Advances in Measuring Quality-of-Life Outcomes in Cancer Care

Advances in Measuring Quality-of-Life Outcomes in Cancer Care

2 Seminars in Oncology Nursing, Vol 26, No 1 (February), 2010: pp 2-11 ADVANCES IN MEASURING QUALITY-OF-LIFE OUTCOMES IN CANCER CARE CAROL ESTWING F...

246KB Sizes 0 Downloads 80 Views


Seminars in Oncology Nursing, Vol 26, No 1 (February), 2010: pp 2-11

ADVANCES IN MEASURING QUALITY-OF-LIFE OUTCOMES IN CANCER CARE CAROL ESTWING FERRANS OBJECTIVE: To provide practical guidance for the selection and use of qualityof-life (QOL) instruments for research and clinical practice.

DATA SOURCES: Published articles, books, and web resources. CONCLUSION: Even among instruments designed specifically to measure QOIL, there are vast differences in what they actually measure. The choice of instrument can make the difference between whether real changes in QOL are captured or not.

IMPLICATIONS FOR NURSING PRACTICE: QOL outcomes are ideal for determining the efficacy and impact of cancer care. Incorporating QOL into standard clinical practice holds great promise for improving communication with health care providers, with a resultant improvement in patient outcomes. KEY WORDS: Quality of life, measurement tools, outcomes measures in health care, outcomes assessment, instruments, cancer.


UALITY-OF-LIFE (QOL) outcomes are ideal for determining the efficacy and impact of cancer care. This concept is uniquely suited for

Carol Estwing Ferrans, PhD, RN, FAAN: Professor and Associate Dean for Research, Co-Director, Center of Excellence in Eliminating Health Disparities, Department of Biobehavioral Health Science, College of Nursing, University of Illinois at Chicago, Chicago, IL. Address correspondence to Carol Estwing Ferrans, PhD, RN, FAAN, University of Illinois at Chicago, College of Nursing (MC 802), 845 S. Damen Ave, Chicago, IL 60612; e-mail: [email protected] Ó 2010 Elsevier Inc. All rights reserved. 0749-2081/10/2601-$32.00/0. doi:10.1016/j.soncn.2009.11.002

oncology, giving us the means to convey what we strive for in our care, and focusing our efforts on long-term outcomes for the whole patient. But selecting a measure of QOL can be challenging, given the hundreds of instruments (questionnaires) currently available. Even among instruments designed specifically to measure QOL, there are vast differences in what they actually measure. The choice of instrument can make the difference between whether real changes in QOL are captured or not. This article provides practical guidance for the selection and use of QOL instruments for research and clinical practice. QOL commonly is referred to as a single multidimensional construct. However, developments of the field over the past 20þ years show that QOL more accurately may be considered a family of



Characteristics of the Individual

Personality Motivation

Symptom Amplification

Biological and Physiological Variables

Symptom Status

Functional Status

Psychological Supports

Social and Economic Supports

Values Preferences

General Health Perceptions

Overall Quality of Life

Social and Psychological Supports

Nonmedical Factors Characteristics of the Environment

FIGURE 1. Wilson and Cleary’s model for health-related QOL. (Reprinted with permission: Wilson and Cleary, 1995.3)

concepts, rather than a single one. For example, the US National Institutes of Health defines health-related QOL measures as ‘‘patient outcome measures that extend beyond traditional measures of mortality and morbidity, to include such dimensions as physiology, function, social activity, cognition, emotion, sleep and rest, energy and vitality, health perception, and general life satisfaction.’’1 This explains why leaders in the field are comfortable with the fact that there is no widely accepted definition or gold standard for measurement. The ‘‘best’’ instrument for any given situation is case-specific, determined by the fit with the aims to be accomplished, the target population, and the setting (research, clinical practice, community outreach, etc).

