New scoring methodology improves the sensitivity of the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) in clinical trials

Alzheimer's Research and Therapy

Volumn 7, Issue 1, 2015, Pages

  Verma, Nishant ^a,b   Beretvas, S Natasha ^c   Pascual, Belen ^d   Masdeu, Joseph C ^d   Markey, Mia K ^a,e  

^a The University of Texas at Austin   (United States)

^b NeuroTexas Institute   (United States)

^c UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^d HOUSTON METHODIST RESEARCH INSTITUTE   (United States)

^e UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ALZHEIMER DISEASE; ALZHEIMER DISEASE ASSESSMENT SCALE COGNITIVE SUBSCALE; ALZHEIMER DISEASE ASSESSMENT SCALE COGNITIVE SUBSCALE ITEM RESPONSE THEORY; ARTICLE; COGNITION ASSESSMENT; COGNITIVE DEFECT; CONTROLLED STUDY; DISEASE CLASSIFICATION; DISEASE COURSE; EVIDENCE BASED MEDICINE; FEMALE; HUMAN; MAJOR CLINICAL STUDY; MALE; PRIORITY JOURNAL; PSYCHOMETRY; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; TREATMENT RESPONSE; VALIDATION STUDY; ACCESS TO INFORMATION; CLINICAL TRIAL; CLINICAL TRIAL (TOPIC); COMPUTER SIMULATION; INTERNET; LONGITUDINAL STUDY; NEUROPSYCHOLOGICAL TEST; PSYCHOLOGY; TIME FACTOR;

ACCESS TO INFORMATION; ALZHEIMER DISEASE; CLINICAL TRIALS AS TOPIC; COMPUTER SIMULATION; FEMALE; HUMANS; INTERNET; LONGITUDINAL STUDIES; MALE; NEUROPSYCHOLOGICAL TESTS; PSYCHOMETRICS; SENSITIVITY AND SPECIFICITY; TIME FACTORS;

EID: 84946762305     PISSN: None     EISSN: 17589193     Source Type: Journal    
DOI: 10.1186/s13195-015-0151-0     Document Type: Article

References (67)

