Evaluation of Quality of Life in Clinical Trials Selecting Quality-of-Life Measures Ingela Wiklund MSc, PhD, and Johan Karlberg MD, PhD Department of Medicine, Ostra Hospital, and Department of Anatomy, Gothenburg University, Gothenburg, Sweden
ABSTRACT: The strategy for evaluating quality of life in clinical trials is an important and complex issue. By comparing the performance of different quality-of-life measures before and after estrogen replacement therapy, it was shown that disease-specific measures had obvious advantages. Although narrow in applicability to the particular patient group, they were the most responsive measures in detecting small, clinically important changes. In clinical trials more attention should be given to how side effects, which often have important implications with regard to quality-of-life, are recorded.
KEY WORDS: Quality-of-life, measurement, clinical trials, estrogen therapy, side effects
INTRODUCTION The first major task in conducting a quality-of-life study is the selection of a proper and responsive quality-of-life instrument for the patient group and/ or health-care problem under study. The basic question to be addressed in this paper is "Is it necessary to use disease-specific measures?" At first sight this question might be regarded as a simple one. However, its importance will be brought into light, and discussed, by using examples from the literature and a relevant Swedish study of postmenopausal women.
Generic or Specific Measures?
Although generic measures provide a comprehensive, general evaluation of health-related quality-of-life, applicable to most patients with chronic disease, specific measures focus on aspects of health targeted to a specific disease or symptom complex. Provided that satisfactory reliability and validity have been confirmed, a critical property of a measure to be used for evaluative purposes in a clinical trial is its responsiveness--its ability to detect small and clinically important changes [1,2].
Address reprint requests to: Ingela Wiklund, MSc, PhD, Departmentof Medicine, Plan 2 CK, Ostra Hospital, S-416 85, Gothenburg, Sweden. Received July 11, 1990; revisedMarch 25, 1991.
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Experience from previous studies shows that, in terms of responsiveness, performance of generic measures such as the Sickness Impact Profile (SIP) [3] are less than satisfactory [4-6]. When health-related quality of life was evaluated using the SIP in a randomized placebo-controlled trial in men with stable angina pectoris, active treatment was found to have no advantage over placebo [7]. There was, however, no discussion of either the relevance of the SIP for use in patients with angina pectoris or its ability to detect changes in a trial design based on a two-week comparison period. Side effects are known to interfere with quality of life, and a sufficiently long period of observation is important to allow the patient to adapt to therapy and for changes in quality of life to occur. Current knowledge suggests that disease-specific measures offer several advantages compared with generic measures. The selection of quality-of-life measures has consequences in terms of patient motivation, clinical credibility, and practical aspects. Generic measures require lengthier evaluation and primarily characterize more severe degrees of dysfunction. These features may limit their applicability. Deyo [8] reports that patient complaints about SIP were related to its length and the fact that it was not disease-specific. An approach to the evaluation of quality of life in clinical trials will be described below. Further analyses of the quality-of-life data have been performed in order to clarify the relevance of the quality-of-life measures, and to compare their ability to detect treatment-induced changes.
METHODS A Generic and Specific Measures Approach to Assess Health-Related Quality of Life in Postmenopausal Women The effect of transdermal estrogen patches was investigated in a doubleblind, crossover study comparing two doses of Estraderm (50 and 100 lag per 24 hours) in combination with a gestagen (5 mg medroxyprogesterone acetate for 14 days each cycle). The objectives of the study were to compare metabolic effects and clinical efficacy of the two different doses of Estraderm given in combination with a gestagen, to investigate the feasibility of using different methods for assessing quality of life in women with postmenopausal disorders, and to assess reliability, validity, and responsiveness of the quality-of-life measures. The study was designed as a randomized, double-masked, eight-months' crossover trial, with four months' treatment crossovers. Quality-of-life was assessed at baseline before the patient started active therapy, and after four months of therapy. Patients. Seventy women with postmenopausal disorders were randomized
for the study; 59 women, median age 52 years (range 39-71 years), completed the first four months of the trial. The w o m e n included had had their last menstruation at least 6 months prior to the first consultation, complained about common climacteric symptoms such as sweating, hot flushes, insomnia, and/or atrophic symptoms and had had no hormone replacement therapy during the six weeks prior to indusion.
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Methods. The evaluation included self-administered quality-of-life measures, the physician's assessment of climacteric symptoms and the patient's selfrating of climacteric symptoms. The approach for the quality-of-life assessm e n t was to use a generic measure to evaluate the impact of health-related distress and dysfunction, and in view of the psychological nature of postmenopausal disorders [9-11] measures of well-being and mood.
Kupperman's Index. The physician's assessment of climacteric symptoms, summarized in a menopausal index, was based u p o n the most c o m m o n complaints (hot flushes, sweating, sleep disturbance, nervousness, depression, vertigo, fatigue, arthralgia, headache, tachycardia, vaginal dryness) [12]. A Swedish version of Kupperman's Index was used in the present study. The symptoms are converted to a summary numerical figure based upon their severity (graded 0-3). The severity score of sweating, sleep disturbance, and nervousness is multiplied by two and hot flushes by four.
Patient's Self-Rating of Disease-Specific Symptoms. The patients were asked to rate their climacteric symptoms using Visual Analogue Scales (VAS) [13]. The following symptoms were rated: hot flushes, sweating, sleep disturbance, nervousness, depression, irritability, vertigo, fatigue, arthralgia, headache, tachycardia, vaginal dryness. An ~ factor analysis (varimax rotation) [14] was done to investigate if the symptoms combined into different factors. Three factors were distinguished. The first factor included nervousness, depression, irritability, sleep disturbance, and headache (~ = 0.82); the second tachycardia and vaginal dryness (~x = 0.54); and the third hot flushes and sweating (cx = 0.49). Cronbach's o~for the total score was 0.78. In addition to the climacteric symptoms a single item of "general complaints" was assessed.
