in the early phase of Parkinson’s disease, a five-year follow-up. Acta Neurologica Scandinavica, 132(2), 79–88.CrossRefGoogle ScholarPubMed
Dubois, B., Burn, D., Goetz, C., Aarsland, D., Brown, R.G., Broe, G.A., Dickson, D., Duyckaerts, C., Cummings, J., Gauthier, S., & Korczyn, A. (2007). Diagnostic procedures for Parkinson’s disease dementia: Recommendations from the movement disorder society task force. Movement Disorders, 22(16), 2314–2324.CrossRefGoogle ScholarPubMed
Elgh, E., Domellöf, M., Linder, J., Edström, M., Stenlund, H., & Forsgren, L. (2009). Cognitive function in early Parkinson’s disease: A population-based study. European Journal of Neurology, 16(12), 1278–1284.CrossRefGoogle ScholarPubMed
Emre, M., Aarsland, D., Brown, R., Burn, D.J., Duyckaerts, C., Mizuno, Y., Broe, G.A., Cummings, J., Dickson, D.W., Gauthier, S., & Goldman, J. (2007). Clinical diagnostic criteria for dementia associated with Parkinson’s disease. Movement Disorders, 22(12), 1689–1707. doi: 10.1002/mds.21507.CrossRefGoogle ScholarPubMed
Folstein, M.F., Folstein, S.E., & McHugh, P.R. (1975). “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189-198. doi: 10.1016/0022-3956(75)90026-6.CrossRefGoogle ScholarPubMed
Galtier, I., Nieto, A., Lorenzo, J.N., & Barroso, J. (2016). Mild cognitive impairment in Parkinson’s disease: Diagnosis and progression to dementia. Journal of Clinical and Experimental Neuropsychology, 38(1), 40–50.CrossRefGoogle Scholar
Gasca-Salas, C., Estanga, A., Clavero, P., Aguilar-Palacio, I., González-Redondo, R., Obeso, J.A., & Rodríguez-Oroz, M.C. (2014). Longitudinal assessment of the pattern of cognitive decline in non-demented patients with advanced Parkinson’s disease. Journal of Parkinson’s Disease, 4(4), 677–686. doi: 10.3233/JPD-140398.Google ScholarPubMed
Hobson, P. & Meara, J. (2004). The risk and incidence of dementia in a cohort of older subjects with Parkinson’s disease int the UK. Movement Disorders, 19(9), 1043–1049. doi: 10.1002/mds.20216.CrossRefGoogle Scholar
Hobson, P. & Meara, J. (2015). Mild cognitive impairment in Parkinson’s disease and its progression onto dementia: A 16-year outcome evaluation of the Denbighshire cohort. International Journal of Geriatric Psychiatry, 30(10), 1048–1055. doi: 10.1002/gps.4261.CrossRefGoogle ScholarPubMed
Hoogland, J., Boel, J.A., de Bie, R.M., Geskus, R.B., Schmand, B.A., Dalrymple-Alford, J.C., Marras, C., Adler, C.H., Goldman, J.G., Tröster, A.I., & Geurtsen, G.J. (2017). Mild cognitive impairment as a risk factor for Parkinson’s disease dementia. Movement Disorders, 32(7), 1056–1065. doi: 10.1002/mds.27002.CrossRefGoogle ScholarPubMed
Hoops, S., Nazem, S., Siderowf, A.D., Duda, J.E., Xie, S.X., Stern, M.B., & Weintraub, D. (2009). Validity of the MoCA and MMSE in the detection of MCI and dementia in Parkinson disease. Neurology, 73(21), 1738–1745.CrossRefGoogle Scholar
Hughes, T.A., Ross, H.F., Musa, S., Bhattacherjee, S., Nathan, R.N., Mindham, R.H.S., & Spokes, E.G. (2000). A 10-year study of the incidence of and factors predicting dementia in Parkinson’s disease. Neurology, 54(8), 1596–1603.CrossRefGoogle ScholarPubMed
Huizenga, H.M., Smeding, H., Grasman, R.P., & Schmand, B. (2007). Multivariate normative comparisons. Neuropsychologia, 45, 2534–2542. doi: 10.1016/j.neuropsychologia.2007.03.011.CrossRefGoogle ScholarPubMed
