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Although patients’ function, symptoms, and supportive care needs are obviously related, a better understanding of these relationships could improve patient management.
In this cross-sectional, observational study, 117 cancer patients completed the Supportive Care Needs Survey-34 and EORTC-QLQ-C30. Each symptom and function domain from the EORTC-QLQ-C30 was dichotomized (high vs. low) using a cut-off of reference sample mean scores. Each need domain was dichotomized using a cut-off of an average score representing an unmet need. We explored within-patient patterns of function, symptom, and need domains using latent class analysis. Based on these patterns, patients were categorized as high versus low function; high versus low symptom; and high versus low need. We examined the concordance between categorizations of patients’ function, symptoms, and needs.
The categorizations of function, symptoms, and needs were concordant for 66 patients (56%). Among patients with deficits in at least one area (n = 68), categorizations for 51 patients (75%) were discordant.
About 50% of patients have similar classifications of their level of function, symptoms, and needs, but discordance was common among patients with deficits in at least one area, emphasizing the importance of assessing all of these outcomes as part of patient evaluations.
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McLachlan, S.-A., Allenby, A., Matthews, J., et al. (2001). Randomized trial of coordinated psychosocial interventions based on patient self-assessment versus standard care to improve the psychosocial functioning of patients with cancer. Journal of Clinical Oncology, 19, 4117–4125. PubMed
Aaronson, N. K., Cull, A. M., & Kaasa, S. (1996). The European Organization for Research and Treatment of Cancer (EORTC) modular approach to quality of life assessment in oncology: An update. In B. Spilker (Ed.), Quality of life and pharmacoeconomics in clinical trials (2nd ed., pp. 179–189). Philadelphia: Lippincott-Raven.
Fayers, P. M., Weeden, S., Curran, D., on behalf of the EORTC Quality of Life Study Group. (1998). EORTC QLQ-C30 Reference Values. Brussels: EORTC (ISBN: 2-930064-11-0).
McCutcheon, A. L. (1987). Latent class analysis. Quantitative applications in the social sciences series No. 64. Thousand Oaks, CA: Sage Publications.
Clogg, C. C. (1995). Latent class models. In G. Arminger, C. C. Clogg, & M. E. Sobel (Eds.), Handbook of statistical modeling for the social and behavioral sciences, (Chapter 6 (pp. 311–359). New York: Plenum Press.
- Concordance of cancer patients’ function, symptoms, and supportive care needs
Claire F. Snyder
Amanda L. Blackford
Julie R. Brahmer
Michael A. Carducci
Antonio C. Wolff
Sydney M. Dy
Albert W. Wu
- Springer Netherlands