Impact of Quality of Life Outcomes on Clinical Practice

November 1, 1995

This paper reviews the current status of translation of quality of life outcomes from research to clinical practice. A major barrier in this process is the lack of mature results from quality of life studies in phase III randomized controlled trials. As more trials are completed, we can expect the diffusion of those results into clinical practice and decision making. Further, as quality of life measurement tools are used more widely and become more user-friendly, we can anticipate their adoption in the routine clinical assessment of patients in the oncologist's practice. [ONCOLOGY 9(Suppl):61-65, 1995]

This paper reviews the current status of translation of quality of life outcomes from research to clinical practice. A major barrier in this process is the lack of mature results from quality of life studies in phase III randomized controlled trials. As more trials are completed, we can expect the diffusion of those results into clinical practice and decision making. Further, as quality of life measurement tools are used more widely and become more user-friendly, we can anticipate their adoption in the routine clinical assessment of patients in the oncologist's practice.

Introduction

During the past 10 to 15 years, we have experienced the phenomenal development of a new scientific technology that allows for the reliable and valid assessment of patient outcomes in research and clinical practice [1-3]. The technology of patient outcomes relies heavily on patient self-report of various aspects of health and well-being, as well as symptoms associated with disease. The tools for measuring these outcomes are derived from social science research and the field of psychometrics. The science of measuring quality of life and the criteria for evaluation of candidate tools have been described extensively by others [4-6].

In this paper, we assume that oncologists will soon have a choice of several validated general cancer and site-specific quality of life (QOL) instruments for use in their practices. This may allow future clinicians to order and utilize "quality of life tests" much as they would order a serum glucose test or an electrocardiogram. When this is the case, what will be the impact of quality of life outcomes on clinical practice?

Should We Expect QOL Outcomes to Affect Clinical Practice?

Clinical practice and treatment decisions are influenced by a variety of factors based on the physician's training and clinical experience, synthesis of the relevant literature, and familiarity with consensus opinions developed by scientific bodies, treatment guidelines, and the results of randomized clinical trials. While clinical trials are considered the "gold standard" for the scientific evaluation of new treatments, relatively few therapies have been subjected to such rigorous evaluation. More important, even when a new therapy has been demonstrated to be efficacious, there may be very slow diffusion of the findings and limited adoption of the effective therapy. For example, two randomized trials comparing breast conservation therapy with mastectomy were published in a prestigious journal during the early 1980s [7,8]; however, several years after those results, there was only limited adoption of breast conservation, and extraordinary geographic variation in the use of this approach to the management of primary breast cancer [9,10].

If clinicians have so much difficulty changing their clinical practice in the face of data from well-controlled scientific studies that use familiar biomedical outcomes (eg, survival and recurrence), how can we expect them to accept without question the findings from quality of life studies, whose measures may be unfamiliar and whose outcomes are at times contrary to clinical opinion?

Sources of QOL Outcome Data in Oncology

We have only recently begun to see the systematic incorporation of QOL outcomes in randomized clinical trials [11,12]. This process began over a decade ago in European and Canadian trials, and has been gradually introduced into US treatment trials during the past 5 years. Some pharmaceutical companies began to incorporate QOL measures into their studies because of their potential importance in the drug approval process [13]. Many current phase III trials within the US cooperative groups include QOL assessment; however, it will be many years before these studies mature and the QOL data are examined. Therefore, at present, only a limited amount of QOL outcome information from randomized clinical trials is available for clinicians. Quality of life data from some phase III trials may be useful to clinicians in their practice, eg, the observation that patients being treated with chemotherapy for metastatic breast cancer had a better quality of life if treated on a continuous rather than intermittent schedule [14] (discussed below). As current phase III trials mature, this important source of QOL data will expand rapidly.