Quality-of-Life Assessment. Three standardized questionnaires were used to assess the health-related quality of life: the Nottingham Health Profile [15], the Psychological General Well-Being Index [16] and the Mood Adjective Check List [17]. The Nottingham Health Profile (NHP). The NHP is a generic measure developed in Britain, extensively tested with regard to reliability and validity [18,19]. After translation into Swedish following standard principles in order to avoid linguistic and conceptual problems [20,21], the reliability and validity of the Swedish version of the NHP was tested [22]. The NHP is in two parts. The 38 yes/no items of part I reflect degree of distress within the sections of mobility, energy, pain, sleep, emotions and social isolation. The sections of mobility and pain were omitted being considered less relevant to the problems of the present patient population. The answers of the NHP have been weighted using several patient and nonpatient populations [23]. Weights in each section total 100, indicating the presence of all possible problems, whereas 0 equals no problems at all. Swedish weights have also been produced and were employed in the present trial [24]. Part II of NHP has 7 yes/no statements about the frequency of health-related problems with paid employment, housework, social life, family life, sex life, hobbies, and holidays. The responses
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to the NHP can be compared to "normal" or average scores in a population adjusted for age and sex [25].
The Psychological General Well-Being Index (PGWB). This index consists of 22 questions that cover the six subscales of anxiety (a --- 0.82), depression (a = 0.89), well-being (a = 0.88), self-control (a = 0.76), health (a = 0.61), and vitality (a = 0.85) [16]. The PGWB index was translated into Swedish following standard principles and the alpha-coefficients represent the values obtained in the Swedish version. The 22 items combine into an overall score. Patients rate each question on a six-point scale (with six as the most negative option and one as the most positive). The Mood Adjective Check List (MACL). The MACL contains 38 items which denote feelings representing positive and negative affects [17]. Three separate dimensions of mood denoting activation-deactivation, positive and negative appraisal, i.e., pleasantness-unpleasantness, and degree of arousal, i.e., tension--calmness, can be formed. The response format for each item uses four categories.
RESULTS
Validity The intercorrelations among the quality-of-life measures are shown in Table 1. The intercorrelations between quality of life and subjective symptoms and Kupperman's Index are shown in Table 2. As could be expected there was more consistency among the quality-of-life measures than between quality of life and Kupperman's Index. The highest correlations were found between Kupperman's Index and the patient's perception of the same symptoms. The psychological impact of postmenopausal complaints was reflected by the significant relationships among Kupperman's Index, well-being, and mood, which support the relevance of the quality-of-life measures.
Table 1
Intercorrelations of the Quality-of-Life Measures Quality-of-Life Measure I
Anxiety Depression Well-being Health Vitality Self-control NHP energy Emotions MACL tension Deactivation Unpleasantness
II
Ill
IV
-- 0.86 0.73 0.58 -0.87 0.53 -0.52 --
V
VI
VII
VIII
IX
X
XI
0.62 0.69 0.77 0.58 --
0.79 0.78 0.77 0.48 0.63 --
0.64 0.62 0.63 0.58 0.70 0.6! --
0.78 0.82 0.78 0.55 0.70 0.83 0.78
0.80 0.64 0.62 0.32 0.53 0.64 0.65 0.69
0.65 0.67 0.74 0.52 0.79 0.70 0.82 0.78 0.71 w
0.74 0.76 0.79 0.53 0.74 0.75 0.76 0.83 0.83 0.86
--
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Correlation of Quality-of-Life Measures, Subjective Climacteric Symptoms, and Kupperman's Index Before Therapy ~
QOL Measure PGWB total score Anxiety Depression Well-Being Health Vitality Self-Control MACL Tension Deactivation Unpleasantness NHP
Sleep Energy Emotions Social isolation VAS Total score Emotional Hot flushes/Sweats Tachycardia/Vaginal dryness General complaints Number of women: 59
Kupperman's Index 0.42 0.30 0.34 0.37 0.15a 0.45 0.29 0.31 0.52 0.34 0.51 0.32 0.33 0.33 0.67 0.56 0.56 0.24 0.33
"Not significant.
Clinical Relevance and Responsiveness In an attempt to estimate the clinical relevance and responsiveness of the different measures, the correlations between the change scores of quality-oflife and the conventional outcome were calculated (Table 3). Clinician-rated improvement, summarized in Kupperman's Index, was associated with a range of outcomes in quality of life. Whereas comparatively high correlations were found with the overall disease-specific symptom score, and with two of the symptom combinations, the correlations with the problem-oriented and the general outcomes were modest. The change score correlations suggested that problem-oriented measures of anxiety, tension, depression, sleep disturbance and lack of vitality as well as the overall PGWB score provided highly relevant information. The single item "general complaints," often used in clinical trials as an outcome, appeared to be among the least relevant. In order to illustrate the clinical relevance of change in health-related quality of life (NHP), reference values obtained in a W H O screening in Gothenburg, were used for comparison. The responses of w o m e n aged 35-65 years were compared with the responses of the postmenopausal w o m e n before and after estrogen therapy (Figs. I and 2). Of interest is that the postmenopausal women reported a similar level of health-related quality of life as the reference group after therapy, i.e., had regained health to a degree that was comparable with healthy females. The efficacy of estrogen therapy is well-documented [26,27], and all mea-
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Evaluation of Quality of Life in Clinical Trials Table 3
Correlation of Change Scores in Quality of Life and Kupperman's Index QOL Measure
Kupperman's Index
PGWB total score Anxiety Depression Well-Being Health Vitality Self-Control
0.38 0.37 0.40 0.34 0.22" 0.48 0.17"
MACL Tension Deactivation Unpleasantness
0.41 0.33 0.46
NHP
Sleep Energy Emotions Social isolation
0.50 0.15~ 0.32 0.23"
VAS
Emotional Hot flushes/Sweats Tachycardia/Vaginal dryness General complaints
0.61 0.59 0.19' 0.20
Number of women: 59 "Not significant.
"Normal" females (n=200)
Mean value (out of 100)
[~
Postmenopausal women after therapy {n=59)
m
Postmenopausal women before therapy (n=59)
30
20
10
Sleep
Figure I
Energy
Emotions
Social isolation
A comparison of the responses to the Nottingham Health Profile, part I, of postmenopausal women before and after estrogen therapy, and "normal females."
