Diagnostic Stability of Mild Cognitive Impairment, and Predictors of Reversion to Normal Cognitive Functioning

Mild cognitive impairment (MCI) is a diagnostic entity designed to identify individuals who are in an intermediate stage between normal cognitive aging and dementia [1]. MCI has proven to be a relatively unstable concept with longitudinal data showing reversion rates, averaging at 26.4% [2], to be higher than rates of progression to dementia [3]. Furthermore, some studies have reported that a substantial number with stable MCI change subtype, for example, switch from amnestic to non-amnestic subtype [4, 5]. However, few studies report frequency of subtype fluctuation. In addition, a limited number of studies report [5-7] the long-term trajectory of MCI with multiple follow-ups, particularly tracking those individuals who revert to normal. These individuals are particularly interesting as it has been established that they are more liable to progress to dementia than those without a MCI diagnosis [7]. Fluctuations in subtypes and unstable MCI trajectories threaten the utility of MCI as a diagnostic entity; hence, more research is necessary in regard to reversion and stability in order to determine whether MCI is a sound concept to identify individuals with high risk of dementia progression.

A growing body of research focuses on factors related to reversion, which include younger age [7, 8-10], male sex [7], both higher [11] and lower education [4], having a life partner [7, 12] or not [10], better global cognitive functioning [4, 7, 9] and neuropsychological test scores [7, 10, 13], day-to-day cognitively stimulating activities, for example, driving a car or reading [14], and improvement of depressive symptoms [15]. Moreover, better vision/smelling ability [12], greater hippocampal volume [12, 13], and lack of APOE-4 [7, 9, 10, 13] are also predictive of reversion. Diagnostic criteria factors include using liberal MCI criteria [12], single-domain MCI [4, 7, 9, 12] and the non-amnestic subtype [7, 9], and the absence of subjective/informant-based complaint [9, 12].

In addition to these factors, fluctuations in performance during cognitive assessment due to lack of concentration, circadian rhythms (time of day) [16, 17], which cognitive test (test version), and when (test order) the test is administrated in the cognitive test battery [18] can consequently lead to the misdiagnosis of MCI. The usage of inappropriate normative scoring, for example, bracket creep (moving into a higher age group at subsequent examination with lower cutoff values for norms can also cause misdiagnosis of MCI) [5]. Yet, none of these influences on cognitive assessment have been studied in relation to reversion.

In summary, there is a need to better understand the stability of MCI, its long-term trajectory, and the causes of MCI reversion. By confirming old and establishing novel predictors for reversion, clinicians can better inform MCI patients about viable future prospects and improve selection of which MCI patients should engage in clinical trials. Thus, this study aimed to assess the stability and trajectory of MCI diagnosis and factors influencing rate of reversion from MCI to normal cognitive functioning using population-based longitudinal data.

The study procedures have been described in detail elsewhere [19] and are only briefly described here. The sample was drawn from the Swedish longitudinal aging study Good Aging in Skåne (GÅS) [20] and consisted of participants from 2 baseline waves collected in 2001 (wave 1) and 2007 (wave 2) with 6-year follow-up data (Fig. 1). Participants were stratified by age into groups 60–69, 70–79, and 80+. To examine aims concerning 12-year stability and trajectory, participants from wave 1 were used (Fig. 2). The following participants were excluded: nonnative speakers with language difficulties, participants with no psychological testing data or lacking enough data to be classified as MCI or non-cognitively impaired, and those with impaired daily functional abilities or dementia. Of the excluded 1,188, 551 participants selected at random were excluded for the purpose of creating a normative sample. The study was approved by the regional Ethics Committee of Lund University, and written consent from all participants was obtained.