1. Rosen WG, Mohs RC, Davis KL. A new rating scale for Alzheimer's disease. Am J Psychiatry. 1984;141:1356-64.
2. Cano SJ, Posner HB, Moline ML, Hurt SW, Swartz J, Hsu T, et al. The ADAScog in Alzheimer's disease clinical trials: psychometric evaluation of the sum and its parts. J Neurol Neurosurg Psychiatry. 2010;81:1363-8.
3. Raghavan N, Samtani MN, Farnum M, Yang E, Novak G, Grundman M, et al. The ADAS-Cog revisited: novel composite scales based on ADAS-Cog to improve efficiency in MCI and early AD trials. Alzheimers Dement. 2013;9:S21-31.
4. Hobart J, Cano S, Posner H, Selnes O, Stern Y, Thomas R, et al. Putting the Alzheimer's cognitive test to the test II: Rasch Measurement Theory. Alzheimers Dement. 2013;9:S10-20.
5. Hobart J, Cano S, Posner H, Selnes O, Stern Y, Thomas R, et al. Putting the Alzheimer's cognitive test to the test I: Traditional psychometric methods. Alzheimers Dement. 2013;9:S4-9.
6. Fleisher AS, Donohue M, Chen K, Brewer JB, Aisen PS. Applications of neuroimaging to disease-modification trials in Alzheimer's disease. Behav Neurol. 2009;21:129-36.
7. Salloway S, Mintzer J, Weiner MF, Cummings JL. Disease-modifying therapies in Alzheimer's disease. Alzheimers Dement. 2008;4:65-79.
8. Grove RA, Harrington CM, Mahler A, Beresford I, Maruff P, Lowy MT, et al. A randomized, double-blind, placebo-controlled, 16-week study of the H3 receptor antagonist, GSK239512 as a monotherapy in subjects with mild-tomoderate Alzheimer's disease. Curr Alzheimer Res. 2014;11:47-58.
9. Skinner J, Carvalho JO, Potter GG, Thames A, Zelinski E, Crane PK, et al. The Alzheimer's Disease Assessment Scale-Cognitive-Plus (ADAS-Cog-Plus): an expansion of the ADAS-Cog to improve responsiveness in MCI. Brain Imaging Behav. 2012;6:489-501.
10. Harrison J, Minassian SL, Jenkins L, Black RS, Koller M, Grundman M. A neuropsychological test battery for use in Alzheimer disease clinical trials. Arch Neurol. 2007;64:1323-9.
11. Talwalker S, Overall JE, Srirama MK, Gracon SI. Cardinal features of cognitive dysfunction in Alzheimer's disease: a factor-analytic study of the Alzheimer's Disease Assessment Scale. J Geriatr Psychiatry Neurol. 1996;9:39-46.
12. Olin JT, Schneider LS. Assessing response to tacrine using the factor analytic structure of the Alzheimer's disease assessment scale (Adas)-cognitive subscale. Int J Geriatr Psychiatry. 1995;10:753-6.
13. Kim YS, Nibbelink DW, Overall JE. Factor structure and reliability of the Alzheimer's Disease Assessment Scale in a multicenter trial with linopirdine. J Geriatr Psychiatry Neurol. 1994;7:74-83.
14. Weintraub D, Somogyi M, Meng X. Rivastigmine in Alzheimer's disease and Parkinson's disease dementia: an ADAS-cog factor analysis. Am J Alzheimers Dis Other Demen. 2011;26:443-9.
15. Balsis S, Unger AA, Benge JF, Geraci L, Doody RS. Gaining precision on the Alzheimer's Disease Assessment Scale-cognitive: a comparison of item response theory-based scores and total scores. Alzheimers Dement. 2012;8:288-94.
16. Crane PK, van Belle G, Larson EB. Test bias in a cognitive test: differential item functioning in the CASI. Stat Med. 2004;23:241-56.
17. Persson CM, Wallin AK, Levander S, Minthon L. Changes in cognitive domains during three years in patients with Alzheimer's disease treated with donepezil. BMC Neurol. 2009;9:7.
18. Rafii MS, Walsh S, Little JT, Behan K, Reynolds B, Ward C, et al. A phase II trial of huperzine A in mild to moderate Alzheimer disease. Neurology. 2011;76:1389-94.
19. Quinn JF, Raman R, Thomas RG, Yurko-Mauro K, Nelson EB, Van Dyck C, et al. Docosahexaenoic acid supplementation and cognitive decline in Alzheimer disease: a randomized trial. JAMA. 2010;304:1903-11.
20. Tariot PN, Schneider LS, Cummings J, Thomas RG, Raman R, Jakimovich LJ, et al. Chronic divalproex sodium to attenuate agitation and clinical progression of Alzheimer disease. Arch Gen Psychiatry. 2011;68:853-61.
