0000000000133825
AUTHOR
A. Elsäßer
showing 3 related works from this author
Coupled variable selection for regression modeling of complex treatment patterns in a clinical cancer registry.
2013
For determining a manageable set of covariates potentially influential with respect to a time-to-event endpoint, Cox proportional hazards models can be combined with variable selection techniques, such as stepwise forward selection or backward elimination based on p-values, or regularized regression techniques such as component-wise boosting. Cox regression models have also been adapted for dealing with more complex event patterns, for example, for competing risks settings with separate, cause-specific hazard models for each event type, or for determining the prognostic effect pattern of a variable over different landmark times, with one conditional survival model for each landmark. Motivat…
Postersitzung 2: Das metastasierte Prostatakarzinom
1988
Weltweit sind betrachtliche Unterschiede in der Morbiditat und Mortalitat des Prostatacarcinoms bekannt. Die hochste Inzidenz besteht bei der schwarzen Bevolkerung in den USA, Asiaten hingegen erkranken nur sehr selten.
Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer--comparison between Adjuvant!, St G…
2009
Background: Defining risk categories in breast cancer is of considerable clinical significance. We have developed a novel risk classification algorithm and compared its prognostic utility to the Web-based tool Adjuvant! and to the St Gallen risk classification. Patients and methods: After a median follow-up of 10 years, we retrospectively analyzed 410 consecutive node-negative breast cancer patients who had not received adjuvant systemic therapy. High risk was defined by any of the following criteria: (i) age 2 cm. All patients were also characterized using Adjuvant! and the St Gallen 2007 risk categories. We analyzed disease-free survival (DFS) and overall survival (OS). Results: The Node-…