(Stroke. 1997;28:1883-1887.)
© 1997 American Heart Association, Inc.
Articles |
From the Neurosciences Trials Unit, Department of Clinical Neurosciences, University of Edinburgh, Western General Hospital, Edinburgh, UK.
Correspondence to Dr Paul Dorman, Neurosciences Trials Unit, Department of Clinical Neurosciences, University of Edinburgh, Western General Hospital, Crewe Rd, Edinburgh EH4 2XU, UK. E-mail pd{at}skull.dcn.ed.ac.uk
| Abstract |
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Methods We studied the validity of the EuroQol in a series of 152 patients from our prospective registry of patients with first (or recurrent) stroke. We asked patients to ensure that a friend or relative (a proxy) who knew them well was available at the time of the interview. We asked each proxy to complete a EuroQol questionnaire independently on behalf of the patient.
Results Proxies completed forms for 130 patients (86%).
Agreement between responses from the patients and those from their
proxies was better for patients who were able to self-complete the
EuroQol than for patients who required the EuroQol to be administered
by interview. For both groups, agreement was best for the self-care
domain and worst for the domain that assessed psychological outcome.
For the more severely affected patients, agreement was only fair for
the pain and social functioning domains and no better than chance alone
for the psychological functioning domain (
=0.05, 95% confidence
interval, 0 to 0.43). Patients tended to rate their own health status
as better than their proxies did (P<.05).
Conclusions We found moderate agreement between responses from patients and those from their proxies for the more directly observable domains of the EuroQol. Proxy agreement was less good for the more subjective domains. In health surveys, allowing responses by a proxy increases response rate. However, the disadvantages inherent in the use of proxy responses must be considered carefully. In general, some domains of HRQoL information obtained from a proxy may be sufficiently valid and unbiased to be useable in most types of trials and surveys.
Key Words: observer variation stroke outcome quality of life
| Introduction |
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It is often difficult to measure the HRQoL of many patients with stroke because physical and cognitive problems limit their ability to complete complex questionnaires.6 In a large study of over 2000 stroke patients who were sent postal versions of the EuroQol and Short Form-36 (SF-36) more than 3 months after their stroke, about half were unable to complete either type of questionnaire by themselves.7 Asking someone else, such as the caregiver, may be the only way to assess quality of life for a patient who is unable to complete the questionnaire themselves (this is often referred to as a proxy measure). Proxy measures of the SF-36 were disappointingly inaccurate.8 However, rating of a patients' functioning on the EuroQol by a proxy could prove to be valid, since much of the information sought is concrete and observable. We therefore examined whether a proxy could assess a stroke patient's HRQoL accurately and without bias using the EuroQol.
| Methods |
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Analysis
We calculated the level of agreement for the categorical data
items of the EuroQol between the assessments of the patients' health
status by the patients and their proxies. We did not use a correlation
coefficient (eg, Spearman rank) to assess agreement because it only
measures association and would be constant under deviations of scale or
bias.11 We therefore used the
statistic, which
measures the amount of agreement beyond that which could be expected by
chance.11 12 We calculated the variance of the
statistic using Altman's method.12 Because the scale
items had three levels of response, we used all three levels for the
estimation of
. We assessed agreement separately for patients who
were able to complete the EuroQol questionnaire themselves and those
who could not complete the EuroQol themselves and consequently had to
be interviewed. Unfortunately, no absolute definitions exist for the
interpretation of any given
statistic. We planned to base our
interpretation of the
statistic on the following widely cited
guidelines: <0.2 implies poor agreement, 0.21 to 0.40 implies fair
agreement, 0.41 to 0.60 implies moderate agreement, 0.61 to 0.80
implies good agreement, and 0.81 to 1.00 implies very good
agreement.11 12 13
The analysis of the continuous data from the visual analogue scale on overall HRQoL was more complex. Differences between the patients and their proxies in their estimates of the patients' overall HRQoL might be due to observer error, systematic differences (ie, bias), or random effects (ie, the play of chance). To display the raw data, we planned to plot a simple scatterplot and calculate a linear correlation coefficient. However, this plot gives little information on systematic differences, so we also performed a Bland and Altman analysis, which plots the difference between the two estimates against the mean of the two estimates.14 The EuroQol is bounded at 0 and 100, which limits the value of a Bland and Altman plot, so we also used a factorial ANOVA (SPSS for Windows, Release 6.1, SPSS Inc) to calculate the intraclass correlation coefficient, an appropriate measure of agreement for continuous data.15
| Results |
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Agreement between the proxies' and the patients' estimate of HRQoL is
shown in Table 1
. Agreement was better
for patients who were able to self-complete the EuroQol than for
patients who required the EuroQol to be administered by interview. For
both groups, agreement was best for the self-care domain and worst for
the domain used to assess psychological outcome. For the more severely
affected patients (assuming that the reasons for being unable to
self-complete are generally stroke-related), agreement was only fair
for the pain and social functioning domains and no better than chance
alone for the psychological functioning domain (
=0.05, 95%
confidence interval [CI], 0 to 0.43).
