This article has Open Peer Review reports available.
Word reading threshold and mild cognitive impairment: a validation study
© Arsenault-Lapierre et al.; licensee BioMed Central Ltd. 2012
Received: 6 June 2011
Accepted: 28 May 2012
Published: 24 July 2012
It was previously found, in a pilot study, that Word Reading Threshold (WRT) test is abnormally prolonged in individuals with Alzheimer’s disease (AD) and Mild Cognitive Impairment (MCI), with high sensitivity and specificity. This validation study examines the WRT test as a prognostic tool in MCI individuals. We wish to confirm in a larger group the sensitivity and specificity of the WRT test and determine whether it is influenced by deterioration on other cognitive domains.
We measured WRT in 60 MCI individuals, 29 AD patients, and 33 normal elderly control (NE). We followed the MCI individuals over 8 years to monitor who progressed to dementia.
We found a statistically significant difference in WRT scores between the three groups. However, using the same cutoff of 85 milliseconds suggested by Massoud and his colleagues, we found lower diagnostic sensitivity (72%) and specificity (76%) when comparing NC and AD. Furthermore, the test did not clearly differentiate MCI individuals who progressed to dementia from those who did not. WRT was found to correlate to some degree with other cognitive domains, especially attention.
We conclude that the WRT is insufficient alone as a diagnostic tool for prodromal AD.
The term Mild Cognitive Impairment (MCI) describes a group of individuals who are at an intermediate stage between normal aging and dementia from clinical, neurological, and neuropsychological standpoints. In fact, individuals with MCI present with subjective memory complaints, corroborated by objective deficits on mental status testing and standardized neuropsychological tests, without functional or social impairment needed to diagnose dementia . Prospective studies show that these individuals are at an increased risk of developing AD. Indeed, 10% to 15% of the individuals with MCI will progress to dementia each year, compared to an annual rate of 1% to 2% in the general population over 65 years old . Ultimately, in most memory clinics, between 50% and 75% of patients presenting with MCI will go on to dementia over long term follow-up [2, 3]. MCI individuals often show hippocampal atrophy, a characteristic feature of Alzheimer’s disease (AD), to a degree midway between that of normal individuals and demented patients . Recently, it has even been proposed that MCI individuals with MRI atrophy or other AD-like biomarkers, be considered as having prodromal AD .
The existence of such a group of individuals at risk of developing AD has encouraged research on diagnostic tools that could discriminate those who will progress to AD. Because of the demands of clinical settings, such discriminative tests ought to be relatively inexpensive, fairly quick to administer and opaque to other factors that can affect cognitive functions such as depression [6, 7]. Memory loss being the core symptom of AD, research has focused largely on neuropsychological tests that assess this symptom. However, memory loss can be easily confounded with encoding and attention deficits seen in other conditions such as depression [8–10]. More sophisticated memory tests may need to be administered by neuropsychologists. At the same time, more studies show that episodic memory deficits might not be the only feature of mild AD . For example, studies have found subtle visuoperceptual deficits in AD, particularly changes in word perceptual threshold . Perceptual tests, being for less attention demanding, are likely to be less influenced by depression – a major advantage for an AD tests. One explanation of the deficits observed in word-recognition tests could be the degeneration of the “word-form area” in the occipital-temporal extrastriate cortex  also affected, albeit to a lesser degree than memory areas, in AD [13, 14]. Another possible explanation could be that patients with AD show poorer performance on more demanding perceptual tasks because they have slower central processing abilities. For instance, a masked word recognition test is more demanding on the central processing abilities than an unmasked letter recognition test, and therefore, the former test would be more sensitive in the earlier disease stages.
