|
Advertisement |
|
|
||
 |
|
|||||
|
|||||
|
 |
||||||
|
||||||
|
||||||
|
© 1999 American Society for Clinical Oncology
Proposed Agenda for the Measurement of Quality-of-Care Outcomes in Oncology PracticeFrom the Department of Medicine, Institute of Health Care Research and Policy and Lombardi Cancer Center, Georgetown University School of Medicine, Washington, DC; Departments of Medicine and Health Services Research, Jonsson Comprehensive Cancer Center and School of Public Health, and Department of Medicine, Division of General Internal Medicine and Health Services Research, University of California at Los Angeles, Los Angeles; and Health Program, RAND, Los Angeles, CA. Address reprint requests to Jeanne Mandelblatt, MD, MPH, Cancer and Aging and Cancer Outcomes Research, 2233 Wisconsin Ave, Suite 430, Washington, DC 20007; email mandelbj{at}gunet.georgetown.edu
ABSTRACT: Cancer is an important disease, and health care services have the potential to improve the quality and quantity of life for cancer patients. The delivery of these services also has recently been well codified. Given this framework, cancer care presents a unique opportunity for clinicians to develop and test outcome measures across diverse practice settings. Recently, the Institute of Medicine released a report reviewing the quality of cancer care in the United States and called for further development and monitoring of quality indicators. Thus, as we move into the 21st century, professional and regulatory agencies will be seeking to expand process measures and develop and validate outcomes-oriented measures for cancer and other diseases. For such measures to be clinically relevant and feasible, it is key that the oncology community take an active leadership role in this process. To set the stage for such activities, this article first reviews broad methodologic concerns involved in selecting measures of the quality of care, using breast cancer to exemplify key issues. We then use the case of breast cancer to review the different phases of cancer care and provide examples of phase-specific measures that, after careful operationalization, testing, and validation, could be used as the basis of an agenda for measuring the quality of breast cancer care in oncology practice. The diffusion of process and outcome measures into practice; the practicality, reliability, and validity of these measures; and the impact that these indicators have on practice patterns and the health of populations will be key to evaluating the success of such quality-of-care paradigms. Ultimately, improved quality of care should translate into morbidity and mortality reductions.
AFTER LUNG CANCER, breast cancer is the most common cause of cancer deaths in women in the United States.1 The majority of women who are at risk for or who have breast cancer are now receiving their health care from oncologists. The oncology community has recently taken the lead in developing standardized practice guidelines for the delivery of such services to women.2 Given this infrastructure, breast cancer care presents a unique, exemplary condition for clinicians to develop and test measures of the outcomes of care across diverse practice settings. Although interest in measuring quality is not new,3,4 a new era of measuring the quality of health plans began in 1989 with the first Health Plan Employer Data and Information Set (HEDIS), developed by the National Committee on Quality Assurance.5-7 Recently, the Institute of Medicine released a report reviewing the quality of cancer care in the United States and called for further development and monitoring of quality indicators.8 At present, the most commonly used oncology quality indicator is the mammography screening rate. As we move into the 21st century, there is a need for expanded practice-based measures. For such measures to be clinically relevant, feasible, and broadly applicable to a variety of cancers, it is key that the oncology community take an active leadership role in this process. To set the stage for such activities, this article first reviews broad methodologic concerns involved in selecting measures of the quality of care, using breast cancer to exemplify key issues. We then use the case of breast cancer to review the different phases of cancer care—from early detection through posttreatment surveillance—and provide examples of phase-specific measures that, after careful operationalization, testing, and validation, could be used as the basis of an agenda for measuring the quality of breast cancer care in oncology practice. Many of the potential measures discussed are clearly associated with improved outcomes (eg, mammography screening rates); others have face validity, but their ability to affect outcomes has not yet been tested (eg, time from abnormal screening mammogram to diagnosis). Also, although the implementation of some performance measures would be relatively straightforward, operationalizing others may be more challenging. This review is intended to serve as a focal point for discussion and extension of existing efforts to improve the quality of cancer services.
There are many methodologic challenges inherent in developing, selecting, implementing, and evaluating practice-based oncology quality-of-care measures. In this section, after providing some definitions, we use the case of breast cancer to highlight broad methodologic issues, outline some future research needs, and propose an approach to selecting measures.
