- Email: [email protected]
Use of the EQ-5D among patients suffering from dementia
Journal of Clinical Epidemiology 56 (2003) 1055–1063
Use of the EQ-5D among patients suffering from dementia J. Ankria,*, B. Beaufilsb, J.-L. Novellac, I. Morroned, F. Guillemine, D. Jollyf, L. Plotong, F. Blanchardc a
Hoˆpital Ste Pe´rine, Universite´ de Paris V, RFR 12 Sante´ Vieillissement Socie´te´, 49 rue Mirabeau 75016 Paris, France b Universite´ Paris VIII, RFR 12 Sante´ Vieillissement Socie´te´, 49 rue Mirabeau 75016 Paris, France c Me´decine interne et ge´rontologie clinique, hoˆpital Se´bastopol 51092 Reims Cedex, France d Re´e´ducation fonctionnelle, hoˆpital Se´bastopol, 51092 Reims Cedex, France e Ecole de Sante´ Publique, EA 1124, BP 184 54505, Vandoeuvre les Nancy, France f De´partement d’information me´dical, hoˆpital Maison Blanche, 51092 Reims Cedex, France g Universite´ Lumie`res, 69676 Bron Cedex, France Accepted 12 May 2003
Abstract Background and objective: This study was designed to determine the acceptability, feasibility, reliability, and validity of the French version of EQ-5D measuring HRQol in subjects with dementia. Methods: EQ-5D was administered to 142 subjects. The feasibility and acceptability were determined by the refusal rate, the type of administration, and the percentage and distribution of missing data. Test-retest reliability was studied by kappa coefficients and validity by agreement between subjects’ and proxies’ assessments. Results: The response rate was satisfactory. The instrument discriminated well among the subjects. Test-retest reliability was average. The validity was poor if we consider the agreement between patients’ and caregivers’ reports, but other criteria of validity produced better results. Subjects’ responses on each dimension were related with their global judgment of health in the expected direction. Significant relations were found between the Katz index of ADL and self-rated difficulties only for expected dimensions. Relations with age and with gender were in line with expectations. Conclusion: Results led to consider that patients’ responses are not entirely devoid of judgment. It seems that dementia patients are capable of expressing their health-related quality of life through a brief instrument as the EQ-5D. 쑖 2003 Elsevier Inc. All rights reserved. Keywords: Quality of life; Dementia; Alzheimer’s disease; HRQol; EQ-5D
1. Introduction Health-related quality of life (HRQOL) has become a high priority in health and social services for the elderly, a population in which cognitive function is sometimes impaired because of dementia. The prevalence of dementia in people over 65 is 5%, but the rate increases sixfold in people over 90 [1]. Factors associated with dementia can pose methodologic problems in evaluating quality of life in this population, raising questions about the validity of such evaluations. Impaired memory, judgment, and language, which are typical of dementia, may make it impossible to administer a quality-of-life questionnaire. Interpreting a self-evaluation of health-related quality of life in patients denying their disease state may also be problematic. Given the frequency of psychologic and behavioral problems that, themselves, * Corresponding author. Tel.: 33-1-44-96-32-14; fax: 33-1-44-96-31-46. E-mail address: [email protected] (J. Ankri). 0895-4356/03/$ – see front matter 쑖 2003 Elsevier Inc. All rights reserved. doi: 10.1016/S0895-4356(03)00175-6
undermine quality of life, one might question the pertinence of such evaluations. But if a patient is able to complete a self-assessment of HRQOL, may this fact be considered as a valid indicator of her (his) HRQOL in itself? The effects of intellectual deterioration on subjects’ comprehension, expression of expectations and wishes, and language, have led certain investigators to conclude that these patients are not by themselves able to evaluate their quality of life. Therefore, an indirect approach is often taken, relying on family or institutional proxies for evaluation [2,3], but some researchers question the validity of such assessments [4–8]. On the other hand, Kiyak et al. [9], in a longitudinal study, showed that, contrary to a widely accepted belief, patients with Alzheimer’s disease are conscious of the decline in their functional and cognitive abilities. So, it makes sense to ask whether a brief HRQOL instrument may be used in such a population. There are several health-related quality-of-life scales in French that have been validated on elderly people, some
1056
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
suffering from cognitive impairment [10–12]. One of these, the EQ-5D [13], has the advantage of being a generic instrument, and therefore, allows for comparisons between people in different age groups and with different pathologies. Another advantage is that it contains few items, making it suitable for administration to subjects with dementia.
Consequences of dementia in patient’s functioning have also been recorded by Katz’s index of Activities of Daily Living (ADL [16]). The Katz index is a measure of independency of the subject in six basic activities of daily living (bathing, dressing, using the toilet, transferring bed to chair, continence, eating). According to the index, performance is summarized as grades implying more and more difficulties. 3.3. Instrument
2. Aim of the study This study was designed to ascertain the acceptability, feasibility, reliability, and validity of the EQ-5D for a French population of subjects suffering from dementia.
3. Method 3.1. Patient sample Subjects (male and female) were recruited by 16 French geriatric hospital centers belonging to the French “Re´seau Qualite´ de vie et De´mence” to ensure a broad range of disease severity and settings. The patient population was hospitalized in geriatric care units (for various conditions), institutionalized, or outpatients. To be included in the study, subjects had to be at least 60 years old and present a dementia according to the DSMIII-R diagnostic criteria. Patients who were blind, seriously hearing impaired, or could not speak French were not included. In the event of instability in the patient’s condition, which might modify his or her subjective health status during the period, the patient was not included. Proxies were recruited at the same time. The family caregiver was chosen from among people who knew and saw the patient most regularly and was capable of fitting the instrument. The professional caregiver was recruited from the health care team directly responsible for the patient: nurse’s aides and nurses who take care of the patient in the hospital or institution or physician in consultation. Informed consent was obtained from each patient and his or her family caregiver after the study has been explained and they had been given an explanatory letter. The Champagne Ardennes Ethics Committee approved the study. 3.2. Data collection For each patient, sex, age, marital status, school leaving age, residential arrangements, type of dementia diagnosed and Folstein’s Mini-Mental State Examination (MMSE [14]) have been recorded. The MMSE is a brief screening test (range 0–30) that assesses several cognitive functions and is one of the most widely used screening instrument for cognitive impairment in clinical setting and epidemiologic studies. The higher the MMSE score, the better the subject’s cognitive state is. Patient’s dementia stage was determined by clinicians using the Hughes’s Clinical Dementia Rating Scale (CDR [15]) in questionable (CDR0.5), mild (CDR1), moderate (CDR2), or severe stage (CDR3).
EQ-5D is a self-administered questionnaire in which responders have to evaluate their health state “today” on five dimensions: mobility, self-care, usual activities, pain/ discomfort, and anxiety/depression. A one-to-three scale is used for each dimension, representing no problem, some problem, or extreme problem, making it impossible for the subject to engage in the activity alone; for the pain and anxiety items, the three ratings relate to the severity of symptoms. The subject’s responses may be used to create a profile. The instrument also has a visual analog scale “thermometer” VAS, a 20-cm scale anchored at 0 “worse imaginable health state” and 100 “best imaginable health state.” The EQ-5D has been translated into several languages and has been validated and employed in many studies on general populations [17,18], on subjects with medical or surgical problems [5,17,19–24], and on subjects with mild dementia [25]. Two studies have validated the instrument in elderly subjects [10,11]. This generic instrument is designed to assess quality of life across diseases groups, and the question remains if any of its measures have face validity for use in dementia [26]. The questionnaire is intentionally brief, so the items do not cover all the facets of quality of life described in the literature [27]; but they do, however, appear to represent the most important dimensions of healthrelated quality of life. 3.4. Instrument administration Because of the particular problems in this population and in line with previous studies in which this procedure had to be done [4,5,17,18,28,29], it was decided that the EQ-5D questionnaire could be administered by a trained interviewer. In addition, the time taken to complete the EQ-5D questionnaire was noted. Institutional and family caregivers were also asked to complete the questionnaire in assessing patient’s health status. A subgroup of one patient in four was drawn from the sample for a new administration of the instrument three days after the first exposure to determine test-retest reliability. 4. Statistical methods 4.1. SPSS (version 9.0 for Windows) was used to analyze the data 4.1.1. Determination of an overall score The EQ-5D was designed to provide profiles on health status. The possible responses to each item are ordinal categories, and therefore, no allowance was made for an overall
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
score based on a combination of the responses. It appeared, however, that the instrument might legitimately be used to establish an overall score. If the ordinal responses are converted into numerical ratings, a score can be obtained for each item, and scores can be added. The refusal rate was taken as a measurement of acceptability of the questionnaire, administration type (self- or interviewer-administered), time to complete, and the number and distribution of missing data were taken as indicators of the feasibility of the questionnaire. Responses’ variability was also studied. Test-retest reliability was studied on a quarter of the subjects chosen at random. Test-retest was determined by kappa coefficients [30] of the responses for categorized data after elimination of agreement that would occur by chance. Following the classification of Landis and Koch [31], the kappa coefficients reflect moderate agreement when they are between 0.41 and 0.60, while those below this level indicate weak agreement. Intraclass correlation coefficients (ICC [32]) were obtained on continuous variables such as the VAS and the overall score. The two-way, mixed-effect model/absolute agreement definition ICC (2,1) model was chosen [32]. In lack of a gold standard, validity was studied by agreement between subjects’ and proxies’ assessments determined by kappa coefficients for the categorized data and by ICC for continuous data. The construct validity was tested in terms of several relationships hypothesized. Dimensions of EQ-5D and the overall scores were expected to be linked with VAS. Functional dimensions of EQ-5D and pain, but not the anxiety item, were expected to be linked with ADL. Women were expected to be more anxious than men in having poorer overall assessment of their health. Association of EQ-5D scores with age and with dementia severity was studied (ANOVA, Pearson correlation, chi-square according to variables). 5. Results A total of 142 patients were included in the study (Table 1). There were 29 men (20.4%) and 113 women (79.6%). Their average age was 82.9 years, with a range of 60 to 99 years, and one in five subjects lived at home. On average, the women were older, widows, and lived more often in an institution. They had less schooling than men in the sample. In most cases, the dementia was associated with Alzheimer’s disease (70.4%), followed by vascular dementia (12.7%). As measured by the CDR, slightly more than a quarter of the subjects (27.9%) presented severe dementia, and 33.8% had an MMSE equal to or lower than 10. Distribution of the severity of dementia and of demographic characteristics in this sample is difficult to compare with dementia general population because severity tools used in epidemiologic studies are not the same ones, and data issued from dementia general population are often sketchy. One hundred thirty-three institutional and 126 family caregivers were available. About 50% of the family caregivers were children, most often daughters (34%), and 28%
1057
Table 1 Subject characteristics at selection
Number Age
Residence
Marital status
Schoolleaving age
Diagnosis
CDR
MMSE
Katz
Age in years (s) Range Home Hospital Institution Single Married Divorced Widowed Mean (s) Less than 12 years 12–16 More than 16 years Alzheimer’s disease Vascular Alcoholic Other Probable deficit Light Moderate Severe Mean (s) Range 0–5 6–10 11–14 15 or over A B C D E F G H
Men
Women
Total
29 (20.4%) 77 (9.3)
113 (79.6%) 84.4 (7.4)
142 82.9 (8.32)
61–89 31.0% 41.4% 27.6% 10.3% 58.6% 6.9% 24.1% 16.7 (3.14) 0
60–99 19.4% 36.1% 44.4% 15.5% 20.9% .9% 62.7% 14.2 (3.04) 10.3%
60–99 21.9% 37.2% 40.9% 14.4% 28.8% 2.2% 54.7% 14.7 (3.22) 8.1%
50% 50%
77.0% 12.6%
71.2% 20.7%
69%
70.8%
70.4%
6.9% 13.8% 10.3% 0
14.2% 8% 4.7% 0.9%
12.7% 9.2% 4.9% 0.7%
25.9% 48.1% 25.9% 12.0 (6.2) 2–27 20.7% 20.7% 24.1% 34.5% 27.6 3.4 3.4 17.2 10.3 20.7 3.4 13.8
23.9% 46.8% 28.4% 13.1 (5.5) 0–26 8.0% 23.9% 31.0% 37.2% 13.3 8.8 8.8 4.4 11.5 30.1 8.0 14.2
24.3% 47.1% 27.9% 12.8 (5.6) 0–27 10.6% 23.2% 29.6% 36.6% 16.2 7.7 7.7 7.0 11.3 28.2 7.0 14.1
were spouses. Ninety percent of institutional caregivers were nurses.