Based on these premises, our group conducted a pilot study , testing the discriminative power of the Word Reading Threshold (WRT) test. In brief, we used a computerized test designed to assess visual perception changes encountered in AD or MCI. We found that the mean WRT was significantly longer in the 13 patients with AD than in the 12 normal controls (NC), and, with a threshold of 85 milliseconds (ms), there was a diagnostic sensitivity of 77% and a diagnostic specificity of 92%. It was also found that all of the four individuals with MCI who progressed to dementia after two years of follow-up also scored above that threshold. This test is inexpensive and simple to administer. These results therefore warranted confirmation in a larger group of subjects in order to test the specificity, reliability, and replicability of WRT, as well as its opacity to other cognitive domains. Consequently, the goal of this study is to validate the WRT as a diagnostic tool in MCI individuals. More precisely, we want to measure its sensitivity and specificity in a larger sample of AD, MCI and NC individuals, and examine potential cognitive correlates of word recognition and prolonged WRT.
Demographic and neuropsychological information
GDSa, b, c
MMSEa, b, c
WRT a, b, c
LM2a, b, c
VR2 a, b, c
RAVLT delay a, b, c
COWA lexicala, b
COWA semantic a, b, c
BNT a, b, c
TRAIL a, b, c
To calculate the sensitivity and the specificity of the WRT at the suggested cut-off score of 85 ms, we compared NC and AD patients as follow. Sensitivity is TP/(TP + FN) and Specificity is TN/(TN + FP), where TP is the number of true positives; FP, the number of false positives; FN, the number of false negatives; and TN, the number of true negatives. We also carried a Receiver-Operating Characteristic (ROC) analysis to evaluate the performance of WRT in classifying appropriately NC and AD, and MCIp and MCInp.
Finally, to verify whether the WRT is opaque to other cognitive domains, we correlated the WRT scores with tests of memory, language and attention. We tested the subjects on Logical Memory (LM) I and II subscales and Visual Reproduction (VR) I and II subscales of the Weschler Memory Scale-Revised (WMS-R ), Rey Auditory-Verbal Learning Test (RAVLT ), Boston Naming Test (BNT ), Controlled Word Association Test (COWA ), the Trail Making Test, subscale A (TRAIL ), and Stroop Test .
To determine group differences in WRT scores, one-way ANOVA were performed, controlling for confounding variables, such as the number of years of education and depression scores on the Geriatric Depression Scale (GDS). To specify which pair-groups were different, Bonferroni’s post hoc analyses were performed. A difference was deemed statistically significant if the p-value was smaller than 0.05. ROC analyses were performed on WRT and other neuropsychological tests comparing NC and AD first, and then comparing MCIp and MCInp. To assess the opacity of WRT to other cognitive functions, performances on WRT were correlated with neuropsychological tests using partial correlations to control for confounding variables (education and depression), in the whole study sample first, then in each diagnostic group. Bonferroni’s corrections for multiple comparisons were applied to the partial correlations and a p-value of 0.005 was used.
We collected WRT scores for 60 individuals with MCI, 29 patients with AD, and 33 NC. The three groups differed in terms of years of education (F(2,120) = 6.9, p = 0.001) and depression scores as measured by Geriatric Depression Scale (GDS : F(2,111) = 6.0, p = 0.003), which correlated with WRT scores. Therefore, education and GDS were entered as covariates in our analyses. Age difference did not reach statistical significance.
Correlations between WRT and neuropsychological tests
Similar to previous findings from this laboratory , we found a significant difference in the WRT scores of the AD compared to the MCI and NC groups. Even though the WRT classified correctly NC and AD 81% of the time, it showed lower diagnostic sensitivity (72%) and specificity (76%) than previously found (77% and 92% respectively). On average, the AD subjects included in our study have shorter WRT and the MCI have somewhat longer WRT than those in Massoud’s study (Massoud: MCI 60.3 ± 15.9 ms and AD 122.6 ± 70.8 ms; Present study: MCI 73.4 ± 25.7 ms and AD 92.6 ± 31.7 ms).