Definitions Process measures have the advantage of being amenable to tailoring to settings and populations. For instance, one could define rates of use of services, such as mammography, as the rate of use in a specified time period (eg, annually, biannually) among women of a specific age (eg, 50 to 74 years) and condition (eg, life expectancy of > 3 years), based on scientific evidence and expert judgment. The main disadvantage of process measures is the lack of data that serve to link many processes (eg, being offered a choice) to improved outcomes (eg, better quality of life [QOL] or longer life). Outcomes of care are defined as the net effects of the health care process on the health and well-being of individuals and populations.14 As such, outcomes encompass clinical, financial, functional, and psychosocial arenas (usually included under the rubric of QOL).14-16 The most crude clinical measure of health outcome is vital status: alive or dead. For cancer, 5-year survival or the interval of disease-free survival have customarily been used to evaluate the success of treatment. Other clinical events, such as tumor response or stage shifts, can serve as intermediate measures of outcome, principally because they are believed to be associated with differences in survival. Intermediate measures are often useful, because they are more prevalent than final outcome events; the major disadvantage of some intermediate measures is the lack of data that link intermediate events with mortality outcomes. The net effects of health care structure and process on outcomes (and costs) can also be summarized using cost-effectiveness analyses.17
Methodologic Concerns For many measures, rates will be influenced by the selection of women included in the denominator. For instance, for screening rates, inclusion of women who have not been continuously treated for 1 year or more by the same organization or provider may bias rates downward, and inclusion of women with symptoms can spuriously increase the screening rate. Comorbid medical conditions may also affect rates. Several types of outcomes will vary according to other patient or population characteristics, including the length of time that continuous care is received in the measurement setting, age and comorbidity, risks for breast cancer, rates of prevalent disease, and prior access to screening. For instance, stage distribution and survival can be expected to be better among women with regular ongoing lifetime screening compared with women who have poor access to services.19 Comorbidity is also likely to affect screening20,21 and/or treatment choices,22 as well as the patient's tolerance or eligibility for therapy (ie, systemic chemotherapy). In addition, even if treatment is received, a woman with coexistent disease may not live long enough to realize the full benefits of therapy.23 Thus outcome measures may need to be "adjusted" for some of these factors; alternatively, rates could be calculated separately for women newly presenting to a practice from rates for women enrolled for 1 year or more, where the latter is the most relevant measure of practice performance. Despite being the second leading cause of death in the United States population, cancer is still a relatively uncommon condition. Thus in any given practice setting or plan, there may only be a small number of incident breast cancer cases. As such, for many measures, such as cancer stage, few settings will have sufficient numbers of women to produce stable estimates of local disease rates. Numbers will also be far too low for meaningful provider-level evaluation, and meaningful between-plan differences will also be difficult to detect. Potential solutions include measuring cumulative 5-year rates24 or calculating a rate of local disease among all cancers for which proven early-detection methods exist (eg, breast, colorectal, and cervical cancer). Validation of these and other approaches is a key future research need; in fact, the most recent HEDIS indicators include stage as a research "test set" measure.25 Before implementation of practice-based measures, indicators need to be evaluated for reliability and validity in the target settings and populations. Measures, such as those capturing QOL, should have good internal consistency, be sensitive to clinically meaningful changes in condition over time, have face validity for the phase of care, and ideally, have predictive validity. For instance, a measure of functioning of women with advanced metastatic cancer would need to be able to capture small differences in ability to perform low-level activities, given the high level of overall impairment in this group (ie, not be subject to floor effects).26 As another example, use of services, such as systemic chemotherapy, should lead to improved disease-free or overall survival or QOL. At present, much of the available information on reliability and validity of measures is derived from research settings rather than clinical practice. Although some measures of health outcomes and functioning are starting to be used and evaluated in clinical settings,2 the literature on their application is limited.27,28 Response rates can also affect the usefulness of patient-reported measures, such as QOL data.29 For instance, if the healthiest women respond to surveys and the less functional do not, then outcomes will spuriously seem to be better than they actually are. However, making survey response mandatory (versus voluntary) raises ethical and legal concerns.
Selection of Measures
Implementing and Evaluating Measures Evaluation of the reliability and predictive validity of measures will generally employ routine statistical methods. However, skewed distributions of risk adjustors or outcomes in the population and differences in units of measurement and analysis may pose some challenges. In the next sections, we review potential measures for each phase of cancer care against this backdrop of measurement methodology, using the case of breast cancer as an example of a common oncologic condition.