ORGANIZING FRAMEWORK FOR QOL INSTRUMENTS With such variety in the field, an organizing framework is needed. Wilson and Cleary2,3 developed a conceptual model of the most common ways of measuring health-related QOL (Fig. 1). The model focuses on the five boxes in the middle of the figure, representing five categories of outcomes. The first box begins the causal chain, but is not actually a QOL concept.2 This is because biological and physiological variables focus on the function of cells, organs, and organ systems. These are not assessed through patientreported outcomes (PROs), but through labora-

tory tests, physical assessment, and histologic studies. The following four boxes in the model are QOL concepts and are all assessed through PROs. To be considered a PRO, the information must be provided by the patient, typically by questionnaire, rather than by a health professional or other person. A rating based on professional judgment, even if it is based on information provided by the patient, would not qualify as a PRO. The term ‘‘PRO’’ sometimes is used interchangeably with QOL, but this is not actually correct. QOL measures are all PROs, but not all PROs are QOL measures. The four QOL components of the model begin with the second box, symptom status. This refers to emotional and cognitive symptoms, as well as physical symptoms, functional status, includes physical, psychological, social, and role functioning. The fourth box, general health perceptions, provides an integration of all the boxes preceding it, and refers to the patient’s subjective rating of their health. Overall QOL is the fifth and final box, which refers to how happy or satisfied someone is with life as a whole. In the model, the patient’s values and preferences influence both general health perceptions and overall QOL.

WHAT QOL INSTRUMENTS MEASURE To use this model to identify what QOL instruments actually measure, we performed an item analysis of the three most commonly used



instruments in cancer clinical trials: the FACTG,4 EORTC QLQ C-30,5 and SF-36.6 Each item was sorted into one of the four QOL components of the Wilson and Cleary model (Fig. 2). The analysis showed that there were indeed differences among the instruments.7 The FACT-G predominantly measures symptoms, with a 3:1 ratio of symptom to functioning items. The EORTC QLQ-C30 also is composed primarily of symptom and functioning items, but with a more balanced 3:2 ratio of symptom to functioning items. In contrast, the SF-36 predominantly measures functioning, with a 1:2 ratio of symptom to functioning items. The next two components of the Wilson and Cleary model have negligible representation in the three instruments. There were no general health perception questions in the FACT-G, one in the EORTC-QLQ C30, and two in the SF-36. For overall QOL, the FACT-G and EORTC-QLQ C30 each had one item for this component. The SF-36 had no questions asking the respondent to rate their QOL. The website for the SF-36 (Quality Metric) states that it measures ‘‘functional health,’’ which is consistent with our item analysis.8 This also is consistent with the developer’s early publications describing the instrument, which called it a measure of health status, but not specifically a QOL instrument (see Ware, 19849). It is clear from this analysis that there are substantial differences in what the three instruments measure, and so will provide different information. Because of this, it is essential to examine the items (questions) in the instruments themselves, to consider which one provides the best fit for the situation and use. This is also important for the evaluation of completed studies, such as clinical trials, when considering whether a specific instrument was a good fit for the intended clinical application and population. If instruments are not sufficiently sensitive, studies may erroneously conclude that Percentage 80 70 60 50 40 30 20 10 0 Symptoms

there are no differences between two therapies or that an intervention has no effect. The final component of the Wilson and Cleary model, overall QOL, could be considered the quintessential element of the model because it provides a summation of all the components that come before it.7 A patient’s evaluation of overall QOL can be measured by a single global QOL question. An example of a global question is the Spitzer Uniscale, which is widely used in symptom management trials in cancer. The Uniscale is a single item, stating ‘‘Please rate your overall quality of life’’.10 Another example is, ‘‘How would you rate your overall quality of life during the past week?’’ from the EORTC QLQC30. The FACT-G asks patients to respond to the statement ‘‘I am content with the quality of my life now’’ on a scale ranging from ‘‘not at all’’ to ‘‘a little bit.’’ These questions could be pulled out and used as global QOL questions, but this is not part of the standard scoring procedure. For the EORTC QLQ-C30, the global QOL question is combined with a general health rating (‘‘How would you rate your overall health during the past week?’’) to produce the EORTC QLQ C30 global health and QOL scale. For the FACT-G the global QOL question is combined with six other questions addressing other aspects of life, to form the FACT functional well-being scale. Overall QOL also can be assessed through multi-item scales, such as those designed to measure happiness or life satisfaction. Two examples are the Quality of Life Index (QLI)11,12 and the Frisch Quality of Life Inventory (QOLI), which measure life satisfaction and include patient’s ratings of importance when calculating scores.13 In fact, there is an entire field focusing on happiness and life satisfaction, often referred to as subjective well-being. For a review of this research over the past 30 years, see Diener et al.14



Gen Health

Overall QOL

FIGURE 2. Components of QOL measured by the FACT-G, EORTC QLQ-C30, and SF-36.