The participant was examined by a nurse, a physician, and psychological test administrator. Participants filled out self-rated questionnaires regarding level of education, marital status, and functional ability. A cognitive assessment including tests measuring 4 cognitive domains: memory (3 tests: 16-item word-recall test, a 16-word recognition test, and a 5-object delayed recall test), speed of processing (2 tests: digit cancellation and pattern comparison task), verbal ability (2 tests: word fluency, category and letters), and visuospatial skills (2 tests: mental rotation, speed and accuracy). The test administrator assessed depression using the Comprehensive Psychiatric Rating Scale [18]. Level (good or bad) of the participant’s concentration and motivation during cognitive testing was assessed qualitatively by the test administrator. Concentration was classified as bad when the participant was easily distracted and required repetition of the test instructions. Motivation was classified as bad when the participant was fluctuating in willingness to follow through with the testing or did not care if their answers were right or wrong. Two testing orders of the test battery and 3 test versions of the word recall/recognition test and speed of processing test were distributed evenly among participants. Slight difficulty differences have been reported between selected test versions [18, 21].

Dementia was diagnosed by the examining physician in accordance with Diagnostic and Statistical Manual of Mental Disorders-IV and medical records.

An algorithmic approach was applied using the expanded original Mayo Clinic criteria [1] to define MCI cases: subjective and/or informant cognitive complaint, normal functional ability, no dementia, and objective cognitive impairment in one or more cognitive domains relative to normative data [19]. MCI cases were further divided into the subgroups single-domain amnestic MCI or multidomain amnestic, single-domain non-amnestic MCI or multidomain non-amnestic. Single MCI was defined by having at least one impaired test score in the cognitive domain, whereas multi-MCI was defined by having an impaired test score in multiple cognitive domains. Normative data were derived from a subsample of GÅS (n = 511) and from a sister study SNAC-Blekinge (n = 1,402) [22] and was created using a quantile regression method, this process has been described elsewhere [19]. Cognitive impairment was defined as having a score below the 7th percentile of test scores in the normative sample, taking age, sex, and education into account.¹

Subjective and informant cognitive complaint was confirmed either through a complaint from the participant based on the question “do you think your memory has gotten worse” or by a concern from the examining physician. Katz’ activities of daily living (ADL) index [23] was used to asses functional abilities. Participants with impaired personal ADL were excluded from the MCI sample; mild problems of instrumental ADL were permissible [1]. Bracket creepers were identified as those who changed norm age-category at follow-up (e.g., moving from 60 age group to 70). To assess severity of cognitive impairment, a lenient (1 impaired test score) and a strict (2+ impaired test scores) criterion for MCI was created.

Proportions with 95% CIs were computed for the participants who reverted back to normal cognition (NCI) and compared to those who stayed MCI. To assess the factors associated with reversion, χ² tests or t test were computed between reverters and those individuals who remained MCI at 6-year follow-up (non-reverters). Each investigative predictor was assigned to 1 of 4 sets including baseline characteristics: demographical factors, psychological status, cognitive testing session factors, and factors tied to the MCI criteria. Five multivariable logistic regression analyses were performed separately. The first 4 models included only the factors in each set when controlling for age and sex. The fifth model included the factors that were significantly associated with reversion in the first 4 models. All analyses were performed using IBM-SPSS statistics package 22.

Of the participants with data at baseline and 6-year follow-up, the average follow-up time was M years = 6.05 (SD 0.84). A total of 30.4% of the baseline sample (n = 1,188) and 20% (n = 440) of the sample with follow-up data were excluded; the excluded groups were older, contained more women and participants with lower education and lower Mini-Mental State Examination (MMSE) scores (presented in Table 1). A total of 601 participants dropped out/died prior to follow-up, and this group contained significantly more (p < 0.001) participants with MCI (28.3%) than the follow-up group (20.3%). Of those with MCI at baseline that had dropped out or died, there were more males (p < 0.01), they were older (p < 0.001), and they had lower MMSE scores (p < 0.001) in comparison to those who were NCI at baseline.