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% rl
40 rl
30
20
10
Sex life
House work
Paid employment
Hobbies
Family life
Social life
Holidays
Figure 2 A comparison of health-related problems/the Nottingham Health Profile, part II in postmenopausal women before and after estrogen therapy, and "normal," females. sures showed a highly significant improvement after treatment using sign rank test, based upon within patient score changes. The score changes were therefore compared using paired t statistics, and the percent change, according to the method of Deyo [6]. Kupperman's Index and the disease-specific symptom scores showed the greatest percent change and also the largest t statistics. Using this method, the Mood scales and the PGWB Index showed the least percent change. Although displaying a high percent change, the single items of NHP, part II, had the lowest t statistics. Another estimate of the responsiveness of the different measures was calculated using the formula suggested by Guyatt et al. [28]. Lacking information about variation within stable patients, the variability in the change scores was employed: (mean diff)/(SD diff V~). Sim~arly, the degree of change was expressed in terms of the effect-size index (d value) of Cohen [29]. The dvalue was determined by dividing the change score by the standard deviation at the first measurement. According to Cohen, a d value ~ 0.5 or ~ -0.5, can be regarded as a significant degree of improvement or deterioration. The responsiveness and the effect size index are shown in Table 5. The results of the two approaches are very much in agreement and indicate that the diseasespecific outcomes were the most responsive. Generally the responsiveness was somewhat increased by combining symptoms or subscales into overall scores. In spite of being relatively crude, the NHP seemed to perform equally well compared with the PGWB index, which had performed well in another study using a large number of problem-oriented and psychosocial measures [3O]. The feasibility of assessing quality of life in postmenopausal women employing an approach that combined specific, problem-oriented and general measures was demonstrated. The quality-of-life measures provided valid and multidimensional information about the impact of disease and response to therapy. The limitations of the study is that it only enabled comparisons before
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Table 4
Score Changes after Estrogen T h e r a p y in W o m e n With Climacteric Problems Percent
Measures Kupperman's Index PGWB Total score Anxiety Depression Well being Health Vitality Self-control MACL Tension Deactivation Unpleasantness NHP
Sleep Energy Emotions Social isolation
VAS
Total score Emotional Hot flushes/sweats Tachycardia/vaginal dryness
General complaints NHP
Part II: Paid employment Housework Social life Family life Sex life Hobbies Holidays
Mean Change
(SD)
Change' (%)
Paired t-Statistics
p Value
18.23 13.02 2.92 1.90 2.50 1.42 3.20 1.52
(8.0) (13.6) (3.8) (2.7) (3.1) (2.6) (3.5) (3.0)
70 22 22 28 19 17 25 22
17.01 6.83 5.87 5.23 5.90 4.26 7.02 3.89
.0001 .0001 .0001 .0001 .0001 .0001 .0001 .0003
0.42 0.34 0.26
(0.5) (0.4) (0.4)
18 16 13
5.54 6.27 4.45
.0001 .0001 .0001
19.82 15.83 11.99 7.56
(23.4) (24.8) (18.4) (17.5)
53 57 60 66
6.51 4.83 4.99 3.28
.0001 .0001 .0001 .0018
279.04 110.47 91.27 31.82
(169.8) (88.5) (49.7) (42.1)
65 63 83 58
11.85 9.43 13.62 5.71
.0001 .0001 .0001 .0001
35.72
(28.8)
56
9.38
.0001
0.21 0.17 0.16 0.17 0.26 0.12 0.10
(0.5) (0.5) (0.4) (0.5) (0.4) (0.4) (0.4)
67 50 75 71 67 50 60
3.51 2.62 2.88 2.82 4. 2.18 1.76
.0009 .01 .0056 .0064 .0001 .0336 .08
Number of women = 59 aPercent change calculated as (mean score change/mean initial score). a n d after therapy, which is insufficient. The ultimate w a y of testing the responsiveness of quality-of-life measures p r o p e r l y is b y e m p l o y i n g t h e m in a controlled clinical trial to compare different therapies.
Side Effects and Quality of Life A n o t h e r issue that is closely related to the selection of the most " a p p r o priate" quality-of-life measure in a clinical trial concerns side effects. Side effects occur both d u r i n g active and placebo treatment. I m p r o v e m e n t was almost always reported b y participants in a trial i n d e p e n d e n t of d r u g administration [31], and in a n o t h e r study, the n u m b e r of side effects increased o n inert substances [32]. The significance of placebo-induced side effects was s h o w n in the evaluation of antihypertensive d r u g s in the MRC-trial [33], a n d
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R e s p o n s i v e n e s s a n d Effect Size in the O u t c o m e M e a s u r e s U s e d to Evaluate the Efficacy of Estrogen T h e r a p y Measure
Responsiveness a
Effect Size Index b
Kupperman's Index VAS Total score Hot flushes/sweats Emotional TachycardiaYvaginal dryness
1.61 1.16 1.30 0.88 0.53
2.16 1.62 1.93 1.09 0.73
VAS scales: Sweatings Hot flushes Sleep disturbances Depresesion Fatigue Irritability Headache Nervousness Vaginal dryness Tachycardia Vertigo Arthralgia General complaints
1.17 1.02 0.98 0.60 0.59 0.56 0.51 0.47 0.44 0.43 0.39 0.33 0.88
1.80 1.43 1.37 0.78 0.78 0.73 0.63 0.62 0.63 0.57 0.41 0.38 1.69
PGWB
Total score Vitality Well-being Anxiety Depression Health Self-control
0.68 0.66 0.57 0.54 0.49 0.39 0.36
0.65 0.63 0.62 0.52 0.45
MACL
Deactivation Tension Unpleasantness
0.61 0.54 0.44
0.58 0.65 0.41
NHP
Sleep Emotions Energy Isolation
0.60 0.46 0.45 0.30
0.70 0.46 0.44 0.42
0.41 0.33 0.27 0.26 0.24 0.20 0.16
0.52 0.45 0.38 0.39 0.36 0.28 0.27
Part II: Sex life Paid employment Social life Family life Housework Hobbies Holidays Mean (diff) aResponsiveness SD (diff)V~" Mean (diff) bEffect size index = SD (first measurement)'
0.78 0.77
NHP
