Department of Psychiatry, University of Leipzig, Germany
Correspondence: Anja Busse, Department of Psychiatry, University of Leipzig, Johannisallee 20, D-04317 Leipzig, Germany. Tel: +493419724530; fax: +493419724539; e-mail: krausem{at}medizin.uni-leipzig.de
Declaration of interest The study was supported by the
Interdisciplinary Centre for Clinical Research, University of Leipzig (JZKF,
IKS9504, Project C7_79934700).
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ABSTRACT |
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Aims To report age-specific prevalence, incidence and predictive validities for four diagnostic concepts of mild cognitive impairment.
Method A community sample of 1045 dementia-free individuals aged 75 years and over was examined by neuropsychological testing in a three-wave longitudinal study.
Results Prevalence rates ranged from 3% to 20%, depending on the concept applied. The annual incidence rates applying different case definitions varied from 8 to 77 per 1000 person-years. Rates of conversion to dementia over 2.6 years ranged from 23% to 47%.
Conclusions Mild cognitive impairment is frequent in older people. Prevalence, incidence and predictive validities are highly dependent on the diagnostic criteria applied.
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INTRODUCTION |
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METHOD |
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Of the overall sample of 1692 persons, 242 (14.2%) declined to participate,
57 (3.4%) had died and 15 (0.9%) were not traceable. Information on 113
members of the study sample (6.7%) who were shielded by their relatives was
obtained solely by proxy interviews. Clinical interviews incorporating
neuropsychological assessment were conducted with 1265 (74.8%) participants;
these people did not differ significantly from the remainder of the sample in
terms of age (U=263 553, P=0.455), gender
(2=0.391, d.f.=1, P=0.532) or marital status
(
2=5.027, d.f.=3, P=0.170). Two hundred and twenty
(17.4%) of these 1265 participants were suffering from dementia according to
DSMIV criteria (American Psychiatric
Association, 1994). The analysis is based on the remaining 1045
participants, who showed no DSMIV dementia.
Instruments
Neuropsychological assessment
The main instrument employed was the Structured Interview for Diagnosis of
Dementia of Alzheimer type, Multi-infarct Dementia and Dementia of other
Aetiology according to ICD10 and DSMIIIR (SIDAM;
Zaudig et al, 1991).
The SIDAM consists of a neuropsychological test battery including the
Mini-Mental State Examination (MMSE), a section for clinical judgement and
third-party information on psychosocial impairment. The neuropsychological
test battery covers six areas of neuropsychological functioning:
For each cognitive domain, age-specific and education-specific norms were employed in the evaluation of impairment in cognitive function. The norms were developed on the baseline population (participants without dementia) from which the study sample was recruited.
Data on socio-demographic variables, mild cognitive impairment and possible risk factors for dementia were collected. A series of validated scales examining the capacity to perform a wide range of activities of daily living such as use of the telephone, feeding, dressing and personal hygiene were completed. Complaints of subjective memory impairment were assessed before cognitive testing by asking participants if they had any problems with their memory (answer yes or no). Depressive symptoms were assessed by means of the Centre for Epidemiological Studies Depression (CESD) scale (Radloff, 1977) and the Structured Clinical Interview for DSMIIIR (SCID; Spitzer et al, 1987).
Data collection
Structured clinical interviews were conducted by trained psychologists and
physicians during visits to the participants' homes. In addition, structured
third-party interviews were conducted, in order to obtain information on
cognitive and psychosocial functioning as well as subjective memory
impairment. Baseline interviews were conducted between January 1997 and June
1998. Study participants were requested to take part in two follow-up
assessments, which were conducted 18 months and 36 months after baseline
assessment. If it was not possible to administer the SIDAM at follow-up (e.g.
owing to death or severe weakness, or because relatives refused participation
on behalf of the elderly person in their care), we offered the option of a
fully structured proxy interview. This included the Clinical Dementia Rating
(CDR) scale (Hughes et al,
1982) for assessment of cognitive functioning.