6. Acceptability, feasibility, and responses’ variability 6.1. Acceptability One hundred thirty-seven of the 142 patients accepted to complete the questionnaire. 6.2. Feasibility Although 14 subjects were able to complete the questionnaire on their own, the vast majority (n ⫽ 123) responded
1058
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
with the help of a trained interviewer. Subjects who selfadministered the questionnaire had a significantly higher MMSE score than those who did not (18 vs. 12.4; t ⫽ 3.72; P ⬍ .0001). Average time to complete the questionnaire was 15.3 min, but the variability (SD ⫽ 13.9) was high, with some subjects taking more than an hour. This time is not significantly linked with an MMSE score or with EQ-5D dimensions. As shown in Table 2, the response rate for each of the five items on the EQ-5D was between 90 and 98%. More than 80% of the subjects (114 of 137) answered all five items; all the subjects but seven answered at least four items. The response rate was much higher for all dimensions when subjects with an MMSE equal to or below 5 were eliminated (92 to 100%, according to the item). It was even higher when only subjects with an MMSE above 14 were included (94 to 100%). Only the VAS seemed to pose problems, with a nonresponse rate of nearly 22%. This rate was 18% for subjects with a MMSE ⬎5 and 11.8% with an MMSE ⬎14. 6.3. Responses’ variability No ceiling or floor effect was observed (Table 2), and the response rate for each choice on the five items describing health status was never below 10% or above 57%. The entire VAS was covered, with the possible minimum (0) and maximum (100) used, and the standard deviation reflecting good variability in the responses. A profile could be established for the 114 subjects who answered all five items. Fifty-nine different profiles were found in the sample out of the theoretically possible 243 (35). The most common profiles reflected perfect health (code 11111), chosen by 17
Dimension
Category
Number
Percentage of responses
Mobility
No problem Some problem Extreme problem No response No problem Some problem Extreme problem No response No problem Some problem Extreme problem No response No problem Some problem Extreme problem No response No problem Some problem Extreme problem No response
60 54 16 7 74 36 20 7 62 36 25 14 50 67 17 3 53 58 20 6
43.8 39.4 11.7 5.1 54.0 26.3 14.6 5.1 45.3 26.3 18.2 10.2 36.5 48.9 12.4 2.2 38.7 42.3 14.6 4.4
62.9 (23.2)
No response ⫽ 21.9%
Usual activities
Pain/discomfort
Anxiety/depression
VAS (0–100) Mean(s)
7. Test-retest reliability Test-retest reliability was determined by having the questionnaire administered a second time to 47 randomly selected patients after a 3-day interval. Kappa coefficients obtained (Table 3) reflected a moderate concordance, and even a weak concordance for pain/discomfort. The significant intraclass correlation coefficient found for the VAS showed average correlation and concordance [ICC(2.1) ⫽ 0.44, P ⫽ .004]. The mean difference in evaluation between the two administrations was moderate (5.72 points for a 0–100 scale) and not significant, but the absolute difference was 18.3 points. Furthermore, there was more than a 10-point difference in the evaluations given by nearly one in two subjects (45.5%). The mean value of overall scores was 8.4, with a standard deviation of 2.6. The test-retest reliability of this overall score as reflected in an intraclass correlation coefficient was satisfactory [ICC(2.1) ⫽ 0.74, P ⫽ .0001]. Because the questionnaire was designed to produce profiles, their test-retest reliability was determined. Of the 37 subjects who answered all five items at both administrations, a third (13 subjects) reproduced the same profile. The profile for five subjects corresponded to perfect health. 7.1. Validity
Table 2 Responses’ distribution on the EuroQol
Self-care
subjects (14.9%), isolated pain (code 11121, 10 subjects, 8.8%) or anxiety (code 11112, 5 subjects, 4.4%), or a combination of the two (11122, 6 subjects, 5.3%). The profiles of five subjects (4.4%) reflected an absence of self-care problems and moderate problems in the other dimensions (code 21222).
In the absence of a gold standard, there is no objective external criterion for testing the validity of a health-related quality-of-life questionnaire. A solution is to combine an array of findings, each of which can provide at least an indication, if not actual proof, of validity. Several analyses were performed to study different aspects of validity. Table 3 Test-retest reliability Domains Mobility Self-care Usual activities Pain/discomfort Anxiety/ depression
VAS (0–100) Overall score (1–15)
Kappa statistic
% of same choice
N
0.59 0.51 0.59 0.34 0.53
75.6 73.3 75.0 62.8 71.4
45 45 40 43 42
ICC coefficient 0.44 (P ⫽ .004) 0.74 (P ⬍ .0001)
Mean difference 5.72 .11
Correlation r ⫽ 0.45 r ⫽ 0.74
N 33 38
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
1059
family proxies (ICC ⫽ 0.41, P ⬍ .0001) and between subjects and their care-provider proxies (ICC ⫽ 0.42, P ⬍ .0001). The concordance between the proxies was no better (ICC ⫽ 0.54, P ⬍ .0001). The profiles of the 114 subjects who answered all five items corresponded exactly with their family caregiver’s evaluations in only 4.4% of the cases. Correspondence with their institutional caregiver occurred in less than 2% of the cases. Between-proxy concordance was found for 13 of the 114 subjects (11%). Although the “11111” profile (no problems with anything) was the most frequently found among patients (14.9%), the “22222” (some problems with everything) profile emerged most frequently among the institutional caregivers (7.5%) and the family ones (8.5%). These results may lead to conclude that the instrument is not accurate for dementia patients, so further analysis were performed to try to verify if patients’ responses are actually irrelevant.
7.2. Agreement between subjects and proxies The use of information provided by proxies, usually informal or professional caregivers, is a way to obtain supposedly better information concerning cognitively impaired persons [33]. In our sample, kappa coefficients (Table 4) indicated no more than mediocre agreement between the subjects and their proxies. Only the agreement on mobility, the most observable of the dimensions investigated, produced an acceptable level of agreement (kappa ⫽ 0.53 for the institutional caregiver and 0.44 for the family one). As it can be seen, the percent of agreement is poorer when only subjects with MMSE ⭐10 are kept (kappa coefficients were not calculated for the small sample size and because the margins of the tables are very unbalanced). Similarly, the evaluations on the VAS produced significant but low linear correlations and large and significant differences in means, especially for the relations between patient judgments and the judgments of their family caregiver (r ⫽ 0.235). Strict concordance was weak, as measured by intraclass correlation coefficients [ICC(2.1) ⫽ 0.20 for family caregiver, and ICC(2.1) ⫽ 0.23 for institutional caregivers]. The agreement between the two kinds of caregivers, although higher, remained below the usually accepted level, except on the mobility item. This agreement seemed better when only subjects with MMSE ⭐10 are kept. Intraclass correlation coefficient was higher for VAS [ICC(2.1) ⫽ 0.40, P ⬍ .0001]. The intraclass correlation coefficients for the overall scores calculated on subjects’ and proxies’ responses reflected average concordance between subjects and their
7.3. Construct validity and relevance of responses Self-assessed health-related quality of life could be expected to decrease on the VAS in step with poorer health states described in the items. A clear decrease in the average quality-of-life values in fact occurred in the expected direction for the five dimensions (Table 5), and was found to be significant overall for usual activities, mobility, pain/ discomfort, and anxiety/depression. The overall scores on the five items were significantly correlated with the self-evaluation scores on the VAS (r ⫽ 0.43, P ⫽ 0001). Relations between ADL and the five dimensions of EQ5D have been investigated. We found expected correlations between the Katz indicator and mobility (F ⫽ 16.4,
Table 4 Interrater agreement Subject and family proxy All subjects Kappa(%agreement) Mobility Self-care Usual activities Pain/Discomfort Anxiety/depression MMSE⭐10 %agreement Mobility Self-care Usual activities Pain/discomfort Anxiety/depression VAS ICC Overall score ICC
0.44(65.8%)(N ⫽ 117) 0.21(42%)(N ⫽ 119) 0.17(40.7%)(N ⫽ 113) 0.22(54.6%)(N ⫽ 119) 0.10(45.3%)(N ⫽ 117)
Subject and institutional proxy
0.53(71.9%)(N ⫽ 128) 0.12(34.4%)(N ⫽ 128) 0.00(27.7%)(N ⫽ 119) 0.16(52.3%)(N ⫽ 130) 0.07(43.4%)(N ⫽ 128)
Family proxy and institutional proxy
0.61(76.4%)(N ⫽ 123) 0.29(58.5%)(N ⫽ 123) 0.36(62.5%)(N ⫽ 120) 0.21(57.9%)(N ⫽ 121) 0.25(60.2%)(N ⫽ 123)
64.9 36.9 21.6 46.2 47.2
67.5 27.5 28.5 41.5 33.3
66.7 66.7 70.5 59.1 73.3
0.20 (P ⫽ .01) (r ⫽ 0.235) (N ⫽ 99)
0.23 (P ⫽ .006) (r ⫽ 0.25) (N ⫽ 104)
0.40 (P ⬍ .0001) (r ⫽ 0.43) (N ⫽ 121)
0.41 (P ⬍ .0001) (r ⫽ 0.51) (N ⫽ 105)
0.42 (P ⬍ .0001) (r ⫽ 0.52) (N ⫽ 110)
0.54 (P ⬍ .0001) (r ⫽ 0.55) (N ⫽ 118)
1060
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
Table 5 Scoresa on the VAS, visual analog scale, (m, s) according to responses on dimensions
Mobility Self-care Usual activities Pain/ discomfort Anxiety/ depression
No problem
Some problem
Extreme problem
F (P)
71.9 (22.0) 66.5 (21.6) 73.2 (19.5)
58.4 (19.6) 57.2 (25.2) 56.2 (19.4)
44 (24.1) 56.4 (24.2) 51.2 (27.2)
10.98 (.0001) 2.2 (.12) 10.64 (.0001)
69.8 (22.6)
59.3 (22.9)
55.9 (23.3)
3.10 (.049)
72.1 (22.1)
57.3 (23.3)
54.4 (19.2)
6.41 (.002)
a
0 indicates “worst imaginable health state.” 100 indicates “best imaginable health sate.”