Mammography is presently recommended annually for women who are 50 to 74 years of age,31 and in January 1998, Medicare coverage for this service was extended from biannual to yearly screening, with waiver of Part B deductibles.32 The current HEDIS indicator, based on service use as a proxy for a process measure, is the biannual mammography rate among women 50 years and older.25 Based on current professional recommendations, we recommend that annual screening rates, together with documentation of performance of clinical breast examination, replace the HEDIS measure (Table 2). The denominator for calculating the screening rate could include all women in the age group who receive continuous care for more than 1 year, with no prior diagnosis of breast cancer. As more women have ever been screened, a key process indicator will be the rate of return annual screening. The quality of mammography itself should be ensured by the new United States Food and Drug Administration accreditation requirements for American College of Radiology Accreditation and use of the Breast Imaging Reporting and Data System.33,34
Although the ultimate outcome of a successful breast cancer screening program is a decrease in mortality from breast cancer, a potential intermediate outcome marker is the stage distribution of diagnosed breast cancer cases (Table 3). Definition of a minimum acceptable proportion of cases diagnosed with local-stage cancer could be a rate comparable to United States population averages, as reported to the SEER registries in the same time period. As noted previously, rates could also be "adjusted" to reflect prior screening history, length of time under continuous care, or comorbidity. Time-trend analyses could also be performed to ensure that the plan-level proportion of early-stage cancer increases as screening rates increase. Lack of parallel trends in these two indicators could indicate a potential problem in a quality control, such as a problem in mammography interpretation, temporary influxes of women with high rates of prevalent and/or symptomatic disease, or delays in diagnosis after abnormal screening results (see Diagnosis).
Suboptimal quality control in the diagnostic phase of care, such as poor technical performance or diagnostic delays, particularly if compounded by delays in the receipt of treatment, may result in later stages of disease than would have been seen under ideal circumstances, with possible reduced survival. An example of a process indicator for this domain of care could include a measure of time to diagnostic resolution after an abnormal mammogram or clinical examination, where the start of the measure begins with the date of the initial mammogram, and resolution is defined as the date of the last test that establishes a definitive diagnosis of cancer or a noncancerous condition (Table 2). A clinically exact interval beyond which delay is likely to affect stage, treatment, and survival is not known, although most suggest that follow-up should be completed in a period of 4 months.35 Before implementation, "abnormal" mammograms will need to be defined in a clinically meaningful manner, and any "delay" measure will need to be linked to stage and survival data to evaluate the validity of this concept in the context of other predictors (ie, tumor markers, treatment). In terms of outcome measures (Table 3), one example of the quality (and efficiency) of care for the diagnostic domain could be the rate of true-positive biopsies. Based on current practices and published series of biopsy predictive values, acceptable rates of true-positive biopsies range from 20% to 35%.36 The positive predictive value of a biopsy depends on prevalence of disease in a population; certain patient characteristics (such as age, breast density, and use of hormone replacement therapy) may also bias true-positive rates and/or make cross-population comparisons difficult. Thus it is possible that rates of true-positive biopsies will need to be "adjusted" for such factors or measured as age-specific rates. In addition to establishing a cancer diagnosis, evaluation of biopsy specimens (with the exception of fine-needle aspirates) usually includes an evaluation of selected biomarkers. These markers can be important guides to treatment decisions and prognosis.37 Also, because hormone receptor status may be difficult to ascertain late in the course of illness, knowledge of the initial receptor status can be important in treatment decisions for recurrent or metastatic disease. Determination of hormone receptor status is currently a measure of the Joint Commission on Accreditation of Healthcare Organizations. The American Society of Clinical Oncology also currently recommends that histologic grading be routinely performed.38 Finally, extensive preoperative staging with radiographic and nuclear medicine scans does not seem to be warranted in early-stage breast cancer (stage II or less), as the risk of disseminated disease is very low for small tumors.39,40 Thus potential staging quality indicators could include rates of clinical screening and, if abnormalities are present, documentation of more extensive testing or reasons for nonevaluation (eg, information will not affect treatment choices). In addition, rates of radiologic evaluation of clinical symptoms (eg, bone pain) or physical findings (eg, enlarged liver) could be measured. For patients with more advanced tumors (eg, T3 or larger and/or extensive clinical nodal disease), preoperative staging is appropriate to determine if metastatic disease is present before recommending local breast surgery. The usefulness and appropriateness of these latter potential preoperative staging measures depend on both accurate documentation of patient status (both general health and cancer-related symptoms) and their application in patients for whom such information is likely to affect patient and physician treatment decision making. Operative staging information on the number of lymph nodes involved with metastatic disease (obtained in conjunction with local surgical treatment; see Cancer Treatment) has historically been the standard of care in evaluating the risk for recurrence and the need for adjuvant chemotherapy.41,42 With time, several new lines of evidence have suggested that the use of lymph node dissection should only be considered for certain women, because axillary lymph node dissection (with or without radiation) has been associated with short- and intermediate-term morbidity for women, including lymphedema and other arm morbidities such as pain, paresthesias, weakness, and impaired shoulder function.43,44 Axillary sampling, as an alternative to full dissection, is an area of evolving clinical paradigms. For example, a new procedure, the sentinel node biopsy, has recently been proposed to replace axillary dissection.45,46 As standards for axillary dissection evolve and reach consensus, measures will need to be developed.