Janvin, C., Aarsland, D., Larsen, J.P., & Hugdahl, K. (2003). Neuropsychological profile of patients with Parkinson’s disease without dementia. Dementia and Geriatric Cognitive Disorders, 15(3), 126–131. doi: 10.1159/000068483.CrossRefGoogle ScholarPubMed
Kaplan, E., Goodglass, H., & Weintraub, S. (1983). Boston Naming Test. Philadelphia, PA: Lea & Febiger.Google Scholar
Kobayakawa, M., Koyama, S., Mimura, M., & Kawamura, M. (2008). Decision making in Parkinson’s disease: Analysis of behavioral and physiological patterns in the Iowa gambling task. Movement Disorders, 23(4), 547–552.CrossRefGoogle ScholarPubMed
Lezak, M.D., Howieson, D.B., Bigler, E.D., & Tranel, D. (2012). Neuropsychological Assessment (5th ed.). New York: Oxford University Press.Google Scholar
Litvan, I., Aarsland, D., Adler, C.H., Goldman, J.G., Kulisevsky, J., Mollenhauer, B., Rodriguez-Oroz, M.C., Tröster, A.I., & Weintraub, D. (2011). MDS task force on mild cognitive impairment in Parkinson’s disease: Critical review of PDMCI. Movement Disorders, 26(10), 1814–1824. doi: 10.1002/mds.23823.CrossRefGoogle Scholar
Litvan, I., Goldman, J.G., Tröster, A.I., Schmand, B.A., Weintraub, D., Petersen, R.C., Mollenhauer, B., Adler, C.H., Marder, K., Williams-Gray, C.H., & Emre, M. (2012). Diagnostic criteria for mild cognitive impairment in Parkinson’s disease: Movement Disorder Society Task Force guidelines. Movement Disorders, 27(3), 349–356. doi: 10.1002/mds.24893.CrossRefGoogle ScholarPubMed
Mamikonyan, E., Moberg, P.J., Siderowf, A., Duda, J.E., Ten Have, T., Hurtig, H.I., Stern, M.B., & Weintraub, D. (2009). Mild cognitive impairment is common in Parkinson’s disease patients with normal Mini-Mental State Examination (MMSE) scores. Parkinsonism & Related Disorders, 15(3), 226–231.CrossRefGoogle ScholarPubMed
Mimura, M., Oeda, R., & Kawamura, M. (2006). Impaired decision-making in Parkinson’s disease. Parkinsonism & Related Disorders, 12(3), 169–175.CrossRefGoogle ScholarPubMed
Muslimović, D., Post, B., Speelman, J.D., De Haan, R.J., & Schmand, B. (2009). Cognitive decline in Parkinson’s disease: A prospective longitudinal study. Journal of the International Neuropsychological Society, 15(3), 426–437.CrossRefGoogle ScholarPubMed
Muslimović, D., Post, B., Speelman, J.D., & Schmand, B. (2005). Cognitive profile of patients with newly diagnosed Parkinson disease. Neurology, 65(8), 1239–1245. doi: 10.1212/01.wnl.0000180516.69442.95.CrossRefGoogle ScholarPubMed
Nasreddine, Z.S., Phillips, N.A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J.L. & Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699.CrossRefGoogle ScholarPubMed
Nelson, H.E. (1976). A modified card sorting test sensitive to frontal lobe defects. Cortex, 12(4), 313–324.CrossRefGoogle ScholarPubMed
Pagonabarraga, J., Kulisevsky, J., Llebaria, G., García-Sánchez, C., Pascual-Sedano, B., & Gironell, A. (2008). Parkinson’s disease-cognitive rating scale: A new cognitive scale specific for Parkinson’s disease. Movement Disorders, 23(7), 998–1005.CrossRefGoogle ScholarPubMed
Pearson Assessment (2009). Advanced Clinical Solutions for the WAIS-IV/WMS-IV. San Antonio, TX: Author.Google Scholar
Pedersen, K.F., Larsen, J.P., Tysnes, O.B., & Alves, G. (2017). Natural course of mild cognitive impairment in Parkinson disease: A 5-year population-based study. Neurology, 88(8), 767–774.CrossRefGoogle ScholarPubMed
Reitan, R.M. (1992). Trail Making Test: Manual for Administration and Scoring. Tucson, AZ: Reitan Neuropsychological Laboratory.Google Scholar