Much of the information that we have about QOL in cancer patients comes from well-designed research studies. Although not phase III randomized clinical trials, these studies have the advantage of being comprehensive and often use multiple tools for QOL assessment-something that is not feasible within the clinical trial setting. The major advantage of a research study is the adequacy of support staff for collection of QOL data, which usually results in less missing data. Limitations of research studies include the lack of treatment randomization and use of volunteer samples. Nevertheless, the high quality and comprehensiveness of data from research studies make it possible to draw important conclusions about the quality of life impact of some therapies.

For example, in a descriptive study of a community-based sample of women treated for early-stage breast cancer, Ganz et al [15] found no significant differences in the major dimensions of health-related quality of life between women choosing mastectomy and those choosing breast conservation (discussed below). The clinical implications of these findings are that we can describe these two surgical treatments for breast cancer in terms of their impact on survival and quality of life, and use this information to help patients make treatment decisions.

In situations in which there are no data from clinical trials or the research literature, clinicians must rely on the clinical interview. Unfortunately, few clinicians have been trained to incorporate questions about health-related quality of life into their usual patient interviews. Instead, physicians usually focus on physical symptoms and findings. Even under these circumstances, more subjective symptoms such as pain are often ignored. Clinical interviews are seldom multidimensional (unlike a QOL instrument) and are usually unsystematic with regard to psychosocial concerns [16,17]. The incorporation of several open-ended questions that address physical, emotional, and social functioning could enhance the standard clinical interview. Other tools, such as short screening instruments (eg, the Duke Health Profile [18] or the Dartmouth COOP charts [19]), could facilitate the clinical identification of QOL concerns of patients in the clinical setting. Unfortunately, most of these tools have been evaluated only in general medical settings and have not been tested with oncology patients.

Limitations of Existing Data Sources

Despite the expanding interest in measurement of QOL outcomes in cancer clinical trials, there are few data available to guide the clinician. Although many trials with QOL endpoints are in progress, these are fewer than might be hoped, due to the complexity of appending these studies to clinical trials and the limitation of resources available to conduct these additional studies [20]. The National Cancer Institute of Canada has been an exception in requiring the use of QOL endpoints in all of its phase III clinical trials [21]. Thus far, this policy has been implemented successfully and with high rates of compliance to data collection. As these trials mature, we can expect valuable information to emerge that will likely have an impact on clinical care.

As with treatment trials, QOL outcomes data may sometimes be counterintuitive (eg, lack of significant differences between mastectomy and breast conservation therapy), and thus, as with treatment trials, it is important to confirm QOL study results. Only the regular and systematic measurement of QOL in all phase III treatment trials will permit clinicians to determine which therapies have the best survival, response, and QOL outcomes.

Quality of life endpoints are particularly critical for the evaluation of therapies in advanced metastatic disease (eg, non-small-cell lung cancer), where survival gains of treatment are modest and treatment toxicity is considerable. However, a major limitation of QOL evaluation in lung cancer trials has been the high rate of missing QOL data due to death and deterioration [22,23]. There is keen interest in developing statistical methods for dealing with missing QOL data, typically from the sickest patients, in longitudinal studies [23].

Other Methodological Problems

There are other methodological problems that need to be addressed prior to the clinical application of QOL outcomes study results. Several popular generic and cancer-specific tools are now being widely used in clinical and research studies [24]. Although statistical comparison tests can have adequate power to detect changes between groups of patients, the clinical meaning of individual changes in scores in the clinical setting is uncertain. For example, what does a 2-point change in physical functioning on a particular QOL instrument mean in an individual patient when assessed at two different points in time? That is to say, what is the clinical significance for the individual patient, and could this merely represent an error in measurement? Furthermore, will two different instruments that measure physical functioning show the same direction of change? These questions are not currently answerable for most of the commonly used QOL instruments. As noted by Guyatt et al, instruments that are reliable and valid in the cross-sectional evaluation of a sample may not be responsive to change over time [25].

Another parallel problem is the lack of head-to-head comparisons of different instruments simultaneously in the same patient population. This type of information would be useful to examine the relative strengths and limitations of some of the leading QOL tools, as well as to develop some form of common scoring system across several measures. This last question is being addressed by Cella in an ongoing research program (personal communication).

