Vivian Huang, PhD1, David B. Hogan, MD2,3, Zahinoor Ismail, MD2,3,4,7, Colleen J. Maxwell, PhD3,5, Eric E. Smith, MD2,3, Brandy L. Callahan, PhD3,4,6
1Department of Psychology, Ryerson University, Toronto, ON
2Cumming School of Medicine, University of Calgary, Calgary, AB
3Hotchkiss Brain Institute, Calgary, AB
4Mathison Centre for Mental Health Research & Education, Calgary, AB
5Schools of Pharmacy and Public Health & Health Systems, University of Waterloo, Waterloo, ON
6Department of Psychology, University of Calgary, Calgary, AB
7Department of Psychiatry, University of Calgary, Calgary, AB, Canada
DOI: https://doi.org/10.5770/cgj.23.416
ABSTRACT
Background
Studies of mild cognitive impairment (MCI) employ rigorous eligibility criteria, resulting in sampling that may not be representative of the broader clinical population.
Objective
To compare the characteristics of MCI patients in a Calgary memory clinic to those of MCI participants in published Canadian studies.
Methods
Clinic participants included 555 MCI patients from the PROspective Registry of Persons with Memory SyMPToms (PROMPT) registry in Calgary. Research participants included 4,981 individuals with MCI pooled from a systematic literature review of 112 original, English-language peer-reviewed Canadian studies. Both samples were compared on baseline sociodemographic variables, medical and psychiatric comorbidities, and cognitive performance for MCI due to Alzheimer’s disease and Parkinson’s disease.
Results
Overall, clinic patients tended to be younger, more often male, and more educated than research participants. Psychiatric disorders, traumatic brain injury, and sensory impairment were commonplace in PROMPT (up to 83% affected) but > 80% studies in the systematic review excluded these conditions. PROMPT patients also performed worse on global cognition measures than did research participants.
Conclusion
Stringent eligibility criteria in Canadian research studies excluded a considerable subset of MCI patients with comorbid medical or psychiatric conditions. This exclusion may contribute to differences in cognitive performance and outcomes compared to real-world clinical samples.
Key words: mild cognitive impairment, exclusion criteria, generalizability
The field of dementia research is focused increasingly on an early phase conceptualized as mild cognitive impairment (MCI).(1) MCI research has significantly advanced the diagnosis, prognosis, and prevention for this condition; however, translating results of this research to practice remains a challenge. Despite the value of past research, MCI participant pools meet rigorous inclusion and exclusion criteria designed to minimize potential confounders and diagnostic errors, resulting in biased case identification(2) and sampling that is not representative of the broader clinical population. Researchers in many fields(2–6) have begun to acknowledge this misalignment between individuals enrolled in research protocols and those with the condition of interest in real-world samples. The representativeness of MCI research and clinic samples has not been quantified in a Canadian context. Given that medical(7) and psychiatric disorders(8) are common in older Canadians and associated with dementia-related outcomes,(9–11) it is important to understand how excluding these cases from MCI research samples could impact findings and the ability to generalize them to clinical practice in a Canadian context. Such exclusion seems particularly relevant as a growing proportion of cases seen in Canadian memory clinics (for example, in Calgary(12)) have MCI, relative to dementia, which was more common in earlier decades.(13)
This study compared the characteristics of MCI patients in a Calgary memory clinic to those of MCI participants in published Canadian studies. We focused primarily on a clinical, rather than population-based, sample because we were interested in how the representativeness of research cohorts may impact generalizability to clinical practice. We acknowledge that clinical samples may not resemble the broader population in terms of disease severity and prognosis.(14) Given findings from other literature,(2–6) it was hypothesized that memory clinic patients would be more racially diverse, have fewer years of education, more medical and psychiatric comorbidities, and lower scores on baseline cognitive measures, relative to those enrolled in research studies.
Data were drawn from two sources: clinic participants from the PROspective Registry of Persons with Memory SyMPToms (PROMPT) registry(15) in Calgary, and research participants derived from a literature review of Canadian MCI cohorts. The PROMPT registry was selected as convenience sample due to data availability and accessibility. Variables of interest included sociodemographic data (age, sex, education, race), medical issues (cardiovascular/cerebrovascular disease, traumatic brain injury [TBI], vascular risk factors, neurological disorders, sensory impairment, neurological signs), psychiatric comorbidities (mood, anxiety, psychotic and substance abuse disorders, as well as current depressive symptoms) and cognitive performance (Mini-Mental State Examination [MMSE](16) and Montreal Cognitive Assessment [MoCA](17)).