Local Treatment Up to 12 years of follow-up of randomized controlled trials with stage I and II breast cancer patients have demonstrated that there is no difference in survival between breast-conserving surgery (BCS) and modified radical mastectomy.47-49 Post-BCS radiation decreases the risk of local recurrence by 30% to 40%48; however, as yet, no survival benefit has been observed for the addition of radiation. Examples of process indicators for the quality of treatment include documentation of offering treatment choices and documentation of patient participation in treatment choice (Table 2), because women who participate in treatment decisions have been noted to have better posttreatment QOL and satisfaction with care.50 Illustrations of outcome indicators for the local treatment phase of care include disease-free and overall survival rates that are calculated separately by treatment and control for age, comorbidity, and other prognostic indicators (ie, hormonal receptors) (Table 3). Patient-assessed QOL and satisfaction are other important local treatment outcome measures.51,52 QOL measures are also potential candidate indicators for other phases of treatment. Good reviews of such tools commonly used with breast cancer patients are summarized elsewhere.53,54 Any practice-based measures will need to be brief and acceptable to patients and physicians. Ideally, baseline precancer QOL would be available to evaluate individual outcomes, although this is not necessary for a "risk-adjusted" group measure. As noted previously, adjustment for competing causes of morbidity and mortality will need to accompany any treatment process and outcome measures that are adapted for general use.55-57 Because patient preferences also have a substantial role in choices and may lead to different patterns and outcomes of care,58 another indicator for this phase of care includes assessment of preferences. Such an indicator will require extensive research on the most reliable, feasible, and valid measurement approach in clinical practice settings.54
Systemic Treatment
Reconstruction and Rehabilitation Two process measures might be considered for measuring the quality of rehabilitative care. First, rates of clinical assessment of the need for psychologic support services (both group and individual) could be documented. Standard tools could be used to screen for psychologic distress or depression to identify women in need of such services.64 Second, because axillary surgery (and radiotherapy) can be associated with clinically meaningful decrements in arm and upper body functioning, arm function should be assessed and documented at a 1-month postoperative visit. Examples of rehabilitative outcome measures include postoperative physical and emotional functioning (Table 3).
Surveillance
Recurrence, Palliative Care, and Terminal Care In conclusion, cancer is an important disease, and health care services have the potential to improve the quality and quantity of life for cancer patients. Oncologists are optimally placed to take an active leadership role in defining the agenda for discussions of the quality of cancer care. As a focal point for such activities, we have suggested potential measures of the outcomes of care, using breast cancer as a case study. In the next phase of development, assessment of the clinical relevance, reliability, feasibility, and validity of such measures will be paramount; any proposed performance measures should also adhere to a set of methodologic standards and undergo peer review. Once developed and validated, the diffusion of these types of process and outcome measures into practice and the impact that such indicators have on practice patterns27 and the health of populations will be key to evaluating the success of this quality-of-care paradigm. For instance, will the selection of measures affect the time spent focusing on those targeted areas? Ultimately, improved quality of care should translate into important mortality reductions.