P ⬍ .0001), self-care (F ⫽ 6.3, P ⬍ .0001), usual activities (F ⫽ 6.8, P ⬍ .002), and pain (F ⫽ 6.8, P ⬍ .002). These correlations are indicative of convergent validity. As expected, no relation was found between this indicator of ADL and anxiety, evidencing of discriminant validity. VAS scores were not linked with ADL scores, evidencing the difference between incapacities and subjective global perceived quality of life. Based on findings in the general population, women were expected to give a higher rating than men on anxiety/depression and a poorer overall assessment of their health. These expectations were confirmed in this study, with significant results on anxiety/depression (χ2 ⫽ 10.49, P ⫽ .005), VAS [F(1, 105) ⫽ 3.97, P ⫽ .049], and overall score [F(1, 113) ⫽ 7.76, P ⫽ .006]. We also expected that the HRQOL should be related to age. The responses to the five dimensions indicated deterioration in health status with aging, except for pain (usual activities: F ⫽ 3.6, P ⫽ .03, self-care: F ⫽ 3.3, P ⫽ .04, anxiety/depression: F ⫽ 5, P ⫽ .008, mobility: F ⫽ 6.8, P ⫽ .002). Age did not seem related to self-evaluations of overall state of health on the VAS (r ⫽ ⫺0.18, ns). However, the shape of this relationship between age and VAS was interesting. For the youngest subjects, perceived quality of life tended to be quite good, but with advancing age, responses’ variability increased, and, if more and more negative assessments gradually emerged, positive evaluations were still present. One also would expect the self-evaluated quality of life to be poorer with a greater severity of dementia. The results were more complex than that, and quality of life measured by the VAS did not vary with MMSE score. For the five dimensions, only anxiety/depression was associated with MMSE score, with moderately anxious or depressed subjects having the higher MMSE score (F ⫽ 6.86, P ⫽ .001). No significant relations have been found between CDR and any of the five dimensions or the VAS. 8. Discussion In this study, the EQ-5D was administered to a sample of patients with dementia as defined by internationally accepted
criteria. Even though EQ-5D is intended to be self-administrated, the questionnaire was almost always administered in our study by an interviewer. Given the impairments in this population and the methodology used in previous studies, allowance was made for this possibility in the study design. Some studies have found no differences between the results from self-administered and interviewer-administered instruments [34,35] while other ones found the opposite [36]. It is impossible to know whether the use of interviewers influenced the subjects’ responses in this study. Few subjects refused to complete the questionnaire. Although the nonresponse rate for the first five questions was related to dementia severity, it accounted for less than 10% overall. These results are similar to those found in healthy women aged 75 or over not specifically suffering from dementia [10]. Highest nonresponse rate was found for the VAS as in the study of Coast [11] in a sample of hospitalized but not confused patients over 65. According to recognized criteria, the reliability of this questionnaire for our subjects was not very high. A weak test-retest reliability was also found by Dorman [20] in subjects following a stroke, but the discordance frequency was lower than in our study. Test-retest method provides more information on reliability when the dimensions measured are stable over time, while with EQ-5D, patients are asked to describe their state of health on the day of questionnaire administration. The lack of reliability might reflect changes that actually occurred in the patients’ health. In fact, mobility, the most stable dimension, showed the best agreement, with 76% of the subjects assigning it the same rating in the test and retest conditions, and pain, the most unstable dimension, showed the worst agreement. The mean difference (5.72) between the test and retest conditions on the VAS in this study was not much higher than the mean (4.97 point difference) found by Brazier et al. [10] among healthy women aged 75 or over. This difference was not significantly linked with either MMSE scores (r ⫽ 0.058; ns) or advancing age (r ⫽ 0.078; ns). It perhaps reflected subjective impression of well-being, which can vary from day to day. The lack of association between MMSE, CDR, and EQ5D may be considered as a direct consequence of lack of insight into the subjects’ illness but we found relations between the Katz objective indicator of ADL and self-report of mobility, self-care, usual activities, and pain and not with anxiety. Other results brought arguments that subjects’ responses were not random or odd data. The mean global self-perceived health found in this study was consistent with results obtained in other studies. A clear decrease in VAS was associated with poorer heath states self-attributed on the five dimensions. As expected, dimensions of EQ-5D, except pain, were linked with age. Women described themselves as more anxious or depressed than men, and having poorer health. The weak agreement between the judgments of the subjects with dementia and those of other people, the family,
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
and institutional proxies, is known. In a review of health status measures [37] little evidence was brought to support the validity of proxy assessments in cognitively impaired populations. Such discrepancies have been found in subjects suffering from dementia [25] but also with subjects who were neither elderly nor demented [3,5,15,38–44]. Discordance were also found between external raters who had to value, on the VAS, the HrQOL of “vignettes” showing the responses to the five items of virtual subjects [45]. The greater discrepancies found that when MMSE was ⭐10 it does not necessarily imply that patient’s judgments are more and more questionable as their dementia makes progress, but it might actually reflect greater difficulty for significant others to decode these patients’ health status. Poor agreement was also found between the institutional and family caregivers. Variability of responses, discrepancies, and inconsistent ratings in the valuations of the same “vignettes” have also been systematically found [46–53]. The question of whose ratings are more valid or truer as asked by Selai [26] remains. Such results led more and more authors to conclude that assessments’ proxies should be used with cautious [6–9,54]. We consider that the three sources of assessment have to be taken into account according to the aim of the assessment, even if each source may be influenced by, for instance, disease or anosognosia for the patient, physical or psychologic burden for the family, or work organization for the professionals. We compared the obtained mean on the VAS in this study with other ones. As shown in Table 6, this evaluation reflects a self-perceived health status poorer than that of healthy women aged 75 and over [10] and of subjects aged 65 and over [18], but similar to that found in subjects over 50 with physical illnesses [12]. When compared with subjects suffering from mild dementia (CDR ⭐2) [25], subjects of our sample stated a poorer HRQOL. We can also compare the 14.9% of subjects in this study rating themselves as having no problem on the five dimensions with the 48% obtained by Coucill et al. [25] with subjects suffering from questionable to moderate dementia. So the responses of these study’s subjects may be plausible. Table 6 Comparison with other studies
Present study Johnson and Coons [15] Brazier et al. 6 [10] Dolan [16] Fransen and Edmonds [12] Coucill [22] a
Age
Subjects
Mean VASa
60–74 75–99 65–74 75⫹ 75–79 80–84 85⫹ 52–91 ⬎50
Dementia
Colles’ fracture Osteoarthritis
53–91
Dementia (mild)
70.3 60.9 81.5 74.4 69 66 65 71.6 62–73, depending on severity 71.5
General General
0 indicates “worst imaginable health state.” 100 indicates “best imaginable health state.”
1061
Otherwise, one may wonder about the impact of comorbidities, such as behavioral symptoms, which are common in persons with dementia, and could have profound influences on certain domains of the EQ-5D. During the questionnaire administration, the investigator noted signs of agitation, when present. Only 13.9% of the subjects were in this case. No significant influence of this factor had been shown on overall score [F(1, 112) ⬍ 1]. In the same way, no differences were found between psychotropic drugs users and non users [F(1, 115) ⬍ 1] or depending on the dementia’s etiology [F(3, 110) ⫽ 1.55, P ⫽ .21]. Further investigations are needed on this topic.
9. Conclusion Overall, this study seems to show that an evaluation of quality of life with the EQ-5D questionnaire is possible in patients with dementia. The severity of the pathology has little effect on the instrument’s reliability and validity, but it does affect its acceptability. The questionnaire was well received and the response rate was good, except for the VAS, which seems to present problems. Even if the test-retest reproducibility and the agreement between patient responses and proxy responses were not very strong, further support for the validity came from various analyses, which suggested that the subjects’ responses, in fact, reflected their subjective perceived mental and physical health, the goal of the instrument. Insofar as these patients seemed highly aware of their condition, new studies are needed to find observable indicators in people with dementia that are correlated with these internal states. The decoding of such signs by significant others might well pave the way to improving the quality of life and well-being of these people. Health-related quality of life will then no longer be considered merely as a measure, but as a goal.
Acknowledgments This study was made possible by funding from: DG V of the European Commission, Contract No. SOC972016 18O5F03(97CVVF34180); INSERM, Contract No. 4R0 02C; The Conseil Re´gional de Champagne Ardenne; The Recherche et Partage foundation; and The Re´gate association.