The PROMPT registry(15) comprises patients from the University of Calgary Cognitive Neurosciences Clinic that offers consultation, assessment, and follow-up services to referred patients with suspected cognitive impairment. All referred patients are eligible for inclusion in the registry with > 90% consenting to enrolment, making it highly representative of the clientele served. In this study, we only included patients initially diagnosed with MCI per the National Institute on Aging and the Alzheimer’s Association (NIA-AA) core criteria(18) including: 1) cognitive concern; 2) impairment in ≥ 1 cognitive domain; 3) preserved function; and 4) no dementia. Suspected etiologies were determined based on published reports and criteria,(19–21) pre-existing diagnosis,(22) neuroimaging evidence,(23) and the presence of any core or suggestive features of the etiologies based on psychiatric and physical assessments. MCI was considered due to Alzheimer’s disease (MCI-AD) if memory was primarily affected with longitudinal evidence of decline and no major vascular, traumatic or other medical causes.(18) The etiology was considered due to Parkinson’s disease (MCI-PD) when there was a pre-existing diagnosis of PD, and to vascular cognitive impairment (MCI-VCI) when there was neuroimaging(23) evidence of vascular insult or history of stroke that was felt sufficient to account for the cognitive issues (this was consistent with criteria from the American Heart Association/American Stroke Association criteria).(23) Other suspected etiologies of MCI included frontotemporal lobar degeneration,(19) Lewy body disease,(20) corticobasal degeneration,(21) and progressive supranuclear palsy.(22)
Sociodemographic information and physician-diagnosed disorders were obtained from patient, informant, and medical records. The 15-item Geriatric Depression Scale (GDS-15)(24) assessed current depressive symptoms. The MMSE(16) and MoCA(17) assessed general cognition.
The systematic review was conducted in accordance with PRISMA guidelines.(25,26) Medline, PsychINFO, EMBASE, and PubMed were searched for studies published prior to July 2018 using the terms: (MCI OR “mild cognitive impairment”) AND (Canada[Affiliation/Location]). Inclusion criteria were: 1) English-language; 2) original peer-reviewed research; 3) participants exclusively recruited within Canada; 4) MCI diagnosed using formal criteria (e.g., Petersen’s(27) or NIA-AA(18)); and 5) results contained extractable MMSE and/or MoCA scores. When several studies reported on the same dataset, only the largest sample was retained to ensure sample independence. Case studies and multinational studies merging Canadian and non-Canadian data were excluded. Baseline data were used for studies with multiple time points. Four independent reviewers assessed titles, abstracts, and full texts (on selected articles) for eligibility. Two independent reviewers extracted study and sample characteristics. A third independent reviewer resolved any discrepancies.
Descriptive statistics were computed on baseline characteristics of PROMPT patients. Cases with missing data were excluded pairwise from analyses, and no attempt was made to impute data. Cohen’s kappa (κ) assessed interreviewer agreement in the systematic review. Descriptive statistics were generated from the weighted mean and standard deviation of age, education, MMSE, and MoCA scores (Appendix A).
To compare clinic and research samples, chi-square tests with Yates correction and independent samples t-tests using weighted means were conducted. Given the most studied suspected etiologies of MCI in the literature were AD or PD (see Results), only these cases were retained from PROMPT and used in comparative analyses. All tests were two-tailed, α = 0.05, and 95% confidence intervals were used to determine statistical significance of differences found between samples. The University of Calgary’s Conjoint Health Research Ethics Board approved the study (REB18-1007).
A total of 555 PROMPT patients were diagnosed with MCI (mean age = 65.2, SD = 10.2; mean education = 13.49, SD = 3.41; 56.2% male). As demonstrated in Table 1, there was substantial heterogeneity in the suspected etiologies for MCI found among PROMPT patients. Physical and psychiatric comorbidities, sensory impairment, and traumatic brain injury were common, and 83% of the overall sample had at least 1 of these conditions.
TABLE 1 Sociodemographic and health characteristics of MCI cases in the PROMPT registry by etiology
The literature search resulted in 1,122 potentially relevant articles. After removing duplicates, applying inclusion criteria, and ensuring independence of samples, a total of 112 studies were retained with a total of 4,981 participants (Figure 1). Cohen’s κ coefficients were 0.76 (95% CI [0.71, 0.80]) for the title and abstract review stage, and 0.71 (95% CI [0.62, 0.80]) for the full-text review stage, indicating moderate reviewer agreement.