Six-year trajectory of MCI classification is presented in Table 2. Over half of the participants (58%, 95% CI 52.7–63.3) with MCI reverted back to normal at follow-up and the remaining 42% were stable MCI. Of those with stable MCI, 78/138 (56.5%, 95% CI 48.2–64.8) changed subtype and 60 remained within their subtype; 13/138 (9%, 95% CI 4.23–13.8) were reclassified from single to multidomain within the same subtype (e.g., single-domain amnestic MCI to multidomain amnestic MCI) and 16/138 (11.6%, 95% CI 6.26–16.9) vice versa (multidomain to single-domain); 20/138 (14.4%, 95% CI 8.54–20.3) changed from amnestic to non-amnestic subtype and 29/138 (21%, 95% CI 14.2–27.8) changed from non-amnestic to an amnestic subtype. Notably, those who changed from non-amnestic type to amnestic type, 18/29 (62.1%, 95% CI 44.4–79.6), added an amnestic component to their already impaired cognition. That is, they went from single non-amnestic to multi-amnestic. Of all MCI participants, 18/349 (5%) converted to dementia. As reversion rates are contingent on the operationalization of MCI, reversion rates were calculated using different MCI definitions, seen in Table 3. Reversion rates were lowered somewhat in the altered definitions; however, none of the rates were below 50%. Dementia diagnosis at follow-up was more likely for those individuals who had MCI (4.4%) at baseline than those with NCI (2.0%) at baseline; χ²(1) = 8.16, p < 0.004.

During the 6-year and 12-year follow-up visits, 17% (95% CI 9.63–24.4) of the participants never reverted from their original MCI diagnosis. Sixteen of the 67 (23.9%, 95% CI 13.7–34.1) 6-year follow-up reverters re-transitioned back to MCI at 12-year follow-up and 51 participants (76.1%, 95% CI 65.9–86.3) remained NCI. Out of the 33 participants with MCI at baseline and MCI at 12-year follow-up, 16 participants (48.5%, 95% CI 31.4–65.5) had the following trajectory MCI-NCI-MCI (unstable MCI), whereas 17 participants (51.5%, 95% CI 34.4–68.6) had MCI-MCI-MCI (stable MCI). See Figure 2 for trajectory of MCI and NCI at baseline with 2 follow-ups (6 and 12 years). Table 4 presents subtype classification at baseline and at 12-year follow-up for those with NCI at 6-year follow-up. There were 2 individuals who had MCI at baseline, NCI at 6-year follow-up, and then dementia at 12-year follow-up; these 2 individuals had single-domain non-amnestic MCI, with at least 2 impaired test scores in their respective domain (strict criterion for cognitive impairment).

When analyzed separately, 5 of 15 factors differed significantly between the reverters and the non-reverters. Lower age, higher MMSE, good concentration and motivation, and single-domain subtype at baseline were all markers for reversion to normal cognition at follow-up. There were neither more bracket creepers nor those with severe MCI in the reverter group than in the non-reverter group. No factors associated with the cognitive testing session differed between the 2 groups (Table 5).

The results of the multivariable analyses per set are presented in Table 6. All models were adjusted for age and sex. Significant baseline predictors for reversion in the set demographical factors were lower age and better global functioning. Good concentration at baseline cognitive testing was the only predictor in the set psychological status, and in the set cognitive testing session factors, no significant predictors were observed. In the last analysis, that is, when examining predictors of the MCI criteria, participants with single-domain subtype were more likely to revert than those with multidomain subtype.

The final logistic regression model containing all the significant predictors observed in the above 4 sets provided similar results as in the previous regression analyses, with lower age, better global functioning, good concentration, and single-domain subtype leading to higher odds for reversion. As the outcome reversion was an immediate consequence of MMSE results for cases with not enough cognitive data to be diagnosed, the strength of MMSE as a predictor of reversion could be overestimated. In a separate analysis, with these 15 missing cases excluded, MMSE was still a major predictor of reversion.

This population-based study examined the trajectory and stability of MCI during a 6- and 12-year follow-up period. Our main findings show high reversion rates, and for stable MCI, it was common to switch between subtypes. Our 12-year data revealed that it was common to revert to normal cognitive functioning and then re-transition to MCI. Lower age, higher MMSE scores, single-domain subtype, and good concentration while performing tests were all predictors for reversion at 6-year follow-up. This is the first Nordic European study to report factors associated to reversion.