Definition of cases
Consensus conferences of physicians and psychologists were held for each
subject. The clinical diagnosis of dementia was made according to DSMIV
criteria. The cognitive criteria for a dementia diagnosis were based either on
cognitive testing or CDR data (in case of proxy interviews). The reported
prevalence and incidence rates for mild cognitive impairment are based on
individuals who performed cognitive testing at baseline (prevalence rates) and
at least at one follow-up examination (incidence rates). Four diagnostic
concepts for mild cognitive impairment were established: mild cognitive
impairment (MCI), and a modification (MCImodified); and age-associated
cognitive decline (AACD), and a modification (AACDmodified). Reported
predictive validities of these concepts include participants for whom only CDR
data were available at follow-up.
Mild cognitive impairment
Mild cognitive impairment was diagnosed according to the criteria of
Petersen et al
(1999); the condition is now
described as MCIamnestic, following a new
sub-classification (Petersen et
al, 2001). These criteria were:
Age-associated cognitive decline
Age-associated cognitive decline was diagnosed according to Levy et
al's (1994) criteria:
Modifications
Modifications of the above states were also evaluated. These modifications
were defined by the same criteria as the original concepts of MCI and AACD,
with the exception of criterion (a), memory impairment. The importance of
subjective memory impairment in the prediction of dementia is questionable and
it may not be of additional predictive value
(Jorm et al,
1997).
Following these case definitions we find a diagnostic overlap: participants classified into the original concepts also meet criteria of the modified concepts, and subjects with MCI are also identified as having AACD. Levy et al's exclusion criteria were applied for all four diagnostic concepts, to rule out the possibility of memory changes due to medical or psychiatric conditions.
Analysis
The frequencies of all four diagnostic entities at baseline are described
in terms of percentage prevalences. For analysis of incidence, the
person-years at risk method was used. Incidence rates were
estimated as the number of new cases divided by person-years at risk. The
at-risk population comprised those without a diagnosis of mild cognitive
impairment at baseline. Age bands were based on age at the prevalence wave.
Person-years for those without cognitive impairment were calculated as the
time between baseline and the final follow-up examination at which the
cognitive diagnosis was based on cognitive testing. For individuals with
cognitive impairment or dementia, the time of occurrence of the diagnosis was
assumed to be the midpoint between two examinations. Person-years were
calculated accordingly. Study entrants who refused the incidence wave, could
not be traced, died or did not perform cognitive testing were excluded from
the analysis of incidence.
In order to analyse possible non-response bias, chi-squared analysis and
the Mann-Whitney U test were applied. Possible differences in the
prevalence rates between men and women were analysed by 2
testing. For all analyses an
level of 0.01 was used.
To assess the validity of each concept, receiver operating characteristic (ROC) analysis was applied to evaluate the relative predictive powers of the different sets of diagnostic criteria in the predictive of future dementia. In addition, the positive predictive power for each concept was calculated as the proportion of participants who had received a diagnosis of mild cognitive impairment at baseline and developed dementia before follow-up (true positives) over all participants for whom information (including CDR data) were available at follow-up who had received a diagnosis of mild cognitive impairment at baseline (true and false positives).
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RESULTS |
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Age-specific prevalence rates are summarised in Table 1. A diagnosis of MCI was assigned to 3.1% (95% CI 2.0-4.2) of the study participants, of MCI-modified to 5.1% (95% CI 3.7-6.5) AACD to 8.8% (95% CI 7.0-10.7) and of AACD-modified to 19.7% (95% CI 17.1-22.3). The prevalences of AACD and AACD-modified significantly increased with age. There was no significant change with age in the prevalences of MCI and MCI-modified. No difference in prevalence rates between men and women were found.
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Incidence
Table 2 shows sample size
and attrition at follow-up according to the four different diagnostic
concepts. Participants who were investigated at follow-up were significantly
younger and had a significantly higher MMSE score at baseline compared with
those for whom no cognitive testing was performed at follow-up. There was no
difference between those leaving the study and participants with regard to
education and subjective cognitive complaints at the baseline assessment. The
remaining participants had at least one follow-up assessment. The diagnosis at
the last follow-up visit at which the participant had undergone cognitive
testing was taken as the main outcome measure.