QOL instruments have traditionally been characterized in terms of the domains they measure, rather than what they measure within those domains. For example, Table 1 lists the domains (scales and subscales) measured by a variety of well-established QOL instruments used in patients with cancer. For the majority, the domain names were designed to show the breadth of what



TABLE 1. Domains of Instruments Used to Measure QOL Cancer Rehabilitation Evaluation System (CARES)-Short Form15 Physical Psychosocial Marital Sexual Medical Interaction EORTC Quality of Life Questionnaire (EORTC QLQ-C30)5,16 Physical Functioning Role Functioning Cognitive Functioning Emotional Functioning Social Functioning Pain Fatigue Nausea and Vomiting Appetite Loss Diarrhea Constipation Sleep Disturbance Financial Impact Global health & QOL Functional Assessment of Cancer Therapy (FACT/FACIT)4,17 Physical Well-Being Social/Family Well-Being Emotional Well-Being Functional Well-Being Functional Living Index-Cancer (FLIC)18,19 Physical Functioning Psychological Functioning Current Well-Being Gastrointestinal Symptoms Social Functioning

McGill Quality of Life Questionnaire20 Physical Symptoms Psychological Symptoms Outlook on Life Meaningful Existence Quality of Life Index-Cancer Version (QLI)11,12,21 Health and Functioning Psychological/Spiritual Social and Economic Family Quality of Life Scale for Cancer (QOL-CA)22 Physical Well-Being Psychological Well-Being Spiritual Well-Being Social Well-Being SF-36 Health Survey6,23 Physical Function Physical Role Function Vitality Bodily Pain Mental Health Emotional Role Function Social Function General Health Perceptions

Note: All the instruments listed were developed for use with cancer patients, except for the SF-36, which was designed for the general population.

the instrument measured. When these instruments were developed in the 1980s and 1990s, a primary goal was to expand QOL measures beyond physical functioning. At that time Karnofsky’s Performance Status scale24 was considered a measure of QOL, even though it was designed only to assess physical performance rated on a scale from 0 to 100 (0 ¼ dead; 100 ¼ normal activity). Thus, the goal was to develop QOL instruments that would capture the whole of life, and this is reflected in their domain names. The FACT-G is an example of one of these early QOL instruments. To identify what is measured within each of the FACT-G domains, we again performed an item analysis, this time sorting the items for

each domain into one of the four components of the Wilson and Cleary model (Fig. 3). As seen in Fig. 3, there are differences in what is measured even within the individual domains, which is not conveyed by the domain names. Another example is the Ferrans and Powers Quality of Life Index (QLI).12 The QLI actually measures life satisfaction, which is characterized in the fifth box of the Wilson and Cleary model (overall QOL). Conceptual models also have been developed to portray the idea that QOL encompasses the whole of life, and these have characterized QOL in terms of domains. Thus, the intention of these models was to define the nature of QOL, unlike the Wilson and Cleary model, which was designed to provide




Physical Well Being & Symptoms

100 90 80 70 60 50 40 30 20 10 0

Symptoms Functioning Gen Health Overall QOL




Psychological Well Being Sense of Control Anxiety Depression Enjoyment/Leisure Fear of Recurrence Happiness Fear Cognition/Attention

Pain Functional Ability Strength/Fatigue Sleep & Rest Nausea Appetite Constipation


FACT-G Domains

FIGURE 3. Components of QOL within the FACT-G domain subscales. an organizing framework for the many ways of measuring QOL. Two examples of these early models are the City of Hope model (Fig. 4)25 and the Ferrans model for QOL (Fig. 5).12,26 Because the two models were developed simultaneously and independently, and both were generated and tested based on patient information, the similarities between the two models provide validation for each other. The domains originally proposed in these two models are now widely represented as the essential domains of QOL.27,28

SELECTING THE RIGHT INSTRUMENT Traditionally, QOL instruments have been characterized as generic or disease-specific. Generic instruments are designed to measure QOL broadly, typically across all the domains of life. These instruments are useful for making comparisons with the general population and other illness groups, which aids meaningful interpretation of the scores. They also help to understand the impact of illness on life as a whole, as well as to screen for unanticipated adverse effects of treatment. However, the fact that they measure QOL broadly also can be a disadvantage, because important aspects of life may be addressed only superficially or not at all. In contrast, diseasespecific instruments are designed to focus more narrowly for a specific type of cancer or treatment. This usually provides more power to detect changes in specific symptoms, but a narrow focus may cause other effects of therapy to be missed. To address this concern, some families of instruments have developed additional modules for increased specificity. For example, the core instruments for the FACT-G and EORTC QLQC30 were both developed for use in all types of cancer clinical trials. Later, modules were devel-