References [1] Lobo A, Launer LJ, Fratiglioni L, Andersen K, Di Carlo A, Breteler MM, Copeland JR, Dartigues JF, Jagger C, Martinez-Lage J, Soininen H, Hofman A. Prevalence of dementia and major subtypes in Europe. A collaborative study of population based cohorts. Neurologic Diseases in the Elderly Research Group. Neurology 2000;54:S4–9. [2] Albert SM, Del Castillo-Castaneda C, Sano M, Jacobs DM, Marder K, Bell K, Bylsma F, Lafleche G, Brandt J, Albert M, Stern Y. Quality
1062
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10] [11] [12]
[13]
[14]
[15]
[16] [17]
[18] [19] [20]
[21]
[22]
[23]
[24]
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063 of life in patients with Alzheimer’s disease as reported by patient proxies. J Am Geriatr Soc 1996;44(11):1342–7. Magaziner J. Use of proxies to measure health and functional outcomes in effectiveness research in persons with Alzheimer’s disease and related disorders. Alzheimer Dis Assoc Disord 1997;11(6):168–74. Brod M, Stewart AL, Sands L, Walton P. Conceptualization and measurement of quality of life in dementia: The Dementia Quality of Life Instrument (DQoL). Gerontologist 1999;39(1):25–35. Dorman PJ, Waddell F, Slattery J, Dennis M, Sandercock P. Are proxy assessments of health status after stroke with the EQ-5D questionnaire feasible, accurate and unbiased? Stroke 1997;28(10):1883–7. Hays RD, Vickrey BG, Hermann BP, Perrine K, Cramer J, Meador K, Spritzer K, Devinsky O. Agreement between self reports and proxy reports of quality of life in epilepsy patients. Qual Life Res 1995;4(2):159–68. Andresen EM, Vahle VJ, Lollar D. Proxy reliability: health-related quality of life (HRQoL) measures for people with disability. Qual Life Res 2001;10(7):609–19. Yip JY, Wilber KH, Myrtle RC, Grazman DN. Comparison of older adult subject and proxy responses on the SF-36 health-related quality of life instrument. Aging Ment Health 2001;5(2):136–42. Kiyak HA, Teri L, Borson S. Physical and functional health assessment in normal aging and in Alzheimer’s disease: self-report vs family reports. Gerontologist 1994;34(3):324–30. Brazier JE, Walters SJ, Nicholl JP, Kohler B. Using the SF-36 and EQ-5D on an elderly population. Qual Life Res 1996;5:195–204. Coast J, Peters TJ, Richards SH, Gunnell DJ. Use of the EuroQol among elderly acute care patients. Qual Life Res 1998;7:1–10. Fransen M, Edmonds J. Reliability and validity of the EuroQol in patients with osteoarthritis of the knee. Rheumatol 1999;38(9): 807–13. Kind P. In: Spilker B, ed. The EuroQol instrument: an index of healthrelated quality of life. In: Quality of life and pharmacoeconomics in clinical trials. Philadelphia: Lippincott-Raven; 1996. Folstein MF, Folstein SE, Mc Hugh PR. Mini mental state. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12(3):189–98. Hughes CP, Berg L, Danziger WL, Coben LA, Martin RL. A new clinical scale for the staging of dementia. Br J Psychiatry 1982; 140:566–72. Katz S, Down T, Cash H, Grotz R. Progress in development of index of, ADL. Gerontologist 1970;10:20–30. Brazier J, Jones N, Kind P. Testing the validity of the Euroqol and comparing it with the SF-36 Health Survey Questionnaire. Qual Life Res 1993;2(3):169–80. Johnson JA, Coons SJ. Comparison of the EQ-5D and SF-12 in an adult US sample. Qual Life Res 1998;7(2):155–66. Dolan PJ, Torgerson D, Kumar Kakarlapudi T. Health-related quality of life of Colles’ fracture patients. Osteoporos Int 1999;9:196–9. Dorman PJ, Waddell F, Slattery J, Dennis M, Sandercock P. Is the Euroqol a valid measure of health-related quality of life after stroke? Stroke 1997;28(10):1876–82. Dorman PJ, Slattery J, Farrell B, Dennis M, Sandercock P. Qualitative comparison of the reliability of health status assessments with the EuroQol and SF-36 questionnaires after stroke. Stroke 1998;29(1):63–8. Dorman PJ, Dennis M, Sandercock P. How do scores on the EuroQol relate to scores on the SF-36 after stroke? Stroke 1999;30(10): 2146–51. Essink-Bot ML, Krabbe PF, Bonsel GJ, Aaronson NK. An empirical comparison of four generic health status measures. The Nottingham Health Profile, the Medical Outcomes Study 36-item Short Form Health Survey, the COOP/WONCA charts and the EuroQol instrument. Med Care 1997;35(5):522–37. Hurst NP, Jobanputra P, Hunter M, Lambert CM, Lochead A, Brown H. Validity of EuroQol-a generic health status instrument in patients with rheumatoid arthritis. Br J Rheumatol 1994;33:655–62.
[25] Coucill W, Bryan S, Bentham P, Buckley A, Laight A. EQ-5D in patients with dementia. Med Care 2001;39(8):760–71. [26] Selai C. Assessing quality of life in dementia. Med Care 2001;39(8): 753–5. [27] Lawton MP. Assessing quality of life in Alzheimer disease research. Alzheimer Dis Assoc Disord 1997;11(6):91–9. [28] Kerner DN, Patterson TL, Grant I, Kaplan RM. Validity of the quality of Well-Being Scale for patients with Alzheimer’s disease. J Aging Health 1998;10(1):44–61. [29] Rabins PV, Kasper JD. Measuring quality of life in dementia: conceptual and practical issues. Alzheimer Dis Assoc Disord 1997;11(6): 100–4. [30] Cohen J. Weighted kappa: nominal scale agreement with provision for scaled disagreement or partial credit. Psychol Bull 1968;70(4):213–20. [31] Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159–74. [32] Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull 1977;86(2):420–8. [33] Corder LS, Woodbury MA, Manton KG. Proxy response patterns among the aged: effects on estimates of health status and medical care utilization from the 1982–1984 long term care surveys. J Clin Epidemiol 1996;49(2):173–82. [34] Cook DJ, Guyatt GH, Juniper E, Griffith L, McIlroy W, Willan A, Jaeschke R, Epstein R. Interviewer versus self-administered questionnaires in developing a disease-specific, health-related quality of life instrument for asthma. J Clin Epidemiol 1993;46(6):529–34. [35] Weinberger M, Oddone EZ, Samsa GP, Landsman PB. Are healthrelated quality-of-life measures affected by the mode of administration? J Clin Epidemiol 1996;49(2):135–40. [36] Grootendorst PV, Feeny DH, Furlong W. Does it matter whom and how you ask? Inter- and intra-rater agreement in the Ontario Health Survey. J Clin Epidemiol 1997;50(2):127–35. [37] Riemsma RP, Forbes CA, Glanville JM, Eastwood AJ, Kleijnen J. General health status measures for people with cognitive impairment: learning disability and acquired brain injury. Health Technol Assess 2001;5(6):1–100. [38] Ostbye T, Tyas S, McDowell I, Koval J. Reported activities of daily living: agreement between elderly subjects with and without dementia and their caregivers. Age Ageing 1997;26(2):99–106. [39] Rothwell PM, McDowell Z, Wong CK, Dorman PJ. Doctors and patients don’t agree: cross sectional study of patients’ and doctors’ perceptions and assessments of disability in multiple sclerosis. BMJ 1997;314:1580–3. [40] Sainfort F, Becker M, Diamond R. Judgments of quality of life of individuals with severe mental disorders: patient self-report versus provider perspectives. Am J Psychiatry 1996;153(4):497–502. [41] Santos-Eggimann B, Zobel F, Clerc Be´rod A. Functional status of elderly home care users: do subjects, informal and professional caregivers agree? J Clin Epidemiol 1999;52(3):181–6. [42] Sneeuw KC, Aaronson NK, Osoba D, Muller MJ, Hsu MA, Yung WK, Brada M, Newlands ES. The use of significant others as proxy raters of the quality of life of patients with brain cancer. Med Care 1997;35(5):490–506. [43] Teri L, Wagner AW. Assessment of depression in patient with Alzheimer’s disease: concordance among informants. Psychol Aging 1991; 6(2):280–5. [44] Volicer L, Camberg L, Hurley AC, Ashley J, Woods P, Ooi WL, McIntyre K. Dimensions of decreased psychological well-being in advanced dementia. Alzheimer Dis Assoc Disord 1999;13(4):192– 201. [45] Polsky D, Willke RJ, Scott K, Schulman KA, Glick HA. A comparison of scoring weights for the EuroQol derived from patients and the general public. Health Econ 2001;10(1):27–37. [46] van Agt HM, Essink-Bot ML, Krabbe PF, Bonsel GJ. Test-retest reliability of health state valuations collected with the EuroQol questionnaire. Soc Sci Med 1994;39(11):1537–44.
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063 [47] Badia X, Roset M, Herdman M. Inconsistent responses in three preference-elicitation methods for health states. Soc Sci Med 1999; 49(7):943–50. [48] Dolan P, Kind P. Inconsistency and health state valuations. Soc Sci Med 1996;42(4):609–15. [49] Hurst NP, Kind P, Ruta D, Hunter M, Stubbings A. Measuring healthrelated quality of life in rheumatoid arthritis: validity, responsiveness and reliability of EuroQol (EQ-5D). Br J Rheumatol 1997;36(5): 551–9. [50] Krabbe PF, Stouthard ME, Essink-Bot ML, Bonsel GJ. The effect of adding a cognitive dimension to the EuroQol multiattribute healthstatus classification system. J Clin Epidemiol 1999;52(4):293–301.
1063
[51] Krabbe PF, Essink-Bot ML, Bonsel GJ. The comparability and reliability of five health-state valuation methods. Soc Sci Med 1997;45(11): 1641–52. [52] Macran S, Kind P. “Death” and the valuation of health-related quality of life. Med Care 2001;39(3):217–27. [53] Suarez-Almazor ME, Conner-Spady B, Kendall CJ, Russell AS, Skeith K. Lack of congruence in the ratings of patients’ health status by patients and their physicians. Med Decis Making 2001;21(2):113–21. [54] Novella JL, Jochum C, Jolly D, Morrone I, Ankri J, Bureau F, Blanchard F. Agreement between patients’ and proxies’ reports of quality of life in Alzheimer’s disease. Qual Life Res 2001;10(5):443–52.