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Plotting the differences between the patients' and proxies' estimates
of overall HRQoL against the mean score (Bland and Altman plot) showed
an expected distribution for a score bounded at 0 and 100
(Figure
). For all patients combined, the
mean of the differences between the patients' and proxies' estimates
of overall HRQoL was 2 (95% CI for a pair of differences=-38 to 42,
Table 2
); this indicates that the
proxies' estimates of overall HRQoL were not significantly different
from the patients'. A factorial ANOVA also suggested that there was no
statistically significant variance between patients' and proxies'
numeric estimates of overall health status. For all patients combined,
the intraclass correlation coefficient (a measure of the agreement
between the patients' and proxies' estimates of overall health
status) was moderate with an intraclass correlation coefficient of .49
(P<.0001). Agreement for the estimates of overall HRQoL was
better for the subgroup of patients who were able to complete the
EuroQol themselves (intraclass correlation coefficients for those able
to complete: .53 versus .32 for patients unable to complete by
themselves).
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When the categorical data were used, a higher proportion of patients
reported "no problems" in each of the five domains than their
proxies (Table 3
). In these categorical
domains of the EuroQol, the proxy estimated the level of functioning to
be the same as that reported by the patient for 466 of the potential
640 outcomes. For 100 outcomes, the proxy estimated the functioning to
be worse than that estimated by the patient. In contrast, there were
only 74 outcomes for which the proxy estimate of the patients'
functioning was better than that reported by the patient (test for
symmetry, P<.05).
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| Discussion |
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In this study, the agreement was apparently less among more severely
affected patients. This loss of agreement could have been due to
observer error by the proxy or a systematic difference due to the
different mode of questionnaire administration. The latter notion is
supported by a recent report that suggests that patients give a more
optimistic picture of their health status when assessed by interview
than by self-completed questionnaire.16 Furthermore,
random errors may be important; the sample size was quite small
(especially for the subgroup analysis in Table 1
) so the 95%
CI around each estimate of agreement is wide and does not exclude the
possibility of substantially better agreement. There are a number of
other possible sources for less than perfect agreement. When a patient
and his/her proxy appear to disagree about the patients' health status
after a stroke, the following factors may contribute to the
disagreement: the domain under study, systematic differences in
perceived health (ie, bias), relationship of the proxy to the patient,
random error, and the choice of statistic to measure agreement. The
poor agreement for social functioning, pain, psychological functioning,
and overall HRQoL probably reflected the subjective nature of these
domains.
The proxy tended to report the patient's problems as more severe than did the patient. This suggests that proxy assessments of HRQoL do indeed differ systematically from self-assessments. Were the patients more optimistic about their health status than their proxies, did the patients adjust to or fail to perceive their own deficits, or were the proxy responders being pessimistic? The patients' view is likely to be more valid, as HRQoL instruments primarily aim to assess the patients' subjective perception of their own health. However, we cannot be certain, since there is no accepted gold standard for the measurement of HRQoL.
We allowed the patient to decide who could act as their proxy (rather than stipulate that they must choose a spouse or a close family member). It is possible that some of the proxies were selected simply because they were available and so might not have known the patient well enough to complete the assessment accurately. If allowing the patient to choose the proxy does introduce some extra measurement error, the error might not be reduced by insisting that a family member is used as the proxy: regrettably not all blood relations are sufficiently familiar to assess their relatives' HRQoL reliably! Furthermore, many patients do not have any family members living nearby and so a relatively imprecise estimate by a close friend may well be better than a very imprecise estimate from a distant family member and probably better than no estimate at all.
