Abstract
Objective:
The Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects evaluates familial frontotemporal lobar degeneration (FTLD) kindreds with MAPT, GRN, or C9orf72 mutations. Objectives were to examine whether health-related quality of life (HRQoL) correlates with clinical symptoms and caregiver burden, and whether self-rated and informant-rated HRQoL would correlate with each other.
Methods:
Individuals were classified using the Clinical Dementia Rating CDR® Scale plus National Alzheimer’s Coordinating Center (NACC) FTLD. HRQoL was measured with DEMQOL and DEMQOL-proxy; caregiver burden with the Zarit Burden Interview (ZBI). For analysis, Pearson correlations and weighted kappa statistics were calculated.
Results:
The cohort of 312 individuals included symptomatic and asymptomatic individuals. CDR® plus NACC FTLD was negatively correlated with DEMQOL (r=−0.20, p=.001), as were ZBI and DEMQOL (r=−0.22, p=0.0009). There was fair agreement between subject and informant DEMQOL (κ=0.36, p<.0001).
Conclusion:
Lower HRQoL was associated with higher cognitive/behavior impairment and higher caregiver burden. These findings demonstrate the negative impact of FTLD on individuals and caregivers.
Keywords: frontotemporal dementia, quality of life, MAPT, GRN, C9orf72, tau, TDP-43
Background
There has been growing interest in understanding quality of life effects from chronic illnesses such as Alzheimer’s disease (AD) and other neurodegenerative disorders. The World Health Organization defines quality of life as “an individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns” [1]. Quality of life (QOL) is a multi-dimensional construct which includes several domains related to emotional, physical and social well-being. The term health-related quality of life (HRQoL) has been used more recently to focus specifically on the effects health, disease states, and medical treatments on quality of life [2]. The cognitive, physical and emotional changes associated with dementia have been associated with lower QOL and increased caregiver burden [3, 4].
There are a number of studies examining the natural history of HRQoL in the context of neurocognitive disorders, although there are conflicting results on the impact of depression, cognitive status and social/demographic variables on quality of life [5]. Even less is known regarding QOL in sporadic or familial frontotemporal lobar degeneration spectrum disorders (hereafter abbreviated FTLD). Although FTLD is less common than AD, there is tremendous morbidity and emotional distress associated with this disorder. Behavior variant frontotemporal dementia (bvFTD) affects an estimated 50,000–60,000 Americans and represents an estimated 10%−20% of all dementia cases [6]. FTLD tends to present at an earlier age than AD, and is recognized as one of the most common causes of young onset dementia [7]. FTLD is more often associated with alterations in mood, personality, and behavior. Because FTLD individuals are more likely to develop features earlier in life compared to AD, individuals and caregivers may experience particular challenges in adjusting to changes in life roles, including work and family responsibilities. Younger age has been associated with decreased QOL measures in dementia [8]. Some studies have suggested that caregivers in FTLD have lower HRQoL and higher levels of distress than with AD [9, 10]. In a more recent study comparing caregivers for those with FTLD and AD, the caregivers of those with FTD had a higher HRQoL than AD caregivers, and maintained a higher HRQoL over two years [11]. The trajectory of HRQoL over the course of FTLD is not well understood and requires further research to understand determinants of HRQoL that have the potential to guide appropriate psychosocial interventions for individuals and caregivers [12]. Depression, care burden and unmet care needs in FTLD are associated with lower ratings of QOL in some studies [11, 13, 14]. However, another study showed no association with unmet care and overall ratings of HRQoL in Young Onset Dementia [13]. There has been no clear association found between declining cognitive function and QOL in dementia [5, 15]. One study found that amongst the oldest old, there were high QOL measures in individuals with and without cognitive impairment and that QOL was more strongly associated with depressive symptoms than severity of dementia [16].
HRQoL can be difficult to assess in individuals with cognitive impairment and particularly in those with more advanced disease. Informant or proxy reports of HRQoL are often used in evaluating individuals with dementia to gather a fuller picture of HRQoL. Proxy reports of HRQoL have been shown to be a reliable measure with moderate to high levels of agreement with individual based measures [17–19]. However, there have been concerns about bias in proxy measures of HRQoL in dementia and it is important that proxy measures not be used as a substitute for self-assessments of HRQoL [20–23].
In this study the first objective was to examine the correlation between subject HRQoL and clinical symptoms in familial FTLD and caregiver burden. The second objective was to determine whether self-rated HRQoL and informant-rated HRQoL would correlate with each other. We hypothesized that HRQoL for subjects would correlate with clinical symptoms in FTLD and caregiver burden, and also hypothesized that the subject and informant HRQoL ratings of the subject would correlate with each other.
Methods
This study was completed as part of a larger longitudinal study, the Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS), which included 8 study sites [24]. This study has been approved by the Institutional Review Board (IRB) of each participating site. Written informed consent was obtained from individuals and/or legally authorized representatives. All individuals underwent a detailed interview, comprehensive neurologic examination and neuropsychological assessment. Data were collected between February 2015 and May 2018.
Inclusion/exclusion criteria
The detailed protocol, inclusion/exclusion criteria and methods for recruitment are described elsewhere [24]. Individuals were eligible for inclusion if they were members of families with a known mutation in one of the three major FTLD-related genes (microtubule associated protein tau (MAPT), progranulin (GRN), or chromosome 9 open reading frame 72 (C9orf72), age 18 or older, and willing to participate and complete required visits and testing (MRI and neuropsychological testing). Each subject is required to have a reliable informant with whom they have personal contact at least weekly. The informant can be a spouse, partner, sibling, parent, child, friend, or relative. Exclusion criteria included presence of a structural brain lesion (e.g., tumor, cortical infarct), presence of another neurologic disorder which could impact findings (e.g., multiple sclerosis), unwillingness to return for follow-up yearly, unwillingness to undergo neuropsychological testing and MR imaging, and no reliable informant.
Clinical dementia rating
Individuals were assessed for the presence or absence of symptoms and symptom severity using the 8-item Clinical Dementia Rating (CDR) plus National Alzheimer’s Coordinating Center (NACC) Frontotemporal Lobar Degeneration (FTLD) CDR® plus NACC FTLD scale [25], which is a modification of the standard CDR scale [26]. The CDR combines structured information gathered from both the patient and a knowledgeable informant. It has been used widely in a variety of clinical and research settings including clinical trials in Alzheimer’s disease (AD) treatments [27]. The Behavior/Comportment and Language domains were added to the original CDR to address the variable clinical presentations typical of familial FTLD [25]. Individuals were classified based on CDR® plus NACC FTLD as asymptomatic (CDR® plus NACC FTLD=0), questionable/mild cognitive or behavioral changes (CDR® plus NACC FTLD=0.5), mild dementia (CDR® plus NACC FTLD=1.0), and moderate to severe (CDR® plus NACC FTLD>1) dementia.