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similarly in relation to postinfarction treatments where side effects were common on both active and placebo treatment [34]. However, side effects tend to disappear when the patient is adapted to therapy [35], which also underscores the need for a sufficiently long period of observation during followup. Because it has been argued that the presence of side effects impairs quality of life [7,30], standardized methods tailored to the specific drugs used in a trial are required to supplement the quality-of-life measures. Hitherto, there has been a conspicious lack of attention to how side effects are recorded. Side effects are typically recorded using spontaneous reports and/or active questioning by the physician. This makes comparisons within as well as between studies difficult. More refined and sensitive methods for the recording of drug-specific side effects are required. Preliminary reports have shown promising results using a recently developed minor side effect profile [36]. It proved feasible to use a specific, reliable and sensitive measure to measure the patient's response to initiation of drug therapy [37]. DISCUSSION The choice of strategy for evaluating health-related quality of life in clinical trials is a complex issue. The "best" approach does not necessarily imply that the "best" measure, in terms of responsiveness, should be singly employed. Disease-specific quality-of-life measures have a high relevance for outcome and provide specific information in a concise way. Specific measures tailored to the disease enhance compliance and do not overburden the patient. On the other hand, some standardized psychosocial measures that focus on problems of well-being or dimensions of mood are universal, and could be employed over different patient groups. Reference values are often available, and could be used for comparative purposes. The understanding of the clinical relevance of observed changes would therefore be facilitated. The findings in the estrogen study indicate the importance of having comparison data against which to set the information about the impact of health-related quality of life. For patient populations with more pronounced degrees of distress and dysfunction, selected subscales of generic measures provide valuable information about the impact of disease on quality of life. Disease-specific measures represent obvious advantages in terms of responsiveness. There is no gold standard for comparing the responsiveness of different measures. The different methods described in the literature [6,28,29,38] yield somewhat divergent results. Methods based upon the withinindividual variation in relation to observed changes after therapy give more congruent results irrespective of whether or not more refined statistical operations have been added. An issue of vital concern is whether the assessment should be based upon conventional clinical evidence or upon patient ratings. Again there is no conclusive answer. Generally the correlation between assessments made by physicians and patients with regard to arthritic pain [22], functional capacity [39], general improvement [40], or quality-of-life [41] is modest. From the patient's perspective the ultimate goal of medical intervenfion is increased physical and emotional well-being. Whereas conventional methods show important changes in the patient's clinical status, they are poor
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I. Wiklund and J. Karlberg indicators of h o w the patient feels and functions in day-to-day activity. On the other hand, quality-of-life variables cannot be u s e d as the only outcome unless they bear a relation to physiologic findings. In conclusion, both types of measures are n e e d e d to satisfy clinical credibility as well as relevance to patient. No doubt health is a major c o m p o n e n t of quality of life (42,43), but m a n y more dimensions are required to fully describe health-related quality of life. In that sense, disease-specific measures that solely focus u p o n s y m p t o m s , are too narrow. The estrogen study suggested that other quality-of-life measures a d d e d highly relevant complementary information. Therefore a feasible approach might be to tailor a package of disease-specific, problem-oriented as well as generic measures. More consideration should be given to h o w side effects, which have important implications with regard to quality-of-life, are recorded.
REFERENCES
1. Guyatt G, Bombardier C, Tugwel! PA: Measuring disease-specific quality of life in clinical trials. JAMA 134:889--895, 1986 2. Kirschner B, Guyatt G: A methodological framework for assessing health indexes. J Chronic Dis 38:27-36, 1985 3. Bergner M, Bulpitt RA, Carter WB, Gibson BS: The Sickness Impact Profile: De- • velopment and final revision of a health status measure. Med Care 19:787-805, 1981 4. Deyo RA, Inni TS: Toward clinical applications of health status measures: Sensitivity of scales to clinically important changes. Health Serv Research 19:275--289, 1984 5. Deyo RA, Carter RM: Assessing the responsiveness of functional scales to clinical change: an analogy to diagnostic test performance. J Chronic Dis 39:897-906, 1986 6. MacKenzie CR, Charlsson ME, DiGioia D, Kelley K: Can the Sickness Impact Profile measure change? An example of scale assessment. J Chronic Dis 39:429438, 1986 7. Fletcher A, McLoone P, Bulpitt C: Quality of life in angina therapy: A randomised controlled trial of transdermal glyceryl trinitrate against placebo. Lancet 2:4-8, 1988 8. Deyo RA, Inni TS, Leininger JD, Overman SS: Measuring functional outcomes in chronic disease: A comparison of traditional scales and a selfadministered health status questionnaire in patients with rheumatoid arthritis. Med Care 21:180-192, 1983 9. Ballinger CB, Browning MCK, Smith AHW: Hormone profiles and psychological symptoms in peri-menopausal women. Maturitas 9:235-251, 1987 10. Dennerstein L, Burrows GD: A review of studies of the psychological symptoms found at the menopause. Maturitas 1:55--64, 1978 11. Hunter M, Battersby R, Whitehead M: Relationship between psychological symptoms and menopausal status. Maturitas 8:217-228, 1986 12. Kupperman HS, Blatt MHG, Wiesbader H, Filler W: Comparative clinical evaluation of estrogenic preparations by the menopausal and amenorrheal indices. Endocrinology 13:688-703, 1953 13. Aitken RC: Measurement of feelings using visual analogue scales. Proc Roy Soc Med 2:989-993, 1969