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Age-specific incidence rates are summarised in Table 3. Gender-specific rates are not given owing to the small number of incidence cases. The annual incidence rate for the MCI condition for individuals aged 75 years or more was 8.5 (95% CI 4.8-14.1) per 1000 person-years and for MCI-modified it was 12.2 (95% CI 63.3-92.9). Although the incidences for AACD and AACD-modified significantly increased with age, incidence rates for the other two diagnostic concepts did not.
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Prediction of dementia
Of the 929 participants available for baseline examination, 77 were lost to
followup (refused assessment or not traceable). These 77 individuals did not
differ significantly from the remainder of the sample (n=852) as
regards age (U=29 823, P=0.186), gender
(2=0.337, d.f.=1, P=0.068) or subjective cognitive
complaints at baseline assessment (
2=2.773, d.f.=3,
P=0.428). However, they were slightly less educated
(
2=7.941, d.f.=3, P=0.019) and had a significantly
lower MMSE score at baseline (U=26 919, P=0.009). The
remaining 852 participants attended at least one follow-up assessment.
Participants were followed for an average of 2.6 years (s.d.=0.73). The
diagnosis at the last follow-up visit attended by the participant (or where an
informant interview could be conducted) was taken as the main outcome
measure.
Eighty-nine people in the study developed dementia. The conversion rates to dementia over 2.6 years are similar for those in the MCI (n=9, 33%) and AACD-modified (n=55, 36%) groups (Table 4). The conversion rate was highest for AACD (n=33, 47%) and lowest for MCI-modified (n=10, 23%). The conversion rate for participants who did not fulfil the diagnostic criteria was between 5% and 10%, depending on which set of diagnostic criteria was applied.
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There was no difference in the duration of follow-up between participants who had become demented by the follow-up examination and those who had not, between participants with mild cognitive impairment and those without, and between the different diagnostic groups of mild cognitive impairment.
The ROC curves indicate an inability of the MCI and MCI-modified criteria to predict dementia (Table 5): area under the curve (AUC) is 0.539 (P=0.231) and 0.534 (P=0.295) respectively. However, the ROC curves for the other concepts indicate a significant predictive power: for AACD, AUC=0.661 (P=0.000); for AACD-modified, AUC=0.746 (P=0.000). The AACD-modified criteria show the highest sensitivity (62%) and the MCI criteria the lowest (10%). The AACD-modified criteria have the highest relative predictive power for the development of dementia (sensitivity 62%, specificity 87%).
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DISCUSSION |
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Prevalence of mild cognitive impairment
Several research centres use the term mild cognitive
impairment (Petersen et
al, 2001), although there seems to be little agreement on its
diagnostic algorithms (Ritchie &
Touchon, 2000). Prevalence studies of mild cognitive impairment
(Frisoni et al, 2000;
Kivipelto et al,
2001; Ritchie et al,
2001) used different operational criteria with different outcomes.
For example, the study by Ritchie et al
(2001), which related mild
cognitive impairment to an isolated memory loss, reported a prevalence rate of
only 3% in people aged 60 years and over. This is comparable with our results
for MCI and MCImodified.
Kivipelto et al (2001) defined mild cognitive impairment as an objective impairment of memory or in one other area of cognitive function and recorded a prevalence rate of 6% in people aged 65-79 years. Only people scoring 24 or less on the MMSE were subjected to a full diagnostic evaluation, which might have underestimated the true prevalence in this population. Frisoni et al (2000) defined mild cognitive impairment as a score 1 s.d. below the mean of age- and education-specific norms on the MMSE, and reported a prevalence rate of 15% for their study sample, aged 75-95 years.
Age- and gender-specific prevalence rates
According to our study the prevalences of AACD and AACDmodified
increase with age. An increase in prevalence with age was also found in other
studies (Coria et al,
1993; Di Carlo et al,
2000; Unverzagt et
al, 2001). A general decline with age was found in one study
(Koivisto et al,
1995) but others found no significant influence of age on the
frequency of mild cognitive impairment
(Hänninen et al,
1996; Frisoni et al,
2000). Like the study by Hänninen et al
(1996) we found no gender
difference in the prevalence of mild cognitive impairment. However, higher
prevalence rates for men (Koivisto et
al, 1995) and women (Di
Carlo et al, 2000) have been reported.
