Literature DB >> 17651459

Efron-type measures of prediction error for survival analysis.

Thomas A Gerds1, Martin Schumacher.   

Abstract

Estimates of the prediction error play an important role in the development of statistical methods and models, and in their applications. We adapt the resampling tools of Efron and Tibshirani (1997, Journal of the American Statistical Association92, 548-560) to survival analysis with right-censored event times. We find that flexible rules, like artificial neural nets, classification and regression trees, or regression splines can be assessed, and compared to less flexible rules in the same data where they are developed. The methods are illustrated with data from a breast cancer trial.

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Year:  2007        PMID: 17651459     DOI: 10.1111/j.1541-0420.2007.00832.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  33 in total

1.  Robust prediction of t-year survival with data from multiple studies.

Authors:  Tianxi Cai; Thomas A Gerds; Yingye Zheng; Jinbo Chen
Journal:  Biometrics       Date:  2010-07-28       Impact factor: 2.571

2.  Genomic heterogeneity in core-binding factor acute myeloid leukemia and its clinical implication.

Authors:  Nikolaus Jahn; Tobias Terzer; Eric Sträng; Anna Dolnik; Sibylle Cocciardi; Ekaterina Panina; Andrea Corbacioglu; Julia Herzig; Daniela Weber; Anika Schrade; Katharina Götze; Thomas Schröder; Michael Lübbert; Dominique Wellnitz; Elisabeth Koller; Richard F Schlenk; Verena I Gaidzik; Peter Paschka; Frank G Rücker; Michael Heuser; Felicitas Thol; Arnold Ganser; Axel Benner; Hartmut Döhner; Lars Bullinger; Konstanze Döhner
Journal:  Blood Adv       Date:  2020-12-22

3.  Individualized dynamic prediction of prostate cancer recurrence with and without the initiation of a second treatment: Development and validation.

Authors:  Mbéry Sène; Jeremy Mg Taylor; James J Dignam; Hélène Jacqmin-Gadda; Cécile Proust-Lima
Journal:  Stat Methods Med Res       Date:  2014-05-20       Impact factor: 3.021

4.  Evaluating Random Forests for Survival Analysis using Prediction Error Curves.

Authors:  Ulla B Mogensen; Hemant Ishwaran; Thomas A Gerds
Journal:  J Stat Softw       Date:  2012-09       Impact factor: 6.440

5.  Impact of genomic risk factors on outcome after hematopoietic stem cell transplantation for patients with chronic myeloid leukemia.

Authors:  Anne M Dickinson; Kim F Pearce; Jean Norden; Stephen G O'Brien; Ernst Holler; Heike Bickeböller; Yesilda Balavarca; Vanderson Rocha; Hans-Jochem Kolb; Ilona Hromadnikova; Petr Sedlacek; Dietger Niederwieser; Ronald Brand; Tapani Ruutu; Jane Apperley; Richard Szydlo; Els Goulmy; Wolfgang Siegert; Theo de Witte; Alois Gratwohl
Journal:  Haematologica       Date:  2010-03-19       Impact factor: 9.941

6.  Large-scale Radiomic Profiling of Recurrent Glioblastoma Identifies an Imaging Predictor for Stratifying Anti-Angiogenic Treatment Response.

Authors:  Philipp Kickingereder; Michael Götz; John Muschelli; Antje Wick; Ulf Neuberger; Russell T Shinohara; Martin Sill; Martha Nowosielski; Heinz-Peter Schlemmer; Alexander Radbruch; Wolfgang Wick; Martin Bendszus; Klaus H Maier-Hein; David Bonekamp
Journal:  Clin Cancer Res       Date:  2016-10-10       Impact factor: 12.531

7.  Cardiovascular risk associated with interactions among polymorphisms in genes from the renin-angiotensin, bradykinin, and fibrinolytic systems.

Authors:  John P Bentley; Folkert W Asselbergs; Christopher S Coffey; Patricia R Hebert; Jason H Moore; Hans L Hillege; Wiek H van Gilst
Journal:  PLoS One       Date:  2010-09-15       Impact factor: 3.240

8.  Absolute risk regression for competing risks: interpretation, link functions, and prediction.

Authors:  Thomas A Gerds; Thomas H Scheike; Per K Andersen
Journal:  Stat Med       Date:  2012-08-02       Impact factor: 2.373

9.  The validation and assessment of machine learning: a game of prediction from high-dimensional data.

Authors:  Tune H Pers; Anders Albrechtsen; Claus Holst; Thorkild I A Sørensen; Thomas A Gerds
Journal:  PLoS One       Date:  2009-08-04       Impact factor: 3.240

10.  Incorporating pathway information into boosting estimation of high-dimensional risk prediction models.

Authors:  Harald Binder; Martin Schumacher
Journal:  BMC Bioinformatics       Date:  2009-01-13       Impact factor: 3.169

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