Quality of Life

Social Well Being Caregiver Burden Roles & Relationship Affection/Sexual Function Appearance Financial Burden

Spiritual Well Being Hopefulness Suffering Meaning of Illness Religiosity Transcendence Uncertainty

FIGURE 4. City of Hope model of QOL. oped for specific cancer types and treatment, such as the biological response modifier module for the FACT (FACT-BRM). It is critically important to choose instruments that are sufficiently sensitive, so they can detect real changes in QOL or its components. For this reason, the choice of instrument needs to be driven by the specific purpose and context for its use. This Health and Functioning Domain

Psychological/ Spiritual Domain Quality of Life Social and Economic Domain

Family Domain

FIGURE 5. Ferrans Conceptual Model for Quality of Life.


is true for both research studies and clinical practice settings, and means that no one instrument will be the best for all situations. For example, a comprehensive review of clinical trials in breast cancer by Ganz and Goodwin29 showed that measures of symptom control (such as pain, fatigue, nausea, treatment toxicities, and physical performance status) were the most sensitive for demonstrating the efficacy of pharmacologic agents. On the other hand, for psychosocial interventions, psychosocial measures were most sensitive for demonstrating efficacy. Thus, in some situations investigators may choose to measure selected aspects of QOL, such as symptoms or functioning, because they are anticipated to provide the greatest sensitivity for that particular situation. In addition, studies have shown that conclusions about QOL can differ, depending on which components of the Wilson and Cleary model are assessed. A meta-analysis of 12 studies in chronic illness showed that patient ratings of their health and global QOL were determined by different things.30 Perceived health status was primarily determined by physical functioning and to a lesser extent by emotional well-being. Conversely, global QOL was primarily influenced by emotional wellbeing, and secondarily by physical functioning. In a study of 493 older patients, 43% of those with the worst physical functioning considered their global QOL to be good or better.31 In contrast, 15% of those with the best physical functioning thought their QOL to be only fair or poor. More surprisingly, there also was a lack of concordance between psychological symptoms and QOL. Of those with the fewest psychological symptoms, 21% rated their QOL as only fair or poor. Considering the components of the Wilson and Cleary model, it could be asked whether the power to detect change decreases when moving from left to right in the model (away from biological and physiological variables and toward overall QOL). In other words, is overall QOL too far ‘‘downstream’’ to be sensitive? An answer is provided by a phase II study of temozolomide in recurrent anaplastic astrocytoma, which showed that the effect of treatment on global QOL could be as strong as the effect on symptoms. QOL was measured by the EORTC QLQ-C30 and its Brain Cancer Module. Comparisons were made in patients before treatment and after 6 months of temozolomide. The changes in global QOL for the progression-free group were as great or greater than the changes in the symptoms of pain, fatigue,


insomnia, and dyspnea. The changes were even greater in both emotional and social functioning as the changes in symptoms. These changes were both statistically and clinically significant, and resulted in the recommendation for a phase III trial of temozolomide.32

OTHER CONSIDERATIONS FOR SELECTING A QOL MEASURE There are several additional factors to consider when selecting a QOL instrument. The first prerequisite is well-established evidence of reliability and validity across a wide variety of circumstances, as well as the ability to detect change. ‘‘Homemade’’ questionnaires should be avoided because so many QOL instruments are currently available, with excellent track records of successful use. The second is guidance for interpretation of scores, based on data collected from a variety of groups and populations. Guidance also should be provided for clinical significance, which is defined as the magnitude of change in scores large or important enough to affect patient care or treatment. For example, for the EORTC QLQ-C30 a mean change of 5 to 10 points is considered a small clinically significant difference, 10 to 20 points a moderate one, and more than 20 points a large difference.33,34 Ease of scoring is another consideration, which may be particularly salient in a clinical setting if scoring is cumbersome and requires a computer. QOL instruments typically are copyrighted, and cost for permission for use is another consideration. Many instruments are provided free of charge for non-profit use, but others require fees ranging from a flat one-time usage fee to a charge for each person who completes the questionnaire. For example, the Medical Outcomes Study (MOS) version of the SF-36 is provided free of charge on the MOS website, but Quality Metric requires a signed license agreement for all uses of the SF36 family of instruments. The final consideration focuses on the evidence of cultural appropriateness for the target group. Availability of translations into appropriate languages and/or literacy levels is a necessary, but not sufficient requirement. Supporting evidence also is required to show that the instrument is understood and interpreted as intended by the target population. Both careful development of items plus testing with



cognitive interviewing have been used to establish a culturally appropriate version of an instrument.

