156
Views
0
CrossRef citations to date
0
Altmetric
Article

Modeling survival response using a parametric approach in the presence of multicollinearity

ORCID Icon
Pages 1889-1898 | Received 19 Mar 2021, Accepted 27 Mar 2022, Published online: 05 Apr 2022

References

  • Adusumilli, P., M. L. Konatam, S. Gundeti, S. Bala, and L. S. Maddali. 2017. Treatment challenges and survival analysis of human epidermal growth factor receptor 2-positive breast cancer in real world. Indian Journal of Medical and Paediatric Oncology: Official Journal of Indian Society of Medical & Paediatric Oncology 38 (1):22–7.
  • Belot, A., A. Ndiaye, M.-A. Luque-Fernandez, D.-K. Kipourou, C. Maringe, F. J. Rubio, and B. Rachet. 2019. ‘Summarizing and communicating on survival data according to the audience: A tutorial on different measures illustrated with population-based cancer registry data. Clinical Epidemiology 11:53–65. doi:10.2147/CLEP.S173523.
  • Cox, C, and M. Matheson. 2014. A comparison of the generalized gamma and exponentiated weibull distributions. Statistics in Medicine 33 (21):3772–80. doi:10.1002/sim.6159.
  • Desmedt, C., B. Haibe-Kains, P. Wirapati, M. Buyse, D. Larsimont, G. Bontempi, M. Delorenzi, M. Piccart, and C. Sotiriou. 2008. Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clinical Cancer Research: An Official Journal of the American Association for Cancer Research 14 (16):5158–65. doi:10.1158/1078-0432.CCR-07-4756.
  • Desmedt, C., F. Piette, S. Loi, Y. Wang, F. Lallemand, B. Haibe-Kains, G. Viale, M. Delorenzi, Y. Zhang, M. S. d’Assignies, et al. 2007. Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the transbig multicenter independent validation series. Clinical Cancer Research: An Official Journal of the American Association for Cancer Research 13 (11):3207–14. doi:10.1158/1078-0432.CCR-06-2765.
  • Haibe-Kains, B., C. Desmedt, C. Sotiriou, and G. Bontempi. 2008. A comparative study of survival models for breast cancer prognostication based on microarray data: Does a single gene beat them all? Bioinformatics (Oxford, England) 24 (19):2200–8. doi:10.1093/bioinformatics/btn374.
  • Kelly, C., P. Majewska, S. Ioannidis, M. H. Raza, and M. Williams. 2017. Estimating progression-free survival in patients with glioblastoma using routinely collected data. Journal of Neuro-Oncology 135 (3):621–7. doi:10.1007/s11060-017-2619-1.
  • Klein, J. P, and M. L. Moeschberger. 2003. Survival analysis: Techniques for censored and truncated data. Vol. 2, 3–5. New York: Springer Science & Business Media.
  • Krawczyk, N., A. Hartkopf, M. Banys, F. Meier-Stiegen, A. Staebler, M. Wallwiener, C. Röhm, J. Hoffmann, M. Hahn, and T. Fehm. 2014. Prognostic relevance of induced and spontaneous apoptosis of disseminated tumor cells in primary breast cancer patients. BMC Cancer 14 (1):394. doi:10.1186/1471-2407-14-394.
  • Lee, E. T, and O. T. Go. 1997. Survival analysis in public health research. Annual Review of Public Health 18 (1):105–34. doi:10.1146/annurev.publhealth.18.1.105.
  • Longatto Filho, A., J. M. Lopes, and F. C. Schmitt. 2010. Angiogenesis and breast cancer. Journal of Oncology 2010:1–7. doi:10.1155/2010/576384.
  • Ma, J., D.-X. Luo, C. Huang, Y. Shen, Y. Bu, S. Markwell, J. Gao, J. Liu, X. Zu, Z. Cao, et al. 2012. Akr1b10 overexpression in breast cancer: Association with tumor size, lymph node metastasis and patient survival and its potential as a novel serum marker. International Journal of Cancer 131 (6):E862–E871. doi:10.1002/ijc.27618.
