The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Flexible Methods for Analyzing Survival Data Using Splines, with Applications to Breast Cancer Prognosis
Abstract
In this article some flexible methods for modeling censored survival data using splines are applied to the problem of modeling the time to recurrence of breast cancer patients. The basic idea is to use fixed knot splines with a fairly modest number of knots to model aspects of the data, and then to use penalized partial likelihood to estimate the parameters of the model. Test statistics are proposed which are analogs of those used in traditional likelihood analysis, and approximations to the distributions of these statistics are suggested. In an analysis of a large data set taken from clinical trials conducted by the Eastern Cooperative Oncology Group, these methods are seen to give useful insight into how prognosis varies as a function of continuous covariates, and also into how covariate effects change with follow-up time.
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Citations
Cites
Spline Models for Observational Data
Wahba, G. (1990) · doi:10.1137/1.9781611970128 · Cited by 4,184
Cited by
Loi, S., Haibe-Kains, B., Desmedt, C., Lallemand, F., Tutt, A. M., Gillet, C., Ellis, P., Harris, A., Bergh, J., Foekens, J. A., et al. (2007) · Journal of Clinical Oncology · doi:10.1200/jco.2006.07.1522 · Cited by 837
Scirica, B. M., Braunwald, E., Raz, I., Cavender, M. A., Morrow, D. A., Jarolim, P., Udell, J. A., Mosenzon, O., Im, K., Umez-Eronini, A. A., et al. (2014) · Circulation · doi:10.1161/circulationaha.114.010389 · Cited by 725
Graphical methods for assessing violations of the proportional hazards assumption in cox regression
Hess, K. R. (1995) · Statistics in Medicine · doi:10.1002/sim.4780141510 · Cited by 549
A randomized trial of a family-support intervention in intensive care units
White, D. B., Angus, D. C., Shields, A.-M., Buddadhumaruk, P., Pidro, C., Paner, C., Chaitin, E., Chang, C.-C. H., Pike, F., Weissfeld, L., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1802637 · Cited by 524
Penalized Survival Models and Frailty
Therneau, T. M., Grambsch, P. M., & Pankratz, V. S. (2003) · Journal of Computational and Graphical Statistics · doi:10.1198/1061860031365 · Cited by 481
Metadata
- Authors
- Gray, R. J.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1992-12
- Volume
- 87
- Issue
- 420
- Pages
- 942-951
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2014315605
- Cited by
- 502
- References
- 1
- FWCI
- 6.89
- Type
- journal article
- Language
- en
- Open access
- closed
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- Gray, R. J. (1992). Flexible Methods for Analyzing Survival Data Using Splines, with Applications to Breast Cancer Prognosis. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1992.10476248
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