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FIGURE 1 Search strategy for the systematic review |
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All study characteristics are reported in Appendix B. The retained research studies included 102 observational studies, 6 randomized controlled trials (RCT), 2 non-randomized feasibility studies, 1 randomized feasibility study, and 1 retrospective chart review. Fourteen studies(28–41) (12.5%) did not mention any inclusion/exclusion criteria and five(42–46) (4.5%) had criteria that were not specific to medical or psychiatric conditions. The remaining 93 (83.9%) explicitly excluded select medical, psychiatric, or neurological conditions. Depression and alcohol/substance use concerns were the most frequent exclusionary conditions in 17.0% and 38.4% of published studies, respectively; an additional 25.0% of studies did not specify the psychiatric conditions that were exclusionary. All but one study(44) focused on MCI-AD (N = 4,881) or MCI-PD (N = 100), thus comparisons with PROMPT patients only refer to these MCI subtypes. One study(44) (N = 20) included MCI-VCI, but no comparison analyses were conducted due to the small sample size.
MCI-AD was diagnosed in 148 PROMPT cases (26.7%), while MCI-PD was diagnosed in 12 (2.2%). Missing data in these cases ranged from 0.7–35.8% for MCI-AD cases (data were primarily missing for current [35.8%] or past [33.8%] history of alcohol abuse, and GDS-15 score [24.8%]), and 18.2–54.5% for MCI-PD cases (mostly missing for current [54.5%] or past [54.5%] history of alcohol abuse, education [27.3%], and GDS-15, MMSE, and MoCA scores [each 18.2%]). Data were missing at random (Little’s missing completely at random test: χ2(151) = 169.98, p =.14; χ2(31) = 24.02, p = .81 for MCI-AD and MCI-PD, respectively).
MCI-AD clinic patients were younger, more often male, and more educated than research participants (Table 2). Dyslipidemia and other medical conditions (e.g., cancer, osteoporosis) were more common among clinic than research participants, except for hypertension which was more prevalent among research participants. TBI, psychiatric disorders, and sensory impairment were either not reported or explicitly excluded from all research studies. At least one of these conditions was present in 66.2% of MCI-AD clinic patients. The samples also differed on MMSE and MoCA scores, with clinic patients performing worse on both tests. Further, Cohen’s effect size values (d/h ranges from 0.22 to 1.27) suggested a small to large practical significance for the aforementioned differences found between clinic patients and research participants.
TABLE 2 Sample and health characteristics of MCI-AD participants
MCI-PD clinic patients were more educated than research participants, but not different on age or sex (Table 3). TBI, psychiatric disorders, and sensory impairment were again absent from all research studies, and at least one of these conditions was present in 83.3% of MCI-PD clinic patients. Clinic patients also had marginally lower MoCA scores but similar MMSE scores. Further, Cohen’s effect size values (d/h ranges from 0.53 to 1.77) suggested a moderate to large practical significance for the aforementioned differences found between clinic patients and research participants.
TABLE 3 Sample and health characteristics of MCI-PD participants
Results from this study indicate that Canadian research participants are not fully representative of MCI patients seen at a local memory clinic, with significant sociodemographic and clinical differences between samples that co-occur with differences in cognitive performance.
Contrary to a priori hypotheses and past findings,(2,4,5) clinic patients were more educated than research participants. It is possible that Quebecois participants, who comprised the majority of published samples, obtained lower total years of schooling despite comparable educational level attained due to province-specific differences(47) (e.g., high school is complete after 11 years in Quebec but 12–13 years elsewhere in Canada). These findings may also be attributed to higher average educational attainment in Calgary as a major site of migration due to job prospects in certain industries (e.g., oil and gas and health care) compared to other major Canadian cities,(48,49) or may reflect cohort differences and secular trends towards higher education in younger generations. Moreover, research studies with a cognitive assessment component may need to make a concerted effort to include individuals with diverse educational backgrounds to avoid ceiling effects as the general population becomes more educated. Regarding sex, there were more men among clinic patients than among research participants. This result is consistent with unbalanced sex distributions in research studies, in which females are typically overrepresented.(50) The potential sex (and, perhaps, gender) differences related to MCI are not fully known. Given mixed results with respect to sex differences in the prevalence and prognosis of MCI,(51–55) future research should aim to systematically examine possible vulnerabilities in older men and women.
In both samples, most individuals were Caucasian. Racial and ethnic minority status has previously been shown to be associated with lower health-care literacy,(56) health-care access and utilization,(57) and research participation.(58) The eligibility criteria of language fluency may further limit the number of ethnic minority participants in MCI research studies. Calgary is relatively homogenous, with visible minorities accounting for 33.7% of the population(59) (comparatively, Toronto’s population has 51.1% visible minorities(60)). Thus, both samples in this study were less ethnically diverse than anticipated.