Our 6-year reversion rate of 58% was higher than those reported in the literature. For instance, 2 meta-analyses on population-based studies when using the Mayo Clinic criteria reported similar reversion rates 31% (for amnestic MCI) [24] and 29% (all type MCI) [25], ranging across 4–58% for all the included studies. The highest reported reversion rate prior to our study, using a population-based sample from Wisconsin (USA), was 58.3% [26]. Notably, this study used a small sample (n = 24) with amnestic MCI. Our rates are among the highest reported, and this could be explained by the following: (1) our relatively long follow-up could have led to selection bias and nonrandom attrition, where the most unfit left the study before follow-up, supported by the results of our dropout analysis, where baseline MCI participants that dropped out had lower MMSE scores and were older than those who stayed on. Although, it is generally found that longer follow-up studies tend to produce lower reversion rates because the unstable MCI groups become stable or progress to dementia [6, 7, 24]. (2) We allowed a tolerant definition of cognitive impairment (1 or more impaired test scores), and previous studies show that reversion occurs more often when classification is based on the scores of a single cognitive test than when it is based on 2 or more tests [27, 28]. Notably, differences in severity of cognitive impairment (1 vs. 2+ tests) did not explain reversion in our data. (3) Our sample was drawn from a population-based study. Higher reversion rates are found in these samples rather than in clinical ones [24, 25]. (4) Many studies mix stable MCI and dementia progressors in the group that is compared to the reverters; this tends to pull reversion rates down. Affirmatively, a slight decrease in reversion rate was observed when dementia was included in the non-reverter group.

A yo-yo effect of MCI [29] was observed for our 12-year data as over half of our participants with MCI at both baseline and at 12-year follow-up reverted to normal at 6-year follow-up. Similar unstable trajectories have been described previously, with 20–46% (multiple follow-ups, lasting between 5 and 10 years) of those diagnosed with MCI reported to have reverted at least once during these studies’ course [5-7]. These results together with ours signify that MCI trajectory fluctuates, containing better and worse cognitive periods [7, 9, 29].

Consistent with previous findings, we detected changes in subtypes in the MCI stable group. Approximately half (48%) of a stable MCI group in a Korean population-based sample changed subtype, which is comparable to our 56.5% [4]. Unsurprisingly, a portion of those who switched subtype proposedly worsened their status, that is, went from single to multidomain. Remarkably, 11.6% went from multidomain to single domain, this could imply improvement of cognitive status. Also, there were a substantial number of participants that converted from non-amnestic to amnestic and vice versa. Subtypes are helpful in assessing the etiology of the observed cognitive impairment and thus predict the type of dementia [1, 30]. High rates of conversion from one cognitive domain to another challenges the advantageousness of subtypes. A supplementary analysis (data not shown) found fewer participants classified with more severe MCI (2 or more impaired tests) to switch between subtypes than those classified with a lenient form of MCI (1 impaired test), suggesting that the application of a stricter criterion to define cognitive impairment could reduce uncertainty in the subtype trajectory. Further research is required related to subtype trajectories and conversion.

Our analyses identified a limited number of predictors for reversion: lower age, better global cognitive functioning, and single-domain subtype. These factors have all previously been linked with reversion [9, 11]; this is not surprising as the opposing factors (e.g., multidomain, higher age) are frequently associated with progression to dementia from MCI [31, 32].

No previous reversion studies have examined variations in cognitive testing settings or the psychological disposition of the participant at the first assessment, so our findings are worthy contributions in this research. Lack of concentration was a significant predictor for reversion and was seemingly a proxy for permanently reduced cognition [33], rather than a marker for misclassification of MCI at first assessment. Additionally, depression did not explain reversion in our MCI sample. Depressive symptoms tend to evoke lower cognitive test scores [34], occasionally leading to a misclassification of MCI and consequently reversion (if depression symptoms reduce). As it is common for depression to coincide with MCI [35, 36] and this co-relationship has been found to predict future progression of AD [37], we propose that further research on the role of depression on reversion is necessary.