Outcome Measures
Quality of life
Subject HRQoL was measured in two ways, first by self-report using the DEMQOL, and second as rated by their informant using the DEMQOL-proxy [18]. The 28-item DEMQOL and 31-item DEMQOL-proxy are dementia specific measures of QOL, designed with rigorous psychometric properties and validated to assess QOL in persons with dementia. The DEMQOL is appropriate for self-report in individuals with mild to moderate dementia [18], while the DEMQOL-proxy is more useful for severe dementia [28]. The DEMQOL measures five domains of QOL (daily activities and self-care, health and well-being, cognitive functioning, social relationships and self-concept) and rates overall QOL as very good, good, fair and poor. Cronbach’s alpha for the self-report was (0.94) for the 28-item overall score and also acceptable for the four preliminary subscales (daily activities 0.84, memory 0.89, negative emotion 0.84 and positive emotion 0.85) [29]. Cronbach’s alpha for the 31-item proxy scale was (0.90) for the overall score and similar for both subscales (functioning 0.90 and emotion 0.85). The DEMQOL and DEMQOL-proxy have been validated in different clinical settings as well as cultures [18, 30–33].
Caregiver burden
Informants completed the Zarit Burden Interview (ZBI) for caregiver burden [34]. This measure includes 22 items related to feelings about caregiving, negative effects of caregiving and perceived stress. For each item, a response of 0 (Never), 1 (Rarely), 2 (Sometimes), 3 (Quite frequently), or 4 (Nearly always) is given. The ZBI categorizes scoring as 0–21 little or no burden, 21–40 mild to moderate burden, 41–60 moderate to severe burden, and 61–88 severe burden. The ZBI has been validated in individuals with dementia and their caregivers in a variety of clinical situations and cultures. [35, 36] The DEMQOL and ZBI data were analyzed from the baseline visit only.
Participant demographics
Of the 345 individuals initially enrolled, 17 were excluded based on diagnosis and 16 were excluded due to discrepant information between clinical diagnosis and CDR score, leaving a final sample of 312 individuals. This cohort of 312 individuals included symptomatic mutation carriers, asymptomatic mutation carriers, and non-carrier family controls. The demographic information is summarized in Table 1. Participants had a mean age of 48.5 years (range 18–80), with a mean of 15.5 years of education, and were predominantly white (297, 95%) and not Hispanic or Latino (305, 98.1%). There were slightly more females (169, 54.3 %) than males (142, 45.7%). The most common informant was a spouse (137, 52.3%).
Table 1.
Baseline demographic and clinical characteristics by mutation status
| Carrier (N=149) | Not a carrier (N=105) | Not tested (N=58) | Total (N=312) | |
|---|---|---|---|---|
| Age at visit | 49.15 (14.25) | 48.90 (13.47) | 46.35 (15.58) | 48.54 (14.25) |
| Sex | ||||
| Male | 71 (48.0%) | 48 (45.7%) | 23 (39.7%) | 142 (45.7%) |
| Female | 77 (52.0%) | 57 (54.3%) | 35 (60.3%) | 169 (54.3%) |
| Education (yrs) | 15.77 (2.51) | 15.29 (2.50) | 15.40 (2.27) | 15.54 (2.47) |
| Race | ||||
| White | 140 (94.6%) | 101 (96.2%) | 56 (96.6%) | 297 (95.5%) |
| Black or African American | 0 (0.0%) | 0 (0.0%) | 1 (1.7%) | 1 (0.3%) |
| American Indian or Alaska | 0 (0.0%) | 1 (1.0%) | 0 (0.0%) | 1 (0.3%) |
| Native | ||||
| Asian | 7 (4.7%) | 1 (1.0%) | 1 (1.7%) | 9 (2.9%) |
| Other (Specify) | 1 (0.7%) | 0 (0.0%) | 0 (0.0%) | 1 (0.3%) |
| Unknown | 0 (0.0%) | 2 (1.9%) | 0 (0.0%) | 2 (0.6%) |
| Ethnicity | ||||
| Not Hispanic or Latino | 143 (96.6%) | 104 (99.0%) | 58 (100.0%) | 305 (98.1%) |
| Hispanic or Latino | 3 (2.0%) | 0 (0.0%) | 0 (0.0%) | 3 (1.0%) |
| Unknown | 2 (1.4%) | 1 (1.0%) | 0 (0.0%) | 3 (1.0%) |
| Informant relationship | ||||
| Wife | 43 (34.1%) | 16 (18.2%) | 7 (14.6%) | 66 (25.2%) |
| Husband | 33 (26.2%) | 22 (25.0%) | 16 (33.3%) | 71 (27.1%) |
| Other relative | 22 (17.5%) | 27 (30.7%) | 15 (31.3%) | 64 (24.4%) |
| Other | 11 (8.7%) | 5 (5.7%) | 4 (8.3%) | 20 (7.6%) |
| Friend/companion | 9 (7.1%) | 9 (10.2%) | 5 (10.4%) | 23 (8.8%) |
| Daughter | 4 (3.2%) | 6 (6.8%) | 1 (2.1%) | 11 (4.2%) |
| Son | 4 (3.2%) | 3 (3.4%) | 0 (0.0%) | 7 (2.7%) |
| Primary clinical phenotype | ||||
| Clinically Normal | 90 (60.4%) | 97 (92.4%) | 49 (84.5%) | 236 (75.6%) |
| bvFTD +/− ALS | 38 (25.5%) | 1 (1.0%) | 6 (10.3%) | 45 (14.4%) |
| MCI | 15 (10.1%) | 7 (6.7%) | 3 (5.2%) | 25 (8.0%) |
| Primary Progressive | 4 (2.7%) | 0 (0.0%) | 0 (0.0%) | 4 (1.3%) |
| Aphasia | ||||
| Corticobasal Syndrome | 2 (1.3%) | 0 (0.0%) | 0 (0.0%) | 2 (0.6%) |
| QoL, self-rated* | ||||
| Poor | 2 (1.7%) | 1 (1.1%) | 1 (2.0%) | 4 (1.6%) |
| Fair | 10 (8.5%) | 11 (12.5%) | 3 (5.9%) | 24 (9.3%) |
| Good | 48 (40.7%) | 26 (29.5%) | 22 (43.1%) | 96 (37.4%) |
| Very good | 58 (49.2%) | 50 (56.8%) | 25 (49.0%) | 133 (51.8%) |
| QoL, informant-rated** | ||||
| Poor | 3 (2.4%) | 1 (1.1%) | 2 (4.5%) | 6 (2.3%) |
| Fair | 13 (10.4%) | 5 (5.3%) | 1 (2.3%) | 19 (7.2%) |
| Good | 44 (35.2%) | 32 (33.7%) | 17 (38.6%) | 93 (35.2%) |
| Very good | 65 (52.0%) | 57 (60.0%) | 24 (54.5%) | 146 (55.3%) |
| CDR® plus NACC FTLD | ||||
| 0 | 90 (60.4%) | 97 (92.4%) | 49 (84.5%) | 236 (75.6%) |
| 0.5 | 20 (13.4%) | 7 (6.7%) | 4 (6.9%) | 31 (9.9%) |
| 1 | 12 (8.1%) | 0 (0.0%) | 4 (6.9%) | 16 (5.1%) |
| 2 | 19 (12.8%) | 1 (1.0%) | 1 (1.7%) | 21 (6.7%) |
| 3 | 8 (5.4%) | 0 (0.0%) | 0 (0.0%) | 8 (2.6%) |
| ZBI*** | 14.74 (16.03) | 5.38 (8.44) | 9.40 (13.69) | 10.47 (13.97) |
Values presented are N (%) for categorical variables and mean (standard deviation) for continuous variables. Data presented above are based on non-missing values for each variable only.
