Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-28T10:36:22.568Z Has data issue: false hasContentIssue false
  • English
  • Français

Informant questionnaire on cognitive decline in the elderly (IQCODE) for classifying cognitive dysfunction as cognitively normal, mild cognitive impairment, and dementia

Published online by Cambridge University Press:  31 May 2017

Moon Ho Park
Moon Ho Park*
Affiliation:
Department of Neurology, Korea University Medical College, Seoul, South Korea & Korea University Ansan Hospital, Ansan, South Korea
*
Correspondence should be addressed to: Moon Ho Park, MD, PhD, Department of Neurology, Korea University Ansan Hospital, 516, Gojan-dong, Danwon-gu, Ansan-si, Gyeonggi-do, South Korea. Phone: +82-31-412-5150; Fax: +82-31-412-5154. Email: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

Background:

The Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) is a reliable, validated informant-based instrument in screening for cognitive dysfunction. However, previous studies have evaluated only the ability to discriminate dichotomously, such as dementia from cognitively normal (CN) individuals or mild cognitive impairment (MCI) from CN. This study investigated the ability of the IQCODE to classify not only dichotomous but also multiple stages of cognitive dysfunction.

Methods:

We examined 228 consecutive participants (76 CN, 76 with MCI, and 76 with dementia). Receiver operating characteristic (ROC) curves determined dichotomous classification parameters. Multi-category ROC surfaces were evaluated to classify three stages of cognitive dysfunction.

Results:

Dichotomous classification using the ROC curve analyses showed that the area under the ROC curve was 0.91 for dementia from participants without dementia and 0.71 for MCI from CN. Simultaneous multi-category classification analyses showed that the volume under the ROC surface was 0.61 and the derived optimal cut-off points were 3.15 and 3.73 for CN, MCI, and dementia. The Youden index for the IQCODE was estimated as 0.51 and the derived optimal cut-off points were 3.33 and 3.70. The overall classification accuracy by the VUS was 58.3% and that by the Youden index 61.8%.

Conclusions:

IQCODE is useful to classify the dichotomous and multi-category stages of cognitive dysfunction.

Keywords

IQCODEclassifyingscreening
Type
Research Article
Information
International Psychogeriatrics , Volume 29 , Issue 9 , September 2017 , pp. 1461 - 1467
Copyright
Copyright © International Psychogeriatric Association 2017 

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.)