It is worth noting that we found slightly bigger standard deviations in the NC and MCI groups, and smaller ones in the AD group than what was previously reported, indicating that our groups might have been less homogenous. Examining the individuals scores from Massoud’s study  and our own replication study illustrates this difference clearly (Figure 2). In the pilot study, only 1 out of 12 NC had a WRT score greater than the 85 ms, compared to 8 out of 33 in our follow-up study. Similarly, in Massoud’s study, only 3 out of 13 AD patients scored below the cut-off, compared with 8 out of 25 in the current study. We simply failed to maintain this striking separation between NC and AD patients in a larger cohort. Even though the age and dementia severity, measured by MMSE, of the groups were similar in the two studies, we must conclude that the pilot study, being smaller, simply showed less heterogeneity than was found in our replication study.
The ROC analyses showed that WRT does not perform better than chance level in classifying MCI individuals who will progress to AD or not (AUC = 0.45, p > 0.1). Indeed, in the current study, WRT only correctly classified 32% of the MCI individuals who progressed to dementia, which is less impressive than what Massoud and his colleagues had found, where all of the MCI subjects who had scored ≥ 85 ms on WRT had progressed to AD after 2 years of follow-up. It is important to note that the follow-up period in our study was of 8 years. Massoud’s study included 4 individuals with MCI who progressed to AD, which is within the expected published rates of progression to AD (15% a year). The current study, in contrast, yielded a larger sample of converters. However, the average rate of progression from MCI to AD in our study (about 4% a year) is lower than in most studies . In addition, examination of the AUC for other neuropsychological tests reveals that the delayed recall of Logical Memory and Ray Auditory Verbal Learning Tests were better at discriminating MCIp from MCInp (Table 1).
Massoud and colleagues found that WRT scores correlated with scores on a global cognitive assessment test, the MMSE. In our study, we replicated this finding, but we wanted to evaluate whether WRT scores were related to those of other cognitive tests. We found evidence for an association between WRT scores and measures of memory and language. These associations might be spurious, however, as they were found only when the three groups were collapsed, with the exception of the lexical subtest of the Controlled Word Association test in the NC group. WRT scores were also correlated with measures of attention, more precisely Trail Making Test A and Stroop dots subtest. This suggests that performance on WRT is related to overall mental speed and attention processing. However, we found that the association with Trail Making Test A was maintained in the NC, MCInp, and AD groups, but not in the MCIp group. Similarly, the association with Stroop dots remained significant only in the NC and MCInp groups. Although explaining the absence of correlation in the MCIp or AD groups is beyond the scope of this study, it might suggest that at the MCI stage of AD pathology different cognitive domains are affected to different degrees. As for the absence of correlation between MMSE and WRT scores in the NC and MCI groups, it can easily be explained by ceiling effect. In the NC and MCI groups, MMSE scores do not vary enough, whereas in the AD group, MMSE scores range from 11 to 29.
Despite the fact that we selected the participants of our study in the same way as Massoud and colleagues did, MCI individuals whose WRT was greater than 85 ms were not more likely to progress to AD after 8 years follow-up. This can be explained again by the larger sample size. The original study was a small pilot study and it is common for larger samples to lack the robust separation found in smaller, more homogeneous samples. Without doubt, our larger sample introduced heterogeneity, as expressed in the increased standard deviations in WRT scores of NC and MCI individuals. The follow up period in our replication study was significantly longer than in Massoud’s study, which brings more support to the present findings. The participants included in our replication study compared fairly well to those of Massoud’s. They had similar education and MMSE score, as well as similar duration of illness (this study: 3.9 (0–15), Massoud’s study: 4.5 (2–10) for the MCI and AD groups. The participants also compared well in term of age and BNT scores.