DEMQOL.
DEMQOL-proxy.
Zarit Burden Interview.
Data Analysis
Our study includes data from 312 individuals from the LEFFTDS cohort. The first step in the data analysis consisted of summarizing key variables by CDR® plus NACC FTLD score. Then, to investigate the association of QOL, both subject- and informant-reported, with CDR® plus NACC FTLD and ZBI, Pearson correlation coefficients were used. Weighted kappa statistics using linear weighting with corresponding 95% confidence intervals were used to assess agreement between the subject and informant HRQoL ratings of the subject. The weighted kappa statistic was computed amongst everyone in the data as well as in CDR® plus NACC FTLD subgroups (0 vs. ≥ 0.5) to assess whether or not agreement is different between symptomatic and asymptomatic individuals and in subgroups based on whether or not the informant was a spouse to assess whether or not agreement varies by relationship. Data analysis was completed using SAS version 9.4 (SAS Institute, Cary, NC).
Results
Participant clinical characteristics
The clinical characteristics of participants are summarized in Table 1. The majority of primary clinical phenotypes are clinically normal (75.6%), bvFTD ± by bvFTD ± amyotrophic lateral sclerosis (ALS; 14.4%), mild cognitive impairment (MCI; 8.0%), Primary Progressive Aphasia (1.3%), and Corticobasal Syndrome (0.6%). Participants with higher CDR® plus NACC FTLD scores were significantly older than those who were asymptomatic. (p<0.0001)
QOL and caregiver burden
Table 2 shows age, HRQoL ratings, and Zarit caregiver burden scores for all 312 participants broken down by CDR® plus NACC FTLD. Two hundred thirty six (75.6%) subjects were asymptomatic (CDR® plus NACC FTLD=0), 31 (9.9%) were questionably/minimally symptomatic (CDR® plus NACC FTLD=0.5), and 45 (14.4%) were definitely symptomatic (CDR® plus NACC FTLD≥1). Of those who were definitely symptomatic who were further categorized by symptom severity, 16 (5.1%) had mild (CDR® plus NACC FTLD=1), 21 (6.7%) moderate (CDR® plus NACC FTLD=2), and 8 (2.6%) severe (CDR® plus NACC FTLD=3) symptoms. There were 257 individuals who completed the self-report DEMQOL, 264 caregivers who completed the DEMQOL-proxy, and 262 caregivers who completed the ZBI. Majority of the scores on both the DEMQOL (89%) and DEMQOL-proxy (91%) ranged from good to very good QOL, and a smaller percentage showed fair to poor QOL. The ZBI scores were low (mean score=10.5) when all informants were grouped together, indicating little or no caregiver burden. However, ZBI scores were higher among informants of individuals with mild and moderate symptoms (CDR® plus NACC FTLD=1 and 2), indicating mild to moderate caregiver burden (mean ZBI scores 32.6 and 35.3, respectively). Informants of individuals who were severely symptomatic (CDR® plus NACC FTLD=3) showed low caregiver burden (mean ZBI score11.8). The F-test for age indicates that at least one CDR® plus NACC FTLD group is different in terms of age than the other groups. Asymptomatic individuals in the group with CDR® plus NACC FTLD=0 are younger than the other groups, which is not surprising.
Table 2.
Age, QOL Ratings, and ZBI by CDR® plus NACC FTLD
| CDR® plus NACC FTLD |
||||||
|---|---|---|---|---|---|---|
| All | 0 | 0.5 | 1 | 2 | 3 | |
| (n=312) | (n=236) | (n=31) | (n=16) | (n=21) | (n=8) | |
| Age at Visit* | 48.5 (14.2) | 45.6 (14.1) | 55.8 (10.1) | 58.7 (9.0) | 59.1(12.5) | 59.0 (10.4) |
| QOL, self-reported** | ||||||
| Very good | 133 (51.8%) | 117 (58.2%) | 9 (32.1%) | 5 (38.5%) | 1 (7.7%) | 1 (50.0%) |
| Good | 96 (37.4%) | 68 (33.8%) | 12 (42.9%) | 5 (38.5%) | 11 (84.6%) | 0 (0.0%) |
| Fair | 24 (9.3%) | 13 (6.5%) | 6 (21.4%) | 3 (23.1%) | 2 (16.7 %) 1 (7.7%) | 1 (50.0%) |
| Poor | 4 (1.6%) | 3 (1.5%) | 1 (3.6%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) |
| QOL, informant-rated*** | ||||||
| Very good | 146 (55.3%) | 126 (62.7%) | 9 (34.6%) | 4 (28.6%) | 6 (30.0%) | 1 (33.3%) |
| Good | 93 (35.2%) | 68 (33.8%) | 9 (34.6%) | 8 (57.1%) | 7 (35.0%) | 1 (33.3%) |
| Fair | 19 (7.2%) | 5 (2.5%) | 7 (26.9%) | 1 (7.1 %) | 6 (30.0 %) | 0 (0.0%) |
| Poor | 6 (2.3%) | 2 (1.0%) | 1 (3.8%) | 1 (7.1%) | 1 (5.0%) | 1 (33.3%) |
| ZBI**** | 10.5 (14.0) | 5.9 (8.6) | 15.5 (16.2) | 32.6 (16.2) | 35.3 (12.8) | 11.8 (10.2) |
The ANOVA F-test p-value for comparing Age at Visit across CDR® plus NACC FTLD is <.0001.