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14. Kaiser HF, Caffrey J: Alpha factor analysis. Psychometrika 30:1-14, 1965 15. Hunt SM, McEwen J: The development of a subjective health indicator. Sociol Health lllness 2:231-246, 1980 16. Dupuy HJ: The Psychological General Well-Being (PGWB) Index. In: Assessment of Quality of Life in Clinical Trials of Cardiovascular Therapies, Wenger NK, Masson ME, Furberg CD, Elinson J, Eds. New York, Le Lacq, 1984, pp 170-183 17. Sj6berg L, Svensson E, Persson L-O: The measurement of mood. Scand J Psychol 20:1-18, 1979 18. Hunt SM, McKenna SP, Williams J: Reliability of a population survey tool for measuring perceived health problems: A study of patients with osteoarthrosis. J Epidemiol Community Health 35:297-300, 1981 19. Hunt SM, McKenna SP, McEwen J, Backett EM, Williams J, Papp E: A quantitative approach to perceived health status: A validation study. J Epidemiol Community Health 34:281-286, 1980 20. Werner O, Campbell P: Translating working through interpreters and the problem of decentering. In: A Handbook of Method in Cultural Antropology, Narrol R, Cohen R, Eds. New York, American Museum of National History, 1970, pp 348420 21. Hunt SM, McEwen J, McKenna SP: Measuring health status. Kent, UK, Croom Helm, 1986 22. Wiklund I, Romanus B, Hunt SM: Self-assessed disability in patients with arthrosis of the hip joint. Reliability of the Swedish version of the Nottingham Health Profile. Int Disabil Stud 10:159-163, 1988 23. McKenna SP, Hunt SM, McEwen J: Weighting the seriousness of perceived health problems using Thurstone's method of paired comparisons. Int J Epidemio110:9397, 1981 24. Hunt SM, Wiklund I: Cross-cultural variation in the weighting of health statements: A comparison of English and Swedish valuations. Health Policy 8:227-235, 1987 25. Hunts S, McEwen J, McKenna SP: Perceived health; age and sex norms in a community. J Epidemiol Community Health 38:156-160, 1984 26. Nichols KC, Schenkel L, Benson H: 17 [3-estradiol for postmenopausal estrogen replacement therapy. Obstet Gynecol 39(suppl):230-245, 1984 27. Judd H: Efficacy of transdermal estradiol. Am J Obstet Gynecol 156:1326-1331, 1987 28. Guyatt G, Walter S, Norman G: Measuring change over time: Assessing the usefulness of evaluative instruments. J Chronic Dis 40:171-178, 1987 29. Cohen J: Statistical power analysis for the behavioral sciences. New York, Academic, 1969 30. Croog SH, Levine S, Testa MA, Brown B, Bulpitt CJ, Jenkins CD, Klerman GL, Williams GH: The effects of antihypertensive therapy on the quality of life. N Engl J Med 314:1657-1664, 1986 31. Mann AA: Hypertension: Psychological aspects and diagnostic impact in a clinical trial. Psychol Med Monogr (suppl 5): 1-35, 1984 32. Gliedman LA, Nash EH, Imber SD, Stone AR, Frenk JD: Reduction of symptoms by plasmacologically inert sutstances and by short-term psychotherapy. Arch Neurol Psychiatry 79:345-351, 1958 33. Medical Research Council Working Party on Mild to Moderate Hypertension. Adverse reactions to bendrofluazide and propranolol for the treatment of mild hypertension. Lancet 2:539-543, 1981 34. Yusuf S, Peto R, Lewis J, Collins P: Beta-blockade during and after myocardial infarction: An overview of the randomized trials. Prog Cardiovasc Dis 27:335-371, 1985
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ABSTRACT: The strategy for evaluating quality of life in clinical trials is an important and complex issue. By comparing the performance of different quality-of-life measures before and after estrogen replacement therapy, it was shown that disease-specific measures had obvious advantages. Although narrow in applicability to the particular patient group, they were the most responsive measures in detecting small, clinically important changes. In clinical trials more attention should be given to how side effects, which often have important implications with regard to quality-of-life, are recorded.
KEY WORDS: Quality-of-life, measurement, clinical trials, estrogen therapy, side effects
INTRODUCTION The first major task in conducting a quality-of-life study is the selection of a proper and responsive quality-of-life instrument for the patient group and/ or health-care problem under study. The basic question to be addressed in this paper is "Is it necessary to use disease-specific measures?" At first sight this question might be regarded as a simple one. However, its importance will be brought into light, and discussed, by using examples from the literature and a relevant Swedish study of postmenopausal women.
Generic or Specific Measures?
Although generic measures provide a comprehensive, general evaluation of health-related quality-of-life, applicable to most patients with chronic disease, specific measures focus on aspects of health targeted to a specific disease or symptom complex. Provided that satisfactory reliability and validity have been confirmed, a critical property of a measure to be used for evaluative purposes in a clinical trial is its responsiveness--its ability to detect small and clinically important changes [1,2].
Address reprint requests to: Ingela Wiklund, MSc, PhD, Departmentof Medicine, Plan 2 CK, Ostra Hospital, S-416 85, Gothenburg, Sweden. Received July 11, 1990; revisedMarch 25, 1991.
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Experience from previous studies shows that, in terms of responsiveness, performance of generic measures such as the Sickness Impact Profile (SIP) [3] are less than satisfactory [4-6]. When health-related quality of life was evaluated using the SIP in a randomized placebo-controlled trial in men with stable angina pectoris, active treatment was found to have no advantage over placebo [7]. There was, however, no discussion of either the relevance of the SIP for use in patients with angina pectoris or its ability to detect changes in a trial design based on a two-week comparison period. Side effects are known to interfere with quality of life, and a sufficiently long period of observation is important to allow the patient to adapt to therapy and for changes in quality of life to occur. Current knowledge suggests that disease-specific measures offer several advantages compared with generic measures. The selection of quality-of-life measures has consequences in terms of patient motivation, clinical credibility, and practical aspects. Generic measures require lengthier evaluation and primarily characterize more severe degrees of dysfunction. These features may limit their applicability. Deyo [8] reports that patient complaints about SIP were related to its length and the fact that it was not disease-specific. An approach to the evaluation of quality of life in clinical trials will be described below. Further analyses of the quality-of-life data have been performed in order to clarify the relevance of the quality-of-life measures, and to compare their ability to detect treatment-induced changes.
