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Literature DB >> 31104561

The Importance of Uncertainty and Opt-In v. Opt-Out: Best Practices for Decision Curve Analysis.

Kathleen F Kerr¹, Tracey L Marsh², Holly Janes².

Abstract

Entities: CellLine Chemical Disease Gene Species

Mesh：

Year: 2019 PMID： 31104561 PMCID： PMC6786944 DOI： 10.1177/0272989X19849436

Source DB: PubMed Journal: Med Decis Making ISSN： 0272-989X Impact factor: 2.583

× No keyword cloud information.

7 in total

1. Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use.

Authors: Kathleen F Kerr; Marshall D Brown; Kehao Zhu; Holly Janes
Journal: J Clin Oncol Date: 2016-05-31 Impact factor: 44.544

2. A Systematic Review of the Literature Demonstrates Some Errors in the Use of Decision Curve Analysis but Generally Correct Interpretation of Findings.

Authors: Paolo Capogrosso; Andrew J Vickers
Journal: Med Decis Making Date: 2019-02-28 Impact factor: 2.583

3. Decision curve analysis: a novel method for evaluating prediction models.

Authors: Andrew J Vickers; Elena B Elkin
Journal: Med Decis Making Date: 2006 Nov-Dec Impact factor: 2.583

4. Assessing the Clinical Impact of Risk Models for Opting Out of Treatment.

Authors: Kathleen F Kerr; Marshall D Brown; Tracey L Marsh; Holly Janes
Journal: Med Decis Making Date: 2019-01-16 Impact factor: 2.583

5. Using relative utility curves to evaluate risk prediction.

Authors: Stuart G Baker; Nancy R Cook; Andrew Vickers; Barnett S Kramer
Journal: J R Stat Soc Ser A Stat Soc Date: 2009-10-01 Impact factor: 2.483

Review 6. Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators.

Authors: Ben Van Calster; Laure Wynants; Jan F M Verbeek; Jan Y Verbakel; Evangelia Christodoulou; Andrew J Vickers; Monique J Roobol; Ewout W Steyerberg
Journal: Eur Urol Date: 2018-09-19 Impact factor: 20.096

7. Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers.

Authors: Andrew J Vickers; Angel M Cronin; Elena B Elkin; Mithat Gonen
Journal: BMC Med Inform Decis Mak Date: 2008-11-26 Impact factor: 2.796

7 in total

4 in total

The Importance of Uncertainty and Opt-In v. Opt-Out: Best Practices for Decision Curve Analysis.

1. Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use.

2. A Systematic Review of the Literature Demonstrates Some Errors in the Use of Decision Curve Analysis but Generally Correct Interpretation of Findings.

3. Decision curve analysis: a novel method for evaluating prediction models.

4. Assessing the Clinical Impact of Risk Models for Opting Out of Treatment.

5. Using relative utility curves to evaluate risk prediction.

Review 6. Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators.

7. Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers.

1. Statistical inference for net benefit measures in biomarker validation studies.

2. Uncertainty and the Value of Information in Risk Prediction Modeling.

Review 3. Noninvasive biomarkers for lung cancer diagnosis, where do we stand?

4. Recalibration Methods for Improved Clinical Utility of Risk Scores.