REVIEW ARTICLE

PharmacoEconomics I (2): 84-94. 1992 1170-7690/ 92/0002-0084/ $05.50/0 © Adis International Limited. All rights reserved.

PECl18

Quality of Life Instruments in the Evaluation of New Drugs

Roman Jaeschke, 1,2 Gordon H. Guyau2,3 and Deborah Cook l ,2,3 I Department of Medicine, St Joseph's Hospital, Hamilton, Ontario, Canada 2 Department of Medicine, McMaster University, Hamilton, Ontario, Canada 3 Department of Clinical Epidemiology and Biostatistics, McMaster University,

Hamilton, Ontario, Canada

Contents 84 85 85 86 87 87 88 89 90 91

Summary

Summary I. Defining Quality of Life (QOL) 2. Necessary Attributes of QOL Measurement Instruments 3. Taxonomy and Potential Use of QOL Measurement Instruments

3.1 Health Profiles 3.2 Utility Measurements 3.3 Specific Instruments

4. Use of Multiple QOL Measures in Clinical Studies 5. Cautions in Interpretation of Results of Studies Using QOL Measures 6. Conclusions

The importance of measuring changes in a patient's quality oflife when evaluating the efficacy of new drugs is increasingly recognised. In this paper, we review the steps associated with this process - recognising the opportunity and the need to include quality of life instruments during the investigation, choosing the most suitable instrument(s) and interpreting the results. To be useful in clinical trials, quality of life measures must be both responsive (able to detect all im­portant differences) and valid. Generic instruments are applicable to a wide variety of populations but may lack responsiveness. Disease-specific instruments are more likely to be responsive and are directly relevant to patients and clinicians. The approach to measurement in a specific clinical trial should be dictated by the goals of the investigators.

The purpose of this article is to address issues facing investigators interested in including Quality of life (QOL) instruments in clinical trials evalu­ating new drugs. These issues include reaching agreement on what the concept of Quality of life actually entails, identifying the purpose for which

the QOL instrument is to be used, recognising and confirming the attributes which instruments should have to fulfil in their role, choosing from many available QOL measurement instruments, and in­terpreting data obtained with their use.

The severity of any disease process and the use-

Quality of Life and Drug Therapy

fulness of therapeutic interventions (whether new drugs, surgical operations, or psychological tech­niques) designed to ameliorate or eliminate the im­pact of the disease may be judged on several dif­ferent levels. In some situations, the most compelling evidence of the efficacy of a new drug may be a reduction in mortality (e.g. streptokinase after myocardial infarction), rate of hospitalisation (neuroleptics for schizophrenia), rate of disease oc­currence (antihypertensives for strokes) or recurr­ence (some form of chemotherapy after surgical cancer treatment). Frequently, clinicians rely on direct physiological measures of the severity of a disease process - for example, left ventricular ejec­tion fraction in congestive heart failure, spirometry in chronic airflow limitation, or glycosylated haemoglobin level in diabetes mellitus.

Over the last several years, it became increas­ingly recognised that there are other important as­pects of the usefulness of the new interventions which physiological or biochemical outcomes do not address. These encompass the ability to func­tion normally; to be free of pain and other physi­cal, psychological and social symptoms; to be free from iatrogenic problems associated with treat­ment; and (in some health care systems) to remain solvent. It was also noticed that, on occasion, the conclusion reached when evaluating different out­comes may differ - physiological measurements may change without people feeling better (Fran­ciosa et al. 1984; Packer 1987); a drug may amel­iorate symptoms without measurable change in physiological function; or life prolongation may be achieved at the expense of unacceptable pain and suffering (Danis et al. 1988). Recognition of these subjective, patient-oriented (versus disease-ori­ented) areas of well-being led to the introduction of a jargon term: 'quality of life'. Various terms used have been defined for the reader in the Guide Chart at the end of this article (p. 94).

1. Defining Quality of Life (QOL)

The attempts to include QOL assessment in ad­dressing the efficacy of new interventions requires a common understanding of what the term means.

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As it is often used, QOL lacks focus and precision and, because it is an abstract concept, its definition has led to much debate. Quality of life has been described as an area encompassing aspects (do­mains) of physical, social and emotional health that are relevant and important to the patient (Levine 1991). Since the patient's subjective well-being is influenced by many factors unrelated to disease process or treatment (e.g. level of education, qual­ity of the environment, etc.), a narrower term has been introduced: 'health-related quality of life' (HRQOL). In this article the term 'quality of life' is used to denote health-related quality of life.