  • Mehmood, T., M. Sadiq, and M. Aslam. 2019. Filter-based factor selection methods in partial least squares regression. IEEE Access 7:153499–508. doi:10.1109/ACCESS.2019.2948782.
  • Mendes, D., C. Alves, N. Afonso, F. Cardoso, J. L. Passos-Coelho, L. Costa, S. Andrade, and F. Batel-Marques. 2015. The benefit of her2-targeted therapies on overall survival of patients with metastatic her2-positive breast cancer-a systematic review. Breast Cancer Research: BCR 17 (1):140. doi:10.1186/s13058-015-0648-2.
  • Royston, P, and P. C. Lambert. 2011. Flexible parametric survival analysis using stata: Beyond the cox model, Vol. 347. College Station, TX: Stata press.
  • Sadiq, M., D. K. F. Alnagar, A. T. Abdulrahman, and R. Alharbi. 2022. The partial least squares spline model for public health surveillance data. Computational and Mathematical Methods in Medicine 2022:1–7. doi:10.1155/2022/8774742.
  • Sadiq, M, and T. Mehmood. 2021. A flexible and robust approach to analyze survival systems in the presence of extreme observations. Mathematical Problems in Engineering 2021:1–11. doi:10.1155/2021/9927377.
  • Sadiq, M., T. Mehmood, and M. Aslam. 2019. Identifying the factors associated with cesarean section modeled with categorical correlation coefficients in partial least squares. PloS One 14 (7):e0219427. doi:10.1371/journal.pone.0219427.
  • Schmidt, M., D. Böhm, C. Von Törne, E. Steiner, A. Puhl, H. Pilch, H.-A. Lehr, J. G. Hengstler, H. Kölbl, and M. Gehrmann. 2008. The humoral immune system has a key prognostic impact in node-negative breast cancer. Cancer Research 68 (13):5405–13. doi:10.1158/0008-5472.CAN-07-5206.
  • Sotiriou, C., P. Wirapati, S. Loi, A. Harris, S. Fox, J. Smeds, H. Nordgren, P. Farmer, V. Praz, B. Haibe-Kains, et al. 2006. Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis. JNCI: Journal of the National Cancer Institute 98 (4):262–72. doi:10.1093/jnci/djj052.
  • van de Vijver, M., Y. He, L. van 't Veer, H. Dai, A. Hart, D. Voskuil, G. Schreiber, J. Peterse, C. Roberts, M. Marton, et al. 2002. A gene-expression signature as a predictor of survival in breast cancer. New England Journal of Medicine 347 (25):1999–2009. doi:10.1056/NEJMoa021967.
  • Van Diest, P. J., G. Brugal, and J. Baak. 1998. Proliferation markers in tumours: Interpretation and clinical value. Journal of Clinical Pathology 51 (10):716–24.
  • Van Uden, D., M. Van Maaren, L. J. Strobbe, P. Bult, J. Van Der Hoeven, S. Siesling, J. De Wilt, and C. Blanken-Peeters. 2019. Metastatic behavior and overall survival according to breast cancer subtypes in stage iv inflammatory breast cancer. Breast Cancer Research: BCR 21 (1):113. doi:10.1186/s13058-019-1201-5.
  • Wang, J., Y. Li, W. Fu, Y. Zhang, J. Jiang, Y. Zhang, and X. Qi. 2019. Prognostic nomogram based on immune scores for breast cancer patients. Cancer Medicine 8 (11):5214–22. doi:10.1002/cam4.2428.
  • Zhou, Z., J. X. Qiao, A. Shetty, G. Wu, Y. Huang, N. E. Davidson, and Y. Wan. 2014. Regulation of estrogen receptor signaling in breast carcinogenesis and breast cancer therapy. Cellular and Molecular Life Sciences: CMLS 71 (8):1549. doi:10.1007/s00018-013-1376-3.
  • Zimmerman, M., M. A. Posternak, and I. Chelminski. 2004. Implications of using different cut-offs on symptom severity scales to define remission from depression. International Clinical Psychopharmacology 19 (4):215–20.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.