Rey, A. (1964). L’examen clinique en psychologie. Paris, France: Presses Universitaires de France.Google Scholar
Royall, D.R., Cordes, D.A., & Polk, M. (1998). CLOX: An executive clock drawing task. Journal of Neurology, Neurosurgery, and Psychiatry, 64, 588–594.CrossRefGoogle Scholar
Santangelo, G., Vitale, C., Picillo, M., Moccia, M., Cuoco, S., Longo, K., Pezzella, D., di Grazia, A., Erro, R., Pellecchia, M.T., & Amboni, M. (2015). Mild cognitive impairment in newly diagnosed Parkinson’s disease: A longitudinal prospective study. Parkinsonism & Related Disorders, 21(10), 1219–1226.CrossRefGoogle ScholarPubMed
Schwab, J.F. & England, A.C. (1969). Projection technique for evaluating surgery in Parkinson’s disease. In: Billingham, F.H. & Donaldson, M.C. (Eds.), Third Symposium on Parkinson’s Disease (pp. 152–157). Edinburgh: Churchill Livingstone.Google Scholar
Skorvanek, M., Goldman, J.G., Jahanshahi, M., Marras, C., Rektorova, I., Schmand, B., van Duijn, E., Goetz, C.G., Weintraub, D., Stebbins, G.T., & Martinez-Martin, P. (2018). Global scales for cognitive screening in Parkinson’s disease: Critique and recommendations. Movement Disorders, 33(2), 208–218.CrossRefGoogle ScholarPubMed
Su, T., Schouten, J., Geurtsen, G.J., Wit, F.W., Stolte, I.G., Prins, M., Portegies, P., Caan, M.W., Reiss, P., Majoie, C.B., & Schmand, B.A. (2015). Multivariate normative comparison, a novel method for more reliably detecting cognitive impairment in HIV infection. AIDS, 29(5), 547–557.Google ScholarPubMed
Testa, S.M., Winicki, J.M., Pearlson, G.D., Gordon, B. & Schretlen, D.J. (2009). Accounting for estimated IQ in neuropsychological test performance with regression-based techniques. Journal of the International Neuropsychological Society, 15(6), 1012–1022.CrossRefGoogle ScholarPubMed
Van der Putten, J.J., Hobart, J.C., Freeman, J.A., & Thompson, A.J. (1999). Measuring change in disability after inpatient rehabilitation: Comparison of the responsiveness of the Barthel index and the Functional Independence Measure. Journal of Neurology, Neurosurgery & Psychiatry, 66(4), 480–484.CrossRefGoogle ScholarPubMed
Wechsler, D. (1981). Wechsler Adult Intelligence Scale – Revised (WAIS-R). New York: Psychological Corporation.Google Scholar
Wechsler, D. (1997). Wechsler Adult Intelligence Scale (WAIS-III) (3rd ed.). New York: Psychological Corporation.Google Scholar
Wilkinson, G.S. & Robertson, G.J. (2006). Wide Range Achievement Test (4th ed.). Lutz, FL: Psychological Assessment Resources.Google Scholar
Williams-Gray, C.H., Foltynie, T., Brayne, C.E.G., Robbins, T.W. & Barker, R.A. (2007). Evolution of cognitive dysfunction in an incident Parkinson’s disease cohort. Brain, 130(7), 1787–1798. doi: 10.1093/brain/awm111.CrossRefGoogle Scholar
Wilson, B., Cockburn, J., & Baddeley, A. (1983). Rivermead Behavioural Memory Test. Reading, UK: Thames Valley Test Company.Google Scholar
Zachary, R.A. & Gorsuch, R.L. (1985). Continuous norming: Implications for the WAIS-R. Journal of Clinical Psychology, 41(1), 86–94.3.0.CO;2-W>CrossRefGoogle ScholarPubMed
Zigmond, A.S., & Snaith, R.P. (1983). The hospital anxiety and depression scale. Acta psychiatrica scandinavica, 67(6), 361–370.CrossRefGoogle ScholarPubMed
Supplementary material: File

Agelink van Rentergem et al. supplementary material

Agelink van Rentergem et al. supplementary material 1

Download Agelink van Rentergem et al. supplementary material(File)
File 448.3 KB