METHODS A Generic and Specific Measures Approach to Assess Health-Related Quality of Life in Postmenopausal Women The effect of transdermal estrogen patches was investigated in a doubleblind, crossover study comparing two doses of Estraderm (50 and 100 lag per 24 hours) in combination with a gestagen (5 mg medroxyprogesterone acetate for 14 days each cycle). The objectives of the study were to compare metabolic effects and clinical efficacy of the two different doses of Estraderm given in combination with a gestagen, to investigate the feasibility of using different methods for assessing quality of life in women with postmenopausal disorders, and to assess reliability, validity, and responsiveness of the quality-of-life measures. The study was designed as a randomized, double-masked, eight-months' crossover trial, with four months' treatment crossovers. Quality-of-life was assessed at baseline before the patient started active therapy, and after four months of therapy. Patients. Seventy women with postmenopausal disorders were randomized
for the study; 59 women, median age 52 years (range 39-71 years), completed the first four months of the trial. The w o m e n included had had their last menstruation at least 6 months prior to the first consultation, complained about common climacteric symptoms such as sweating, hot flushes, insomnia, and/or atrophic symptoms and had had no hormone replacement therapy during the six weeks prior to indusion.
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Methods. The evaluation included self-administered quality-of-life measures, the physician's assessment of climacteric symptoms and the patient's selfrating of climacteric symptoms. The approach for the quality-of-life assessm e n t was to use a generic measure to evaluate the impact of health-related distress and dysfunction, and in view of the psychological nature of postmenopausal disorders [9-11] measures of well-being and mood.
Kupperman's Index. The physician's assessment of climacteric symptoms, summarized in a menopausal index, was based u p o n the most c o m m o n complaints (hot flushes, sweating, sleep disturbance, nervousness, depression, vertigo, fatigue, arthralgia, headache, tachycardia, vaginal dryness) [12]. A Swedish version of Kupperman's Index was used in the present study. The symptoms are converted to a summary numerical figure based upon their severity (graded 0-3). The severity score of sweating, sleep disturbance, and nervousness is multiplied by two and hot flushes by four.
Patient's Self-Rating of Disease-Specific Symptoms. The patients were asked to rate their climacteric symptoms using Visual Analogue Scales (VAS) [13]. The following symptoms were rated: hot flushes, sweating, sleep disturbance, nervousness, depression, irritability, vertigo, fatigue, arthralgia, headache, tachycardia, vaginal dryness. An ~ factor analysis (varimax rotation) [14] was done to investigate if the symptoms combined into different factors. Three factors were distinguished. The first factor included nervousness, depression, irritability, sleep disturbance, and headache (~ = 0.82); the second tachycardia and vaginal dryness (~x = 0.54); and the third hot flushes and sweating (cx = 0.49). Cronbach's o~for the total score was 0.78. In addition to the climacteric symptoms a single item of "general complaints" was assessed.
Quality-of-Life Assessment. Three standardized questionnaires were used to assess the health-related quality of life: the Nottingham Health Profile [15], the Psychological General Well-Being Index [16] and the Mood Adjective Check List [17]. The Nottingham Health Profile (NHP). The NHP is a generic measure developed in Britain, extensively tested with regard to reliability and validity [18,19]. After translation into Swedish following standard principles in order to avoid linguistic and conceptual problems [20,21], the reliability and validity of the Swedish version of the NHP was tested [22]. The NHP is in two parts. The 38 yes/no items of part I reflect degree of distress within the sections of mobility, energy, pain, sleep, emotions and social isolation. The sections of mobility and pain were omitted being considered less relevant to the problems of the present patient population. The answers of the NHP have been weighted using several patient and nonpatient populations [23]. Weights in each section total 100, indicating the presence of all possible problems, whereas 0 equals no problems at all. Swedish weights have also been produced and were employed in the present trial [24]. Part II of NHP has 7 yes/no statements about the frequency of health-related problems with paid employment, housework, social life, family life, sex life, hobbies, and holidays. The responses
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to the NHP can be compared to "normal" or average scores in a population adjusted for age and sex [25].
The Psychological General Well-Being Index (PGWB). This index consists of 22 questions that cover the six subscales of anxiety (a --- 0.82), depression (a = 0.89), well-being (a = 0.88), self-control (a = 0.76), health (a = 0.61), and vitality (a = 0.85) [16]. The PGWB index was translated into Swedish following standard principles and the alpha-coefficients represent the values obtained in the Swedish version. The 22 items combine into an overall score. Patients rate each question on a six-point scale (with six as the most negative option and one as the most positive). The Mood Adjective Check List (MACL). The MACL contains 38 items which denote feelings representing positive and negative affects [17]. Three separate dimensions of mood denoting activation-deactivation, positive and negative appraisal, i.e., pleasantness-unpleasantness, and degree of arousal, i.e., tension--calmness, can be formed. The response format for each item uses four categories.
RESULTS
Validity The intercorrelations among the quality-of-life measures are shown in Table 1. The intercorrelations between quality of life and subjective symptoms and Kupperman's Index are shown in Table 2. As could be expected there was more consistency among the quality-of-life measures than between quality of life and Kupperman's Index. The highest correlations were found between Kupperman's Index and the patient's perception of the same symptoms. The psychological impact of postmenopausal complaints was reflected by the significant relationships among Kupperman's Index, well-being, and mood, which support the relevance of the quality-of-life measures.
Table 1
Intercorrelations of the Quality-of-Life Measures Quality-of-Life Measure I
Anxiety Depression Well-being Health Vitality Self-control NHP energy Emotions MACL tension Deactivation Unpleasantness
II
Ill
IV
-- 0.86 0.73 0.58 -0.87 0.53 -0.52 --
V
VI
VII
VIII
IX
X
XI
0.62 0.69 0.77 0.58 --
0.79 0.78 0.77 0.48 0.63 --
0.64 0.62 0.63 0.58 0.70 0.6! --
0.78 0.82 0.78 0.55 0.70 0.83 0.78
0.80 0.64 0.62 0.32 0.53 0.64 0.65 0.69
0.65 0.67 0.74 0.52 0.79 0.70 0.82 0.78 0.71 w
0.74 0.76 0.79 0.53 0.74 0.75 0.76 0.83 0.83 0.86
--
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Correlation of Quality-of-Life Measures, Subjective Climacteric Symptoms, and Kupperman's Index Before Therapy ~
QOL Measure PGWB total score Anxiety Depression Well-Being Health Vitality Self-Control MACL Tension Deactivation Unpleasantness NHP
Sleep Energy Emotions Social isolation VAS Total score Emotional Hot flushes/Sweats Tachycardia/Vaginal dryness General complaints Number of women: 59
Kupperman's Index 0.42 0.30 0.34 0.37 0.15a 0.45 0.29 0.31 0.52 0.34 0.51 0.32 0.33 0.33 0.67 0.56 0.56 0.24 0.33
"Not significant.