FINDING QOL INSTRUMENTS Many instruments now have their own websites (Table 1), providing information on the instruments’ performance and appropriate use, including reliability and validity, ability to detect change in QOL, scoring, and guidance for interpretation of scores. In addition, copies of the instrument or family of instruments often can be obtained directly from the website, making it possible to easily examine the items. These instrument websites typically are developed and maintained by the instruments’ authors, and so are the definitive sources of information about the instruments. Websites also have been developed to present information about a large number of QOL instruments. These organize instruments into categories, which can be helpful for browsing when searching for the best instrument for a particular use. The two largest websites specifically developed for QOL instruments are the PROQOLID and the QLMED. The PROQOLID is the Patient Reported Outcome and Quality of Life Instruments Database (http:, which is maintained by the Mapi Research Institute in Lyon, France.35 The PROQOLID currently contains 660 instruments and is well-organized with easy to use search features. However, there are two levels of information access: a free level and a fee level. Only very rudimentary descriptions are provided without charge, and a fee is required to access more detailed information, including the instrument items. The QLMED is the Clinician’s Guide to the Choice of Instruments for Quality of Life Assessment in Medicine (, compiled by Marcello Tamburini of the National Cancer Institute in Milan, Italy.36 Unlike the PROQOLID, access to all information provided in this website is completely free of charge. Information is presented for more than 800 instruments, including summaries and links to other websites and articles. This website has been critiqued for being complex to use, but is unique in providing open access to such a rich database.36 Books and journal articles also provide excellent reviews of instruments, particularly on specific topics, which can be particularly helpful for targeting appropriate measures. Examples are found in this issue of Seminars in Oncology Nursing focusing on QOL in children and adolescent with

cancer, cancer survivors, end of life, cultural groups, and clinical trials. Classic texts providing reviews of instruments (including copies of the instruments themselves) are ‘‘Quality of Life from Nursing and Patient Perspectives’’37 and others.38,39

USE IN CLINICAL PRACTICE Another frontier for progress is the use of QOL instruments in clinical practice to facilitate individualized patient care.40 Traditionally, QOL information has contributed to clinical practice in oncology through research, and large clinical trials in particular (Table 2). But the use of QOL instruments to guide clinical decision making for individual patients is relatively new. One of the best studies showing the usefulness of QOL instrument for individual patient care was performed using the EORTC QLQ-C30 in the practices of 28 oncologists.41 Use of the instrument resulted in an improvement in patients’ QOL, which was associated with the explicit use of the QOL data, including increased discussion of chronic symptoms, pain, and role function. This was all accomplished without prolonging the clinical encounter. Key elements for success in this application were: (1) the patients filled out the instrument in the office just before the clinical encounter; (2) the instrument was scored immediately by computer, so that the results were in the clinician (physicians) hands at the time of the clinical encounter, ready for discussion; (3) the results were provided graphically for the clinician for ease of interpretation; and (4) the clinician was trained in interpretation of the QOL scores in advance. This study used touch-screen computers to administer the QOL instrument, so significant resources are required to replicate this application. Nevertheless, single-item measures for overall QOL and symptoms can be used in clinical practice without need for additional resources.

MODE OF ADMINISTRATION QOL instruments originally were all on paper, developed for use by self-administration or interviewer administration. Advances in the field have kept pace with technological changes, so that QOL instruments now can be administered in a variety of ways. Patients can provide their responses using computers (with the instrument housed on a computer or by accessing the



TABLE 2. Contributions of Quality of Life Research in Cancer Clinical Practice Determine whether a new therapy is preferable to standard therapy Compare two standard therapies having similar survival outcomes Identify the long-term negative effects of therapy, when survival time is long Discover whether a therapeutic regimen is better than supportive care only, when survival time is short Determine the negative effects of adjuvant therapy Identify the need for supportive care Target problems and facilitate communication in clinical practice Reprinted with permission from: Ferrans CE. Quality of life as an outcome in cancer care. In: Yarbro CH, Wujcik D, Gobel B, editors. Cancer Nursing Principles and Practice. 7th ed. Sudbury, MA: Jones and Bartlett, 2010.

