Why do so many prognostic factors fail to pan out? Susan Galloway HilsenbeckGary M ClarkWilliam L McGuire OriginalPaper Pages: 197 - 206
The Nottingham prognostic index in primary breast cancer Marcus H. GaleaRoger W. BlameyIan O. Ellis OriginalPaper Pages: 207 - 219
Confirmation of a prognostic index for patients with metastatic breast cancer treated by endocrine therapy JFR RobertsonAR DixonRW Blamey OriginalPaper Pages: 221 - 227
A graphical approach to the analysis of censored data Robert GentlemanJohn J. Crowley OriginalPaper Pages: 229 - 240
Flexible covariate effects in the proportional hazards model Treyor HastieLynn SleeperRobert Tibshirani OriginalPaper Pages: 241 - 250
Making the most of your prognostic factors: Presenting a more accurate survival model for breast cancer patients Karen L. KnorrSusan G. HilsenbeckGary M. Clark OriginalPaper Pages: 251 - 262
A comparison of all-subset Cox and accelerated failure time models with Cox step-wise regression for node-positive breast cancer Judy-Anne W. ChapmanMaureen E. TrudeauLavina A. Lickley OriginalPaper Pages: 263 - 272
Proportional hazards and recursive partitioning and amalgamation analyses of the southwest oncology group node-positive adjuvant CMFVP breast cancer data base: a pilot study Kathy S. AlbainStephanie GreenC. Kent Osborne OriginalPaper Pages: 273 - 284
A practical application of neural network analysis for predicting outcome of individual breast cancer patients Peter M. RavdinGary M. Clark OriginalPaper Pages: 285 - 293