Supported in part by Agency for Health Care Research and Policy grant no. RO1 HS08395, "Care, Costs, and Outcomes of Local Breast Cancer" (J.S.M.), Avon Breast Cancer Leadership Award (P.A.G.), and Health Care Financing Administration contract no. 500-95-0056, "Research and Demonstration Task Order" (K.L.K.) We thank Kathy Summers for manuscript preparation.
Earlier versions of this work were prepared for Foundation for Accountability and the Agency for Health Care Policy and Research (P.A.G.). This work reflects the viewpoint of the authors.
1. Ries LA, Kosary CL, Hankey BG, et al: SEER Cancer Statistics Review: 1973-1994. Bethesda, MD, National Cancer Institute, NIH publication 97-2789, 1997 2. Carlson R, Edge S, Farrar WB, et al: The panel on National Comprehensive Cancer Network Breast Cancer Practice Guidelines: Practice guidelines and outcomes data in oncology. The University of Texas, M.D. Anderson Cancer Center, Third Annual Conference, Fort Lauderdale, F March 1-4, 1998
3.
Lohr KN, Brook RH: Quality assurance in medicine. Am Behav Sci27:583-607, 1984 4. Donabedian A: The Definition of Quality and Approaches to Its Assessment. Ann Arbor, MI, Health Administration Press, 1980, Explorations in Quality Assessment and Monitoring (vol 1)
5.
Iglehart JK: Health policy report: The national committee for quality assurance. N Engl J Med335:995-999, 1996 6. Blumenthal D: Quality of health care: Part 1. Quality of care—What is it? N Engl J Med335:891-893, 1996
7.
Brook RH, Cleary PD: Quality of health care: Part 2. Measuring quality of care. N Engl J Med335:966-970, 1996 8. National Cancer Policy Board, Institute of Medicine: Ensuring quality cancer care. Washington, DC, National Cancer Policy Board, 1999 9. Lohr KN (ed): Medicare: A Strategy for Quality Assurance. Washington, DC, National Academy Press, 1990 10. Lohr KN, Donaldson MS, Harris-Wehling J: Medicare: A strategy for quality assurance—V. Quality of care in a changing health care environment. Qual Rev Bull18:120-126, 1992 11. Brook RH, Cleary PD: Quality of health care: Part 2. Measuring quality of care. N Engl J Med335:966-970, 1996 12. Starfield B: Primary Care: Concept, Evaluation, and Policy. New York, NY, Oxford University Press, 1992 13. Kahn KL, Rogers WH, Rubenstein LV, et al: Measuring quality of care with explicit process criteria before and after implementation of the DRG-based prospective payment system. JAMA264:1969-1973, 1990[Abstract] 14. Patrick DL, Erickson P: Health Status and Health Policy: Quality of Life in Health Care Evaluation and Resource Allocation. New York, NY, Oxford University Press, 1993 15. Drummond MF, Stoddard GL, Torrance GW: Methods for the Economic Evaluation of Health Care Programmes. New York, NY, Oxford University Press, 1987
16.
American Society of Clinical Oncology: Outcomes of cancer treatment for technology assessment and cancer treatment guidelines. J Clin Oncol14:671-679, 1996 17. Mandelblatt JS, Fryback DG, Weinstein MC, et al: Assessing the effectiveness of health interventions for cost-effectiveness analysis. J Gen Intern Med12:551-558, 1997[Medline] 18. McGlynn EA, Asch SM: Developing a clinical performance measure. Am J Prev Med14:14-21, 1998[Medline] 19. Mandelblatt J, Andrews H, Kao R, et al: Impact of access and social context on breast cancer stage at diagnosis. J Health Care Poor Underserved6:342-51, 1995[Medline] 20. Mandelblatt J, Traxler M, Lakin P, et al: Mammography and papanicolaou smear use by elderly poor black women. J Am Geriatr Soc40:1001-1007, 1992[Medline] 21. Satariano WA: Comorbidity and functional status in older women with breast cancer: Implications for screening, treatment, and prognosis. J Gerontol47:24-31, 1992 22. Greenfield S, Blanco DM, Elashoff RM, et al: Patterns of care related to age of breast patients. JAMA257:2766-2770, 1987[Abstract]
23.