Potential bias
Our results might underestimate prevalence rates, since 25% of those
originally selected were lost to the study. Although there was no significant
difference in age between the participants and the remainder of the study
sample, there could still be a bias particularly as 7% did not
participate because they were shielded by their relatives, and these people
might have been more physically and cognitively impaired than the
participants.
Incidence
To our knowledge, there is no incidence study that has applied MCI or AACD
criteria. Like the prevalence rates, in our study the incidence rates for MCI
and MCImodified were very low. Incidence rates for AACDmodified
were significantly higher than those for AACD. The incidence of AACD was
comparable with dementia incidence rates reported in a meta-analysis on
incidence data (Jorm & Jolley,
1998). Our incidence rates should be considered as conservative
estimates because it has been shown that the effect of people leaving the
study was selective in favour of younger and cognitively less-impaired study
participants.
As with dementia, incidence rates of mild cognitive impairment seem to increase with age (Paykel et al, 1994; Andersen et al, 1999). However, in our study, although the incidence rates for the AACD and AACDmodified groups significantly increased with age, the incidence rates for the other two diagnostic groups did not. In old age, memory impairment commonly occurs together with other cognitive deficits (Ritchie & Touchon, 2000), which excludes participants from the MCI and MCImodified categories.
Prediction of dementia using MCI criteria
The annual rate of conversion of MCI to dementia in our study falls within
the range of results from clinical samples (10-15%)
(Petersen et al,
2001). However, as indicated by the ROC analysis, the MCI
diagnostic concept does not have a significant relative predictive power. We
found a small percentage of MCI cases in our non-dementia population (3%).
Thus, MCI criteria have a low sensitivity in the detection of dementia. This
outcome supports the results of Ritchie et al
(2001), in whose study the
sensitivity of MCIamnestic criteria for the prediction of dementia was
5%.
Prediction of dementia using AACD criteria
To our knowledge, the only population-based study that has applied the AACD
criteria to predict dementia reported a 29% conversion rate within 3 years
(Ritchie et al,
2001). A clinical study applying criteria comparable with the AACD
criteria revealed a 2-year conversion rate to Alzheimer's disease of 28%
(Celsis et al, 1997). In our study the conversion rate to dementia within 2.6 years was higher
(47%), probably because of the greater age of our population.
The AACDmodified criteria yielded the best relative predictive power and the best relation of sensitivity and specificity. The 20% prevalence of AACDmodified found in our study is similar to the AACD prevalence established by Ritchie et al (2001). Our results suggest that in older people with evidence of objective cognitive impairment, the diagnostic criterion of subjective cognitive complaints has no additional predictive power. The predictive power of subjective memory complaints has been questioned because of their multiple determinants and situational variables affecting the interaction between clinicians and patients (Jorm & Christensen, 2001). Jorm et al (1997) concluded that it is inappropriate to include cognitive complaints in diagnostic criteria for mild cognitive impairment. Neuropsychological screening at the primary care level could detect people at risk even if they did not report subjective complaints. Cases of mild cognitive impairment could be missed if the elderly person did not admit cognitive impairment and no third-party information could be obtained. However, in people without demonstrable cognitive impairment, subjective memory complaints might be of prognostic value for future dementia. This may apply especially to highly educated elderly people, owing to the ceiling effect of some cognitive tests (Jonker et al, 2000).
In sum, the AACDmodified criteria represent the best compromise as regards sensitivity and specificity and yield a high conversion rate of 36% within 2.6 years. Moreover, the criterion of deficits in cognitive domains other than memory has been supported by recent research on the prediction of dementia (Bozoki et al, 2001). Since subjective cognitive impairment does not seem to be very useful for the prediction of dementia, it might be preferable to omit it as a criterion for mild cognitive impairment if objective data on cognitive performance are available.
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Clinical Implications and Limitations |
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LIMITATIONS
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Received for publication May 23, 2002. Revision received December 5, 2002. Accepted for publication December 12, 2002.
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