Clinical Relevance and Responsiveness In an attempt to estimate the clinical relevance and responsiveness of the different measures, the correlations between the change scores of quality-oflife and the conventional outcome were calculated (Table 3). Clinician-rated improvement, summarized in Kupperman's Index, was associated with a range of outcomes in quality of life. Whereas comparatively high correlations were found with the overall disease-specific symptom score, and with two of the symptom combinations, the correlations with the problem-oriented and the general outcomes were modest. The change score correlations suggested that problem-oriented measures of anxiety, tension, depression, sleep disturbance and lack of vitality as well as the overall PGWB score provided highly relevant information. The single item "general complaints," often used in clinical trials as an outcome, appeared to be among the least relevant. In order to illustrate the clinical relevance of change in health-related quality of life (NHP), reference values obtained in a W H O screening in Gothenburg, were used for comparison. The responses of w o m e n aged 35-65 years were compared with the responses of the postmenopausal w o m e n before and after estrogen therapy (Figs. I and 2). Of interest is that the postmenopausal women reported a similar level of health-related quality of life as the reference group after therapy, i.e., had regained health to a degree that was comparable with healthy females. The efficacy of estrogen therapy is well-documented [26,27], and all mea-
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Evaluation of Quality of Life in Clinical Trials Table 3
Correlation of Change Scores in Quality of Life and Kupperman's Index QOL Measure
Kupperman's Index
PGWB total score Anxiety Depression Well-Being Health Vitality Self-Control
0.38 0.37 0.40 0.34 0.22" 0.48 0.17"
MACL Tension Deactivation Unpleasantness
0.41 0.33 0.46
NHP
Sleep Energy Emotions Social isolation
0.50 0.15~ 0.32 0.23"
VAS
Emotional Hot flushes/Sweats Tachycardia/Vaginal dryness General complaints
0.61 0.59 0.19' 0.20
Number of women: 59 "Not significant.
"Normal" females (n=200)
Mean value (out of 100)
[~
Postmenopausal women after therapy {n=59)
m
Postmenopausal women before therapy (n=59)
30
20
10
Sleep
Figure I
Energy
Emotions
Social isolation
A comparison of the responses to the Nottingham Health Profile, part I, of postmenopausal women before and after estrogen therapy, and "normal females."
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% rl
40 rl
30
20
10
Sex life
House work
Paid employment
Hobbies
Family life
Social life
Holidays
Figure 2 A comparison of health-related problems/the Nottingham Health Profile, part II in postmenopausal women before and after estrogen therapy, and "normal," females. sures showed a highly significant improvement after treatment using sign rank test, based upon within patient score changes. The score changes were therefore compared using paired t statistics, and the percent change, according to the method of Deyo [6]. Kupperman's Index and the disease-specific symptom scores showed the greatest percent change and also the largest t statistics. Using this method, the Mood scales and the PGWB Index showed the least percent change. Although displaying a high percent change, the single items of NHP, part II, had the lowest t statistics. Another estimate of the responsiveness of the different measures was calculated using the formula suggested by Guyatt et al. [28]. Lacking information about variation within stable patients, the variability in the change scores was employed: (mean diff)/(SD diff V~). Sim~arly, the degree of change was expressed in terms of the effect-size index (d value) of Cohen [29]. The dvalue was determined by dividing the change score by the standard deviation at the first measurement. According to Cohen, a d value ~ 0.5 or ~ -0.5, can be regarded as a significant degree of improvement or deterioration. The responsiveness and the effect size index are shown in Table 5. The results of the two approaches are very much in agreement and indicate that the diseasespecific outcomes were the most responsive. Generally the responsiveness was somewhat increased by combining symptoms or subscales into overall scores. In spite of being relatively crude, the NHP seemed to perform equally well compared with the PGWB index, which had performed well in another study using a large number of problem-oriented and psychosocial measures [3O]. The feasibility of assessing quality of life in postmenopausal women employing an approach that combined specific, problem-oriented and general measures was demonstrated. The quality-of-life measures provided valid and multidimensional information about the impact of disease and response to therapy. The limitations of the study is that it only enabled comparisons before
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Table 4
Score Changes after Estrogen T h e r a p y in W o m e n With Climacteric Problems Percent
Measures Kupperman's Index PGWB Total score Anxiety Depression Well being Health Vitality Self-control MACL Tension Deactivation Unpleasantness NHP
Sleep Energy Emotions Social isolation
VAS
Total score Emotional Hot flushes/sweats Tachycardia/vaginal dryness
General complaints NHP
Part II: Paid employment Housework Social life Family life Sex life Hobbies Holidays
Mean Change
(SD)
Change' (%)
Paired t-Statistics
p Value
18.23 13.02 2.92 1.90 2.50 1.42 3.20 1.52
(8.0) (13.6) (3.8) (2.7) (3.1) (2.6) (3.5) (3.0)
70 22 22 28 19 17 25 22
17.01 6.83 5.87 5.23 5.90 4.26 7.02 3.89
.0001 .0001 .0001 .0001 .0001 .0001 .0001 .0003
0.42 0.34 0.26
(0.5) (0.4) (0.4)
18 16 13
5.54 6.27 4.45
.0001 .0001 .0001
19.82 15.83 11.99 7.56
(23.4) (24.8) (18.4) (17.5)
53 57 60 66
6.51 4.83 4.99 3.28
.0001 .0001 .0001 .0018
279.04 110.47 91.27 31.82
(169.8) (88.5) (49.7) (42.1)
65 63 83 58
11.85 9.43 13.62 5.71
.0001 .0001 .0001 .0001
35.72
(28.8)
56
9.38
.0001
0.21 0.17 0.16 0.17 0.26 0.12 0.10
(0.5) (0.5) (0.4) (0.5) (0.4) (0.4) (0.4)
67 50 75 71 67 50 60
3.51 2.62 2.88 2.82 4. 2.18 1.76
.0009 .01 .0056 .0064 .0001 .0336 .08
Number of women = 59 aPercent change calculated as (mean score change/mean initial score). a n d after therapy, which is insufficient. The ultimate w a y of testing the responsiveness of quality-of-life measures p r o p e r l y is b y e m p l o y i n g t h e m in a controlled clinical trial to compare different therapies.