An example of the value of such comparisons comes from a recent study that evaluated long-term survivors of early-stage prostate cancer. Litwin et al [26] found that a generic health-related QOL tool did not discriminate between healthy controls and patients who received either surgery or radiation therapy. Two cancer-specific measures did a bit better, but it was only a very specific symptom measure that distinguished between the patients and normal healthy men [26]. Thus, the sensitivity and specificity of psychometrically validated QOL tools may not be robust enough to detect subtle differences in functioning among patient groups. Furthermore, these tools have not been tested for monitoring the QOL of individual cancer patients in the clinical setting.

Clinical QOL Data in Oncology Patients

Intermittent vs Continuous Chemotherapy in Women With Advanced Metastatic Breast Cancer-Coates and colleagues [14] reported their results from an evaluation of intermittent vs continuous treatment strategies in women with advanced metastatic breast cancer. This study examined QOL within a multicenter clinical trial whose primary purpose was to assess medical endpoints (response rate and survival), with QOL as a secondary endpoint. The patients were relatively impaired (40% with ECOG performance status 2 or less), and several of the clinical centers did not participate in the QOL study or demonstrated poor compliance to data collection. Because of the physical status of the patients and the limited resources for collection of QOL data, briefer instruments were selected for this study. The measures included five linear analog self-assessment (LASA) scales measuring physical well-being, mood, pain, nausea and vomiting, and appetite, and a single global rating of overall QOL [14,27].

The main findings of the study were that subjects receiving intermittent therapy had a significantly worse response rate, a significantly shorter time to disease progression, and a trend toward shorter survival. The QOL assessment demonstrated that subjects in the doxorubicin-containing treatment arm experienced more nausea and vomiting (a validity check for the QOL measure!) and that QOL improved significantly (all measures except nausea and vomiting) during the first 3 months of treatment when all subjects received therapy [14].

Subsequently, subjects assigned to intermittent therapy reported deterioration in physical well-being, mood, and appetite, as well as overall QOL. Interestingly, changes in QOL were independent prognostic factors in the proportional-hazards models of subsequent survival [14], again suggesting the validity of these measures.

Although this study is somewhat limited because of substantial patient attrition, use of single-item scales, and noncompliance from several clinical centers, it was one of the first clinical trials of cancer therapy to incorporate QOL assessment as an endpoint in addition to the traditional clinical outcome measures [28]. The QOL data analysis from this study was confounded by attrition due to death or declining performance status and by missing data due to investigator noncompliance and inadequate resources to collect data. These problems are common in clinical trials, as discussed earlier. Despite these limitations, the QOL findings are useful in clinically counseling patients about the desirability of continuous vs intermittent therapy.

This study [14] also exemplifies a critical difference between clinical assessments and patient-evaluated assessments of QOL. The clinicians had hypothesized that patients receiving intermittent therapy would have a more favorable QOL rating. Paradoxically, the patient QOL assessment revealed that continuous chemotherapy had fewer negative consequences for QOL (except for nausea and vomiting). The higher objective response rate in the patients receiving continuous therapy was associated with sustained improvements in QOL rather than increased toxicity. The QOL assessment results compare well with the positive clinical findings of the study (improved response rate, disease-free interval, and survival trend) for the continuous therapy group. This study provides an important example of the value of including QOL assessment in the evaluation of treatments for cancer.

Breast Conservation Therapy vs Mastectomy in Early-Stage Breast Cancer-A second example comes from the research literature rather than a clinical trial setting. Ganz and colleagues, in a series of papers, examined the relationship between QOL and a variety of medical and demographic factors in a community-based sample of newly diagnosed beast cancer patients [15,29-32]. Women with a breast cancer diagnosis are often given a choice between breast conservation or mastectomy as primary treatment. Despite the high frequency of this cancer, there is very little systematic information about the impact of either surgical treatment on the patient's quality of life or psychological adjustment.