More elaborate definitions stem from the rec­ognition that quality of life may be considered on different levels: overall assessment of well-being; within several broad domains (physiological, func­tional, psychological, social and economic); or within subcomponents of each domain (e.g. pain, sleep, activities of daily living, and sexual function within physical and functional domains) [Spilker 1990bj. It follows that QOL is a multifactorial con­cept which, from the patient's perspective, repre­sents the final common pathway of all the phys­iological, psychological and social influences of the therapeutic process (Schipper et al. 1990). In this sense, the concept of QOL is close to the World Health Organization (WHO) definition of health, which is 'not merely the absence of disease, but complete physical, psychological, and social well­being' (WHO 1958). It follows also that when as­sessing the impact of a new drug (or any new in­tervention) on patients' QOL, we may be inter­ested in describing the patient status (or changes in the patient status) on each of the foregoing lev­els, and that different strategies and instruments are required to explore separate domains.

2. Necessary Attributes of QOL Measurement Instruments

In general terms, any health-measurement in­strument could be used either to discriminate among patients (either according to current func­tion or according to future prognosis), or to eval-

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uate changes occurring in the health status (in­cluding QOL) over time (Kirshner & Guyatt 1985). In most clinical trials, QOL measurement instru­ments are used for evaluation of the effects of therapy, with treatment effect being expressed as a change in the score of the instrument over time. Occasionally instruments are used to discriminate among patients: for example, when planning a study evaluating the effect of a new drug treatment on functional status in patients after myocardial in­farction, the investigators may wish to divide po­tential patients into those with reasonable and those with poor cardiovascular function (with a view to subsequent intervention in the latter group).

The purpose for which a given instrument is used dictates, to some degree, its necessary attri­butes. Each QOL measurement instrument, re­gardless of its particular use, should be both repro­

ducible and valid. Reproducibility is judged by the degree to which repeated administration of the same instrument yields the same result in stable patients. The validity of an instrument refers to its ability to measure what it is supposed to measure. This attribute of a measurement instrument is difficult to establish when there is no criterion standard, which is certainly the case with evaluation ofQOL. In such situations, the validity of an instrument is frequently established in a stepwise process, in­cluding examination of 'face validity' (or sensibil­ity) [Feinstein 1987] and 'construct validity'. Face validity relies on the intuitive assessment of an in­strument which examines the targeted domain, whereas construct validity refers to the extent to which results from a given instrument relate to other measures in a manner consistent with the theoretical hypotheses. For example, we could hy­pothesise that changes in spirometry related to a use of a new drug in patients with chronic airflow limitation should bear close correlation with changes in functional status of the patients - and a weaker correlation with changes in their emo­tional status.

The final attribute of a QOL measurement in­strument is its ability to detect any clinically im­portant change in QOL. This attribute, usually de­noted 'responsiveness', is crucial when an

PharmacoEconomics 1 (2) 1992

instrument is used for the purposes of evaluating a response to therapy. It is less important when the goal is to discriminate among patients at one point of time. Obviously, to be of use, the ability of an instrument to show change when such change oc­curs (responsiveness) has to be combined with its stability under unchanged conditions (reproduci­bility). For further discussion on this subject the reader is referred to more complete texts (Guyatt et al. 1987; Jaeschke & Guyatt 1990; Levine 1991; Osoba et al. 1991).

3. Taxonomy and Potential Use 0/ QOL Measurement Instruments!

During the past decade, clinical journals started to publish trials in which QOL instruments were the measures of primary outcome (Guyatt et al. 1989). With the expanding importance of the QOL measures in evaluating new therapeutic interven­tions, investigators (and readers) are faced with a large array of instruments. In a recent quality of life bibliography Spilker et al. (1990) refer to sev­eral hundreds of QOL instruments and well over 500 papers with focus on quality of life measure­ments. Different ways of categorising these instru­ments have been proposed - according to the pur­pose of their use: into instruments designed for screening, description of health profiles, preference measurement and clinical decision (Osoba 1991); or into discriminative and evaluative instruments (see section 2). A different taxonomy based on the domains of quality of life which an instrument at­tempts to cover has also been proposed (Guyatt et al. 1989). According to this taxonomy, a QOL in­strument may be categorised, in a broad sense, as 'generic' or 'specific'. Generic instruments cover (or at least aim to cover) the complete spectrum of function, disability, and distress of the patient, and may well be applicable to a variety of populations. Within the framework of generic instruments,

I Based on previous publications: Guyatt et at. (1989) and Guyatt & Jaeschke (1990).