Use of the EQ-5D among patients suffering from dementia J. Ankria,*, B. Beaufilsb, J.-L. Novellac, I. Morroned, F. Guillemine, D. Jollyf, L. Plotong, F. Blanchardc a
Hoˆpital Ste Pe´rine, Universite´ de Paris V, RFR 12 Sante´ Vieillissement Socie´te´, 49 rue Mirabeau 75016 Paris, France b Universite´ Paris VIII, RFR 12 Sante´ Vieillissement Socie´te´, 49 rue Mirabeau 75016 Paris, France c Me´decine interne et ge´rontologie clinique, hoˆpital Se´bastopol 51092 Reims Cedex, France d Re´e´ducation fonctionnelle, hoˆpital Se´bastopol, 51092 Reims Cedex, France e Ecole de Sante´ Publique, EA 1124, BP 184 54505, Vandoeuvre les Nancy, France f De´partement d’information me´dical, hoˆpital Maison Blanche, 51092 Reims Cedex, France g Universite´ Lumie`res, 69676 Bron Cedex, France Accepted 12 May 2003
Abstract Background and objective: This study was designed to determine the acceptability, feasibility, reliability, and validity of the French version of EQ-5D measuring HRQol in subjects with dementia. Methods: EQ-5D was administered to 142 subjects. The feasibility and acceptability were determined by the refusal rate, the type of administration, and the percentage and distribution of missing data. Test-retest reliability was studied by kappa coefficients and validity by agreement between subjects’ and proxies’ assessments. Results: The response rate was satisfactory. The instrument discriminated well among the subjects. Test-retest reliability was average. The validity was poor if we consider the agreement between patients’ and caregivers’ reports, but other criteria of validity produced better results. Subjects’ responses on each dimension were related with their global judgment of health in the expected direction. Significant relations were found between the Katz index of ADL and self-rated difficulties only for expected dimensions. Relations with age and with gender were in line with expectations. Conclusion: Results led to consider that patients’ responses are not entirely devoid of judgment. It seems that dementia patients are capable of expressing their health-related quality of life through a brief instrument as the EQ-5D. 쑖 2003 Elsevier Inc. All rights reserved. Keywords: Quality of life; Dementia; Alzheimer’s disease; HRQol; EQ-5D
1. Introduction Health-related quality of life (HRQOL) has become a high priority in health and social services for the elderly, a population in which cognitive function is sometimes impaired because of dementia. The prevalence of dementia in people over 65 is 5%, but the rate increases sixfold in people over 90 [1]. Factors associated with dementia can pose methodologic problems in evaluating quality of life in this population, raising questions about the validity of such evaluations. Impaired memory, judgment, and language, which are typical of dementia, may make it impossible to administer a quality-of-life questionnaire. Interpreting a self-evaluation of health-related quality of life in patients denying their disease state may also be problematic. Given the frequency of psychologic and behavioral problems that, themselves, * Corresponding author. Tel.: 33-1-44-96-32-14; fax: 33-1-44-96-31-46. E-mail address: [email protected] (J. Ankri). 0895-4356/03/$ – see front matter 쑖 2003 Elsevier Inc. All rights reserved. doi: 10.1016/S0895-4356(03)00175-6
undermine quality of life, one might question the pertinence of such evaluations. But if a patient is able to complete a self-assessment of HRQOL, may this fact be considered as a valid indicator of her (his) HRQOL in itself? The effects of intellectual deterioration on subjects’ comprehension, expression of expectations and wishes, and language, have led certain investigators to conclude that these patients are not by themselves able to evaluate their quality of life. Therefore, an indirect approach is often taken, relying on family or institutional proxies for evaluation [2,3], but some researchers question the validity of such assessments [4–8]. On the other hand, Kiyak et al. [9], in a longitudinal study, showed that, contrary to a widely accepted belief, patients with Alzheimer’s disease are conscious of the decline in their functional and cognitive abilities. So, it makes sense to ask whether a brief HRQOL instrument may be used in such a population. There are several health-related quality-of-life scales in French that have been validated on elderly people, some
1056
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
suffering from cognitive impairment [10–12]. One of these, the EQ-5D [13], has the advantage of being a generic instrument, and therefore, allows for comparisons between people in different age groups and with different pathologies. Another advantage is that it contains few items, making it suitable for administration to subjects with dementia.
Consequences of dementia in patient’s functioning have also been recorded by Katz’s index of Activities of Daily Living (ADL [16]). The Katz index is a measure of independency of the subject in six basic activities of daily living (bathing, dressing, using the toilet, transferring bed to chair, continence, eating). According to the index, performance is summarized as grades implying more and more difficulties. 3.3. Instrument
2. Aim of the study This study was designed to ascertain the acceptability, feasibility, reliability, and validity of the EQ-5D for a French population of subjects suffering from dementia.
3. Method 3.1. Patient sample Subjects (male and female) were recruited by 16 French geriatric hospital centers belonging to the French “Re´seau Qualite´ de vie et De´mence” to ensure a broad range of disease severity and settings. The patient population was hospitalized in geriatric care units (for various conditions), institutionalized, or outpatients. To be included in the study, subjects had to be at least 60 years old and present a dementia according to the DSMIII-R diagnostic criteria. Patients who were blind, seriously hearing impaired, or could not speak French were not included. In the event of instability in the patient’s condition, which might modify his or her subjective health status during the period, the patient was not included. Proxies were recruited at the same time. The family caregiver was chosen from among people who knew and saw the patient most regularly and was capable of fitting the instrument. The professional caregiver was recruited from the health care team directly responsible for the patient: nurse’s aides and nurses who take care of the patient in the hospital or institution or physician in consultation. Informed consent was obtained from each patient and his or her family caregiver after the study has been explained and they had been given an explanatory letter. The Champagne Ardennes Ethics Committee approved the study. 3.2. Data collection For each patient, sex, age, marital status, school leaving age, residential arrangements, type of dementia diagnosed and Folstein’s Mini-Mental State Examination (MMSE [14]) have been recorded. The MMSE is a brief screening test (range 0–30) that assesses several cognitive functions and is one of the most widely used screening instrument for cognitive impairment in clinical setting and epidemiologic studies. The higher the MMSE score, the better the subject’s cognitive state is. Patient’s dementia stage was determined by clinicians using the Hughes’s Clinical Dementia Rating Scale (CDR [15]) in questionable (CDR0.5), mild (CDR1), moderate (CDR2), or severe stage (CDR3).
EQ-5D is a self-administered questionnaire in which responders have to evaluate their health state “today” on five dimensions: mobility, self-care, usual activities, pain/ discomfort, and anxiety/depression. A one-to-three scale is used for each dimension, representing no problem, some problem, or extreme problem, making it impossible for the subject to engage in the activity alone; for the pain and anxiety items, the three ratings relate to the severity of symptoms. The subject’s responses may be used to create a profile. The instrument also has a visual analog scale “thermometer” VAS, a 20-cm scale anchored at 0 “worse imaginable health state” and 100 “best imaginable health state.” The EQ-5D has been translated into several languages and has been validated and employed in many studies on general populations [17,18], on subjects with medical or surgical problems [5,17,19–24], and on subjects with mild dementia [25]. Two studies have validated the instrument in elderly subjects [10,11]. This generic instrument is designed to assess quality of life across diseases groups, and the question remains if any of its measures have face validity for use in dementia [26]. The questionnaire is intentionally brief, so the items do not cover all the facets of quality of life described in the literature [27]; but they do, however, appear to represent the most important dimensions of healthrelated quality of life. 3.4. Instrument administration Because of the particular problems in this population and in line with previous studies in which this procedure had to be done [4,5,17,18,28,29], it was decided that the EQ-5D questionnaire could be administered by a trained interviewer. In addition, the time taken to complete the EQ-5D questionnaire was noted. Institutional and family caregivers were also asked to complete the questionnaire in assessing patient’s health status. A subgroup of one patient in four was drawn from the sample for a new administration of the instrument three days after the first exposure to determine test-retest reliability. 4. Statistical methods 4.1. SPSS (version 9.0 for Windows) was used to analyze the data 4.1.1. Determination of an overall score The EQ-5D was designed to provide profiles on health status. The possible responses to each item are ordinal categories, and therefore, no allowance was made for an overall
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
score based on a combination of the responses. It appeared, however, that the instrument might legitimately be used to establish an overall score. If the ordinal responses are converted into numerical ratings, a score can be obtained for each item, and scores can be added. The refusal rate was taken as a measurement of acceptability of the questionnaire, administration type (self- or interviewer-administered), time to complete, and the number and distribution of missing data were taken as indicators of the feasibility of the questionnaire. Responses’ variability was also studied. Test-retest reliability was studied on a quarter of the subjects chosen at random. Test-retest was determined by kappa coefficients [30] of the responses for categorized data after elimination of agreement that would occur by chance. Following the classification of Landis and Koch [31], the kappa coefficients reflect moderate agreement when they are between 0.41 and 0.60, while those below this level indicate weak agreement. Intraclass correlation coefficients (ICC [32]) were obtained on continuous variables such as the VAS and the overall score. The two-way, mixed-effect model/absolute agreement definition ICC (2,1) model was chosen [32]. In lack of a gold standard, validity was studied by agreement between subjects’ and proxies’ assessments determined by kappa coefficients for the categorized data and by ICC for continuous data. The construct validity was tested in terms of several relationships hypothesized. Dimensions of EQ-5D and the overall scores were expected to be linked with VAS. Functional dimensions of EQ-5D and pain, but not the anxiety item, were expected to be linked with ADL. Women were expected to be more anxious than men in having poorer overall assessment of their health. Association of EQ-5D scores with age and with dementia severity was studied (ANOVA, Pearson correlation, chi-square according to variables). 5. Results A total of 142 patients were included in the study (Table 1). There were 29 men (20.4%) and 113 women (79.6%). Their average age was 82.9 years, with a range of 60 to 99 years, and one in five subjects lived at home. On average, the women were older, widows, and lived more often in an institution. They had less schooling than men in the sample. In most cases, the dementia was associated with Alzheimer’s disease (70.4%), followed by vascular dementia (12.7%). As measured by the CDR, slightly more than a quarter of the subjects (27.9%) presented severe dementia, and 33.8% had an MMSE equal to or lower than 10. Distribution of the severity of dementia and of demographic characteristics in this sample is difficult to compare with dementia general population because severity tools used in epidemiologic studies are not the same ones, and data issued from dementia general population are often sketchy. One hundred thirty-three institutional and 126 family caregivers were available. About 50% of the family caregivers were children, most often daughters (34%), and 28%
1057
Table 1 Subject characteristics at selection
Number Age
Residence
Marital status
Schoolleaving age
Diagnosis
CDR
MMSE
Katz
Age in years (s) Range Home Hospital Institution Single Married Divorced Widowed Mean (s) Less than 12 years 12–16 More than 16 years Alzheimer’s disease Vascular Alcoholic Other Probable deficit Light Moderate Severe Mean (s) Range 0–5 6–10 11–14 15 or over A B C D E F G H
Men
Women
Total
29 (20.4%) 77 (9.3)
113 (79.6%) 84.4 (7.4)
142 82.9 (8.32)
61–89 31.0% 41.4% 27.6% 10.3% 58.6% 6.9% 24.1% 16.7 (3.14) 0
60–99 19.4% 36.1% 44.4% 15.5% 20.9% .9% 62.7% 14.2 (3.04) 10.3%
60–99 21.9% 37.2% 40.9% 14.4% 28.8% 2.2% 54.7% 14.7 (3.22) 8.1%
50% 50%
77.0% 12.6%
71.2% 20.7%
69%
70.8%
70.4%
6.9% 13.8% 10.3% 0
14.2% 8% 4.7% 0.9%
12.7% 9.2% 4.9% 0.7%
25.9% 48.1% 25.9% 12.0 (6.2) 2–27 20.7% 20.7% 24.1% 34.5% 27.6 3.4 3.4 17.2 10.3 20.7 3.4 13.8
23.9% 46.8% 28.4% 13.1 (5.5) 0–26 8.0% 23.9% 31.0% 37.2% 13.3 8.8 8.8 4.4 11.5 30.1 8.0 14.2
24.3% 47.1% 27.9% 12.8 (5.6) 0–27 10.6% 23.2% 29.6% 36.6% 16.2 7.7 7.7 7.0 11.3 28.2 7.0 14.1
were spouses. Ninety percent of institutional caregivers were nurses.