As is the case with many studies that have looked for simple tests discriminating between MCI individuals who will progress to AD and those who will not, the results are not sufficiently robust to suggest WRT as a prognostic test. Apart from obvious methodological differences in diagnosing MCI, these disappointing results might be explained by the now established heterogeneity of AD and the increasingly recognized heterogeneity of MCI. For example, some patients with AD will show greater difficulties with language or executive functions, whereas others will show greater visuoperceptual deficits, this, aside from the frequent comorbidity of other dementia [25, 26]. This heterogeneity of symptoms is also portrayed in the subdivisions of MCI; that is, pure amnestic MCI, multiple-domains (including memory) MCI, single non-memory domain MCI, and multiple non-memory domains MCI. The use of a panel of simple neuropsychological tests, in conjunction with imaging and possibly genetic biomarkers remains potentially more valuable in predicting progression to AD Petersen, .
We want to thank Shelley Solomon, Kathy De Sousa, and Victor Whitehead of the Bloomfield Center for Research in Aging at the Lady Davis Institute for Medical Research of the Jewish General Hospital, Montreal, Canada for their tremendous help with acquisition of the data.
- Petersen RC, Doody R, Kurz A, Mohs RC, Morris JC, Rabins PV, Ritchie K, Rossor M, Thal L, Winblad B: Current concepts in mild cognitive impairment. Arch Neurol. 2001, 58 (12): 1985-1992. 10.1001/archneur.58.12.1985.View ArticlePubMedGoogle Scholar
- Visser PJ, Verhey FR, Hofman PA, Scheltens P, Jolles J: Medial temporal lobe atrophy predicts Alzheimer's disease in patients with minor cognitive impairment. J Neurol Neurosurg Psychiatry. 2002, 72 (4): 491-497.PubMedPubMed CentralGoogle Scholar
- Chertkow HM, Bergman H, Bocti C, McKelvey R, Phillips N, Whitehead V: Amnestic mild cognitive impairment in a referral population-a non-progressing subgroup exists on long-term follow-up. ICAD-Alzheimer's Association 10th International Conference on Alzheimer's Disease and Related Disorders. 2006, Alzheimer's and Dementia (the journal of the Alzheimer's association), Madrid, Spain, S82-S83.Google Scholar
- Grundman M, Petersen RC, Ferris SH, Thomas RG, Aisen PS, Bennett DA, Foster NL, Jack CR, Galasko DR, Doody R, et al: Mild cognitive impairment can be distinguished from Alzheimer disease and normal aging for clinical trials. Arch Neurol. 2004, 61 (1): 59-66. 10.1001/archneur.61.1.59.View ArticlePubMedGoogle Scholar
- Dubois B, Feldman HH, Jacova C, Dekosky ST, Barberger-Gateau P, Cummings J, Delacourte A, Galasko D, Gauthier S, Jicha G, et al: Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria. Lancet Neurol. 2007, 6 (8): 734-746. 10.1016/S1474-4422(07)70178-3.View ArticlePubMedGoogle Scholar
- Klunk WE: Biological markers of Alzheimer's disease. Neurobiol Aging. 1998, 19 (2): 145-147. 10.1016/S0197-4580(98)00013-X.View ArticlePubMedGoogle Scholar
- Cronin-Golomb A, Corkin S, Growdon JH: Visual dysfunction predicts cognitive deficits in Alzheimer's disease. Optom Vis Sci. 1995, 72 (3): 168-176. 10.1097/00006324-199503000-00004.View ArticlePubMedGoogle Scholar
- Hart RP, Kwentus JA, Hamer RM, Taylor JR: Selective reminding procedure in depression and dementia. Psychol Aging. 1987, 2 (2): 111-115.View ArticlePubMedGoogle Scholar
- La Rue A, Swan GE, Carmelli D: Cognition and depression in a cohort of aging men: results from the Western Collaborative Group Study. Psychol Aging. 1995, 10 (1): 30-33.View ArticlePubMedGoogle Scholar