internet), handheld personal digital assistants (PDAs), or telephones with interactive voice dialogues between a human and a computer. These can require significant expense to implement, even when the software already has been developed and is made available for use. However, the use of electronic devices for collecting QOL data makes it possible to (1) obtain data in real time and (2) enter the data automatically into an existing database for scoring. They also may help to obtain more complete data and avoid missing data. For example, Hacker and Ferrans42 showed that immediately following stem cell transplantation, hospitalized patients were willing and able to provide fatigue ratings three times per day for 3 days, even though they were experiencing substantial fatigue (86% completion rate). The patients were prompted to enter their ratings by a sound signal produced by the actiwatch they wore (similar to wearing a wristwatch), and entered the rating on the device. (See Hacker, elsewhere in this issue, for more complete discussion of the use of electronic devices in QOL measurement.) For the most part, these advances have been applications of existing QOL instruments, using the same items and response choices as the paper versions. However, there is a new approach to QOL and PRO measurement, which uses itemresponse theory to create a tailored set of items for each person. This means that the answers provided to earlier questions in the session determine which questions are asked later in that same session. Thus, everyone is not presented with exactly the same set of questions to answer. For example, someone who indicated they were depressed would then trigger a more extensive set of depression items, which would not be presented to someone who was not depressed. A large effort to

develop instrument banks for administration based on item-response theory, funded by the National Institutes of Health, is currently underway and is entitled the Patient Reported Outcomes Measurement Information System (PROMIS). The PROMIS website ( provides information about the progress of the effort and the items selected to date for various concepts.43 The ultimate goal is to improve precision and enable assessment at the individual patient level,44 but the practical issues involved in transitioning to widespread use in research and clinical practice have yet to be addressed.

SELF-REPORT AND SELF-EVALUATION Regardless of the mode of administration, it is generally agreed that QOL instruments require patient self-report. One reason for this is to insure accuracy of the data reported. Ratings assigned by proxies (someone other than the patient) can differ considerably from the ratings patients provide, regardless of whether the proxies are health professionals or family members. For instance, in a study of patients with advanced cancer, physician ratings of drowsiness, shortness of breath, and pain were significantly lower than the patients’. The nurses’ ratings were closer to the patients’, but still significantly different, and the concordance did not improve over time.45 Another study compared ratings of overall QOL with patient reports.46 The correlations ranged from 0.26 to 0.45 for the physicians and from 0.19 to 0.47 for nurses, showing only weak to moderate relationships. Because of this, every effort needs to be made to obtain QOL information from the patients themselves, even from very



young children. Fortunately, there now is a variety of well-established instruments available for children. (See Hinds, elsewhere in this issue.) Another reason for requiring patient self-report is the recognition that patients themselves are the best judge of their own QOL. At its core, QOL is intensely personal, requiring a value judgment about a person’s life, whether it is good or bad, a life worth living or not. People use their own personal standards when evaluating QOL, and in the final analysis the person’s own judgment is the only one that is ethically justifiable.27

FUTURE DIRECTIONS FOR QOL ASSESSMENT Over the past 20 to 30 years we have witnessed an exponential growth in the field of QOL. Development has proceeded for the most part in a non-theoretical manner, leading to conceptual confusion. Not all instruments carrying the QOL label are alike, and there are important differences in what they measure. Wilson and Cleary’s model provides a useful framework for beginning the journey toward conceptual clarity, using terms that identify the aspect of QOL that is actually being measured. The characteristics of each instrument make it more or less appropriate for any particular situation, and there is no single instrument that is the gold standard for QOL measurement. Increased understanding is needed regarding what instruments measure and how this affects the outcomes they produce. This has implications for sensitivity to detect change, as well as the interpretability of findings.