Satariano WA, Ragland DR: The effect of comorbidity on 3-year survival of women with primary breast cancer. Ann Intern Med120:104-110, 1994 24. Kerner JF, Andrews H, Zauber A, et al: Geographically-based cancer control: Methods for targeting and evaluating the impact of screening interventions on defined populations. J Clin Epidemiol41:543-553, 1988[Medline] 25. National Committee for Quality Assurance: HEDIS 3.0 reporting and testing set measures, 1998. Http://www.ncqa.org/pages/policy/hedis/hedis.htm 26. Bindman AB, Keane D, Lurie N: A public hospital closes: Impact on patients' access to care and health status. JAMA264:2899-2904, 1990[Abstract] 27. Ray-Coquard I, Philip T, Lehmann M, et al: Impact of a clinical guidelines program for breast and colon cancer in a french cancer center. JAMA278:1591-1595, 1997[Abstract] 28. McHorney CA, Tarlov AR: Individual-patient monitoring in clinical practice: are available health status surveys adequate? Qual Life Res4:293-307, 1995[Medline] 29. 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, U.S. Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 1991 30. National Committee for Quality Assurance: Desirable attributes of HEDIS measures, 1998. Http://www.ncqa.org/pages/policy/hedis/hedis.htm 31. U.S. Preventive Services Task Force (USPSTF): Guide to Clinical Preventive Services (ed 2). Baltimore, MD, Williams and Wilkins, 1995 32. Health Care Financing Administration: HCFA press releases web site, October 22, 1997. Http://www.hcfa.gov/ 33. Bassett LW: The regulation of mammography. Semin Ultrasound CT MR17:415-423, 1996[Medline] 34. Mammography Quality Standards Act Regulations. Washington, DC, U.S. Food and Drug Administration, December 12, 1994 35. Kerlikowske K: Timeliness of follow-up after abnormal screening mammography. Breast Cancer Res Treat40:53-65, 1996[Medline] 36. Harris JR, Lippman ME, Morrow M, et al (eds): Diseases of the Breast. Philadelphia, Lippincott-Raven Publishers, PA, 1996 37. Early Breast Cancer Trialists' Collaborative Group: Tamoxifen for early breast cancer: An overview of the randomised trials. Lancet351:1451-1467, 1998[Medline] 38. American Society of Clinical Oncology: 1997 update of recommendations for the use of tumor markers in breast and colorectal cancer. J Clin Oncol16:793-795, 1998[Abstract] 39. Brar HS, Sisley JF, Johnson RH Jr: Value of preoperative bone and liver scans and alkaline phosphatase in the evaluation of breast cancer patients. Am J Surg165:221-223, 1993 (discussion 224) [Medline] 40. Cox MR, Gilliland R, Odling-Smee GW, et al: An evaluation of radionuclide bone scanning and liver ultrasonography for staging breast cancer. Aust N Z J Surg62:550-555, 1992[Medline] 41. Moore MP, Kinne DW: Axillary lymphadenectomy: A diagnostic and therapeutic procedure. J Surg Oncol66:2-6, 1997[Medline] 42. Singhal H, O'Malley FP, Tweedie E, et al: Axillary node dissection in patients with breast cancer diagnosed through the Ontario Breast Screening Program: A need for minimally invasive techniques. Can J Surg40:377-382, 1997[Medline] 43. Kissin MW, Della Rovere GQ, Easton D, et al: Risk of lymphoedema following the treatment of breast cancer. Br J Surg73:580-584, 1986[Medline] 44. Maunsell E, Brisson J, Deschenes L: Arm problems and psychological distress after surgery for breast cancer. Can J Surg36:315-320, 1993[Medline] 45. Turner RR, Ollila DW, Krasne DL, et al: Histopathologic validation of the sentinel lymph node hypothesis for breast carcinoma. Ann Surg226:271-276, 1997 (discussion 276-278) [Medline]
46.
Krag D, Weaver D, Ashikaga T, et al: The sentinel node in breast cancer: A multicenter validation study. N Engl J Med339:941-946, 1998
47.
Fisher B, Anderson S, Redmond CK, et al: Reanalysis and results after 12 years of follow-up in a randomized clinical trial comparing total mastectomy with lumpectomy with or without irradiation in the treatment of breast cancer. N Engl J Med333:1456-1461, 1995
48.