6. Acceptability, feasibility, and responses’ variability 6.1. Acceptability One hundred thirty-seven of the 142 patients accepted to complete the questionnaire. 6.2. Feasibility Although 14 subjects were able to complete the questionnaire on their own, the vast majority (n ⫽ 123) responded
1058
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
with the help of a trained interviewer. Subjects who selfadministered the questionnaire had a significantly higher MMSE score than those who did not (18 vs. 12.4; t ⫽ 3.72; P ⬍ .0001). Average time to complete the questionnaire was 15.3 min, but the variability (SD ⫽ 13.9) was high, with some subjects taking more than an hour. This time is not significantly linked with an MMSE score or with EQ-5D dimensions. As shown in Table 2, the response rate for each of the five items on the EQ-5D was between 90 and 98%. More than 80% of the subjects (114 of 137) answered all five items; all the subjects but seven answered at least four items. The response rate was much higher for all dimensions when subjects with an MMSE equal to or below 5 were eliminated (92 to 100%, according to the item). It was even higher when only subjects with an MMSE above 14 were included (94 to 100%). Only the VAS seemed to pose problems, with a nonresponse rate of nearly 22%. This rate was 18% for subjects with a MMSE ⬎5 and 11.8% with an MMSE ⬎14. 6.3. Responses’ variability No ceiling or floor effect was observed (Table 2), and the response rate for each choice on the five items describing health status was never below 10% or above 57%. The entire VAS was covered, with the possible minimum (0) and maximum (100) used, and the standard deviation reflecting good variability in the responses. A profile could be established for the 114 subjects who answered all five items. Fifty-nine different profiles were found in the sample out of the theoretically possible 243 (35). The most common profiles reflected perfect health (code 11111), chosen by 17
Dimension
Category
Number
Percentage of responses
Mobility
No problem Some problem Extreme problem No response No problem Some problem Extreme problem No response No problem Some problem Extreme problem No response No problem Some problem Extreme problem No response No problem Some problem Extreme problem No response
60 54 16 7 74 36 20 7 62 36 25 14 50 67 17 3 53 58 20 6
43.8 39.4 11.7 5.1 54.0 26.3 14.6 5.1 45.3 26.3 18.2 10.2 36.5 48.9 12.4 2.2 38.7 42.3 14.6 4.4
62.9 (23.2)
No response ⫽ 21.9%
Usual activities
Pain/discomfort
Anxiety/depression
VAS (0–100) Mean(s)
7. Test-retest reliability Test-retest reliability was determined by having the questionnaire administered a second time to 47 randomly selected patients after a 3-day interval. Kappa coefficients obtained (Table 3) reflected a moderate concordance, and even a weak concordance for pain/discomfort. The significant intraclass correlation coefficient found for the VAS showed average correlation and concordance [ICC(2.1) ⫽ 0.44, P ⫽ .004]. The mean difference in evaluation between the two administrations was moderate (5.72 points for a 0–100 scale) and not significant, but the absolute difference was 18.3 points. Furthermore, there was more than a 10-point difference in the evaluations given by nearly one in two subjects (45.5%). The mean value of overall scores was 8.4, with a standard deviation of 2.6. The test-retest reliability of this overall score as reflected in an intraclass correlation coefficient was satisfactory [ICC(2.1) ⫽ 0.74, P ⫽ .0001]. Because the questionnaire was designed to produce profiles, their test-retest reliability was determined. Of the 37 subjects who answered all five items at both administrations, a third (13 subjects) reproduced the same profile. The profile for five subjects corresponded to perfect health. 7.1. Validity
Table 2 Responses’ distribution on the EuroQol
Self-care
subjects (14.9%), isolated pain (code 11121, 10 subjects, 8.8%) or anxiety (code 11112, 5 subjects, 4.4%), or a combination of the two (11122, 6 subjects, 5.3%). The profiles of five subjects (4.4%) reflected an absence of self-care problems and moderate problems in the other dimensions (code 21222).
In the absence of a gold standard, there is no objective external criterion for testing the validity of a health-related quality-of-life questionnaire. A solution is to combine an array of findings, each of which can provide at least an indication, if not actual proof, of validity. Several analyses were performed to study different aspects of validity. Table 3 Test-retest reliability Domains Mobility Self-care Usual activities Pain/discomfort Anxiety/ depression
VAS (0–100) Overall score (1–15)
Kappa statistic
% of same choice
N
0.59 0.51 0.59 0.34 0.53
75.6 73.3 75.0 62.8 71.4
45 45 40 43 42
ICC coefficient 0.44 (P ⫽ .004) 0.74 (P ⬍ .0001)
Mean difference 5.72 .11
Correlation r ⫽ 0.45 r ⫽ 0.74
N 33 38
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
1059
family proxies (ICC ⫽ 0.41, P ⬍ .0001) and between subjects and their care-provider proxies (ICC ⫽ 0.42, P ⬍ .0001). The concordance between the proxies was no better (ICC ⫽ 0.54, P ⬍ .0001). The profiles of the 114 subjects who answered all five items corresponded exactly with their family caregiver’s evaluations in only 4.4% of the cases. Correspondence with their institutional caregiver occurred in less than 2% of the cases. Between-proxy concordance was found for 13 of the 114 subjects (11%). Although the “11111” profile (no problems with anything) was the most frequently found among patients (14.9%), the “22222” (some problems with everything) profile emerged most frequently among the institutional caregivers (7.5%) and the family ones (8.5%). These results may lead to conclude that the instrument is not accurate for dementia patients, so further analysis were performed to try to verify if patients’ responses are actually irrelevant.
7.2. Agreement between subjects and proxies The use of information provided by proxies, usually informal or professional caregivers, is a way to obtain supposedly better information concerning cognitively impaired persons [33]. In our sample, kappa coefficients (Table 4) indicated no more than mediocre agreement between the subjects and their proxies. Only the agreement on mobility, the most observable of the dimensions investigated, produced an acceptable level of agreement (kappa ⫽ 0.53 for the institutional caregiver and 0.44 for the family one). As it can be seen, the percent of agreement is poorer when only subjects with MMSE ⭐10 are kept (kappa coefficients were not calculated for the small sample size and because the margins of the tables are very unbalanced). Similarly, the evaluations on the VAS produced significant but low linear correlations and large and significant differences in means, especially for the relations between patient judgments and the judgments of their family caregiver (r ⫽ 0.235). Strict concordance was weak, as measured by intraclass correlation coefficients [ICC(2.1) ⫽ 0.20 for family caregiver, and ICC(2.1) ⫽ 0.23 for institutional caregivers]. The agreement between the two kinds of caregivers, although higher, remained below the usually accepted level, except on the mobility item. This agreement seemed better when only subjects with MMSE ⭐10 are kept. Intraclass correlation coefficient was higher for VAS [ICC(2.1) ⫽ 0.40, P ⬍ .0001]. The intraclass correlation coefficients for the overall scores calculated on subjects’ and proxies’ responses reflected average concordance between subjects and their
7.3. Construct validity and relevance of responses Self-assessed health-related quality of life could be expected to decrease on the VAS in step with poorer health states described in the items. A clear decrease in the average quality-of-life values in fact occurred in the expected direction for the five dimensions (Table 5), and was found to be significant overall for usual activities, mobility, pain/ discomfort, and anxiety/depression. The overall scores on the five items were significantly correlated with the self-evaluation scores on the VAS (r ⫽ 0.43, P ⫽ 0001). Relations between ADL and the five dimensions of EQ5D have been investigated. We found expected correlations between the Katz indicator and mobility (F ⫽ 16.4,
Table 4 Interrater agreement Subject and family proxy All subjects Kappa(%agreement) Mobility Self-care Usual activities Pain/Discomfort Anxiety/depression MMSE⭐10 %agreement Mobility Self-care Usual activities Pain/discomfort Anxiety/depression VAS ICC Overall score ICC
0.44(65.8%)(N ⫽ 117) 0.21(42%)(N ⫽ 119) 0.17(40.7%)(N ⫽ 113) 0.22(54.6%)(N ⫽ 119) 0.10(45.3%)(N ⫽ 117)
Subject and institutional proxy
0.53(71.9%)(N ⫽ 128) 0.12(34.4%)(N ⫽ 128) 0.00(27.7%)(N ⫽ 119) 0.16(52.3%)(N ⫽ 130) 0.07(43.4%)(N ⫽ 128)
Family proxy and institutional proxy
0.61(76.4%)(N ⫽ 123) 0.29(58.5%)(N ⫽ 123) 0.36(62.5%)(N ⫽ 120) 0.21(57.9%)(N ⫽ 121) 0.25(60.2%)(N ⫽ 123)
64.9 36.9 21.6 46.2 47.2
67.5 27.5 28.5 41.5 33.3
66.7 66.7 70.5 59.1 73.3
0.20 (P ⫽ .01) (r ⫽ 0.235) (N ⫽ 99)
0.23 (P ⫽ .006) (r ⫽ 0.25) (N ⫽ 104)
0.40 (P ⬍ .0001) (r ⫽ 0.43) (N ⫽ 121)
0.41 (P ⬍ .0001) (r ⫽ 0.51) (N ⫽ 105)
0.42 (P ⬍ .0001) (r ⫽ 0.52) (N ⫽ 110)
0.54 (P ⬍ .0001) (r ⫽ 0.55) (N ⫽ 118)
1060
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
Table 5 Scoresa on the VAS, visual analog scale, (m, s) according to responses on dimensions
Mobility Self-care Usual activities Pain/ discomfort Anxiety/ depression
No problem
Some problem
Extreme problem
F (P)
71.9 (22.0) 66.5 (21.6) 73.2 (19.5)
58.4 (19.6) 57.2 (25.2) 56.2 (19.4)
44 (24.1) 56.4 (24.2) 51.2 (27.2)
10.98 (.0001) 2.2 (.12) 10.64 (.0001)
69.8 (22.6)
59.3 (22.9)
55.9 (23.3)
3.10 (.049)
72.1 (22.1)
57.3 (23.3)
54.4 (19.2)
6.41 (.002)
a
0 indicates “worst imaginable health state.” 100 indicates “best imaginable health sate.”