This study aimed to explore the role of variations in cognitive testing session factors on reversion, such as when during the day the test-taker is exposed to cognitive assessment and which test order or test version they received. As none of these factors were significant predictors for reversion, we conclude that they play a minor role in the risk of misclassification of MCI. For researchers, test administrators, and clinicians, this outcome is reassuring, although variations in testing settings should be kept at a minimum and standardized testing procedures followed. Last, Aerts et al. [5] suggest that moving to a higher age group with lower norms could explain reversion. Our analyses could not find evidence for this as there was not a higher number of “bracket creepers” in our reversion group in comparison to our non-reverters.

Two types of reversion factors have been explored in this study. First, factors that could lead to the misclassification of MCI at the first assessment, for example, the application of a lenient criterion or that the person was misclassified due to a temporary depression. Second, factors that are recognizably associated with better cognitive status and cognitive reserve, for example, younger age, better global cognitive status, and higher level of education. The first set of factors could be useful for clinicians and researchers at a diagnostic stage, to help prevent misclassification of MCI. The second set of factors could be viewed as protective factors for the individual, leading to a better future prognosis of cognition.

Strengths of this study include a longitudinal design with 6- and 12-year follow-up and the inclusion of multiple and reoccurring identical cognitive tests to define objective impairment. Furthermore, this investigation provides a manifestation of an unstable MCI trajectory over 12 years, which few previous studies have provided. Our study has some limitations. First, the role of nonrandom attrition. Not only does attrition pull up reversion rates but it can also cause power problems for detecting significant associations for factors tied to reversion. Second, biomarkers for reversion, such as blood pressure, cerebrovascular pathology, or genetics, were not examined in the present study. Likewise, measurements of CSF biomarkers for AD can help predict reversion [38, 39] but are not available in the GÅS study. Nevertheless, our aim was to explore sociodemographic and psychological aspects isolated. Third, it could be argued that a consensus approach would be preferred to classify MCI over an algorithmic approach to minimize risk of false classification [40]; however, this latter procedure is not always feasible in large population-based samples; also algorithms have been proven successful in accurately classifying MCI with high sensitivity and specificity [41, 42].

Besides the continual study of factors for reversions, future directions should embrace examining the characteristics of individuals with an unstable MCI trajectory (e.g., MCI-NCI-MCI or MCI-NCI-dementia), as reversion in itself has been proposed to be a risk factor for dementia [7]. By comparing stable MCI/progressors with unstable MCI, researchers may gain knowledge about the nature and speed of MCI progression to dementia. Is the unstable group progressing to dementia in disguise? Also, what are the most important features of a reverter who does not re-transition?

In conclusion, a large proportion of participants improved their cognitive status at follow-up. Hence, should MCI be considered a high- or low-risk condition for incident dementia [3]? Our results suggest, with a high reversion rate of 58% and fluctuating MCI trajectories found in our 12-year data, that MCI is not a straight path to dementia. Despite that these findings suggest that MCI as a diagnostic entity in population-based studies is questionable, it provides insight regarding what type of patients can have a positive prognosis despite their MCI diagnosis. This then can avoid concern of the patients and their relatives as well as exposure to unnecessary treatment and stigma.

A special thanks to the GÅS participants and GÅS team members for collecting the data.

The study was approved by the regional Ethics Committee of Lund University, and the research was conducted ethically in accordance with the World Medical Association Declaration of Helsinki and all participants have provided a written consent.

The authors have no conflicts of interest to declare.

Study funded by Swedish Ministry of Health and Social Affairs, the county Region Skåne, the Medical Faculty at Lund University, and the Swedish Research Council (grant number 2013-8604).

M.O. performed analysis and interpretation of analysis and writing of manuscript. M.P. performed analysis and interpretation of analysis and critical revision of manuscript. S.E. interpretation of data and revision of manuscript.