Exciting possibilities are opening up for novel ways to collect QOL information, which hold promise for increasing both the accuracy and usefulness of the data. Advances in communication technology have provided new avenues for expanding the reach of QOL assessment. Traditional modes of instrument administration are being revamped with fresh approaches, making it possible to collect serial data in real time. The introduction of item-response theory through the PROMIS initiative has provided a completely new approach to QOL assessment, and proponents expect this effort to bring a revolution in patient-reported outcomes. The possibility of incorporating QOL into standard clinical practice holds great promise for improving communication with health care providers, with a resultant improvement in outcomes. The introduction of guidelines for recognizing clinically significant changes, as well as the development of practical ways to administer and score QOL instruments, opens new opportunities for expanding the usefulness of QOL measurement beyond the world of research and clinical trials and into clinical practice. QOL assessment can provide a better understanding of the impact of cancer and treatment from the patient’s perspective. It provides a unique means for incorporating the patient’s values into the evaluation of treatment outcomes. This is particularly salient for interventions aimed at providing comfort, such as symptom alleviation and care at the end of life. Because the ultimate purpose of cancer care is to maximize QOL, we need to press forward in evaluating the effectiveness of care in terms of that goal.

REFERENCES 1. National Information Center on Health Services Research and Health Care Technology, US National Library of Medicine, National Institutes of Health, Available at: http://www.nlm.nih. gov/nichsr/hta101/ta101014.html. Accessed Aug 29, 2009. 2. Ferrans CE, Zerwic JT, Wilbur JE, et al. Conceptual model of health-related quality of life. J Nurs Scholarship 2005;37: 336-342. 3. Wilson IB, Cleary PD. Linking clinical variables with health-related quality of life: a conceptual model of patient outcomes. JAMA 1995;273:59-65. 4. Cella DF, Bonomi AE, Lloyd SR, et al. Reliability and validity of the Functional Assessment of Cancer Therapy-Lung (FACT-L) quality of life instrument. Lung Cancer 1995;12: 199-220. 5. Aaronson NK, Cull AM, Kaasa S, et al. The European Organization for Research and Treatment of Cancer (EORTC) modular approach for quality of life assessment in oncology: an

update. In: Spilker B, ed. Quality of Life and Pharmacoeconomics in Clinical Trials. 2nd ed. Philadelphia, PA: Lippincott-Raven; 1996: pp. 179-189. 6. Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). Med Care 1992;30:473-483. 7. Ferrans CE. Differences in what quality of life instruments measure. J Natl Cancer Inst Monogr 2007;37:22-26. 8. Quality Metric Incorporated. Available at: http://www. Accessed Sept 2, 2009. 9. Ware JE Jr. Conceptualizing disease impact and treatment outcomes. Cancer 1984;53(suppl):2316-2323. 10. Spitzer WO, Dobson AJ, Hall J, et al. Measuring the quality of life of cancer patients: a concise QL-Index for use by physicians. J Chronic Dis 1981;34:585-597. 11. Ferrans CE, Powers MJ. Psychometric assessment of the Quality of Life Index. Res Nurs Health 1992;15:29-38.


12. Ferrans CE. Development of a quality of life index for patients with cancer. Oncol Nurs Forum 1990;17:15-19. 13. Frisch MB. The Quality of Life Inventory: a cognitivebehavioral tool for complete problem assessment, treatment planning, and outcome evaluation. Behav Ther 1993;16:42-44. 14. Diener ED, Suh EM, Lucas RE, et al. Subjective well-being: three decades of progress. Psychol Bull 1999;125:276-302. 15. Schag CA, Ganz PA, Heinrich RL. Cancer Rehabilitation Evaluation System - Short Form (CARES-SF). Cancer 1991;68:1406-1413. 16. Aaronson NK, Ahmedzai S, Bergman B, et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality of life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 1993;85:365-376. 17. Cella DF, Tulsky DS, Gray G, et al. The Functional Assessment of Cancer Therapy (FACT) Scale: development and validation of the general version. J Clin Oncol 1993;11: 570-579. 18. Clinch JJ. The Functional Living Index-Cancer: ten years later. In: Spilker B, ed. Quality of Life and Pharmacoeconomics in Clinical Trials. 2nd ed. Philadelphia, PA: Lippincott-Raven; 1996: pp. 215-225. 19. Morrow GR, Lindke J, Black P. Measurement of quality of life in patients: psychometric analysis of the Functional Living Index-Cancer (FLIC). Qual Life Res 1992;1:287-296. 20. Cohen SR, Mount BM, Strobel MG, et al. The McGill Quality of Life Questionnaire: a measure of quality of life appropriate for people with advanced disease. Palliat Med 1995;9: 207-219. 21. Ferrans CE, Powers MJ. Quality of Life Index: development and psychometric properties. Adv Nurs Sci 1985;8:15-24. 22. Grant MM, Ferrell BR, Schmidt GM, et al. Measurement of quality of life in bone marrow transplantation survivors. Qual Life Res 1992;1:375-384. 23. Stewart AL, Hays RD, Ware JE. The MOS short-form general health survey. Med Care 1988;26:724-735. 24. Karnofsky DA, Burchenal JH. The clinical evaluation of chemotherapeutic agents in cancer. In: MacLeod CM, ed. Evaluation of Chemotherapeutic Agents. New York: Columbia University Press; 1949. 25. Padilla GV, Ferrell BR, Grant MM, et al. Defining the content domain of quality of life for cancer patients with pain. Cancer Nurs 1990;13:108-115. 26. Ferrans CE. Development of a conceptual model of quality of life. Schol Inquiry Nurs Pract 1996;10:293-304. 27. Ferrans CE. Definitions and conceptual models of quality of life. In: Lipscomb J, Gotay CC, Snyder C, eds. Outcomes Assessment in Cancer. Cambridge: Cambridge University Press; 2005: pp. 14-30. 28. Spilker B, Revicki DA. Taxonomy of quality of life. In: Spilker B, ed. Quality of Life and Pharmaeconomics in Clinical Trials. 2nd ed. Philadelphia, PA: Lippincott-Raven Publishers; 1996: pp. 25-31. 29. Ganz PA, Goodwin PJ. Quality of life in breast cancer: what have we learned and where do we go from here?. In: Lipscomb J, Gotay CC, Snyder C, eds. Outcomes Assessment