P ⬍ .0001), self-care (F ⫽ 6.3, P ⬍ .0001), usual activities (F ⫽ 6.8, P ⬍ .002), and pain (F ⫽ 6.8, P ⬍ .002). These correlations are indicative of convergent validity. As expected, no relation was found between this indicator of ADL and anxiety, evidencing of discriminant validity. VAS scores were not linked with ADL scores, evidencing the difference between incapacities and subjective global perceived quality of life. Based on findings in the general population, women were expected to give a higher rating than men on anxiety/depression and a poorer overall assessment of their health. These expectations were confirmed in this study, with significant results on anxiety/depression (χ2 ⫽ 10.49, P ⫽ .005), VAS [F(1, 105) ⫽ 3.97, P ⫽ .049], and overall score [F(1, 113) ⫽ 7.76, P ⫽ .006]. We also expected that the HRQOL should be related to age. The responses to the five dimensions indicated deterioration in health status with aging, except for pain (usual activities: F ⫽ 3.6, P ⫽ .03, self-care: F ⫽ 3.3, P ⫽ .04, anxiety/depression: F ⫽ 5, P ⫽ .008, mobility: F ⫽ 6.8, P ⫽ .002). Age did not seem related to self-evaluations of overall state of health on the VAS (r ⫽ ⫺0.18, ns). However, the shape of this relationship between age and VAS was interesting. For the youngest subjects, perceived quality of life tended to be quite good, but with advancing age, responses’ variability increased, and, if more and more negative assessments gradually emerged, positive evaluations were still present. One also would expect the self-evaluated quality of life to be poorer with a greater severity of dementia. The results were more complex than that, and quality of life measured by the VAS did not vary with MMSE score. For the five dimensions, only anxiety/depression was associated with MMSE score, with moderately anxious or depressed subjects having the higher MMSE score (F ⫽ 6.86, P ⫽ .001). No significant relations have been found between CDR and any of the five dimensions or the VAS. 8. Discussion In this study, the EQ-5D was administered to a sample of patients with dementia as defined by internationally accepted
criteria. Even though EQ-5D is intended to be self-administrated, the questionnaire was almost always administered in our study by an interviewer. Given the impairments in this population and the methodology used in previous studies, allowance was made for this possibility in the study design. Some studies have found no differences between the results from self-administered and interviewer-administered instruments [34,35] while other ones found the opposite [36]. It is impossible to know whether the use of interviewers influenced the subjects’ responses in this study. Few subjects refused to complete the questionnaire. Although the nonresponse rate for the first five questions was related to dementia severity, it accounted for less than 10% overall. These results are similar to those found in healthy women aged 75 or over not specifically suffering from dementia [10]. Highest nonresponse rate was found for the VAS as in the study of Coast [11] in a sample of hospitalized but not confused patients over 65. According to recognized criteria, the reliability of this questionnaire for our subjects was not very high. A weak test-retest reliability was also found by Dorman [20] in subjects following a stroke, but the discordance frequency was lower than in our study. Test-retest method provides more information on reliability when the dimensions measured are stable over time, while with EQ-5D, patients are asked to describe their state of health on the day of questionnaire administration. The lack of reliability might reflect changes that actually occurred in the patients’ health. In fact, mobility, the most stable dimension, showed the best agreement, with 76% of the subjects assigning it the same rating in the test and retest conditions, and pain, the most unstable dimension, showed the worst agreement. The mean difference (5.72) between the test and retest conditions on the VAS in this study was not much higher than the mean (4.97 point difference) found by Brazier et al. [10] among healthy women aged 75 or over. This difference was not significantly linked with either MMSE scores (r ⫽ 0.058; ns) or advancing age (r ⫽ 0.078; ns). It perhaps reflected subjective impression of well-being, which can vary from day to day. The lack of association between MMSE, CDR, and EQ5D may be considered as a direct consequence of lack of insight into the subjects’ illness but we found relations between the Katz objective indicator of ADL and self-report of mobility, self-care, usual activities, and pain and not with anxiety. Other results brought arguments that subjects’ responses were not random or odd data. The mean global self-perceived health found in this study was consistent with results obtained in other studies. A clear decrease in VAS was associated with poorer heath states self-attributed on the five dimensions. As expected, dimensions of EQ-5D, except pain, were linked with age. Women described themselves as more anxious or depressed than men, and having poorer health. The weak agreement between the judgments of the subjects with dementia and those of other people, the family,
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063
and institutional proxies, is known. In a review of health status measures [37] little evidence was brought to support the validity of proxy assessments in cognitively impaired populations. Such discrepancies have been found in subjects suffering from dementia [25] but also with subjects who were neither elderly nor demented [3,5,15,38–44]. Discordance were also found between external raters who had to value, on the VAS, the HrQOL of “vignettes” showing the responses to the five items of virtual subjects [45]. The greater discrepancies found that when MMSE was ⭐10 it does not necessarily imply that patient’s judgments are more and more questionable as their dementia makes progress, but it might actually reflect greater difficulty for significant others to decode these patients’ health status. Poor agreement was also found between the institutional and family caregivers. Variability of responses, discrepancies, and inconsistent ratings in the valuations of the same “vignettes” have also been systematically found [46–53]. The question of whose ratings are more valid or truer as asked by Selai [26] remains. Such results led more and more authors to conclude that assessments’ proxies should be used with cautious [6–9,54]. We consider that the three sources of assessment have to be taken into account according to the aim of the assessment, even if each source may be influenced by, for instance, disease or anosognosia for the patient, physical or psychologic burden for the family, or work organization for the professionals. We compared the obtained mean on the VAS in this study with other ones. As shown in Table 6, this evaluation reflects a self-perceived health status poorer than that of healthy women aged 75 and over [10] and of subjects aged 65 and over [18], but similar to that found in subjects over 50 with physical illnesses [12]. When compared with subjects suffering from mild dementia (CDR ⭐2) [25], subjects of our sample stated a poorer HRQOL. We can also compare the 14.9% of subjects in this study rating themselves as having no problem on the five dimensions with the 48% obtained by Coucill et al. [25] with subjects suffering from questionable to moderate dementia. So the responses of these study’s subjects may be plausible. Table 6 Comparison with other studies
Present study Johnson and Coons [15] Brazier et al. 6 [10] Dolan [16] Fransen and Edmonds [12] Coucill [22] a
Age
Subjects
Mean VASa
60–74 75–99 65–74 75⫹ 75–79 80–84 85⫹ 52–91 ⬎50
Dementia
Colles’ fracture Osteoarthritis
53–91
Dementia (mild)
70.3 60.9 81.5 74.4 69 66 65 71.6 62–73, depending on severity 71.5
General General
0 indicates “worst imaginable health state.” 100 indicates “best imaginable health state.”
1061
Otherwise, one may wonder about the impact of comorbidities, such as behavioral symptoms, which are common in persons with dementia, and could have profound influences on certain domains of the EQ-5D. During the questionnaire administration, the investigator noted signs of agitation, when present. Only 13.9% of the subjects were in this case. No significant influence of this factor had been shown on overall score [F(1, 112) ⬍ 1]. In the same way, no differences were found between psychotropic drugs users and non users [F(1, 115) ⬍ 1] or depending on the dementia’s etiology [F(3, 110) ⫽ 1.55, P ⫽ .21]. Further investigations are needed on this topic.
9. Conclusion Overall, this study seems to show that an evaluation of quality of life with the EQ-5D questionnaire is possible in patients with dementia. The severity of the pathology has little effect on the instrument’s reliability and validity, but it does affect its acceptability. The questionnaire was well received and the response rate was good, except for the VAS, which seems to present problems. Even if the test-retest reproducibility and the agreement between patient responses and proxy responses were not very strong, further support for the validity came from various analyses, which suggested that the subjects’ responses, in fact, reflected their subjective perceived mental and physical health, the goal of the instrument. Insofar as these patients seemed highly aware of their condition, new studies are needed to find observable indicators in people with dementia that are correlated with these internal states. The decoding of such signs by significant others might well pave the way to improving the quality of life and well-being of these people. Health-related quality of life will then no longer be considered merely as a measure, but as a goal.
Acknowledgments This study was made possible by funding from: DG V of the European Commission, Contract No. SOC972016 18O5F03(97CVVF34180); INSERM, Contract No. 4R0 02C; The Conseil Re´gional de Champagne Ardenne; The Recherche et Partage foundation; and The Re´gate association.