Early Breast Cancer Trialists' Collaborative Group: Effects of radiotherapy and surgery in early breast cancer: An overview of the randomized trials. N Engl J Med333:1444-1455, 1995 49. Moore MP, Kinne DW: The surgical management of primary invasive breast cancer. CA Cancer J Clin45:279-288, 1995[Abstract] 50. Morris J, Royle GT: Offering patients a choice of surgery for early breast cancer: A reduction in anxiety and depression in patients and their husbands. Soc Sci Med26:583-585, 1988 51. Ganz PA, Coscarelli A: Quality of life after breast cancer: A decade of research. In Dimsdale J, Baum A (eds): Quality of Life in Behavioral Medicine Research. Newark, New Jersey, Lawrence Erlbaum Associates, 1995, pp 97-113 52. 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, National Cancer Institute, National Institutes of Health, 1991 53. Mandelblatt JS, Eisenberg JM: Historical and methodological perspectives on cancer outcomes research. Oncology 9S:23-32, 1996 54. Cella DF, Bonomi AE: Measuring quality of life: 1995 update. Oncology9:47-60, 1995[Medline] 55. Jencks SF, Daley J, Draper D, et al: Interpreting hospital mortality data: The role of clinical risk adjustment. JAMA260:3611-3616, 1988[Abstract]
56.
Extermann M, Overcash J, Lyman GH, et al: Comorbidity and functional status are independent in older cancer patients. J Clin Oncol16:1582-1587, 1998 57. Newschaffer CJ, Penberthy L, Desch CE, et al: The effect of age and comorbidity in the treatment of elderly women in nonmetastatic breast cancer. Arch Intern Med156:85-90, 1996[Abstract] 58. Palda VA, Llewellyn-Thomas HA, Mackenzie RG, et al: Breast cancer patients' attitudes about rationing postlumpectomy radiation therapy: Applicability of trade-off methods to policy-making. J Clin Oncol15:3192-3200, 1997[Abstract]
59.
Goldhirsh A, Glick JH, Gelber RD, et al: Meeting highlights: International consensus panel on the treatment of primary breast cancer. J Natl Cancer Inst90:1601-1608, 1998 60. The Steering Committee on Clinical Practice Guidelines for the Care and Treatment of Breast Cancer: Adjuvant systemic therapy for women with node-positive breast cancer. Can Med Assoc J 158:S43-51 and S52-64, 1998 61. Early Breast Cancer Trialists' Group: Systematic treatment of early breast cancer by hormonal, cytotoxic, or immune therapy: 133 randomized trials involving 31,000 recurrences and 24,000 deaths among 75,000 women. Lancet339:1-15, 1992[Medline] 62. Rosenqvist S, Sandelin K, Wickman M: Patients' psychological and cosmetic experience after immediate breast reconstruction. Eur J Surg Oncol22:262-266, 1996[Medline] 63. Franchelli S, Leone MS, Berrino P, et al: Psychological evaluation of patients undergoing breast reconstruction using two different methods: Autologous tissues versus prostheses. Plast Reconstr Surg95:1213-1218, 1995[Medline] 64. Burnam MA, Wells KB, Leake B, et al: Development of a brief screening instrument for detecting depressive disorders. Med Care26:775-789, 1988[Medline] 65. The GIVIO Investigators: Impact of follow-up testing on survival and health-related quality of life in breast cancer patients: A multicenter randomized controlled trial. JAMA271:1587-1592, 1994[Abstract] 66. Del Turco MR, Palli D, Cariddi A, et al: Intensive diagnostic follow-up after treatment of primary breast cancer: A randomized trial. JAMA271:1593-1597, 1994[Abstract] 67. Winchester DP, Sener SF, Khanderkar JD, et al: Symptomatology as an indicator of recurrent or metastatic breast cancer. Cancer43:956-960, 1979[Medline] 68. Schapira V, Urban N: A minimalist policy for breast cancer surveillance. JAMA265:380-382, 1991[Medline]
69.
Gotay CC, Muraoka MY: Quality of life in long term survivors of adult-onset cancers. J Natl Cancer Inst90:656-667, 1998 70. McCaffery M, Ferrell BR: How to use the new AHCPR Cancer Pain Guidelines. Am J Nurs94:42-46, 1994 71. Donaldson MS, Fields MJ: Measuring quality of care at the end of life. Arch Int Med158:1221-1228, 1998 Submitted October 13, 1998; accepted April 12, 1999. This article has been cited by other articles:
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|||||||||||
|
|||||||||||
|
|
Copyright © 1999 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
|
TOP
ABSTRACT
INTRODUCTION