in Cancer. Cambridge: Cambridge University Press; 2005: pp. 93-125. 30. Smith KW, Avid NE, Assmann SF. Distinguishing between quality of life and health status in quality of life research: a meta-analysis. Qual Life Res 1999;8:447-459. 31. Covinsky KE, Wu AW, Landefeld CS, et al. Health status versus quality of life in older patients: does the distinction matter? Am J Med 1999;106:435-440. 32. Osoba D, Brada M, Yung WKA, et al. Health-related quality of life in patients with anaplastic astrocytoma during treatment with temozolomide. Eur J Cancer 2000;36: 1788-1795. 33. King MT. The interpretation of scores from the EORTC Quality-of-Life Questionnaire QLQ-C30. Qual Life Res 1996;5:555-567. 34. Osoba D, Rodrigues G, Myles J, et al. Interpreting the significance of changes in health-related quality of life scores. J Clin Oncol 1998;16:139-144. 35. Patient Reported Outcome and Quality of Life Instruments Database, Available at: Accessed Aug 2, 2009. 36. Cella DF. QOL Instruments on the Internet: J Pain Symptom Manage 2001;21:84-85. 37. King CR, Hinds PS, eds. Quality of Life from Nursing and Patient Perspectives. 2nd ed. Boston, MA: Jones and Bartlett; 2003. 38. Fayers PM, Machin D. Quality of Life: The Assessment, Analysis and Interpretation of Patient-reported Outcomes. West Sussex, UK: John Wiley and Sons; 2007. 39. McDowell I. Measuring Health: A Guide to Rating Scales and Questionnaires. New York: Oxford University Press; 2006. 40. Halyard MY, Ferrans CE. Quality of life assessment for routine clinical practice. J Support Oncol 2008;6:221-229. 233. 41. Velikova G, Booth L, Smith AB, et al. Measuring quality of life in routine oncology practice improves communication and patient well-being: a randomized controlled trial. J Clin Oncol 2004;22:714-724. 42. Hacker ED, Ferrans CE. Ecological momentary assessment of fatigue in patients receiving intensive cancer therapy. J Pain Symptom Manage 2007;33:267-275. 43. Patient Reported Outcomes Measurement Information System (PROMIS), Available at: Accessed Sept 2, 2009. 44. Fries JF, Bruce B, Cella DF. The promise of PROMIS: using item response theory to improve assessment of patientreported outcomes. Clin Experimental Rheumatol 2005;23(supp 5):S53-S57. 45. Nekolaichuk CL, Bruera E, Spachynski K, et al. A comparison of patient and proxy symptom assessments in advanced cancer patients. Palliat Med 1999;13:311-323. 46. Molzahn AE, Northcott HC, Dossetor JB. Quality of life of individuals with end stage renal disease: perceptions of patients, nurses, and physicians. ANNA J 1997;24: 325-333.