Literature DB >> 17729377

The need for reorientation toward cost-effective prediction: comments on 'Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond' by M. J. Pencina et al., Statistics in Medicine (DOI: 10.1002/sim.2929).

Sander Greenland1.   

Abstract

Mesh：

Year:  2008        PMID： 17729377     DOI： 10.1002/sim.2995

Source DB:  PubMed          Journal:  Stat Med        ISSN： 0277-6715            Impact factor:   2.373


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  12 in total

1.  Objective Estimates Improve Risk Stratification for Primary Graft Dysfunction after Lung Transplantation.

Authors:  R J Shah; J M Diamond; E Cantu; J Flesch; J C Lee; D J Lederer; V N Lama; J Orens; A Weinacker; D S Wilkes; D Roe; S Bhorade; K M Wille; L B Ware; S M Palmer; M Crespo; E Demissie; J Sonnet; A Shah; S M Kawut; S L Bellamy; A R Localio; J D Christie
Journal:  Am J Transplant       Date:  2015-04-15       Impact factor: 8.086

2.  The lack of utility of circulating biomarkers of inflammation and endothelial dysfunction for type 2 diabetes risk prediction among postmenopausal women: the Women's Health Initiative Observational Study.

Authors:  Chun Chao; Yiqing Song; Nancy Cook; Chi-Hong Tseng; JoAnn E Manson; Charles Eaton; Karen L Margolis; Beatriz Rodriguez; Lawrence S Phillips; Lesley F Tinker; Simin Liu
Journal:  Arch Intern Med       Date:  2010-09-27

Review 3.  Analysis of biomarker data: logs, odds ratios, and receiver operating characteristic curves.

Authors:  Birgit Grund; Caroline Sabin
Journal:  Curr Opin HIV AIDS       Date:  2010-11       Impact factor: 4.283

Review 4.  The potential of novel biomarkers to improve risk prediction of type 2 diabetes.

Authors:  Christian Herder; Bernd Kowall; Adam G Tabak; Wolfgang Rathmann
Journal:  Diabetologia       Date:  2014-01       Impact factor: 10.122

5.  Use of areas under the receiver operating curve (AROCs) and some caveats.

Authors:  B Kowall; W Rathmann; K Strassburger
Journal:  Int J Public Health       Date:  2012-09-04       Impact factor: 3.380

6.  Towards better clinical prediction models: seven steps for development and an ABCD for validation.

Authors:  Ewout W Steyerberg; Yvonne Vergouwe
Journal:  Eur Heart J       Date:  2014-06-04       Impact factor: 29.983

7.  Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers.

Authors:  Michael J Pencina; Ralph B D'Agostino; Ewout W Steyerberg
Journal:  Stat Med       Date:  2010-11-05       Impact factor: 2.373

8.  Updating risk prediction tools: a case study in prostate cancer.

Authors:  Donna P Ankerst; Tim Koniarski; Yuanyuan Liang; Robin J Leach; Ziding Feng; Martin G Sanda; Alan W Partin; Daniel W Chan; Jacob Kagan; Lori Sokoll; John T Wei; Ian M Thompson
Journal:  Biom J       Date:  2011-11-17       Impact factor: 2.207

Review 9.  Evaluation of markers and risk prediction models: overview of relationships between NRI and decision-analytic measures.

Authors:  Ben Van Calster; Andrew J Vickers; Michael J Pencina; Stuart G Baker; Dirk Timmerman; Ewout W Steyerberg
Journal:  Med Decis Making       Date:  2013-01-11       Impact factor: 2.583

10.  Cardiovascular Disease Risk Assessment: Insights from Framingham.

Authors:  Ralph B D'Agostino; Michael J Pencina; Joseph M Massaro; Sean Coady
Journal:  Glob Heart       Date:  2013-03
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