Side Effects and Quality of Life A n o t h e r issue that is closely related to the selection of the most " a p p r o priate" quality-of-life measure in a clinical trial concerns side effects. Side effects occur both d u r i n g active and placebo treatment. I m p r o v e m e n t was almost always reported b y participants in a trial i n d e p e n d e n t of d r u g administration [31], and in a n o t h e r study, the n u m b e r of side effects increased o n inert substances [32]. The significance of placebo-induced side effects was s h o w n in the evaluation of antihypertensive d r u g s in the MRC-trial [33], a n d
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R e s p o n s i v e n e s s a n d Effect Size in the O u t c o m e M e a s u r e s U s e d to Evaluate the Efficacy of Estrogen T h e r a p y Measure
Responsiveness a
Effect Size Index b
Kupperman's Index VAS Total score Hot flushes/sweats Emotional TachycardiaYvaginal dryness
1.61 1.16 1.30 0.88 0.53
2.16 1.62 1.93 1.09 0.73
VAS scales: Sweatings Hot flushes Sleep disturbances Depresesion Fatigue Irritability Headache Nervousness Vaginal dryness Tachycardia Vertigo Arthralgia General complaints
1.17 1.02 0.98 0.60 0.59 0.56 0.51 0.47 0.44 0.43 0.39 0.33 0.88
1.80 1.43 1.37 0.78 0.78 0.73 0.63 0.62 0.63 0.57 0.41 0.38 1.69
PGWB
Total score Vitality Well-being Anxiety Depression Health Self-control
0.68 0.66 0.57 0.54 0.49 0.39 0.36
0.65 0.63 0.62 0.52 0.45
MACL
Deactivation Tension Unpleasantness
0.61 0.54 0.44
0.58 0.65 0.41
NHP
Sleep Emotions Energy Isolation
0.60 0.46 0.45 0.30
0.70 0.46 0.44 0.42
0.41 0.33 0.27 0.26 0.24 0.20 0.16
0.52 0.45 0.38 0.39 0.36 0.28 0.27
Part II: Sex life Paid employment Social life Family life Housework Hobbies Holidays Mean (diff) aResponsiveness SD (diff)V~" Mean (diff) bEffect size index = SD (first measurement)'
0.78 0.77
NHP
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similarly in relation to postinfarction treatments where side effects were common on both active and placebo treatment [34]. However, side effects tend to disappear when the patient is adapted to therapy [35], which also underscores the need for a sufficiently long period of observation during followup. Because it has been argued that the presence of side effects impairs quality of life [7,30], standardized methods tailored to the specific drugs used in a trial are required to supplement the quality-of-life measures. Hitherto, there has been a conspicious lack of attention to how side effects are recorded. Side effects are typically recorded using spontaneous reports and/or active questioning by the physician. This makes comparisons within as well as between studies difficult. More refined and sensitive methods for the recording of drug-specific side effects are required. Preliminary reports have shown promising results using a recently developed minor side effect profile [36]. It proved feasible to use a specific, reliable and sensitive measure to measure the patient's response to initiation of drug therapy [37]. DISCUSSION The choice of strategy for evaluating health-related quality of life in clinical trials is a complex issue. The "best" approach does not necessarily imply that the "best" measure, in terms of responsiveness, should be singly employed. Disease-specific quality-of-life measures have a high relevance for outcome and provide specific information in a concise way. Specific measures tailored to the disease enhance compliance and do not overburden the patient. On the other hand, some standardized psychosocial measures that focus on problems of well-being or dimensions of mood are universal, and could be employed over different patient groups. Reference values are often available, and could be used for comparative purposes. The understanding of the clinical relevance of observed changes would therefore be facilitated. The findings in the estrogen study indicate the importance of having comparison data against which to set the information about the impact of health-related quality of life. For patient populations with more pronounced degrees of distress and dysfunction, selected subscales of generic measures provide valuable information about the impact of disease on quality of life. Disease-specific measures represent obvious advantages in terms of responsiveness. There is no gold standard for comparing the responsiveness of different measures. The different methods described in the literature [6,28,29,38] yield somewhat divergent results. Methods based upon the withinindividual variation in relation to observed changes after therapy give more congruent results irrespective of whether or not more refined statistical operations have been added. An issue of vital concern is whether the assessment should be based upon conventional clinical evidence or upon patient ratings. Again there is no conclusive answer. Generally the correlation between assessments made by physicians and patients with regard to arthritic pain [22], functional capacity [39], general improvement [40], or quality-of-life [41] is modest. From the patient's perspective the ultimate goal of medical intervenfion is increased physical and emotional well-being. Whereas conventional methods show important changes in the patient's clinical status, they are poor
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I. Wiklund and J. Karlberg indicators of h o w the patient feels and functions in day-to-day activity. On the other hand, quality-of-life variables cannot be u s e d as the only outcome unless they bear a relation to physiologic findings. In conclusion, both types of measures are n e e d e d to satisfy clinical credibility as well as relevance to patient. No doubt health is a major c o m p o n e n t of quality of life (42,43), but m a n y more dimensions are required to fully describe health-related quality of life. In that sense, disease-specific measures that solely focus u p o n s y m p t o m s , are too narrow. The estrogen study suggested that other quality-of-life measures a d d e d highly relevant complementary information. Therefore a feasible approach might be to tailor a package of disease-specific, problem-oriented as well as generic measures. More consideration should be given to h o w side effects, which have important implications with regard to quality-of-life, are recorded.
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