Gotay, C. C., Kawamoto, C. T., Bottomley, A., & Efficace, F. (2008). The prognostic significance of patient-reported outcomes in cancer clinical trials. Journal of Clinical Oncology, 26(8), 1355–1363.
Secord, A. A., Coleman, R. L., Havrilesky, L. J., Abernethy, A. P., Samsa, G. P., & CELLA, D. (2015). Patient-reported outcomes as end points and outcome indicators in solid tumours. Nature Reviews Clinical oncology, 12(6), 358–370.
Efficace, F., Gaidano, G., Breccia, M., Voso, M. T., Cottone, F., Angelucci, E., et al. (2015). Prognostic value of self-reported fatigue on overall survival in patients with myelodysplastic syndromes: A multicentre, prospective, observational, cohort study. The Lancet Oncology, 16(15), 1506–1514.
Efficace, F., Bottomley, A., Coens, C., Van Steen, K., Conroy, T., Schoffski, P., et al. (2006). Does a patient’s self-reported health-related quality of life predict survival beyond key biomedical data in advanced colorectal cancer? European Journal of Cancer, 42(1), 42–49.
Quinten, C., Martinelli, F., Coens, C., Sprangers, M. A., Ringash, J., Gotay, C., et al. (2014). A global analysis of multitrial data investigating quality of life and symptoms as prognostic factors for survival in different tumor sites. Cancer, 120(2), 302–311.
Efficace, F., Biganzoli, L., Piccart, M., Coens, C., Van Steen, K., Cufer, T., et al. (2004). Baseline health-related quality-of-life data as prognostic factors in a phase III multicentre study of women with metastatic breast cancer. European Journal of Cancer, 40(7), 1021–1030.
Maisey, N. R., Norman, A., Watson, M., Allen, M. J., Hill, M. E., & Cunningham, D. (2002). Baseline quality of life predicts survival in patients with advanced colorectal cancer. European Journal of Cancer, 38(10), 1351–1357.
Efficace, F., Innominato, P. F., Bjarnason, G., Coens, C., Humblet, Y., Tumolo, S., et al. (2008). Validation of patient’s self-reported social functioning as an independent prognostic factor for survival in metastatic colorectal cancer patients: results of an international study by the Chronotherapy Group of the European Organisation for Research and Treatment of Cancer. Journal of Clinical Oncology, 26(12), 2020–2026.
Fang, F. M., Tsai, W. L., Chiu, H. C., Kuo, W. R., & Hsiung, C. Y. (2004). Quality of life as a survival predictor for esophageal squamous cell carcinoma treated with radiotherapy. International Journal of Radiation Oncology, Biology, Physics, 58(5), 1394–1404.
Chau, I., Norman, A. R., Cunningham, D., Waters, J. S., Oates, J., & Ross, P. J. (2004). Multivariate prognostic factor analysis in locally advanced and metastatic esophago-gastric cancer–pooled analysis from three multicenter, randomized, controlled trials using individual patient data. Journal of Clinical Oncology, 22(12), 2395–2403.
de Graeff, A., de Leeuw, J. R., Ros, W. J., Hordijk, G. J., Blijham, G. H., & Winnubst, J. A. (2001). Sociodemographic factors and quality of life as prognostic indicators in head and neck cancer. European Journal of Cancer, 37(3), 332–339.
Chiarion-Sileni, V., Del Bianco, P., De Salvo, G. L., Lo Re, G., Romanini, A., Labianca, R., et al. (2003). Quality of life evaluation in a randomised trial of chemotherapy versus bio-chemotherapy in advanced melanoma patients. European Journal of Cancer, 39(11), 1577–1585.
Dubois, D., Dhawan, R., van de Velde, H., Esseltine, D., Gupta, S., Viala, M., et al. (2006). Descriptive and prognostic value of patient-reported outcomes: the bortezomib experience in relapsed and refractory multiple myeloma. Journal of Clinical Oncology, 24(6), 976–982.
Eton, D. T., Fairclough, D. L., Cella, D., Yount, S. E., Bonomi, P., & Johnson, D. H. (2003). Early change in patient-reported health during lung cancer chemotherapy predicts clinical outcomes beyond those predicted by baseline report: Results from Eastern Cooperative Oncology Group Study 5592. Journal of Clinical Oncology, 21(8), 1536–1543.
Bottomley, A., Coens, C., Efficace, F., Gaafar, R., Manegold, C., Burgers, S., et al. (2007). Symptoms and patient-reported well-being: Do they predict survival in malignant pleural mesothelioma? A prognostic factor analysis of EORTC-NCIC 08983: Randomized phase III study of cisplatin with or without raltitrexed in patients with malignant pleural mesothelioma. Journal of Clinical Oncology, 25(36), 5770–5776.
Cella, D., Traina, S., Li, T., Johnson, K., Ho, K. F., Molina, A., et al. (2018). Relationship between patient-reported outcomes and clinical outcomes in metastatic castration-resistant prostate cancer: post hoc analysis of COU-AA-301 and COU-AA-302. Annals of Oncology, 29(2), 392–397.
Movsas, B., Hu, C., Sloan, J., Bradley, J., Komaki, R., Masters, G., et al. (2016). Quality of life analysis of a radiation dose-escalation study of patients with non-small-cell lung cancer: A secondary analysis of the radiation therapy oncology group 0617 randomized clinical trial. JAMA Oncology, 2(3), 359–367.
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.