In our study, patients had to be able to complete the EuroQol either by themselves or by interview. We could not have assessed whether the proxy responses were valid for the patients who were unable to complete the EuroQol. Although we observed worse agreement for the patients who required the EuroQol to be administered by interview, we cannot necessarily infer that the agreement would have been even worse for even more severely affected patients (who have greater difficulties with communication) because the observed differences in agreement may have been due to the method of questionnaire administration.16 However, it seems likely that the use of proxies for patients who have difficulties with communication will have greater bias and measurement error because their relatives, friends, and caregivers will almost certainly have less insight into their perceived HRQoL.
The distribution of the random error is likely to be strongly
influenced by the reproducibility of the EuroQol. In other words, some
domains may be more prone to measurement error than others. It is
possible that the more subjective domains have the worst
reproducibility. A number of methodological factors may have caused us
to underestimate the true level of agreement between patients and their
proxies. First, since the EuroQol assesses the patients' HRQoL on the
day of completion, any delay in getting assessments from proxies who
were not available at the time of the interview might have reduced the
true level of agreement (as some of the patients could have changed).
This effect is unlikely to be important because the majority of
assessments (72%) were performed at the time of the home visit and
nearly all of the remaining assessments were completed within 7 days of
the home visit. An unweighted
statistic may also underestimate the
true level of agreement, because it ignores the ordering of the three
levels of the EuroQol. Furthermore, the interval differences between
each of the three levels of the EuroQol ("no problems," "some
problems," and "severe problems") are unlikely to be equal.
The difference between "no problems" and "some problems"
may be greater than that between "some problems" and "severe
problems." Weighting the
statistic to get around these problems
is not necessarily the solution, since any weights will inevitably be
arbitrary. Finally, the dependence of the
statistic on the
prevalence of the underlying attribute being measured complicates its
interpretation.11 Alternatively, it is also possible that
we have overestimated the true level of agreement because we cannot be
sure that some of the questionnaires returned by post were not
completed with some input from the patient.
In a randomized trial or survey that measures HRQoL, allowing a proxy to respond on behalf of the patient has potential disadvantages: it may increase random error and so reduce the statistical power of the study to detect the treatment effect, particularly for the domain of psychological functioning,17 and it may also introduce bias. In an observational study, such bias might make the overall outcome appear worse than if the patient had responded. In a randomized trial, if the treatment were effective, this might reduce the number of patients with poor outcome who can only be assessed by proxy in the treatment group (but not in the control group) and so exaggerate the treatment effect. This type of bias would, however, not be expected to affect the direction of the treatment effect or its statistical significance. Furthermore, the above bias is not unique to the EuroQol because proxy assessments of more objective outcomes, eg, disability, are affected by a similar bias.18 In general, such "second order" biases are not very important. The use of proxy responses is likely to ensure a higher overall response rate that will substantially reduce the risk of random error and bias.
In summary, a proxy assessment appears feasible in a wide variety of patients. The proxy assessed the domains of mobility and self-care accurately and without major bias, although there was a slight tendency for them to take a generally somewhat more pessimistic view of the patients' HRQoL. Therefore, for at least these domains, it seems reasonable to use proxy responses for the EuroQol in stroke patients who cannot complete questionnaires by themselves (especially if face-to-face interviews are not practicable). Proxy assessments of social functioning, pain, and overall HRQoL were associated with more error and must be interpreted more cautiously. Proxy assessments of psychological functioning were the least reliable, particularly in patients who required the EuroQol to be administered by interview, in whom they were no more accurate than chance alone. These findings are consistent with other evaluations of ratings by proxies.19 20 In general, allowing the use of proxy response where necessary is likely to be preferable to forbidding them in randomized controlled trials and many types of observational studies. However, where the focus of an observational study is an aspect of HRQoL other than physical functioning, the use of proxy responses may not be a good idea.
| Acknowledgments |
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Received January 13, 1997; revision received April 22, 1997; accepted May 30, 1997.
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