Literature DB >> 21555714

Problems with risk reclassification methods for evaluating prediction models.

Margaret S Pepe1.   

Abstract

For comparing the performance of a baseline risk prediction model with one that includes an additional predictor, a risk reclassification analysis strategy has been proposed. The first step is to cross-classify risks calculated according to the 2 models for all study subjects. Summary measures including the percentage of reclassification and the percentage of correct reclassification are calculated, along with 2 reclassification calibration statistics. The author shows that interpretations of the proposed summary measures and P values are problematic. The author's recommendation is to display the reclassification table, because it shows interesting information, but to use alternative methods for summarizing and comparing model performance. The Net Reclassification Index has been suggested as one alternative method. The author argues for reporting components of the Net Reclassification Index because they are more clinically relevant than is the single numerical summary measure.

Mesh:

Year:  2011        PMID: 21555714      PMCID: PMC3139963          DOI: 10.1093/aje/kwr013

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  27 in total

Review 1.  Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve.

Authors:  Nancy R Cook
Journal:  Clin Chem       Date:  2007-11-16       Impact factor: 8.327

2.  Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond.

Authors:  Michael J Pencina; Ralph B D'Agostino; Ralph B D'Agostino; Ramachandran S Vasan
Journal:  Stat Med       Date:  2008-01-30       Impact factor: 2.373

3.  Assessing the performance of prediction models: a framework for traditional and novel measures.

Authors:  Ewout W Steyerberg; Andrew J Vickers; Nancy R Cook; Thomas Gerds; Mithat Gonen; Nancy Obuchowski; Michael J Pencina; Michael W Kattan
Journal:  Epidemiology       Date:  2010-01       Impact factor: 4.822

4.  C-reactive protein and parental history improve global cardiovascular risk prediction: the Reynolds Risk Score for men.

Authors:  Paul M Ridker; Nina P Paynter; Nader Rifai; J Michael Gaziano; Nancy R Cook
Journal:  Circulation       Date:  2008-11-09       Impact factor: 29.690

5.  Value of adding single-nucleotide polymorphism genotypes to a breast cancer risk model.

Authors:  Mitchell H Gail
Journal:  J Natl Cancer Inst       Date:  2009-06-17       Impact factor: 13.506

6.  Prediction of incident hypertension risk in women with currently normal blood pressure.

Authors:  Nina P Paynter; Nancy R Cook; Brendan M Everett; Howard D Sesso; Julie E Buring; Paul M Ridker
Journal:  Am J Med       Date:  2009-05       Impact factor: 4.965

7.  Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures.

Authors:  Nancy R Cook; Paul M Ridker
Journal:  Ann Intern Med       Date:  2009-06-02       Impact factor: 25.391

8.  Assessing the value of risk predictions by using risk stratification tables.

Authors:  Holly Janes; Margaret S Pepe; Wen Gu
Journal:  Ann Intern Med       Date:  2008-11-18       Impact factor: 25.391

9.  Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model.

Authors:  Jeffrey A Tice; Steven R Cummings; Rebecca Smith-Bindman; Laura Ichikawa; William E Barlow; Karla Kerlikowske
Journal:  Ann Intern Med       Date:  2008-03-04       Impact factor: 25.391

10.  Evaluating new cardiovascular risk factors for risk stratification.

Authors:  Ralph H Stern
Journal:  J Clin Hypertens (Greenwich)       Date:  2008-06       Impact factor: 3.738

View more
  49 in total

1.  Development and Validation of Risk Prediction Models for Cardiovascular Events in Black Adults: The Jackson Heart Study Cohort.

Authors:  Ervin R Fox; Tandaw E Samdarshi; Solomon K Musani; Michael J Pencina; Jung Hye Sung; Alain G Bertoni; Vanessa Xanthakis; Pelbreton C Balfour; Satya S Shreenivas; Carolyn Covington; Philip R Liebson; Daniel F Sarpong; Kenneth R Butler; Thomas H Mosley; Wayne D Rosamond; Aaron R Folsom; David M Herrington; Ramachandran S Vasan; Herman A Taylor
Journal:  JAMA Cardiol       Date:  2016-04-01       Impact factor: 14.676

Review 2.  Biomarkers for incident CKD: a new framework for interpreting the literature.

Authors:  Michael G Shlipak; Erica C Day
Journal:  Nat Rev Nephrol       Date:  2013-06-11       Impact factor: 28.314

3.  Application of net reclassification index to non-nested and point-based risk prediction models: a review.

Authors:  Laine E Thomas; Emily C O'Brien; Jonathan P Piccini; Ralph B D'Agostino; Michael J Pencina
Journal:  Eur Heart J       Date:  2019-06-14       Impact factor: 29.983

4.  Re: "problems with risk reclassification methods for evaluating prediction models".

Authors:  Nancy R Cook
Journal:  Am J Epidemiol       Date:  2011-08-24       Impact factor: 4.897

5.  Commentary: Reporting standards are needed for evaluations of risk reclassification.

Authors:  Margaret S Pepe; Holly Janes
Journal:  Int J Epidemiol       Date:  2011-05-13       Impact factor: 7.196

6.  Measurement of AKI biomarkers in the ICU: still striving for appropriate clinical indications.

Authors:  John R Prowle
Journal:  Intensive Care Med       Date:  2015-01-22       Impact factor: 17.440

7.  Bivariate Analysis of Age-Related Macular Degeneration Progression Using Genetic Risk Scores.

Authors:  Ying Ding; Yi Liu; Qi Yan; Lars G Fritsche; Richard J Cook; Traci Clemons; Rinki Ratnapriya; Michael L Klein; Gonçalo R Abecasis; Anand Swaroop; Emily Y Chew; Daniel E Weeks; Wei Chen
Journal:  Genetics       Date:  2017-03-24       Impact factor: 4.562

8.  Net risk reclassification p values: valid or misleading?

Authors:  Margaret S Pepe; Holly Janes; Christopher I Li
Journal:  J Natl Cancer Inst       Date:  2014-03-28       Impact factor: 13.506

9.  Comment on Xirouchaki et al.: Impact of lung ultrasound on clinical decision making in critically ill patients.

Authors:  M O'Connor; C E Isitt; M P Vizcaychipi
Journal:  Intensive Care Med       Date:  2014-05-06       Impact factor: 17.440

Review 10.  Key concepts and limitations of statistical methods for evaluating biomarkers of kidney disease.

Authors:  Chirag R Parikh; Heather Thiessen-Philbrook
Journal:  J Am Soc Nephrol       Date:  2014-05-01       Impact factor: 10.121

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.