In a descriptive prospective longitudinal study, these authors evaluated QOL, performance status, and psychological adjustment in 109 women who underwent primary breast cancer treatment [15]. Several different cancer-specific and generic instruments were used to evaluate the study sample. During the year of follow-up, no statistically significant differences in QOL, mood disturbance, performance status, or global adjustment were found between the two surgical groups, and both groups of patients improved significantly (demonstrated recovery of functioning and QOL) during the year of observation (P = .0001). As was predicted, patients receiving mastectomy reported more difficulties with clothing and body image; however, these results apparently did not affect the assessment of mood or QOL.

The authors concluded that patients receiving breast conservation therapy do not experience significantly better QOL or mood than patients undergoing mastectomy. Breast conservation patients have fewer problems with clothing and body image but may, in fact, require more intensive psychosocial intervention in the postoperative period because of the added burden of primary radiation therapy. These results have now been confirmed in several other research and clinical trial studies [33-35].

Although these results may seem counter to clinical judgment and expectation, some women may prefer mastectomy to breast conservation therapy, for both medical and psychological reasons. The critical clinical issue is to consult with the woman and assess her preference. Although there may be more difficulties with body image and clothing after mastectomy, this can be overcome with the use of immediate reconstruction, which is now more commonly employed. One cannot assume that conservation therapy will be better for all women, and, in fact, the main QOL impact on a woman with breast cancer is the threat to her survival that cancer poses and the disruption that is created by the prolonged period of postoperative therapy that is now so common [36]. These are difficulties for all women, independent of the type of surgical treatment.

The Future: Direct Assessment of QOL in the Clinical Setting

We are on the verge of seeing the implementation of routine QOL assessment in the clinical setting. A number of existing QOL tools are available and may be considered for testing in the office setting (see Table). Prior to selecting a QOL tool for clinical use, it is important to evaluate how complicated it is to use and how it is scored. Single-item scales require limited training for scoring, but are not as robust as multi-item scales. Computerized scoring methods are already available for some instruments [37] and are in development for others. If a tool is not user-friendly for patients and staff, it will not be valuable in the clinical setting.

The next critical issue to consider is the content and wording of the instrument's questions. Even though a QOL questionnaire has been extensively tested in research settings, and its psychometric properties examined in detail, the items may not be appropriate for a particular clinical setting. The physician should obtain a copy of the QOL questionnaire and examine the questions to see if they are appropriate for the clinical environment in which he or she is working:

Is the reading level appropriate?

Are important aspects of QOL included?

Is the instrument the right length?

Will your patients find the questions relevant to their situation?

If all of these criteria are met, and there may be several candidate instruments that are appropriate, then there are some additional considerations before making a final selection:

Is the instrument suitable for repeated use, and is there a methodology for tracking scores over time?

Has research shown that the instrument is responsive to clinically meaningful changes in patients with cancer?

And finally, although a tool may have established reliability in the research setting, sufficient for use in looking at group data, is the reliability sufficiently high (eg, Cronbach's alpha score greater than 0.9) to be confident about its use in individual patients?

After one has identified several suitable QOL tools for a particular clinical setting, the next priorities relate to the establishment of goals for their use. Although it is most straightforward to pick a single QOL tool and adopt it for generalized use in the clinical setting, some tools will be better for some purposes than others. In the clinical environment, there are several possible reasons for incorporating QOL assessment, including screening and identifying patient concerns with plans for clinical intervention, measuring outcomes of care, and monitoring quality assurance.

While it is conceivable that a single cancer-specific QOL tool might fulfill all of these goals, there may be some drawbacks to limiting use to one tool. For example, if a goal of the assessment is to ensure that pain is well controlled in all patients receiving care in an oncology setting, then one may wish to use a cancer pain-specific instrument in addition to the more general QOL tool. Similarly, some QOL tools are very general in terms of assessing physical or psychological functioning, and may not provide adequate descriptive information to design a clinical intervention program for patients. Therefore, a clinical program may wish to adopt at least one common QOL instrument that is used in all cancer patients, with the flexibility of using other appropriate measures when the need arises.

