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Annual Meeting of the International Society for Quality of Life Research, October 2011 in Denver, Colorado.
Patient-reported outcomes (PROs) have been found to be significant predictors of clinical outcomes such as overall survival (OS), but the effect of demographic and clinical factors on the prognostic ability of PROs is less understood. Several PROs derived from the 12-item Short-Form Health Survey (SF-12) and M. D. Anderson Symptom Inventory (MDASI) were investigated for association with OS, with adjustments for other factors, including performance status.
A retrospective analysis was performed on data from 90 patients with stage IV non-small cell lung cancer. Several baseline PROs were added to a base Cox proportional hazards model to examine the marginal significance and improvement in model fit attributable to the PRO: mean MDASI symptom interference level; mean MDASI symptom severity level for five selected symptoms; SF-12 physical and mental component summaries; and the SF-12 general health item. Bootstrap resampling was used to assess the robustness of the findings.
The MDASI mean interference level had a significant effect on OS (p = 0.007) when the model was not adjusted for interactions with other prognostic factors. Further exploration suggested the significance was due to an interaction with performance status (p = 0.001). The MDASI mean symptom severity level and the SF-12 physical component summary, mental component summary, and general health item did not have a significant effect on OS.
Symptom interference adds prognostic information for OS in advanced lung cancer patients with poor performance status, even when demographic and clinical prognostic factors are accounted for.
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Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., et al. (2010). The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179–1194. PubMedCrossRef
US Food and Drug Administration. (2009). Guidance for industry. Patient- reported outcome measures: Use in medical product development to support labeling claims. U.S. Department of Health and Human Services. http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM071975.pdf. Accessed 31 July 2012.
Basch, E. M., Reeve, B. B., Mitchell, S. A., Clauser, S. B., Minasian, L., Sit, L., et al. (2011). Electronic toxicity monitoring and patient-reported outcomes. Cancer Journal (Sudbury, Mass.), 17(4), 231–234. CrossRef
Cella, D. F., Tulsky, D. S., Gray, G., Sarafian, B., Linn, E., Bonomi, A., et al. (1993). The Functional Assessment of Cancer Therapy scale: Development and validation of the general measure. Journal of Clinical Oncology, 11(3), 570–579. PubMed
Aaronson, N. K., Ahmedzai, S., Bullinger, M., Crabeels, D., Estapè, J., Filiberti, A., et al. (1991). The EORTC core quality of life questionnaire: Interim results of an international field study. In D. Osoba (Ed.), Effect of cancer on quality of life (pp. 185–203). Boca Raton, FL: CRC Press.
Aaronson, N. K., Ahmedzai, S., Bergman, B., Bullinger, M., Cull, A., Duez, N. J., et al. (1993). The European organization for research and treatment of cancer QLQ-C30: A quality-of-life instrument for use in international clinical trials in oncology. Journal of the National Cancer Institute, 85(5), 365–376. PubMedCrossRef
Wang, X. S., Shi, Q., Lu, C., Basch, E. M., Johnson, V. E., Mendoza, T. R., et al. (2010). Prognostic value of symptom burden for overall survival in patients receiving chemotherapy for advanced nonsmall cell lung cancer. Cancer, 116(1), 137–145. PubMed
Mauer, M., Bottomley, A., Coens, C., & Gotay, C. (2008). Prognostic factor analysis of health-related quality of life data in cancer: A statistical methodological evaluation. Expert Review of Pharmacoeconomics & Outcomes Research, 8(2), 179–196. CrossRef
Armstrong, T. S., Vera-Bolanos, E., Gning, I., Acquaye, A., Gilbert, M. R., Cleeland, C., et al. (2011). The impact of symptom interference using the MD Anderson Symptom Inventory-Brain Tumor Module (MDASI-BT) on prediction of recurrence in primary brain tumor patients. Cancer, 117(14), 3222–3228. PubMedCrossRef
Hoang, T., Xu, R., Schiller, J. H., Bonomi, P., & Johnson, D. H. (2005). Clinical model to predict survival in chemonaive patients with advanced non-small-cell lung cancer treated with third-generation chemotherapy regimens based on eastern cooperative oncology group data. Journal of Clinical Oncology, 23(1), 175–183. PubMedCrossRef
Cleeland, C. S., Mendoza, T. R., Wang, X. S., Woodruff, J. F., Palos, G. R., Richman, S. P., et al. (2011). Levels of symptom burden during chemotherapy for advanced lung cancer: Differences between public hospitals and a tertiary cancer center. Journal of Clinical Oncology, 29(21), 2859–2865. PubMedCrossRef
Sloan, J. A., Aaronson, N., Cappelleri, J. C., Fairclough, D. L., & Varricchio, C. (2002). Assessing the clinical significance of single items relative to summated scores. Mayo Clinic Proceedings, 77(5), 479–487. PubMed
R Documentation. (2012). Compute a concordance measure. http://stat.ethz.ch/R-manual/R-patched/library/survival/html/survConcordance.html. Accessed 31 July 2012.
Burr, D. (1994). A comparison of certain bootstrap confidence intervals in the Cox model. Journal of the American Statistical Association, 89(428), 1290–1302. CrossRef
R Core Team. (2012). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org. Accessed 23 Aug 2012.
Therneau, T. (2012). A package for survival analysis in S. R package version 2.36- 14. The R Project for Statistical Computing. http://cran.r-project.org/web/packages/survival//survival.pdf. Accessed 23 Aug 2012.
R Documentation. (2012). Compute a survival curve from a Cox model. http://stat.ethz.ch/R-manual/R-patched/library/survival/html/survfit.coxph.html. Accessed 31 July 2012.
Ohman, E. M., Granger, C. B., Harrington, R. A., & Lee, K. L. (2000). Risk stratification and therapeutic decision making in acute coronary syndromes. The Journal of the American Medical Association, 284(7), 876–878. CrossRef
- Prognostic value of patient-reported symptom interference in patients with late-stage lung cancer
Bradley J. Barney
Xin Shelley Wang
Valen E. Johnson
Charles S. Cleeland
Tito R. Mendoza
- Springer Netherlands