Quality of Life and Drug Therapy

'health profiles' and 'utility measures' allow 2 dis­tinct approaches to measurement of the global quality of life.

3.1 Health Profiles

A health profile is a single instrument which measures different aspects of QOL. It usually pro­vides a scoring system which allows aggregation of the results into a small number of scores, and sometimes into a single score (in which case, it may be referred to as a Health Index). As generic meas­ures, health profiles are designed for use in a wide variety of conditions. For example, one of the most popular health profiles, the Sickness Impact Profile (SIP), contains 12 'categories' which can be aggre­gated into 2 dimensions and 5 independent cate­gories, and also into a single overall score (Bergner et al. 1981). The SIP has been used in studies of cardiac rehabilitation (Ott et al. 1983), total hip joint arthroplasty (Liang et al. 1985), and treat­ment of back pain (Deyo et al. 1986). In addition to the SIP, several other health profiles are avail­able: these include the Nottingham Health Profile (Hunt et al. 1980), the McMaster Health Index Questionnaire (Sackett et al. 1977) and a collection of related instruments developed by the Rand Cor­poration for their health insurance study (Brook et al. 1979). While each health profile attempts to measure all important aspects of quality oflife, each may slice the QOL pie quite differently. For ex­ample, the McMaster Health Index Questionnaire follows the World Health Organization approach and identifies 3 dimensions: Physical, Emotional, and Social. The Sickness Impact Profile includes a Physical dimension (with categories of ambulation, mobility, body care and movement), a Psychoso­cial dimension (with categories including social interaction and emotional behaviour), and 5 in­dependent categories including eating, work, home management, sleep and rest, and recreations and pastimes.

General health profiles offer a number of ad­vantages to the clinical investigator. As their re­producibility and validity have been established, often in a variety of populations, they can be used

87

for discriminative purposes to examine and estab­lish areas of dysfunction affecting a particular population. Identification of these areas of dys­function may guide investigators in constructing disease-specific instruments to target the therapeu­tic intervention at the areas of potentially greatest impact on the QOL. Health profiles, used as eval­uative instruments, allow determination of the ef­fects of an intervention on different aspects of QOL, without necessitating the use of multiple instru­ments (and thus saving both the investigator's and the patient's time). Because health profiles are de­signed to assess a wide variety of conditions, one can potentially compare the effects on QOL of dif­ferent interventions in different diseases. Profiles which provide a single score can be used in a cost­effectiveness analysis, in which the cost of an in­tervention in dollars is related to its outcome in natural units (Freund & Dittus 1992). The main limitation of health profiles is that they may not focus adequately on the aspects ofQOL specifically influenced by a particular intervention (i.e. lack of responsiveness) [Deyo & Centor 1986; MacKenzie et al 1986].

3.2 Utility Measurements

Utility measures of QOL are derived from eco­nomic and decision theory. QOL is measured hol­istically as a single number along a continuum from death (0.0) to full health (1.0). The use of utility measures in clinical studies requires serial meas­urement of the utility of the patient's QOL throughout the study. There are 2 fundamental ap­proaches to utility measurement in clinical studies. One is to ask patients a number of questions about their function. On the basis of their responses, patients are classified into one of a number of cat­egories. Each category has a utility value associated with it, the utility having been established in pre­vious ratings by another group (such as a random sample of the general population). This approach characterises a widely used instrument called the Quality of Well-Being Scale (Kaplan et al. 1976, 1989; Kaplan & Bush 1982). The second approach is to ask patients to make a single rating which

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takes into account all aspects of their QOL (Torr­ance 1986). There are many ways this rating can be made. In the 'standard gamble' method the sub­jects are asked to choose between their own health state and a gamble in which they may die imme­diately or achieve full health for the remainder of their lives. Using the standard gamble method, patients' utility or QOL is determined by the choices they make, as the probabilities of imme­diate death or full health are varied (Drummond et al. 1987). A more simple and more widely used technique is the time trade-off, in which subjects are asked about the number of years in their pre­sent health state they would be willing to trade off for a shorter life span in full health (Torrance 1986).