Our central finding is that MCI participants with psychiatric, medical, and neurological conditions were regularly excluded from Canadian MCI research studies, despite these conditions being clinically prevalent. Psychiatric disorders, TBI, and sensory impairment were particularly commonplace in PROMPT (83% MCI-PD patients had ≥1), but these conditions were systematic exclusion criteria from > 80% studies in the systematic review. Psychiatric disorders are prevalent among older adults(61–65) and can impact dementia risk and related outcomes.(66–70) The presence of neuropsychiatric symptoms in MCI doubles progression rate to dementia.(71) Cross-sectionally, it is difficult to know whether psychiatric symptoms are a risk factor or a prodrome of dementia.(72) However, large prospective cohorts have demonstrated a linkage between age of onset of psychiatric symptomatology and incident dementia,(73–75) and mild behavioural impairment (MBI, i.e., later life onset of sustained neuropsychiatric symptoms of any severity(76–79)) is an at-risk state for incident cognitive decline and dementia.(80–83) Thus, excluding MCI research participants based on scores above cut-off on a cross-sectional neuropsychiatric measure may inadvertently exclude those with prodromal disease, diluting the sample. The data on MBI can inform the approach to psychiatric conditions in MCI, and including those with MBI may, in fact, enrich the MCI sample for prodromal dementia.
Sensory impairment is common in late life(84–88) and is associated with increased risk of MCI(89) and dementia,(90–93) especially multisensory impairment.(94) Sensory impairment may even serve as a potential biomarker for pathological cognitive aging.(95) Similarly, TBI is another identified risk factor for MCI(96–98) and dementia,(99,100) and is associated with neurodegenerative protein pathology.(101,102) The presence of chronic, systemic health conditions can also exacerbate cognitive decline.(103–107) Given that chronic health conditions and sensory impairments are highly prevalent among Canadian seniors(7,84,85,108) and older adults are at high risk of sustaining a TBI,(109,110) the exclusion of these comorbidities may further undermine the representativeness of MCI samples and research findings. Predictably, these comorbidities were accompanied by between-sample discrepancies in cognitive performance in this study—clinic patients performed approximately two points lower on MMSE and MoCA testing compared to research participants. The magnitude of study effects is likely to be over- or underestimated in MCI research participants who are overall healthier with less cognitive impairment relative to current real-world patient populations. It is additionally possible that healthier, less cognitive impaired individuals self-select into research protocols, further reducing generalizability. Canadian practitioners seeking to implement evidence-based care should carefully consider the characteristics of relevant research samples before applying results derived from them in their practice.
The search terms used in the systematic review were selected to best match the criteria used to diagnose patients in PROMPT. As such, some important Canadian studies of cognitive impairment, no dementia (CIND) or vascular cognitive impairment (VCI)(111) were not captured, such as the Canadian Study of Health and Aging (CSHA),(112) the Canadian Collaborative Cohort of Related Dementias (ACCORD),(113) and the Consortium to Investigate Vascular Impairment of Cognition (CIVIC).(111) The concepts underlying CIND are considerably different from Petersen’s(27) and NIA-AA’s(18) conceptualization of MCI, as CIND encompasses non-neurodegenerative and not necessarily progressive causes of cognitive impairment(114) (including psychiatric, neurodevelopmental and toxic).(113) Nonetheless, these studies offer similar insights to the present work. ACCORD(113) and CIVIC(111) were carried out in Canadian dementia clinics and, like PROMPT, participants frequently had medical and psychiatric comorbidities. CSHA(112) also documented depression (8.0%), psychiatric conditions (6.6%), and substance abuse (8.3%) as common contributors to cognitive decline. Average MMSE scores in ACCORD(113) were similar to those in PROMPT (M = 26.9, SD = 3.0), while those in CIVIC(111) were lower (M = 21.9, SD = 6.2). The differences in the MMSE scores between PROMPT and CIVIC patients may be attributable to the fact that they were a decade older, on average, than PROMPT patients and may have had more severe neurological damage (e.g., stroke).
Our results highlight the diverse presumed neuropathological etiologies of MCI in clinical practice, which is not reflected in the Canadian research literature. The vast majority (95%) of identified published studies focused on MCI due to AD, conceptualized as cognitive impairment primarily affecting memory not better accounted for by other neurologic insults. In the PROMPT sample, however, only about a quarter of patients were thought to have pure AD as the cause for MCI. Many more cases were presumed to have a vascular etiological basis in whole or in part, as well as a large number of other conditions. These results, together with the broader findings of multiple comorbidities in our clinical sample, support our initial hypothesis that memory clinic patients are considerably more diverse in many respects than those included in research studies.