DEMQOL.
DEMQOL-proxy.
Zarit Burden Interview
Values presented are N (%) for categorical variables and mean (standard deviation) for continuous variables Data presented above are based on non-missing values for each variable only.
Correlations of HRQoL with CDR and ZBI
Utilizing a Pearson correlation (Table 3), CDR® plus NACC FTLD was negatively correlated with HRQoL, both self-reported (r=−0.20, n=257, p=0.001) and informant-rated (r=-0.32, n=264, p<0.0001). ZBI score was negatively correlated with both self-report (r=−0.22, n=229, p=0.0009) and informant DEMQOL (r=−0.36, n=253, p<0.0001).
Table 3.
Pearson Correlations with P-Values
| CDR® plus NACC FTLD | ZBI | |
|---|---|---|
| QOL, self-reported* | −0.20 (.001) | −0.22 (.0009) |
| QOL, informant-rated** | −0.32 (<.0001) | −0.36 (<.0001) |
DEMQOL.
DEMQOL-proxy.
Data presented above are based on non-missing values for each variable only.
Subject and Informant HRQoL rating agreement
Using weighted kappa statistics to measure agreement between the subject and informant ratings of subject HRQoL (Table 4), there was fair agreement (κ=0.36, n=232, p<0.0001 between subject and informant QOL ratings, regardless of CDR® plus NACC FTLD (0 κ=0.30, n=180, p<0.0001, ≥0.5 κ=0.40, n=52, p<0.0001), and regardless of whether informants are spouses (κ=0.47, n=112, p<0.0001) or not (κ=0.26, n=97, p=0.0007).
Table 4.
Weighted Kappa for Subject and Informant QOL Rating Agreement
| Weighted Kappa (95% CI) | P-Value | |
|---|---|---|
| Everyone | 0.36 (0.25, 0.46) | <.0001 |
| CDR® plus NACC FTLD=0 | 0.30 (0.16, 0.43) | <.0001 |
| CDR® plus NACC FTLD≥0.5 | 0.40 (0.20, 0.59) | <.0001 |
| Spouse as Informant | 0.47 (0.32, 0.62) | <.0001 |
| Non-Spouse as Informant | 0.26 (0.11, 0.40) | .0007 |
Data presented above are based on non-missing values only.
Discussion
In this study cohort of FTLD kindreds that include symptomatic mutation carriers, asymptomatic mutation carriers, and non-carrier family controls, the main finding is that HRQoL was negatively correlated with clinical status and caregiver burden.
In general the individuals reported high levels of HRQoL with the majority of participants and informants rating HRQoL as either good or very good, even amongst those with dementia (i.e., higher CDR® plus NACC FTLD scores). Higher CDR® plus NACC FTLD scores were negatively correlated with HRQoL ratings, indicating that HRQoL decreases with poorer clinical status, i.e., as individuals become symptomatic. This finding suggests that even mild FTLD features may have a negative impact on HRQoL. Similar to the findings presented here, several studies have indicated a negative correlation with HRQoL and early cognitive changes. In one study, the presence of a memory complaint was associated with lower QOL in individual(s) with MCI but not for normal controls [37]. In another study, MCI was associated with lower self-reported psychological QOL compared to controls [38]. A study of cognitively normal participants showed significantly higher QOL scores compared to those with MCI based on both subject and informant measures [39], and a similar study found reduced QOL in MCI by both participant and proxy reports [40]. In addition, individuals reported higher levels of QOL compared to their caregivers. These four studies in MCI also found that depressive and neuropsychiatric symptoms correlated with lower ratings of QOL. However, not all studies have supported this association with MCI and lower QOL. One study compared QOL measures for those with AD, MCI, and normal controls, and found that while caregivers rated QOL lower in AD than in controls, MCI was not associated with decreased QOL [23]. Furthermore, the self-report measures of QOL did not show any differences across the 3 groups. The trajectory of decreased QOL over the course dementia, from preclinical/asymptomatic to early cognitive changes, and finally clinically significant dementia remains unclear. There is even less available evidence regarding HRQoL over the course of FTLD specifically.
This current study, which includes a high risk familial FTLD cohort, provides a unique opportunity to follow changes in HRQoL longitudinally. Additional work on HRQoL with this cohort will provide more insights on how FTLD impacts QOL in individuals and informants, particularly with regard to phenoconversion from asymptomatic to overtly symptomatic FTLD. Though not specific to FTLD, one study found that decreases in HRQoL preceded the diagnosis of all cause dementia and AD in a community sample, suggesting that changes in HRQoL could be a predictor of cognitive decline [41]. This LEFFTDS cohort may provide an opportunity to test if a similar effect could be seen in FTLD.
In individuals with dementia, it can be more difficult to assess HRQoL due to the inherent impairments in memory, language, and executive function, as well as the decreased insight that is particularly common in some FTLD syndromes. This is an increasing concern with more advanced stages of dementia. Therefore proxy/informant measures of HRQoL have often been used in dementia, though this method also has its limitations. In this study we examined both self-report and proxy reported HRQoL, and demonstrated fair agreement between the two. This cohort is relatively young, with a mean age of 48.5 years, and the majority of the informants are spouses, and likely caregivers. The differences between self-reported and proxy-rated measures could reflect of the impaired’s awareness and insight regarding behavioral, cognitive and functional changes in FTLD and the resulting impact on HRQoL on the part of the symptomatic patient [42]. There may also be factors related to the informant or caregiver that create bias in reporting HRQoL. There are multiple possible sources of bias related to proxy reports of HRQoL for individuals with dementia. Informants may have difficulty objectively evaluating subject HRQoL, such as projecting their own sense of HRQoL onto the dementia patient [20]. Studies in AD have indicated that proxy reports tend to underestimate a patient’s QOL, and proxy reports can vary based on the emotional state of the caregiver and the nature of the relationship between the caregiver and patient [21, 43, 44]. A 2001 study of 40 caregivers found that dementia severity, caregiver depression and caregiver burden negatively affected caregivers’ assessments of patient QOL [45]. This study also indicated that proxy reports differ based on their own assessment versus how they believe the dementia patient would respond. The tendency for informants to report lower QOL compared to patient self-report, has also been demonstrated in MCI [40]. Both patient-reported and proxy measures of QOL impart valuable information. Further research is needed to develop best practices for incorporating both self-reports and proxy reports of QOL in FTLD.