One major advantage of utility measurement is its amenability to cost-utility analysis. In cost-util­ity analysis, the cost of an intervention is com­pared with the number of quality-adjusted life-years (QALYs) gained through application of the inter­vention (Freund & Dittus 1992). Such values may be compared and used to provide a basis for al­location of scarce resources among healthcare pro­grammes. Results from the utility approach may thus be of particular interest to programme eval­uators and health policy decision-makers. How­ever, utility measurement also has limitations. Utilities can vary depending on how they are ob­tained, raising questions of the validity of any single measurement (Llewellyn-Thomas et al. 1982; Suth­erland et al. 1983). Utility measurement does not allow the investigator to determine which aspects of QOL are responsible for changes in utility (as subjects provide a holistic rating, taking both treat­ment and side effects into account). Finally, utili­ties potentially share the disadvantage of health profiles, in that they may not be responsive to small but still clinically important changes in health status.

3.3 Specific Instruments

An alternative approach to QOL measurement is to focus on aspects of health status which are specific to the area of primary interest (Guyatt et al. 1986). The rationale for this approach lies in

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the increased responsiveness which may result from including only those aspects of QOL which are rel­evant and important in a particular disease process or even in a particular patient situation. One could also focus an instrument only on the areas which are likely to be affected by a particular drug. This latest approach is advanced in the design and con­duct of'randomised controlled trials in individual patients' ('N-of-I RCfs') [Guyatt et al. 1990b]2. For example, in 26 N-of-I RCfs conducted in patients with chronic airflow limitation to evaluate the re­sponse of a given patient to a particular drug, the primary outcome measure was a patient-specific QOL measurement instrument (Patel et al. 1991). Construction of these instruments was based on patients' assessment of the areas of life which they thought were affected by the disease and which were important in their day-to-day life. The activities chosen by the patient were then incorporated into the questionnaire examining the degree of short­ness of breath experienced by patients while they performed these activities. Each question had a re­sponse option presented as a 7-point scale. For ex­ample, if the patient stated that dyspnoea while playing with grandchildren was a limitation which was important in day-to-day life, we asked: 'Please indicate how short of breath you have been while playing with your grandchildren during the past day by choosing one of the following options: (a) Ex­tremely short of breath; (b) Very short of breath; (c) Quite a bit short of breath; (d) Moderately short of breath; (e) Mildly short of breath; (f) A little short of breath; (g) Not at all short of breath.'

This approach allows use of a QOL instrument which is not only disease- and patient-specific, but

2 The N-of-I design is based on pairs of active/placebo, high dose/low dose or first drug/alternative drug combinations, the order of administration within each pair being determined by ran­dom allocation. Treatment targets (for example quality of life) are monitored in a double-blind fashion on a regular, predeter­mined schedule throughout the trial. Statistical analysis of the results can include examination of the mean values for all meas­ures for each treatment period, the mean differences between treatment and control periods, and the probability of differences being due to chance.

Quality of Life and Drug Therapy

which also can explore the domains most likely to be influenced by a given new drug. The concept of using N-of-l RCTs in investigating new drugs is discussed elsewhere (Guyatt et al. 1 990a).

In other situations, the instrument may be spe­cific to the disease (instruments for chronic lung disease, rheumatoid arthritis, cardiovascular dis­eases, endocrine problems, etc.); specific to a popu­lation of patients (instruments designed to measure the QOL of the frail elderly, who are afflicted with a wide variety of different diseases); specific to a certain function (questionnaires which examine emotional or sexual function); or specific to a given condition or problem (such as pain) which can be caused by a variety of underlying pathologies (Spilker et al. 1990). Within a single condition, the instrument may differ depending on the interven­tion. For example, while success of a disease-mod­ifying agent in rheumatoid arthritis should result in improved QOL by enabling a patient to increase performance of physically stressful activities of daily living, occupational therapy may improve quality oflife by encouraging family members to take over activities formerly accomplished with difficulty by the patient. Appropriate disease-specific QOL out­come measures should reflect this difference.

Specific instruments can be constructed to re­flect the 'single state' (how tired have you been: very tired, somewhat tired, full of energy) or a 'transition' (how has your tiredness been: better, the same, worse) [MacKenzie & Charlson 1986]. Morbidity, including events such as recurrent myo­cardial infarction, can be integrated into specific measures (Olsson et al. 1986). Disease-specific in­struments may be used for discriminative pur­poses. They may add, for example, in evaluating the extent to which a primary symptom (for ex­ample dyspnoea) is related to the magnitude of physiological abnormality (for example exercise ca­pacity) [Mahler et al. 1987]. Disease-specific in­struments can be applied for evaluative purposes to establish the impact of an intervention on a spe­cific area of dysfunction, and hence add in the elu­cidating the mechanisms of drug action (laeschke et al. 1991). Guidelines for constructing specific

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measures are available (Guyatt et al. 1986; laeschke & Guyatt 1990; MacKenzie & Carlson 1986).