How Soon Is the Future?

With the emergence of the "outcomes movement" as a major aspect of health care delivery and evaluation [1], consumers and providers want to know more about the outcome of cancer care than survival rates alone. The quality of care will be enhanced by collecting information on patient outcomes, and, as a result, consumers will be able to evaluate the health care product they will be purchasing and receiving. As Paul Ellwood noted in his 1988 Shattuck lecture, "the centerpiece and unifying ingredient of outcomes management is the tracking and measurement of function and well being, or quality of life. Although this sounds like a hopelessly optimistic undertaking, I believe that we already have the ability to obtain crucial, reliable data on quality of life at minimal cost and inconvenience. [1]"

This is probably more true in oncology than in other areas of clinical medicine today. However, to obtain QOL data as a routine part of the clinical encounter requires a commitment of resources and the will to implement data collection and tracking systems. Such data tracking is unfamiliar in most clinical settings, and thus there will be a learning curve in terms of implementation and application. Fortunately, there is a growing cadre of oncologists, health services researchers, and others who are poised to assist in this process. It is likely that in the early years of the 21st century, completion of a QOL questionnaire at a patient visit will be as routine as the taking of vital signs.

References:

1. Ellwood PM: Shattuck Lecture: Outcomes management: A technology of patient experience. N Engl J Med 318:1549-1556, 1988.

2. Bergner M: Quality of life, health status, and clinical research. Med Care 27:S148-S156, 1989.

3. Stewart AL, Ware JE Jr (eds): Measuring functioning and well-being, in The Medical Outcomes Study Approach. Durham, NC, Duke University Press, 1992.

4. Aaronson NK: Quality of life: What is it? How should it be measured? Oncology 2:69-74, 1988.

5. Ware JE: Standards for validating health measures: Definition and content. J Chronic Dis 40:473-480, 1987.

6. Cella DF, Tulsky DS: Measuring quality of life today: Methodological aspects. Oncology 4(5)(suppl):29-38, 1990.

7. Veronesi U, Saccozzi R, Del Vecchio M, et al: Comparing radical mastectomy with quadrantectomy, axillary dissection, and radiotherapy in patients with small cancers of the breast. N Engl J Med 305:6-11, 1981.

8. Fisher B, Bauer M, Margolese M, et al: Five years of a randomized clinical trial comparing total mastectomy and segmental mastectomy with or without radiation in the treatment of breast cancer. N Engl J Med 312:665-673, 1985.

9. Farrow DC, Hunt WC, Samet JM: Geographic variation in the treatment of localized breast cancer. N Engl J Med 326:1097-1101, 1992.

10. Nattinger AB, Gottlieb MS, Veum J, et al: Geographic variation in the use of breast-conserving treatment for breast cancer. N Engl J Med 326:1102-1107, 1992.

11. Moinpour CM, Feigl P, Metch B, et al: Quality of life end points in cancer clinical trials: Review and recommendations. J Natl Cancer Inst 81:485-495, 1989.

12. Nayfield SG, Hailey BJ, McCabe M: Quality of Life Assessment in Cancer Clinical Trials. Report of the Workshop on Quality of Life Research in Cancer Clinical Trials, July 16-17, 1990. Bethesda, MD, US Department of Health and Human Services, 1991.

13. Johnson JR, Temple R: Food and drug administration requirements for approval of new anticancer drugs. Cancer Treat Rep 69:1155-1157, 1985.

14. Coates A, Gebski V, Bishop JF, et al: Improving the quality of life during chemotherapy for advanced breast cancer. N Engl J Med 317:1490-1495, 1987.

15. Ganz PA, Schag CAC, Lee JJ, et al: Breast conservation versus mastectomy: Is there a difference in psychological adjustment or quality of life in the year after surgery? Cancer 69:1729-1738, 1992.

16. Badger LW, deGruy FV, Hartman J, et al: Patient presentation, interview content, and the detection of depression by primary care physicians. Psychosom Med 56:128-135, 1994.