This study found that caregiver burden as measured on the ZBI was negatively correlated with patient HRQoL. This is consistent with our hypothesis that as individuals experience a lower quality of life, based on decreased functional status and higher symptoms burden, caregivers are likely to experience increased caregiver demands and distress. This finding is consistent with other studies in dementia [46, 47]. In this current study, caregivers of asymptomatic and minimally symptomatic participants rated caregiver burden in the “little or no burden” category, while caregivers of those with mild to moderate dementia were generally in the “mild to moderate burden” category. However, individuals with the highest symptoms severity showed low levels of caregiver burden. The significance and possible causes of this finding are unclear. It is possible that at the advanced stages of FTLD, caregivers are seeking out additional supports such as home care or moving individuals to long-term care environments, and subsequently have a lower level of caregiver burden. Though there was a significant increase in caregiver burden associated with reductions in HRQoL, overall there were fairly low levels of caregiver burden reported. This is consistent with the generally good ratings of HRQoL within this cohort.
There has been increasing interest in understanding the factors contributing to HRQoL in dementia generally and in FTLD specifically. In addition, there is a strong desire to offer interventions that may help maintain or improve HRQoL for individuals with dementia. There are studies showing potential benefits for a variety of interventions to improve quality of life in dementia [48] and FTLD more specifically [49]. Interventions with evidence of benefit include neurorehabilitation, behavioral therapy, caregiver educations, strategies to improve self-efficacy, occupational therapy, and physical exercise programs, and cognitive stimulation programs. To better target HRQoL in FTLD, it will be important to have a better understanding of the factors that influence HRQoL in FTLD and how HRQoL may change over the course of illness. This study provides preliminary data on the natural course of HRQoL and caregiver burden as disease severity progresses. Additional studies are needed to further explore individual and disease related factors that may influence HRQoL and therefore be a target for intervention studies.
There are several limitations to this study. This study does not examine other possible determinants of HRQoL such as depression, behavioral symptoms or level of care needs. This study does not provide longitudinal data on HRQoL to examine changes over time through the course of disease progression. However, this cohort is part of a longitudinal study and this information will be analyzed as the study continues.
The strengths of this study include that it is one of the few studies to examine HRQoL in a FTLD cohort. This study is unique in being able to track HRQoL ratings of kindred individuals in familial FTLD who are not yet symptomatic or diagnosed with FTLD. This study uses a measure of HRQoL designed specifically for use in dementia individuals, and has the benefits of providing both self-rating and informant rating of HRQoL.
Supplementary Material
Acknowledgements
We extend our appreciation to Drs. John Hsiao and Dallas Anderson from the National Institute on Aging, Drs. Marg Sutherland and Codrin Lungu from the National Institute of Neurological Disorders and Stroke, the staff of all centers, and particularly to our individuals and their families for their participation in this protocol.
Funding
This work is supported by the National Institutes of Health (grants U01 AG045390, PI: Dr. Bradley F Boeve; U54 NS092089, PI: Dr. Adam L Boxer; U24 AG021886, PI: Dr. Tatiana M Foroud; and U01 AG016976, PI: Dr. Walter Anthony Kukull).
Disclosures
Gentry M – nothing to disclose
Lapid M – receives research support from NIH
Syrjanen J – nothing to disclose
Calvert K-no disclosures
Hughes S-no disclosures
Brushaber D – nothing to disclose
Kremers WK - receives research funding from AstraZeneca, Biogen, Roche, DOD and NIH
Bove J – nothing to disclose
Brannelly P – employed by the Rainwater Charitable Foundation
Coppola G – receives research support from NIH
Dheel C – nothing to disclose
Dickerson B – receives research support from NIH
Dickinson S – on staff at the Association for Frontotemporal Degeneration and a member of the National Institute for Neurological Disorders and Stroke Advisory Council
Faber K – receives research support from NIH
Fields J – receives research support from NIH
Fong J – nothing to disclose
Foroud T – receives research support from NIH
Forsberg L – receives research support from NIH
Gavrilova R – receives research support from NIH
Gearhart D – nothing to disclose
Ghoshal N- has participated or is currently participating in clinical trials of anti-dementia drugs sponsored by the following companies: Bristol Myers Squibb, Eli Lilly/Avid Radiopharmaceuticals, Janssen Immunotherapy, Novartis, Pfizer, Wyeth, SNIFF (The Study of Nasal Insulin to Fight Forgetfulness) study, and A4 (The Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease) trial. She receives research support from Tau Consortium and Association for Frontotemporal Dementia and is funded by the NIH.
Goldman J – is serving as a consultant to the Novartis Alzheimer’s Prevention Advisory Board. She receives research support from NIH, HDSA, New York State Department of Health (RFA # 1510130358)
Graff-Radford J – receives research support from the NIH
Graff-Radford J- receives research support from the NIH.
Graff-Radford N – receives royalties from UpToDate, has participated in multicenter therapy studies by sponsored by Biogen, TauRx, AbbVie, Novartis and Lilly. He receives receives research support from NIH
Grossman M - receives grant support from NIH, Avid and Piramal; participates in clinical trials sponsored by Biogen, TauRx, and Alector; serves as a consultant to Bracco and UCB; and serves on the Editorial Board of Neurolog
Haley D – nothing to disclose
Heuer H- receives research support from NIH
Hsiung G - has served as an investigator for clinical trials sponsored by AstraZeneca, Eli Lilly, and Roche / Genentech. He receives research support from Canadian Institutes of Health Research and the Alzheimer Society of British Columbia
Huey E – receives research support from NIH
Irwin D – receives support from NIH, Brightfocus Foundation and Penn Institute on Aging
Jones D – receives research support from NIH and the Minnesota Partnership for Biotechnology and Medical Genomics
Jones L – nothing to disclose
Kantarci K - served on the Data Safety Monitoring Board for Takeda Global Research & Development Center, Inc.; data monitoring boards of Pfizer and Janssen Alzheimer Immunotherapy; research support from the Avid Radiopharmaceuticals, Eli Lilly, the Alzheimer’s Drug Discovery Foundation and NIH
Karydas A – nothing to disclose
Knopman D - serves on the DSMB of the DIAN-TU study, is a site PI for clinical trials sponsored by Biogen, Lilly and the University of Southern California, and is funded by NIH
Kornak J – has provided expert witness testimony for Teva Pharmaceuticals in Forest Laboratories Inc. et al. v. Teva Pharmaceuticals USA, Inc., Case Nos. 1:14-cv-00121 and 1:14-cv-00686 (D. Del. filed Jan. 31, 2014 and May 30, 2014) regarding the drug Memantine; for Apotex/HEC/Ezra in Novartis AG et al. v. Apotex Inc., No. 1:15-cv-975 (D. Del. filed Oct. 26, 2015, regarding the drug Fingolimod. He has also given testimony on behalf of Puma Biotechnology in Hsingching Hsu et al, vs. Puma Biotechnology, INC., et al. 2018 regarding the drug Neratinib. He receives research support from the NIH
Kramer J – receives research support from NIH
Kukull W – receives research support from NIH
Lucente D - receives research support from NIH
Lungu C – honoraria for editorial work from Elsevier, Inc.