In addition to improved responsiveness, dis­ease-specific measures have the advantage of re­lating closely to areas routinely explored by the physician in their regular clinical activities (e.g. symptoms present in and important for this par­ticular patient). For example, one disease-specific measure of quality of life in chronic lung disease focuses on dyspnoea during day-to-day activities, fatigue, and areas of emotional dysfunction includ­ing frustration and impatience (Guyatt et al. 1987). Specific measures may therefore appear clinically sensible to the physician.

The disadvantages of specific measures is that they are (deliberately) not comprehensive, and cannot be used to compare across conditions or, at times, even across programmes. Determining whether specific measures increase responsiveness and clinical credibility sufficiently to warrant their use will require head-to-head comparisons of dif­ferent approaches in the setting ofrandomised con­trolled studies (Bombardier et al. 1986).

4. Use of Multiple QOL Measures in Clinical Studies

Clinical investigators are not restricted to using a single instrument in their studies. Much remains to be learned about optimal ways of measuring QOL, and investigators may wish to see how dif­ferent instruments perform. Aside from this sort of inquiry (which focuses on the instruments, rather than the intervention) an investigator may con­clude that a single instrument will not yield all the relevant information. For example, utility and dis­ease-specific measures contribute quite different sorts of data, and an investigator may want to use one of each.

Another, somewhat different way of using mul­tiple instruments is to administer a battery of spe­cific instruments. One example of a clinical study in which a battery of instruments was used to measure multiple aspects of quality of life is a double-blind, randomised trial of 3 antihyperten­sive agents in primary hypertension (Croog et al.

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1986). The investigators identified 5 dimensions of health they were measuring: the sense of well-being and satisfaction with life; the physical state; the emotional state; intellectual functioning; and abil­ity to perform in social roles, and the degree of satisfaction from those roles. Even within these 5 dimensions, additional components were identi­fied. For example, separate measurements of sleep and sexual function were made. Patients taking I of the 3 drugs under investigation, captopril, scored better on measures of general well-being, work performance, and life satisfaction. The lesson for the clinician is clearly important: one can have an impact on not only the length, but also the qual­ity of the patient's life according to choice of anti­hypertensive agent.

This approach, although comprehensive, has limitations. First, investigators must find a valid, responsive instrument for every attribute they wish to measure. Secondly, it is possible (indeed likely) that only some of the instruments chosen will show differences between the treatments under investi­gation. Unless one of the instruments has been des­ignated as the primary measure of outcome before the study was started, different results in different measures may make interpretation difficult. The greater the number of instruments used, the greater the probability that one or more will favour one treatment or the other, even if the treatments are equally effective. Thus, the a error (the probability of finding an apparent difference between equally effective treatments) increases with each new in­strument used, leading to type I errors. Although this problem may be dealt with through statistical adjustment for the number of instruments used, such adjustment has seldom been made in pre­vious studies (Pocock et al. 1987).

Another problem occurs if only a small pro­portion of the instruments used favour an inter­vention (or if some measures favour the experi­mental treatment and other instruments favour the control). In these situations, the clinician may be unsure how to interpret the results. For example, in a controlled study in which patients with recent myocardial infarction were randomised to receive standard care, an exercise programme, or a coun-

PharmacoEconomics 1 (2) 1992

selling programme, Mayou and colleagues (1981) rated many variables, including work (change in physical activity, satisfaction, and time of return), leisure (change in physical activity, satisfaction, and exercise for health), marriage (change in protec­tiveness and communication), sex (change in frequency and satisfaction), satisfaction with out­come, compliance with advice, psychiatric symp­toms, cardiac symptoms and general health. For almost all of these variables, there was no differ­ence between the 3 groups. However, patients were more satisfied with exercise than with the other 2 regimens; families in the advice group were less protective, and the advice group had a greater number of work hours and a higher frequency of sexual intercourse at follow-up after 18 months. The study was viewed by authors as not supporting the effectiveness of rehabilitation in improving QOL. However, programme advocates might argue that the intervention is worthwhile if any of the ratings favoured treatment. Use of multiple instruments opens the door to such potential controversy.

