Literature DB >> 25318454

A concordance index for matched case-control studies with applications in cancer risk.

Adam R Brentnall1, Jack Cuzick, John Field, Stephen W Duffy.   

Abstract

In unmatched case-control studies, the area under the receiver operating characteristic (ROC) curve (AUC) may be used to measure how well a variable discriminates between cases and controls. The AUC is sometimes used in matched case-control studies by ignoring matching, but it lacks interpretation because it is not based on an estimate of the ROC for the population of interest. We introduce an alternative measure of discrimination that is the concordance of risk factors conditional on the matching factors. Parametric and non-parametric estimators are given for different matching scenarios, and applied to real data from breast and lung cancer case-control studies. Diagnostic plots to verify the constancy of discrimination over matching factors are demonstrated. The proposed simple measure is easy to use, interpret, more efficient than unmatched AUC statistics and may be applied to compare the conditional discrimination performance of risk factors.
Copyright © 2014 John Wiley & Sons, Ltd.

Entities:  

Keywords:  case-control studies; classification; discrimination; matching

Mesh:

Year:  2014        PMID: 25318454     DOI: 10.1002/sim.6335

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


  14 in total

1.  Prediction of reader estimates of mammographic density using convolutional neural networks.

Authors:  Georgia V Ionescu; Martin Fergie; Michael Berks; Elaine F Harkness; Johan Hulleman; Adam R Brentnall; Jack Cuzick; D Gareth Evans; Susan M Astley
Journal:  J Med Imaging (Bellingham)       Date:  2019-01-31

2.  Cytosine methylation predicts renal function decline in American Indians.

Authors:  Chengxiang Qiu; Robert L Hanson; Gudeta Fufaa; Sayuko Kobes; Caroline Gluck; Jing Huang; Yong Chen; Dominic Raj; Robert G Nelson; William C Knowler; Katalin Susztak
Journal:  Kidney Int       Date:  2018-04-27       Impact factor: 10.612

3.  Deep Learning Predicts Interval and Screening-detected Cancer from Screening Mammograms: A Case-Case-Control Study in 6369 Women.

Authors:  Xun Zhu; Thomas K Wolfgruber; Lambert Leong; Matthew Jensen; Christopher Scott; Stacey Winham; Peter Sadowski; Celine Vachon; Karla Kerlikowske; John A Shepherd
Journal:  Radiology       Date:  2021-09-07       Impact factor: 11.105

4.  Predicting Islet Cell Autoimmunity and Type 1 Diabetes: An 8-Year TEDDY Study Progress Report.

Authors:  Jeffrey P Krischer; Xiang Liu; Kendra Vehik; Beena Akolkar; William A Hagopian; Marian J Rewers; Jin-Xiong She; Jorma Toppari; Anette-G Ziegler; Åke Lernmark
Journal:  Diabetes Care       Date:  2019-04-09       Impact factor: 17.152

5.  A comparison of five methods of measuring mammographic density: a case-control study.

Authors:  Susan M Astley; Elaine F Harkness; Jamie C Sergeant; Jane Warwick; Paula Stavrinos; Ruth Warren; Mary Wilson; Ursula Beetles; Soujanya Gadde; Yit Lim; Anil Jain; Sara Bundred; Nicola Barr; Valerie Reece; Adam R Brentnall; Jack Cuzick; Tony Howell; D Gareth Evans
Journal:  Breast Cancer Res       Date:  2018-02-05       Impact factor: 6.466

6.  A novel and fully automated mammographic texture analysis for risk prediction: results from two case-control studies.

Authors:  Chao Wang; Adam R Brentnall; Jack Cuzick; Elaine F Harkness; D Gareth Evans; Susan Astley
Journal:  Breast Cancer Res       Date:  2017-10-18       Impact factor: 6.466

7.  Impact of a Panel of 88 Single Nucleotide Polymorphisms on the Risk of Breast Cancer in High-Risk Women: Results From Two Randomized Tamoxifen Prevention Trials.

Authors:  Jack Cuzick; Adam R Brentnall; Corrinne Segal; Helen Byers; Caroline Reuter; Simone Detre; Elena Lopez-Knowles; Ivana Sestak; Anthony Howell; Trevor J Powles; William G Newman; Mitchell Dowsett
Journal:  J Clin Oncol       Date:  2016-12-28       Impact factor: 44.544

8.  Exploring the prediction performance for breast cancer risk based on volumetric mammographic density at different thresholds.

Authors:  Chao Wang; Adam R Brentnall; Jack Cuzick; Elaine F Harkness; D Gareth Evans; Susan Astley
Journal:  Breast Cancer Res       Date:  2018-06-08       Impact factor: 6.466

9.  Use of the concordance index for predictors of censored survival data.

Authors:  Adam R Brentnall; Jack Cuzick
Journal:  Stat Methods Med Res       Date:  2016-12-29       Impact factor: 3.021

10.  Nomogram for individualized prediction of incident multidrug-resistant tuberculosis after completing pulmonary tuberculosis treatment.

Authors:  Qinglin Cheng; Gang Zhao; Xuchu Wang; Le Wang; Min Lu; Qingchun Li; Yifei Wu; Yinyan Huang; Qingjun Jia; Li Xie
Journal:  Sci Rep       Date:  2020-08-13       Impact factor: 4.379

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