Mackenzie I – receives research funding from Canadian Institutes of Health Research
Manoochehri M – nothing to disclose
McGinnis S – has served as an investigator for clinical trials sponsored by AbbVie, Allon Therapeutics, Biogen, Bristol-Myers Squibb, C2N Diagnostics, Eisai Inc., Eli Lilly and Co., Genentech, Janssen Pharmaceuticals, Medivation, Merck, Navidea Biopharmaceuticals, Novartis, Pfizer, and TauRx Therapeutics. He receives research support from NIH
Miller B – receives research support from NIH
Pearlman R – employed by The Bluefield Project
Petrucelli L – receives research support from NIH
Potter M – receives research support from NIH
Rademakers R – receives research funding from NIH and the Bluefield Project to Cure Frontotemporal Dementia
Ramos E – nothing to disclose
Rankin K – receives research support from NIH
Rascovsky K – receives research support from NIH
Sengdy P – nothing to disclose
Shaw L – receives research support from NIH
Tatton N – employed by the Association for Frontotemporal Degeneration
Taylor J – nothing to disclose
Toga A – receives research support from NIH and the Alzheimer’s Association
Trojanowski J – may accrue revenue in the future on patents submitted by the University of Pennsylvania wherein he is coinventor and he received revenue from the sale of Avid to Eli Lily as coinventor on Aβ amyloid imaging–related patents submitted by the University of Pennsylvania. He receives research support from the NIH and several nonprofits.
Weintraub S – receives research support from NIH
Wong B – receives research support from NIH
Wszolek Z - supported by the NIH, Mayo Clinic Center for Regenerative Medicine, the gift from Carl Edward Bolch, Jr., and Susan Bass Bolch, The Sol Goldman Charitable Trust, and Donald G. and Jodi P. Heeringa. He has also received grant funding support from Allergan, Inc. (educational grant), and Abbvie (medication trials)
Boeve B – has served as an investigator for clinical trials sponsored by GE Healthcare and Axovant. He receives royalties from the publication of a book entitled Behavioral Neurology Of Dementia (Cambridge Medicine, 2009, 2017). He serves on the Scientific Advisory Board of the Tau Consortium. He receives research support from NIH, the Mayo Clinic Dorothy and Harry T. Mangurian Jr. Lewy Body Dementia Program and the Little Family Foundation
Boxer A – receives research support from NIH, the Tau Research Consortium, the Association for Frontotemporal Degeneration, Bluefield Project to Cure Frontotemporal Dementia, Corticobasal Degeneration Solutions, the Alzheimer’s Drug Discovery Foundation and the Alzheimer’s Association. He has served as a consultant for Aeton, Abbvie, Alector, Amgen, Arkuda, Ionis, Iperian, Janssen, Merck, Novartis, Samumed, Toyama and UCB, and received research support from Avid, Biogen, BMS, C2N, Cortice, Eli Lilly, Forum, Genentech, Janssen, Novartis, Pfizer, Roche and TauRx
Rosen H – has received research support from Biogen Pharmaceuticals, has consulting agreements with Wave Neuroscience and Ionis Pharmaceuticals, and receives research support from NIH
References
- [1].World Health Organization. WHOQOL: Measuring Quality of Life. 2014. Accessed: June 26, 2018 Available at: https://www.who.int/healthinfo/survey/whoqol-qualityoflife/en/
- [2].Ferrans CE, Zerwic JJ, Wilbur JE, Larson JL. Conceptual model of health-related quality of life. J Nurs Scholarsh. 2005;37:336–42. doi: 10.1111/j.1547-5069.2005.00058.x. [DOI] [PubMed] [Google Scholar]
- [3].Karg N, Graessel E, Randzio O, Pendergrass A. Dementia as a predictor of care-related quality of life in informal caregivers: a cross-sectional study to investigate differences in health-related outcomes between dementia and non-dementia caregivers. BMC Geriatr. 2018;18:189. doi: 10.1186/s12877-018-0885-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [4].Hoe J, Hancock G, Livingston G, Woods B, Challis D, Orrell M. Changes in the quality of life of people with dementia living in care homes. Alzheimer Dis Assoc Disord. 2009;23:285–90. doi: 10.1097/WAD.0b013e318194fc1e. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Banerjee S, Samsi K, Petrie CD, Alvir J, Treglia M, Schwam EM, et al. What do we know about quality of life in dementia? A review of the emerging evidence on the predictive and explanatory value of disease specific measures of health related quality of life in people with dementia. Int J Geriatr Psychiatry. 2009;24:15–24. doi: 10.1002/gps.2090. [DOI] [PubMed] [Google Scholar]
- [6].Knopman DS, Roberts RO. Estimating the number of persons with frontotemporal lobar degeneration in the US population. J Mol Neurosci. 2011;45:330–5. doi: 10.1007/s12031-011-9538-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Onyike CU, Diehl-Schmid J. The epidemiology of frontotemporal dementia. Int Rev Psychiatry. 2013;25:130–7. doi: 10.3109/09540261.2013.776523. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [8].Banerjee S, Smith SC, Lamping DL, Harwood RH, Foley B, Smith P, et al. Quality of life in dementia: more than just cognition. An analysis of associations with quality of life in dementia. J Neurol Neurosurg Psychiatry. 2006;77:146–8. doi: 10.1136/jnnp.2005.072983. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [9].de Vugt ME, Riedijk SR, Aalten P, Tibben A, van Swieten JC, Verhey FR. Impact of behavioural problems on spousal caregivers: a comparison between Alzheimer’s disease (AD) and frontotemporal dementia. Dement Geriatr Cogn Disord. 2006;22:35–41. doi: 10.1159/000093102. [DOI] [PubMed] [Google Scholar]