Finally, using a battery of instruments gives no indication of the relative importance of various areas of dysfunction to the patient. For example, if Croog et al. (1986) had found that one anti­hypertensive agent disturbed sleep, while another had an adverse impact on sexual function, their approach would not have allowed them to deter­mine which drug had a greater net adverse impact on patients' lives.

5. Cautions in Interpretation of Results of Studies Using QOL Measures

The clinician wanting to include health-related QOL measures in assessing the effectiveness of any new therapeutic intervention faces several form­idable challenges, including the need to interpret the results and communicate them in a meaningful fashion to other clinicians.

The effect of any treatment should be expressed in terms of both statistical significance and clinical relevance. Meeting criteria of statistical signifi­cance carries no guarantee that the differences ob-

Quality of Life and Drug Therapy

served are large enough to mandate treatment, or that the outcomes which result are particularly sat­isfying. When the measures of outcome are discrete events (e.g. mortality, or well defined adverse events), the effect of an intervention may be trans­lated into number oflives saved, number of strokes avoided or cost of hospitalisation saved. In these circumstances, the significance of the treatment ef­fects is similar for the physicians, patients, patients' families and the society.

However, for most QOL measures, especially the specific ones, interpretation is much more dif­ficult. Measuring quality of life involves analysis of patients' subjective assessment of their level of physical dysfunction or psychological discomfort. If we find a mean change of O.4cm on a !Ocm vis­ual analogue scale measuring tiredness, does this constitute a large difference or a clinically trivial difference? Is a difference of 0.4 point per question on a 5-point Likert scale measuring the severity of the same symptom worth continuation of treat­ment (German and Austrian Xamoterol Study Group 1988)? Or is an improvement by 0.5 point on a 52-point scale measuring physical symptoms sufficient to recommend the use of an expensive new drug (Croog et al. 1986)?

Translating changes in a QOL instrument score into clinically meaningful terms is clearly crucial in the interpretation of study results. Such trans­lation may be accomplished in different ways. For general instruments (both health profiles and util­ity measures) it is possible to compare the changes associated with the use of a new drug with those associated (for the same instrument) with use of interventions considered beneficial. For specific in­struments, one possibility is to examine the changes in the instrument score in patients, providing an overall assessment of stability or change. We have recently reported our experience with the use of symptom questionnaires where the response op­tions were presented on a 7-point Likert scale. Two analyses were done, one using data from 3 trials in patients with heart and lung disease (Jaeschke et al. 1989), and the other done on the basis of 36 N-of-I RCTs performed in different conditions and using different drugs (Jaeschke et al. 1991). In both

91

cases we observed that a difference of approxi­mately 0.5 point per question in the questionnaire score corresponded to the minimal amount of change which patients considered significant and worthy of continuation of therapy. Similar obser­vations may be derived from reports of others (Laupacis et al. 1991). Obviously such data are ap­plicable only to results presented on a 7-point scale, and may be even idiosyncratic to the studied con­ditions. On the other hand, with the expanding use of QOL measurement instruments in investigating the effects of different interventions, our under­standing of what changes in these instrument scores actually mean should improve. In the meantime, the analyst should at least comment on the avail­ability of any data that allows clinical interpreta­tion of the results obtained.

6. Conclusions

We have reviewed the theory behind, and the process of using, QOL measurement instruments in the evaluation of new drugs. There is little doubt that the importance of evaluating QOL in trials of drug therapy has gained recognition. For example, among 75 randomised controlled trials reported in the Annals of Internal Medicine. New England Journal of Medicine. and American Journal of Medicine in 1986, 32 used at least one QOL in­strument (Guyatt et al. 1989). While confirming the growing importance attached to examining QOL, the same authors judged, however, that QOL should have been assessed in 25 out of the 43 re­maining trials. They point out that in the majority of situations, instruments of untested validity, re­producibility, and responsiveness have been used. Numerous texts published since 1986 (for example McDowell & Newell 1987; Osoba 1991; Spilker 1990a; Spilker et al. 1990) outline rational and ef­fective approaches to the use ofQOL measures, the choice of appropriate instrument(s), the proper technique of their application, and the interpreta­tion of the results. We refer the interested readers to these publications.

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Acknowledgement

This work was partially supported by the St Joseph's Hospital Foundation and the Ontario Ministry of Health.

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