21. Aisen PS, Schneider LS, Sano M, Diaz-Arrastia R, van Dyck CH, Weiner MF, et al. High-dose B vitamin supplementation and cognitive decline in Alzheimer disease: a randomized controlled trial. JAMA. 2008;300:1774-83.
22. Sano M, Bell KL, Galasko D, Galvin JE, Thomas RG, van Dyck CH, et al. A randomized, double-blind, placebo-controlled trial of simvastatin to treat Alzheimer disease. Neurology. 2011;77:556-63.
23. Samtani MN, Raghavan N, Shi Y, Novak G, Farnum M, Lobanov V, et al. Disease progression model in subjects with mild cognitive impairment from the Alzheimer's disease neuroimaging initiative: CSF biomarkers predict population subtypes. Br J Clin Pharmacol. 2013;75:146-61.
24. Samtani MN, Farnum M, Lobanov V, Yang E, Raghavan N, DiBernardo A, et al. An improved model for disease progression in patients from the Alzheimer's disease neuroimaging initiative. J Clin Pharmacol. 2012;52:629-44.
25. Schafer K, De Santi S, Schneider LS. Errors in ADAS-cog administration and scoring may undermine clinical trials results. Curr Alzheimer Res. 2011;8:373-6.
26. Connor DJ, Sabbagh MN. Administration and scoring variance on the ADAS-Cog. J Alzheimers Dis. 2008;15:461-4.
27. Ueckert S, Plan EL, Ito K, Karlsson M, Corrigan B, Hooker AC. Improved utilization of ADAS-cog assessment data through item response theory based pharmacometric modeling. Pharm Res. 2014;31:2152-65.
28. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology. 1984;34:939.
29. Mohs RC, Knopman D, Petersen RC, Ferris SH, Ernesto C, Grundman M, et al. Development of cognitive instruments for use in clinical trials of antidementia drugs: additions to the Alzheimer's Disease Assessment Scale that broaden its scope. Alzheimer Dis Assoc Disord. 1997;11:13-21.
30. Bock RD, Aitkin M. Marginal maximum likelihood estimation of item parameters: application of an EM algorithm. Psychometrika. 1981;46:443-59.
31. Cai L. High-dimensional exploratory item factor analysis by a Metropolis-Hastings Robbins-Monro algorithm. Psychometrika. 2010;75:33-57.
32. Cai L. Metropolis-Hastings Robbins-Monro algorithm for confirmatory item factor analysis. J Educ Behav Stat. 2010;35:307-35.
33. Reckase MD. Multidimensional item response theory. New York: Springer; 2009.
34. Lord FM. Applications of item response theory to practical testing problems. London: Routledge; 1980.
35. Samejima F. Graded response model. In: Handbook of modern item response theory. New York: Springer; 1997. p. 85-100.
36. Zenisky AL, Hambleton RK, Sireci SG. Effects of local item dependence on the validity of IRT item, test, and ability statistics. MCAT Monograph. Association of American Medical Colleges, Section for the Medical College Admission Test Monograph number: 5. 2001.
37. Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika. 1965;30:179-85.
38. Henson RK, Roberts JK. Use of exploratory factor analysis in published research common errors and some comment on improved practice. Educ Psychol Meas. 2006;66:393-416.
39. Wood JM, Tataryn DJ, Gorsuch RL. Effects of under-and overextraction on principal axis factor analysis with varimax rotation. Psychol Methods. 1996;1:354.
40. Cheung GW, Rensvold RB. Evaluating goodness-of-fit indexes for testing measurement invariance. Struct Equ Modeling. 2002;9:233-55.
41. Tucker LR, Lewis C. A reliability coefficient for maximum likelihood factor analysis. Psychometrika. 1973;38:1-10.
42. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling. 1999;6:1-55.
43. Orlando M, Thissen D. Further investigation of the performance of S-X2: an item fit index for use with dichotomous item response theory models. Appl Psychol Meas. 2003;27:289-98.
44. Zhang B, Stone CA. Evaluating item fit for multidimensional item response models. Educ Psychol Meas. 2008;68:181-96.