- Gron G, Bittner D, Schmitz B, Wunderlich AP, Riepe MW: Subjective memory complaints: objective neural markers in patients with Alzheimer's disease and major depressive disorder. Ann Neurol. 2002, 51 (4): 491-498. 10.1002/ana.10157.View ArticlePubMedGoogle Scholar
- Backman L, Jones S, Berger AK, Laukka EJ, Small BJ: Cognitive impairment in preclinical Alzheimer's disease: a meta-analysis. Neuropsychology. 2005, 19 (4): 520-531.View ArticlePubMedGoogle Scholar
- Petersen SE, Fox PT, Snyder AZ, Raichle ME: Activation of extrastriate and frontal cortical areas by visual words and word-like stimuli. Science. 1990, 249 (4972): 1041-1044. 10.1126/science.2396097.View ArticlePubMedGoogle Scholar
- Arnold SE, Hyman BT, Flory J, Damasio AR, Van Hoesen GW: The topographical and neuroanatomical distribution of neurofibrillary tangles and neuritic plaques in the cerebral cortex of patients with Alzheimer's disease. Cereb Cortex. 1991, 1 (1): 103-116. 10.1093/cercor/1.1.103.View ArticlePubMedGoogle Scholar
- Lewis DA, Campbell MJ, Terry RD, Morrison JH: Laminar and regional distributions of neurofibrillary tangles and neuritic plaques in Alzheimer's disease: a quantitative study of visual and auditory cortices. J Neurosci. 1987, 7 (6): 1799-1808.PubMedGoogle Scholar
- Massoud F, Chertkow H, Whitehead V, Overbury O, Bergman H: Word-reading thresholds in Alzheimer disease and mild memory loss: a pilot study. Alzheimer DisAssocDisord. 2002, 16 (1): 31-39.Google Scholar
- 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 (7): 939-944. 10.1212/WNL.34.7.939.View ArticlePubMedGoogle Scholar
- Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E: Mild cognitive impairment: clinical characterization and outcome. Arch Neurol. 1999, 56 (3): 303-308. 10.1001/archneur.56.3.303.View ArticlePubMedGoogle Scholar
- Satz P, Mogel S: An abbreviation of the WAIS for clinical use. J Clin Psychol. 1962, 18: 77-79. 10.1002/1097-4679(196201)18:1<77::AID-JCLP2270180124>3.0.CO;2-R.View ArticlePubMedGoogle Scholar
- Schmidt M: Rey Auditory-Verbal Learning Test. 1996, Western Psychological Services, Los AngelesGoogle Scholar
- Mack WJ, Freed DM, Williams BW, Henderson VW: Boston Naming Test: shortened versions for use in Alzheimer's disease. J Gerontol. 1992, 47 (3): P154-P158.View ArticlePubMedGoogle Scholar
- Benton AH K, Sivan AB: Multilingual Aphasia Examination. 1994, AJA Associates, IowaGoogle Scholar
- Reitan R, Wolfson D: The Halstead-Reitan neuropsychological test battery. 1985, Neuropsychological Press, Tucson, AZGoogle Scholar
- Stroop JR: Studies of interference in serial berbal reactions. Journal of Experimental Psychology. 1935, 18: 643-661.View ArticleGoogle Scholar
- Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, Leirer VO: Development and validation of a geriatric depression screening scale: a preliminary report. J Psychiatr Res. 1982, 17 (1): 37-49. 10.1016/0022-3956(82)90033-4.View ArticlePubMedGoogle Scholar
- Joanette Y, Melancon L, Ska B, Lecours AR: Heterogeneity of cognitive profiles in dementias of the Alzheimer type: theoretical aspects and clinical consequences. Union Med Can. 1993, 122 (6): 420-426.PubMedGoogle Scholar
- Ritchie K, Touchon J: Heterogeneity in senile dementia of the Alzheimer type: individual differences, progressive deterioration or clinical sub-types?. J Clin Epidemiol. 1992, 45 (12): 1391-1398. 10.1016/0895-4356(92)90201-W.View ArticlePubMedGoogle Scholar
- Petersen RC: Mild cognitive impairment : aging to Alzheimer's disease. 2003, Oxford University Press, Oxford; New YorkGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://0-www.biomedcentral.com.brum.beds.ac.uk/1471-2318/12/38/prepub
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.