Van Steen, K., Curran, D., Kramer, J., Molenberghs, G., Van Vreckem, A., Bottomley, A., et al. (2002). Multicollinearity in prognostic factor analyses using the EORTC QLQ-C30: identification and impact on model selection. Statistics in Medicine, 21(24), 3865–3884.
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.
Cramer, E. M. (1985). Multicollinearity. In S. Kotz, N. L. Johnson & C. B. Read (Eds.), Encyclopedia of statistical sciences. (Vol. 2, pp. 639–643). New York, Wiley.
Slinker, B. K., & Glantz, S. A. (1985). Multiple regression for physiological data analysis: The problem of multicollinearity. The American Journal of Physiology, 249(1 Pt 2), R1–R12.
Sithisarankul, P., Weaver, V. M., Diener-West, M., & Strickland, P. T. (1997). Multicollinearity may lead to artificial interaction: An example from a cross sectional study of biomarkers. The Southeast Asian Journal of Tropical Medicine and Public Health, 28(2), 404–409.
Ediebah, D. E., Coens, C., Zikos, E., Quinten, C., Ringash, J., King, M. T., et al. (2014). Does change in health-related quality of life score predict survival? Analysis of EORTC 08975 lung cancer trial. British Journal of Cancer, 110(10), 2427–2433.
Staren, E. D., Gupta, D., & Braun, D. P. (2011). The prognostic role of quality of life assessment in breast cancer. The Breast Journal, 17(6), 571–578.
Harrell, f. e. jr., Lee, K. L., Matchar, D. B., & Reichert, T. A. (1985). Regression models for prognostic prediction: Advantages, problems, and suggested solutions. Cancer Treatment Reports, 69(10), 1071–1077.
Harrell, F. E. (2015). Regression modeling strategies: With applications to linear models, logistic and ordinal regression, and survival analysis. Cham: Springer.
Simon, R., & Altman, D. G. (1994). Statistical aspects of prognostic factor studies in oncology. British journal of cancer, 69(6), 979–985.
Cohen, J. (2003). Applied multiple regression/correlation analysis for the behavioral sciences. Mahwah: Lawrence Erlbaum Associates Publishers.
Hoerl, A. E., & Kennard, R. W. (2000). Ridge regression: Biased estimation for nonorthogonal problems. Technometrics, 42(1), 80–86.
Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrov, F. Csaki (Ed.), Second international symposium on information theory (pp. 267–281): Budapest: Akademai Kiado.
Hastie, T., Tibshirani, R., & Friedman, J. H. (2001). The elements of statistical learning: data mining, inference, and prediction. New York: Springer.
Fayers, P., Aaronson, N. K., Bjordal, K., Groenvold, M., Curran, D., & Bottomley, A. on behalf of the EORTC Quality of Life Group. (2001). The EORTC QLQ-C30 Scoring Manual (3rd Edn). European Organisation for Research and Treatment of Cancer, Brussels.
Masters, G. (1982). A Rasch model for partial credit scoring. Psychometrika, 47, 149–174.
Lee, E. T., & Go, O. T. (1997). Survival analysis in public health research. Annual Review of Public Health, 18, 105–134.
Bender, R., Augustin, T., & Blettner, M. (2005). Generating survival times to simulate Cox proportional hazards models. Statistics in Medicine, 24(11), 1713–1723.
Altman, D. G., & Andersen, P. K. (1989). Bootstrap investigation of the stability of a Cox regression model. Statistics in Medicine, 8(7), 771–783.
Sauerbrei, W., Boulesteix, A. L., & Binder, H. (2011). Stability investigations of multivariable regression models derived from low- and high-dimensional data. Journal of Biopharmaceutical Statistics, 21(6), 1206–1231.
Efron, B. (1977). The efficiency of Cox’s likelihood function for censored data. Journal of the American Statistical Association, 72, 557–565.
Team, R. C. (2016). R: A language and environment for statistical computing. https://www.R-project.org/.
Morozova, O., Levina, O., Uuskula, A., & Heimer, R. (2015). Comparison of subset selection methods in linear regression in the context of health-related quality of life and substance abuse in Russia. BMC Medical Research Methodology, 15, 71.
Steyerberg, E. W., Eijkemans, M. J., Harrell, F. E. Jr., & Habbema, J. D. (2000). Prognostic modelling with logistic regression analysis: A comparison of selection and estimation methods in small data sets. Statistics in Medicine, 19(8), 1059–1079.
Yoo, W., Mayberry, R., Bae, S., Singh, K., He, P., Q., & Lillard, J. W. Jr. (2014). A study of effects of multicollinearity in the multivariable analysis. International Journal of Applied Science and Technology, 4(5), 9–19.
Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., et al. (2013). Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 27–46.
Xue, X., Kim, M. Y., & Shore, R. E. (2007). Cox regression analysis in presence of collinearity: An application to assessment of health risks associated with occupational radiation exposure. Lifetime Data Analysis, 13(3), 333–350.
Sauerbrei, W., & Schumacher, M. (1992). A bootstrap resampling procedure for model building: Application to the Cox regression model. Statistics in Medicine, 11(16), 2093–2109.
Peduzzi, P., Concato, J., Kemper, E., Holford, T. R., & Feinstein, A. R. (1996). A simulation study of the number of events per variable in logistic regression analysis. Journal of Clinical Epidemiology, 49(12), 1373–1379.
Harrell, F. E. Jr., Lee, K. L., Califf, R. M., Pryor, D. B., & Rosati, R. A. (1984). Regression modelling strategies for improved prognostic prediction. Statistics in Medicine, 3(2), 143–152.