This study represents an important first step in evaluating the real-word representativeness of participants with MCI in Canadian research protocols, and demonstrates key differences between characteristics of memory clinic patients and research samples. Our clinical MCI cohort was fairly large and diverse, and considered generally representative of the MCI clientele served in Calgary. However, it represented a convenience sample that is likely to differ from other Canadian MCI cohorts, and findings may not be generalizable to clinics in other parts of Canada and elsewhere. Our findings may also not be generalizable to population-based samples of person with MCI. Other limitations include the fact that we only examined cognitive performance on the MMSE and MoCA tests; a more comprehensive neuropsychological battery could provide more information about relevant differences between clinic and research samples. Nevertheless, findings highlight the importance of interpreting MMSE and MoCA scores together with patients’ medical and psychiatric history. While we attempted to ensure sample independence in the systematic review, certain participants may have ended up in multiple studies, which could have inflated between-group differences. Moreover, multiple comparison tests may have inflated Type I error rates. Therefore, results should be interpreted with caution; however, substantial effect sizes were found for the aforementioned comparison tests, suggesting practical significance. The accuracy of the etiological diagnoses assigned to the MCI cases in PROMPT cannot be guaranteed, nor can those of patients included in the studies within the systematic review. In PROMPT, routine clinical protocols for determination of presumed etiology did not include AD biomarker testing, which is currently recommended in Canada for research only,(115) or neuropathological confirmation. The prevalence of mixed or multiple etiologies was also likely underestimated. Further, we did not examine differences between sub-types of MCI-AD (amnestic vs. non-amnestic). Given that MCI-PD patients are often seen at movement disorders clinics, patients with this form of MCI were likely underrepresented in the current study. We were unable to examine the MCI-VCI subpopulation, considering this group was underrepresented in the MCI research studies identified in the literature, despite vascular disease being a common contributor to cognitive impairment. Lastly, findings may not be generalizable to non-Caucasian groups.
Despite these limitations, given its relatively large and diverse clinic sample, the current study serves as an important initial step in demonstrating key demographic and clinical differences among MCI memory clinic patients and research participants in Canada.
The authors recognize financial support from the University of Waterloo (Research Chair to CJM), and the Canada Research Chairs Program (Tier II CRC to BLC).
The authors declare that no conflicts of interest exist.
Weighted mean and pooled standard deviation calculation
The weighted mean is a form of average. However, instead of each data point contributing equally to the final average (i.e., an arithmetic mean), some data points contribute more to the final average than others. The weighted mean is calculated by multiplying each data point by the weight, and then dividing it by the sum of all the weights. The weighted mean in the current systematic review was calculated by multiplying the mean scores in each study (i.e., age, years of education, and the MMSE and MoCA scores) by each study’s sample size (i.e., the weight). This was then divided by the sum of the sample sizes in all studies. See the weighted mean formula below:
x = mean; w = sample size
The pooled standard deviation is the weighted average of standard deviations. The pooled standard deviation was calculated by: 1) subtracting 1 from each sample size; 2) then multiply the value by the sample variance (i.e., squaring the standard deviation) and sum the multiplied value for all studies; 3) dividing the results from the first two steps by the overall sample size minus the total number of studies; and 4) taking the square root of the weighted variance terms. See the pooled standard deviation formula below:
For studies that reported median, range, or interquartile range, the mean and standard deviations were estimated via an online calculator (http://www.comp.hkbu.edu.hk/~xwan/median2mean.html). Specifically, if the range of a score was provided in an article, the standard deviation of the sample was estimated using methods proposed by Hozo et al.1 If the article presented only median and interquartile range, the mean of the sample was estimated using methods proposed by Luo and colleagues,2 and the standard deviation was estimated using methods proposed by Wan and colleagues.3
1 Hozo SP, Djulbegovic B, Hozo I. Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol. 2005;5(1); Article number 13. Available from: https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/1471-2288-5-13
2 Luo D, Wan X, Liu J, et al. Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range. Stat Methods Med Res. 2018;27(6):1785–805. Available from: https://journals.sagepub.com/doi/abs/10.1177/0962280216669183
3 Wan X, Wang W, Liu J, et al. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014;14(1); Article number 135. Available from: https://link.springer.com/article/10.1186/1471-2288-14-135.
Articles retained in the systematic review
* Articll diagnostic criteria used in articles included in the systematic review.
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Canadian Geriatrics Journal, Vol. 23, No. 4, December 2020