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20 - Promoting symptom research in cooperative groups
- from Section 3 - Clinical Perspectives In Symptom Management and Research
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- By Lynne I. Wagner, Northwestern University Feinberg Medical School, David Cella, Northwestern University Feinberg Medical School
- Edited by Charles S. Cleeland, University of Texas, M. D. Anderson Cancer Center, Michael J. Fisch, University of Texas, M. D. Anderson Cancer Center, Adrian J. Dunn, University of Hawaii, Manoa
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- Book:
- Cancer Symptom Science
- Published online:
- 05 August 2011
- Print publication:
- 18 November 2010, pp 237-246
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Summary
Established in the 1950s, the oncology cooperative group system is a national clinical trials network supported by the National Cancer Institute (NCI) as part of its National Cancer Program. Membership is composed of public and private institutions, and includes researchers, physicians, and health care professionals. This clinical-trials network is responsible for conducting hundreds of clinical trials each year for the treatment and prevention of all types of cancer, and in the area of cancer symptom management. Since its development in 1983, the NCI-funded Community Clinical Oncology Program links community cancer specialists, primary care physicians, and health care providers to oncology cooperative groups and academic cancer centers. The portfolio of research conducted in the Community Clinical Oncology Program has broadened to include symptom management and quality of life research. The relatively new discipline of symptom research is becoming an increasingly important research focus within the cooperative group system.
In this chapter we summarize key accomplishments of the cooperative groups that have cancer-control research-base funding. Factors that have facilitated the successful conduct of symptom research are described, including cooperative group organizational factors, member institution characteristics, and characteristics associated with research protocols.
Overview of the cooperative group system
The NCI-funded groups responsible for developing and implementing cancer prevention and control clinical trials are called Research Bases. The oncology cooperative group system includes eight Research Bases with NCI-funded cancer-control research (Table 20.1). Each of these cooperative groups leads a research program that includes cancer control and prevention research, and cancer symptom management trials.
11 - Evaluating quality of life in cancer survivors
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- By Brad Zebrack, Ph.D., M.S.W., Assistant Professor University of Southern California, Los Angeles, CA, David Cella, Ph.D., Professor of Psychiatry and Behavioral Science Northwestern University, Evanston, IL
- Edited by Joseph Lipscomb, National Cancer Institute, Bethesda, Maryland, Carolyn C. Gotay, Claire Snyder, National Cancer Institute, Bethesda, Maryland
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- Book:
- Outcomes Assessment in Cancer
- Published online:
- 18 December 2009
- Print publication:
- 23 December 2004, pp 241-263
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Summary
Introduction
Currently, about 1.27 million new cancer cases are diagnosed each year, and 60% of all persons diagnosed with cancer are expected to be alive at least five years from the time of their diagnosis. Furthermore, the US death rate for all cancers combined has been declining since 1990, so annual growth in the number of individuals living with or beyond cancer is expected. Today, there are approximately 9 million cancer survivors in the US. Based upon 1996–1997 population estimates from the US Bureau of the Census, this represents approximately 3% of the entire population. Some of these individuals can be considered cured, while others still have evidence of active disease. Of the 9 million individuals living with a cancer history, over 1 million were diagnosed more than 20 years ago.
While these statistics indicate increased length of survival for individuals diagnosed with cancer, they give no indication of the quality of life:
Regardless of the type of cancer or the extent of survival, all persons diagnosed with cancer must manage the enduring and complex ways in which cancer transforms the self and everyday life.
(p. 239)Understanding how individuals who are cancer survivors manage the impact of cancer and experience the transformation of their lives is critical for health care professionals committed to assisting cancer patients and survivors in their recovery, for payers of health care, and for those engaged in policy regarding health insurance, employment, and disability-related rights of these many survivors.
Should symptoms be scaled for intensity, frequency, or both?
- CHIH-HUNG CHANG, DAVID CELLA, SUSAN CLARKE, ALLEN W. HEINEMANN, JAMIE H. VON ROENN, RICHARD HARVEY
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- Journal:
- Palliative & Supportive Care / Volume 1 / Issue 1 / March 2003
- Published online by Cambridge University Press:
- 29 April 2003, pp. 51-60
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Objective: This study evaluated the comparability of two 5-point symptom self-report rating scales: Intensity (from “not at all” to “very much”) and Frequency (from “none of the time” to “all of the time”). Questions from the Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue 13-item scale was examined.
Methods: Data from 161 patients (60 cancer, 51 stroke, 50 HIV) were calibrated separately to fit an item response theory-based rating scale model (RSM). The RSM specifies intersection parameters (step thresholds) between two adjacent response categories and the item location parameter that reflects the probability that a problem will be endorsed. Along with patient fatigue scores (“measures”), the spread of the step thresholds and between-threshold ranges were examined. The item locations were also examined for differential item functioning.
Results: There was no mean raw score difference between intensity and frequency rating scales (37.2 vs. 36.4, p = n.s.). The high correlation (r = .86, p < .001) between the intensity versus frequency scores indicated their essential equivalence. However, frequency step thresholds covered more of the fatigue measurement continuum and were more equidistant, and therefore reduced floor and ceiling effects.
Significance of results: These two scaling methods produce essentially equivalent fatigue estimates; it is difficult to justify assessing both. The frequency response scaling may be preferable in that it provides fuller coverage of the fatigue continuum, including slightly better differentiation of people with relatively little fatigue, and a small group of the most fatigued patients. Intensity response scaling offers slightly more precision among the patients with significant fatigue.
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