45. Chen WH, Thissen D. Local dependence indexes for item pairs using item response theory. J Educ Behav Stat. 1997;22:265-89.
46. De Ayala RJ. Theory and practice of item response theory. New York: Guilford Publications; 2013.
47. Holland PW, Wainer H. Differential item functioning. London: Routledge; 2012.
48. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Methodol. 1995;57:289-300.
49. Holland PW, Wainer H. (eds.) Differential Item Functioning. Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers, 1993;67-113.
50. Langer MM. A reexamination of Lord's Wald test for differential item functioning using item response theory and modern error estimation. Chapel Hill: The University of North Carolina; 2008.
51. Cohen J. Statistical power analysis for the behavioral sciences. New York: Academic Press; 2013.
52. Salthouse TA, Babcock RL, Skovronek E, Mitchell DR, Palmon R. Age and experience effects in spatial visualization. Dev Psychol. 1990;26:128.
53. Frisoni GB, Henneman WJ, Weiner MW, Scheltens P, Vellas B, Reynish E, et al. The pilot European Alzheimer's disease neuroimaging initiative of the European Alzheimer's disease consortium. Alzheimers Dement. 2008;4:255-64.
54. Thompson PM, Hayashi KM, de Zubicaray G, Janke AL, Rose SE, Semple J, et al. Dynamics of gray matter loss in Alzheimer's disease. J Neurosci. 2003;23:994-1005.
55. Scahill RI, Schott JM, Stevens JM, Rossor MN, Fox NC. Mapping the evolution of regional atrophy in Alzheimer's disease: unbiased analysis of fluid-registered serial MRI. Proc Natl Acad Sci U S A. 2002;99:4703-7.
56. McDonald CR, McEvoy LK, Gharapetian L, Fennema-Notestine C, Hagler DJ, Holland D, et al. Regional rates of neocortical atrophy from normal aging to early Alzheimer disease. Neurology. 2009;73:457-65.
57. Desikan RS, Cabral HJ, Settecase F, Hess CP, Dillon WP, Glastonbury CM, et al. Automated MRI measures predict progression to Alzheimer's disease. Neurobiol Aging. 2010;31:1364-74.
58. Beckett LA, Harvey DJ, Gamst A, Donohue M, Kornak J, Zhang H, et al. The Alzheimer's Disease Neuroimaging Initiative: annual change in biomarkers and clinical outcomes. Alzheimers Dement. 2010;6:257-64.
59. Stern RG, Mohs RC, Davidson M, Schmeidler J, Silverman J, Kramer-Ginsberg E, et al. A longitudinal study of Alzheimer's disease: measurement, rate, and predictors of cognitive deterioration. Am J Psychiatry. 1994;151:390-6.
60. Verma N, Markey MK: Item response analysis of Alzheimer's disease assessment scale. In 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE; 2014:2476-2479.
61. Whitwell JL, Dickson DW, Murray ME, Weigand SD, Tosakulwong N, Senjem ML, et al. Neuroimaging correlates of pathologically defined subtypes of Alzheimer's disease: a case-control study. Lancet Neurol. 2012;11:868-77.
62. Rösler M, Anand R, Cicin-Sain A, Gauthier S, Agid Y, Dal-Bianco P, et al. Efficacy and safety of rivastigmine in patients with Alzheimer's disease. BMJ. 1999;318:633-40.
63. Rogers SL, Farlow MR, Doody RS, Mohs R, Friedhoff LT. A 24-week, doubleblind, placebo-controlled trial of donepezil in patients with Alzheimer's disease. Neurology. 1998;50:136-45.
64. Wang B, Wang H, Wei Z, Song Y, Zhang L, Chen H. Efficacy and safety of natural acetylcholinesterase inhibitor huperzine A in the treatment of Alzheimer's disease: an updated meta-analysis. J Neural Transm. 2009;116:457-65.
65. Li J, Wu HM, Zhou RL, Liu GJ, Dong BR. Huperzine A for Alzheimer's disease. Cochrane Database Syst Rev. 2008;2, CD005592.
66. Benge JF, Balsis S, Geraci L, Massman PJ, Doody RS. How well do the ADAScog and its subscales measure cognitive dysfunction in Alzheimer's disease? Dement Geriatr Cogn Disord. 2009;28:63.
67. Petersen RC, Thomas RG, Grundman M, Bennett D, Doody R, Ferris S, et al. Vitamin E and donepezil for the treatment of mild cognitive impairment. N Engl J Med. 2005;352:2379-88.