References [1] Lobo A, Launer LJ, Fratiglioni L, Andersen K, Di Carlo A, Breteler MM, Copeland JR, Dartigues JF, Jagger C, Martinez-Lage J, Soininen H, Hofman A. Prevalence of dementia and major subtypes in Europe. A collaborative study of population based cohorts. Neurologic Diseases in the Elderly Research Group. Neurology 2000;54:S4–9. [2] Albert SM, Del Castillo-Castaneda C, Sano M, Jacobs DM, Marder K, Bell K, Bylsma F, Lafleche G, Brandt J, Albert M, Stern Y. Quality
1062
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10] [11] [12]
[13]
[14]
[15]
[16] [17]
[18] [19] [20]
[21]
[22]
[23]
[24]
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063 of life in patients with Alzheimer’s disease as reported by patient proxies. J Am Geriatr Soc 1996;44(11):1342–7. Magaziner J. Use of proxies to measure health and functional outcomes in effectiveness research in persons with Alzheimer’s disease and related disorders. Alzheimer Dis Assoc Disord 1997;11(6):168–74. Brod M, Stewart AL, Sands L, Walton P. Conceptualization and measurement of quality of life in dementia: The Dementia Quality of Life Instrument (DQoL). Gerontologist 1999;39(1):25–35. Dorman PJ, Waddell F, Slattery J, Dennis M, Sandercock P. Are proxy assessments of health status after stroke with the EQ-5D questionnaire feasible, accurate and unbiased? Stroke 1997;28(10):1883–7. Hays RD, Vickrey BG, Hermann BP, Perrine K, Cramer J, Meador K, Spritzer K, Devinsky O. Agreement between self reports and proxy reports of quality of life in epilepsy patients. Qual Life Res 1995;4(2):159–68. Andresen EM, Vahle VJ, Lollar D. Proxy reliability: health-related quality of life (HRQoL) measures for people with disability. Qual Life Res 2001;10(7):609–19. Yip JY, Wilber KH, Myrtle RC, Grazman DN. Comparison of older adult subject and proxy responses on the SF-36 health-related quality of life instrument. Aging Ment Health 2001;5(2):136–42. Kiyak HA, Teri L, Borson S. Physical and functional health assessment in normal aging and in Alzheimer’s disease: self-report vs family reports. Gerontologist 1994;34(3):324–30. Brazier JE, Walters SJ, Nicholl JP, Kohler B. Using the SF-36 and EQ-5D on an elderly population. Qual Life Res 1996;5:195–204. Coast J, Peters TJ, Richards SH, Gunnell DJ. Use of the EuroQol among elderly acute care patients. Qual Life Res 1998;7:1–10. Fransen M, Edmonds J. Reliability and validity of the EuroQol in patients with osteoarthritis of the knee. Rheumatol 1999;38(9): 807–13. Kind P. In: Spilker B, ed. The EuroQol instrument: an index of healthrelated quality of life. In: Quality of life and pharmacoeconomics in clinical trials. Philadelphia: Lippincott-Raven; 1996. Folstein MF, Folstein SE, Mc Hugh PR. Mini mental state. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12(3):189–98. Hughes CP, Berg L, Danziger WL, Coben LA, Martin RL. A new clinical scale for the staging of dementia. Br J Psychiatry 1982; 140:566–72. Katz S, Down T, Cash H, Grotz R. Progress in development of index of, ADL. Gerontologist 1970;10:20–30. Brazier J, Jones N, Kind P. Testing the validity of the Euroqol and comparing it with the SF-36 Health Survey Questionnaire. Qual Life Res 1993;2(3):169–80. Johnson JA, Coons SJ. Comparison of the EQ-5D and SF-12 in an adult US sample. Qual Life Res 1998;7(2):155–66. Dolan PJ, Torgerson D, Kumar Kakarlapudi T. Health-related quality of life of Colles’ fracture patients. Osteoporos Int 1999;9:196–9. Dorman PJ, Waddell F, Slattery J, Dennis M, Sandercock P. Is the Euroqol a valid measure of health-related quality of life after stroke? Stroke 1997;28(10):1876–82. Dorman PJ, Slattery J, Farrell B, Dennis M, Sandercock P. Qualitative comparison of the reliability of health status assessments with the EuroQol and SF-36 questionnaires after stroke. Stroke 1998;29(1):63–8. Dorman PJ, Dennis M, Sandercock P. How do scores on the EuroQol relate to scores on the SF-36 after stroke? Stroke 1999;30(10): 2146–51. Essink-Bot ML, Krabbe PF, Bonsel GJ, Aaronson NK. An empirical comparison of four generic health status measures. The Nottingham Health Profile, the Medical Outcomes Study 36-item Short Form Health Survey, the COOP/WONCA charts and the EuroQol instrument. Med Care 1997;35(5):522–37. Hurst NP, Jobanputra P, Hunter M, Lambert CM, Lochead A, Brown H. Validity of EuroQol-a generic health status instrument in patients with rheumatoid arthritis. Br J Rheumatol 1994;33:655–62.
[25] Coucill W, Bryan S, Bentham P, Buckley A, Laight A. EQ-5D in patients with dementia. Med Care 2001;39(8):760–71. [26] Selai C. Assessing quality of life in dementia. Med Care 2001;39(8): 753–5. [27] Lawton MP. Assessing quality of life in Alzheimer disease research. Alzheimer Dis Assoc Disord 1997;11(6):91–9. [28] Kerner DN, Patterson TL, Grant I, Kaplan RM. Validity of the quality of Well-Being Scale for patients with Alzheimer’s disease. J Aging Health 1998;10(1):44–61. [29] Rabins PV, Kasper JD. Measuring quality of life in dementia: conceptual and practical issues. Alzheimer Dis Assoc Disord 1997;11(6): 100–4. [30] Cohen J. Weighted kappa: nominal scale agreement with provision for scaled disagreement or partial credit. Psychol Bull 1968;70(4):213–20. [31] Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159–74. [32] Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull 1977;86(2):420–8. [33] Corder LS, Woodbury MA, Manton KG. Proxy response patterns among the aged: effects on estimates of health status and medical care utilization from the 1982–1984 long term care surveys. J Clin Epidemiol 1996;49(2):173–82. [34] Cook DJ, Guyatt GH, Juniper E, Griffith L, McIlroy W, Willan A, Jaeschke R, Epstein R. Interviewer versus self-administered questionnaires in developing a disease-specific, health-related quality of life instrument for asthma. J Clin Epidemiol 1993;46(6):529–34. [35] Weinberger M, Oddone EZ, Samsa GP, Landsman PB. Are healthrelated quality-of-life measures affected by the mode of administration? J Clin Epidemiol 1996;49(2):135–40. [36] Grootendorst PV, Feeny DH, Furlong W. Does it matter whom and how you ask? Inter- and intra-rater agreement in the Ontario Health Survey. J Clin Epidemiol 1997;50(2):127–35. [37] Riemsma RP, Forbes CA, Glanville JM, Eastwood AJ, Kleijnen J. General health status measures for people with cognitive impairment: learning disability and acquired brain injury. Health Technol Assess 2001;5(6):1–100. [38] Ostbye T, Tyas S, McDowell I, Koval J. Reported activities of daily living: agreement between elderly subjects with and without dementia and their caregivers. Age Ageing 1997;26(2):99–106. [39] Rothwell PM, McDowell Z, Wong CK, Dorman PJ. Doctors and patients don’t agree: cross sectional study of patients’ and doctors’ perceptions and assessments of disability in multiple sclerosis. BMJ 1997;314:1580–3. [40] Sainfort F, Becker M, Diamond R. Judgments of quality of life of individuals with severe mental disorders: patient self-report versus provider perspectives. Am J Psychiatry 1996;153(4):497–502. [41] Santos-Eggimann B, Zobel F, Clerc Be´rod A. Functional status of elderly home care users: do subjects, informal and professional caregivers agree? J Clin Epidemiol 1999;52(3):181–6. [42] Sneeuw KC, Aaronson NK, Osoba D, Muller MJ, Hsu MA, Yung WK, Brada M, Newlands ES. The use of significant others as proxy raters of the quality of life of patients with brain cancer. Med Care 1997;35(5):490–506. [43] Teri L, Wagner AW. Assessment of depression in patient with Alzheimer’s disease: concordance among informants. Psychol Aging 1991; 6(2):280–5. [44] Volicer L, Camberg L, Hurley AC, Ashley J, Woods P, Ooi WL, McIntyre K. Dimensions of decreased psychological well-being in advanced dementia. Alzheimer Dis Assoc Disord 1999;13(4):192– 201. [45] Polsky D, Willke RJ, Scott K, Schulman KA, Glick HA. A comparison of scoring weights for the EuroQol derived from patients and the general public. Health Econ 2001;10(1):27–37. [46] van Agt HM, Essink-Bot ML, Krabbe PF, Bonsel GJ. Test-retest reliability of health state valuations collected with the EuroQol questionnaire. Soc Sci Med 1994;39(11):1537–44.
J. Ankri et al / Journal of Clinical Epidemiology 56 (2003) 1055–1063 [47] Badia X, Roset M, Herdman M. Inconsistent responses in three preference-elicitation methods for health states. Soc Sci Med 1999; 49(7):943–50. [48] Dolan P, Kind P. Inconsistency and health state valuations. Soc Sci Med 1996;42(4):609–15. [49] Hurst NP, Kind P, Ruta D, Hunter M, Stubbings A. Measuring healthrelated quality of life in rheumatoid arthritis: validity, responsiveness and reliability of EuroQol (EQ-5D). Br J Rheumatol 1997;36(5): 551–9. [50] Krabbe PF, Stouthard ME, Essink-Bot ML, Bonsel GJ. The effect of adding a cognitive dimension to the EuroQol multiattribute healthstatus classification system. J Clin Epidemiol 1999;52(4):293–301.
1063
[51] Krabbe PF, Essink-Bot ML, Bonsel GJ. The comparability and reliability of five health-state valuation methods. Soc Sci Med 1997;45(11): 1641–52. [52] Macran S, Kind P. “Death” and the valuation of health-related quality of life. Med Care 2001;39(3):217–27. [53] Suarez-Almazor ME, Conner-Spady B, Kendall CJ, Russell AS, Skeith K. Lack of congruence in the ratings of patients’ health status by patients and their physicians. Med Decis Making 2001;21(2):113–21. [54] Novella JL, Jochum C, Jolly D, Morrone I, Ankri J, Bureau F, Blanchard F. Agreement between patients’ and proxies’ reports of quality of life in Alzheimer’s disease. Qual Life Res 2001;10(5):443–52.