17. Bowers J, Jorm AF, Henderson S, et al: General practitioners' detection of depression and dementia in elderly patients. Med J Aust 153:192-196, 1990.

18. Parkerson GR, Gehlbach SH, Wagner EH, et al: The Duke-UNC Health Profile: An adult health status instrument for primary care. Med Care 19:806-828, 1981.

19. Nelson EC, Landgrof JM, Hays RD, et al: The functional status of patients: How can it be measured in physicians' offices? Med Care 28:1111-1127, 1990.

20. Ganz PA, Moinpour CM, Celia DF, et al: Quality-of-life assessment in cancer clinical trials: A status report. J Natl Cancer Inst 84:994-995, 1992.

21. Osoba D: The Quality of Life Committee of the Clinical Trials Group of the National Cancer Institute of Canada: Organization and functions. Qual Life Res 1:211-218, 1992.

22. Ganz PA, Haskell CM, Figlin R, et al: Estimating the quality of life in a clinical trial of metastatic lung cancer using the Karnofsky Performance Status and the Functional Living Index-Cancer (FLIC). Cancer 61:849-856, 1988.

23. Hopwood P, Stephens RJ, Machin D, for the MRC Lung Cancer-Working Party: Approaches to the analysis of quality of life data: Experiences gained from a Medical Research Council Lung Cancer Working Party palliative chemotherapy trial. Qual Life Res 3:339-352, 1994.

24. Ganz PA: Quality of life measures in cancer chemotherapy. Methodology and implications. PharmacoEconomics 5(5):376-388, 1994.

25. Guyatt G, Walter S, Norman G: Measuring change over time: Assessing the usefulness of evaluative instruments. J Chronic Dis 4(2):171-178, 1987.

26. Litwin MS, Hays RD, Fink A, et al: Quality-of-life outcomes in men treated for localized prostate cancer. JAMA 273:129-135, 1995.

27. Coates AS, Fischer Dillenbeck C, McNeil DR, et al: On the receiving end. II: Linear analogue self-assessment (LASA) in evaluation of aspects of the quality of life of cancer patients receiving therapy. Eur J Cancer Clin Oncol 19:1633-1637, 1983.

28. Ganz PA: Do we need new end points in clinical trials today? (letter). J Natl Cancer Inst 81:1105-1106, 1989.

29. Ganz PA, Schag CC, Cheng H: Assessing the quality of life-A study in newly-diagnosed breast cancer patients. J Clin Epidemiol 43:75-86, 1990.

30. Ganz PA, Lee JJ, Sim M-S, et al: Exploring the influence of multiple variables on the relationship of age to quality of life in women with breast cancer. J Clin Epidemiol 45:473-486, 1992.

31. Schag CAC, Ganz PA, Polinsky ML, et al: Characteristics of women at risk for psychosocial distress in the year after breast cancer. J Clin Oncol 11:783-793, 1993.

32. Ganz PA, Hirji K, Sim M-S, et al: Predicting psychosocial risk in patients with breast cancer. Med Care 31:419-431, 1993.

33. Maunsell E, Brisson J, Deschennes L: Psychological distress after initial treatment for breast cancer: A comparison of partial and total mastectomy. J Clin Epidemiol 42:765-771, 1989.

34. Wolberg WH, Romsaas EP, Tanner MA, et al: Psychosexual adaptation to breast cancer surgery. Cancer 63:1645-1655, 1989.

35. Kiebert GM, de Haes JC, van de Velde CJ: The impact of breast-conserving treatment and mastectomy on the quality of life of early-stage breast cancer patients: A review. J Clin Oncol 9:1059-1070, 1991.

36. Ganz PA: Advocating for the woman with breast cancer. CA Cancer J Clin 45:114-126, 1995.

37. Schag CAC, Heinrich RL: Development of a comprehensive quality of life measurement tool: CARES. Oncology 4(5):135-138, 1990.