References

APA (2000). American psychiatric association. Diagnostic and Statistical Manual of Mental Disorders, 4th edn, text revision. Washington, DC: American Psychiatric Press.Google Scholar
Cherbuin, N., Anstey, K. J. and Lipnicki, D. M. (2008). Screening for dementia: a review of self- and informant-assessment instruments. International Psychogeriatrics, 20, 431–458. doi: 10.1017/S104161020800673X.CrossRefGoogle ScholarPubMed
Choi, S. H. and Park, M. H. (2016). Three screening methods for cognitive dysfunction using the mini-mental state examination and Korean dementia screening questionnaire. Geriatrics & Gerontology International, 16, 252–258. doi: 10.1111/ggi.12464.CrossRefGoogle ScholarPubMed
Cruz-Orduna, I. et al. (2012). Detecting MCI and dementia in primary care: effectiveness of the MMS, the FAQ and the IQCODE [corrected]. Family Practice, 29, 401–406. doi: 10.1093/fampra/cmr114.CrossRefGoogle ScholarPubMed
Ehrensperger, M. M., Berres, M., Taylor, K. I. and Monsch, A. U. (2010). Screening properties of the German IQCODE with a two-year time frame in MCI and early Alzheimer's disease. International Psychogeriatrics, 22, 91–100. doi: 10.1017/S1041610209990962.CrossRefGoogle ScholarPubMed
Ferri, C., Hernández-Orallo, J. and Salido, M. A. (2003). Volume under the ROC Surface for multi-class problems . In Lavrač, N., Gamberger, D., Todorovski, L. and Blockeel, H., (eds.) Machine Learning: ECML 2003: 14th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings (pp. 108–120). Berlin, Germany: Springer-Verlag.CrossRefGoogle Scholar
Folstein, M. F., Folstein, S. E. and 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, 189–198.CrossRefGoogle ScholarPubMed
Han, C., Jo, S. A., Jo, I., Kim, E., Park, M. H. and Kang, Y. (2008). An adaptation of the Korean mini-mental state examination (K-MMSE) in elderly Koreans: demographic influence and population-based norms (the AGE study). Archives of Gerontology and Geriatrics, 47, 302–310. doi: 10.1016/j.archger.2007.08.012.CrossRefGoogle ScholarPubMed
Hancock, P. and Larner, A. J. (2009). Diagnostic utility of the informant questionnaire on cognitive decline in the elderly (IQCODE) and its combination with the Addenbrooke's cognitive examination-revised (ACE-R) in a memory clinic-based population. International Psychogeriatrics, 21, 526–530. doi: 10.1017/S1041610209008941.CrossRefGoogle Scholar
Hanley, J. A. and McNeil, B. J. (1983). A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology, 148, 839–843. doi: 10.1148/radiology.148.3.6878708.CrossRefGoogle ScholarPubMed
Isella, V., Villa, L., Russo, A., Regazzoni, R., Ferrarese, C. and Appollonio, I. M. (2006). Discriminative and predictive power of an informant report in mild cognitive impairment. Journal of Neurology, Neurosurgery & Psychiatry, 77, 166–171. doi: 10.1136/jnnp.2005.069765.CrossRefGoogle ScholarPubMed
Jorm, A. F. (2004). The informant questionnaire on cognitive decline in the elderly (IQCODE): a review. International Psychogeriatrics, 16, 275–293.CrossRefGoogle ScholarPubMed
Jorm, A. F. and Korten, A. E. (1988). Assessment of cognitive decline in the elderly by informant interview. British Journal of Psychiatry, 152, 209–213.CrossRefGoogle ScholarPubMed
Jorm, A. F., Scott, R., Cullen, J. S. and MacKinnon, A. J. (1991). Performance of the informant questionnaire on cognitive decline in the elderly (IQCODE) as a screening test for dementia. Psychological Medicine, 21, 785– 790.CrossRefGoogle ScholarPubMed
Lee, D. W. et al. (2005). Validity of the Korean version of informant questionnaire on cognitive decline in the elderly (IQCODE). Journal of Korean Geriatrics Society, 9, 196–204.Google Scholar
Lin, J. S., O'Connor, E., Rossom, R. C., Perdue, L. A. and Eckstrom, E. (2013). Screening for cognitive impairment in older adults: a systematic review for the US Preventive Services Task Force. Annals of Internal Medicine, 159, 601–612. doi: 10.7326/0003-4819-159-9-201311050-00730.Google Scholar
Lowe, D. A., Balsis, S., Miller, T. M., Benge, J. F. and Doody, R. S. (2012). Greater precision when measuring dementia severity: establishing item parameters for the clinical dementia rating scale. Dementia and Geriatric Cognitive Disorders, 34, 128–134. doi: 10.1159/000341731.CrossRefGoogle ScholarPubMed
Morales, J. M., Bermejo, F., Romero, M. and Del-Ser, T. (1997). Screening of dementia in community-dwelling elderly through informant report. International Journal of Geriatric Psychiatry, 12, 808–816.3.0.CO;2-5>CrossRefGoogle ScholarPubMed
Morris, J. C. (1993). The clinical dementia rating (CDR): current version and scoring rules. Neurology, 43, 2412–2414.CrossRefGoogle ScholarPubMed
Murray, A. L. and McKenzie, K. (2014). The accuracy of the child and adolescent intellectual disability screening questionnaire (CAIDS-Q) in classifying severity of impairment: a brief report. Journal of Intellectual Disability Research, 58, 1179–1184. doi: 10.1111/jir.12115.CrossRefGoogle ScholarPubMed
Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G. and Kokmen, E. (1999). Mild cognitive impairment: clinical characterization and outcome. Archives of Neurology, 56, 303–308.CrossRefGoogle ScholarPubMed
Quinn, T. J., Fearon, P., Noel-Storr, A. H., Young, C., McShane, R. and Stott, D. J. (2014). Informant questionnaire on cognitive decline in the elderly (IQCODE) for the diagnosis of dementia within community dwelling populations. Cochrane Database of Systematic Reviews, 4, CD010079. doi: 10.1002/14651858.CD010079.pub2.Google Scholar
Razavi, M. et al. (2014). Comparison of 2 informant questionnaire screening tools for dementia and mild cognitive impairment: AD8 and IQCODE. Alzheimer Disease and Associated Disorders, 28, 156–161. doi: 10.1097/WAD.0000000000000008.CrossRefGoogle ScholarPubMed
Sikkes, S. A. et al. (2010). How useful is the IQCODE for discriminating between Alzheimer's disease, mild cognitive impairment and subjective memory complaints? Dementia and Geriatric Cognitive Disorders, 30, 411–416. doi: 10.1159/000321697.CrossRefGoogle ScholarPubMed
Tokuhara, K. G., Valcour, V. G., Masaki, K. H. and Blanchette, P. L. (2006). Utility of the informant questionnaire on cognitive decline in the elderly (IQCODE) for dementia in a Japanese-American population. Hawaii Medical Journal, 65, 72–75.Google Scholar
Winblad, B. et al. (2004). Mild cognitive impairment–beyond controversies, towards a consensus: report of the international working group on mild cognitive impairment. Journal of Internal Medicine, 256, 240–246. doi: 10.1111/j.1365-2796.2004.01380.x.CrossRefGoogle Scholar
Xiong, C., van Belle, G., Miller, J. P. and Morris, J. C. (2006). Measuring and estimating diagnostic accuracy when there are three ordinal diagnostic groups. Statistics in Medicine, 25, 1251–1273. doi: 10.1002/sim.2433.CrossRefGoogle ScholarPubMed