- [10].Riedijk SR, De Vugt ME, Duivenvoorden HJ, Niermeijer MF, Van Swieten JC, Verhey FR, et al. Caregiver burden, health-related quality of life and coping in dementia caregivers: a comparison of frontotemporal dementia and Alzheimer’s disease (AD). Dement Geriatr Cogn Disord. 2006;22:405–12. doi: 10.1159/000095750. [DOI] [PubMed] [Google Scholar]
- [11].Hvidsten L, Engedal K, Selbaek G, Wyller TB, Bruvik F, Kersten H. Quality of Life in People with Young-Onset Alzheimer’s Dementia and Frontotemporal Dementia. Dement Geriatr Cogn Disord. 2018;45:91–104. doi: 10.1159/000487263. [DOI] [PubMed] [Google Scholar]
- [12].Oyebode JR, Bradley P, Allen JL. Relatives’ experiences of frontal-variant frontotemporal dementia. Qual Health Res. 2013;23:156–66. doi: 10.1177/1049732312466294. [DOI] [PubMed] [Google Scholar]
- [13].Bakker C, de Vugt ME, van Vliet D, Verhey F, Pijnenburg YA, Vernooij-Dassen MJ, et al. Unmet needs and health-related quality of life in young-onset dementia. Am J Geriatr Psychiatry. 2014;22:1121–30. doi: 10.1016/j.jagp.2013.02.006. [DOI] [PubMed] [Google Scholar]
- [14].Millenaar J, Hvidsten L, de Vugt ME, Engedal K, Selbaek G, Wyller TB, et al. Determinants of quality of life in young onset dementia - results from a European multicenter assessment. Aging Ment Health. 2017;21:24–30. doi: 10.1080/13607863.2016.1232369. [DOI] [PubMed] [Google Scholar]
- [15].Banning LCP, Janssen E, Hamel REG, de Vugt M, Kohler S, Wolfs CAG, et al. Determinants of Cross-Sectional and Longitudinal Health-Related Quality of Life in Memory Clinic Patients Without Dementia. J Geriatr Psychiatry Neurol. 2019:891988719882104. doi: 10.1177/0891988719882104. [DOI] [PMC free article] [PubMed]
- [16].Lapid MI, Rummans TA, Boeve BF, McCormick JK, Pankratz VS, Cha RH, et al. What is the quality of life in the oldest old? Int Psychogeriatr. 2011;23:1003–10. doi: 10.1017/S1041610210002462. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [17].Albert SM, Del Castillo-Castaneda C, Sano M, Jacobs DM, Marder K, Bell K, et al. Quality of life in patients with Alzheimer’s disease (AD) as reported by patient proxies. J Am Geriatr Soc. 1996;44:1342–7. doi: 10.1111/j.1532-5415.1996.tb01405.x. [DOI] [PubMed] [Google Scholar]
- [18].Smith SC, Hendriks AJ, Regan J, Black N. A novel method of proxy reporting questionnaire based measures of health-related quality of life of people with dementia in residential care: a psychometric evaluation. Patient Relat Outcome Meas. 2018;9:221–30. doi: 10.2147/prom.S144000. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [19].Sneeuw KC, Sprangers MA, Aaronson NK. The role of health care providers and significant others in evaluating the quality of life of patients with chronic disease. J Clin Epidemiol. 2002;55:1130–43. doi: 10.1016/s0895-4356(02)00479-1. [DOI] [PubMed] [Google Scholar]
- [20].Arons AM, Krabbe PF, Scholzel-Dorenbos CJ, van der Wilt GJ, Rikkert MG. Quality of life in dementia: a study on proxy bias. BMC Med Res Methodol. 2013;13:110. doi: 10.1186/1471-2288-13-110. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [21].Gomez-Gallego M, Gomez-Garcia J, Ato-Lozano E. Addressing the bias problem in the assessment of the quality of life of patients with dementia: determinants of the accuracy and precision of the proxy ratings. J Nutr Health Aging. 2015;19:365–72. doi: 10.1007/s12603-014-0564-7. [DOI] [PubMed] [Google Scholar]
- [22].Orgeta V, Edwards RT, Hounsome B, Orrell M, Woods B. The use of the EQ-5D as a measure of health-related quality of life in people with dementia and their carers. Qual Life Res. 2015;24:315–24. doi: 10.1007/s11136-014-0770-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23].Ready RE, Ott BR, Grace J. Patient versus informant perspectives of Quality of Life in Mild Cognitive Impairment and Alzheimer’s disease (AD). Int J Geriatr Psychiatry. 2004;19:256–65. doi: 10.1002/gps.1075. [DOI] [PubMed] [Google Scholar]
- [24].Boeve B, Bove J, Brannelly P, Brushaber D, Coppola G, Dever R, et al. The longitudinal evaluation of familial frontotemporal dementia subjects protocol: Framework and methodology. Alzheimer’s & Dementia. 2019. doi: 10.1016/j.jalz.2019.06.4947. [DOI] [PMC free article] [PubMed]
- [25].Miyagawa T, Brushaber D, Syrjanen J, Kremers W, Fields J, Forsberg LK, et al. Use of the CDR(R) plus NACC FTLD in mild FTLD: Data from the ARTFL/LEFFTDS consortium. Alzheimers Dement. 2019. doi: 10.1016/j.jalz.2019.05.013. [DOI] [PMC free article] [PubMed]
- [26].Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology. 1993;43:2412–4. doi: 10.1212/wnl.43.11.2412-a. [DOI] [PubMed] [Google Scholar]
- [27].Morris JC, Weintraub S, Chui HC, Cummings J, Decarli C, Ferris S, et al. The Uniform Data Set (UDS): clinical and cognitive variables and descriptive data from Alzheimer Disease (AD) Centers. Alzheimer Dis Assoc Disord. 2006;20:210–6. doi: 10.1097/01.wad.0000213865.09806.92. [DOI] [PubMed] [Google Scholar]
- [28].Smith SC, Lamping DL, Banerjee S, Harwood RH, Foley B, Smith P, et al. Development of a new measure of health-related quality of life for people with dementia: DEMQOL. Psychol Med. 2007;37:737–46. doi: 10.1017/S0033291706009469. [DOI] [PubMed] [Google Scholar]
- [29].Smith SC, Lamping DL, Banerjee S, Harwood R, Foley B, Smith P, et al. Measurement of health-related quality of life for people with dementia: development of a new instrument (DEMQOL) and an evaluation of current methodology. Health Technol Assess. 2005;9:1–93, iii-iv. doi: 10.3310/hta9100. [DOI] [PubMed] [Google Scholar]
- [30].Chua KC, Bohnke JR, Prince M, Banerjee S. Health-related quality-of-life assessment in dementia: Evidence of cross-cultural validity in Latin America. Psychol Assess. 2019;31:1264–77. doi: 10.1037/pas0000743. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [31].Niikawa H, Kawano Y, Yamanaka K, Okamura T, Inagaki H, Ito K, et al. Reliability and validity of the Japanese version of a self-report (DEMQOL) and carer proxy (DEMQOL-PROXY) measure of health-related quality of life in people with dementia. Geriatr Gerontol Int. 2019;19:487–91. doi: 10.1111/ggi.13646. [DOI] [PubMed] [Google Scholar]
- [32].Park MH, Smith SC, Chrysanthaki T, Neuburger J, Ritchie CW, Hendriks AAJ, et al. Change in Health-related Quality of Life After Referral to Memory Assessment Services. Alzheimer Dis Assoc Disord. 2017;31:192–9. doi: 10.1097/WAD.0000000000000190. [DOI] [PubMed] [Google Scholar]
- [33].Park MH, Smith SC, Neuburger J, Chrysanthaki T, Hendriks AAJ, Black N. Sociodemographic Characteristics, Cognitive Function, and Health-related Quality of Life of Patients Referred to Memory Assessment Services in England. Alzheimer Dis Assoc Disord. 2017;31:159–67. doi: 10.1097/WAD.0000000000000166. [DOI] [PubMed] [Google Scholar]
- [34].Zarit SH, Reever KE, Bach-Peterson J. Relatives of the impaired elderly: correlates of feelings of burden. Gerontologist. 1980;20:649–55. doi: 10.1093/geront/20.6.649. [DOI] [PubMed] [Google Scholar]
- [35].Lin CY, Wang JD, Pai MC, Ku LE. Measuring burden in dementia caregivers: Confirmatory factor analysis for short forms of the Zarit Burden Interview. Arch Gerontol Geriatr. 2017;68:8–13. doi: 10.1016/j.archger.2016.08.005. [DOI] [PubMed] [Google Scholar]
- [36].Flynn Longmire CV, Knight BG. Confirmatory factor analysis of a brief version of the Zarit Burden Interview in Black and White dementia caregivers. Gerontologist. 2011;51:453–62. doi: 10.1093/geront/gnr011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [37].Maki Y, Yamaguchi T, Yamagami T, Murai T, Hachisuka K, Miyamae F, et al. The impact of subjective memory complaints on quality of life in community-dwelling older adults. Psychogeriatrics. 2014;14:175–81. doi: 10.1111/psyg.12056. [DOI] [PubMed] [Google Scholar]
- [38].Muangpaisan W, Assantachai P, Intalapaporn S, Pisansalakij D. Quality of life of the community-based patients with mild cognitive impairment. Geriatr Gerontol Int. 2008;8:80–5. doi: 10.1111/j.1447-0594.2008.00452.x. [DOI] [PubMed] [Google Scholar]
- [39].Teng E, Tassniyom K, Lu PH. Reduced quality-of-life ratings in mild cognitive impairment: analyses of subject and informant responses. Am J Geriatr Psychiatry. 2012;20:1016–25. doi: 10.1097/JGP.0b013e31826ce640. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [40].Barrios H, Narciso S, Guerreiro M, Maroco J, Logsdon R, de Mendonca A. Quality of life in patients with mild cognitive impairment. Aging Ment Health. 2013;17:287–92. doi: 10.1080/13607863.2012.747083. [DOI] [PubMed] [Google Scholar]
- [41].Ezzati A, Zammit AR, Katz MJ, Derby CA, Zimmerman ME, Lipton RB. Health-related Quality of Life, Cognitive Performance, and Incident Dementia in a Community-based Elderly Cohort. Alzheimer Dis Assoc Disord. 2019;33:240–5. doi: 10.1097/WAD.0000000000000324. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [42].Sousa MF, Santos RL, Arcoverde C, Simoes P, Belfort T, Adler I, et al. Quality of life in dementia: the role of non-cognitive factors in the ratings of people with dementia and family caregivers. Int Psychogeriatr. 2013;25:1097–105. doi: 10.1017/S1041610213000410. [DOI] [PubMed] [Google Scholar]
- [43].Sprangers MA, Aaronson NK. The role of health care providers and significant others in evaluating the quality of life of patients with chronic disease: a review. J Clin Epidemiol. 1992;45:743–60. doi: 10.1016/0895-4356(92)90052-o. [DOI] [PubMed] [Google Scholar]
- [44].Novella JL, Jochum C, Jolly D, Morrone I, Ankri J, Bureau F, et al. Agreement between patients’ and proxies’ reports of quality of life in Alzheimer’s disease (AD). Qual Life Res. 2001;10:443–52. doi: 10.1023/a:1012522013817. [DOI] [PubMed] [Google Scholar]
- [45].Karlawish JH, Casarett D, Klocinski J, Clark CM. The relationship between caregivers’ global ratings of Alzheimer’s disease (AD) patients’ quality of life, disease severity, and the caregiving experience. J Am Geriatr Soc. 2001;49:1066–70. doi: 10.1046/j.1532-5415.2001.49210.x. [DOI] [PubMed] [Google Scholar]
- [46].Naglie G, Hogan DB, Krahn M, Black SE, Beattie BL, Patterson C, et al. Predictors of family caregiver ratings of patient quality of life in Alzheimer disease (AD): cross-sectional results from the Canadian Alzheimer’s Disease (AD) Quality of Life Study. Am J Geriatr Psychiatry. 2011;19:891–901. doi: 10.1097/JGP.0b013e3182006a7f. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [47].Srivastava G, Tripathi RK, Tiwari SC, Singh B, Tripathi SM. Caregiver Burden and Quality of Life of Key Caregivers of Patients with Dementia. Indian J Psychol Med. 2016;38:133–6. doi: 10.4103/0253-7176.178779. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [48].Logsdon RG, McCurry SM, Teri L. Evidence-Based Interventions to Improve Quality of Life for Individuals with Dementia. Alzheimers care today. 2007;8:309–18 [PMC free article] [PubMed] [Google Scholar]
- [49].Kortte KB, Rogalski EJ. Behavioural interventions for enhancing life participation in behavioural variant frontotemporal dementia and primary progressive aphasia. Int Rev Psychiatry. 2013;25:237–45. doi: 10.3109/09540261.2012.751017. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.