Comparison of Questionnaire-Based Breast Cancer Prediction Models in the Nurses' Health Study

The Gail model and the model developed by Tyrer and Cuzick are two questionnaire-based approaches with demonstrated ability to predict development of breast cancer in a general population. We compared calibration, discrimination, and net reclassification of these models, using data from questionnair...

Full description

Saved in:
Bibliographic Details
Published in:Cancer epidemiology, biomarkers & prevention biomarkers & prevention, 2019-07, Vol.28 (7), p.1187-1194
Main Authors: Glynn, Robert J, Colditz, Graham A, Tamimi, Rulla M, Chen, Wendy Y, Hankinson, Susan E, Willett, Walter W, Rosner, Bernard
Format: Article
Language:English
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The Gail model and the model developed by Tyrer and Cuzick are two questionnaire-based approaches with demonstrated ability to predict development of breast cancer in a general population. We compared calibration, discrimination, and net reclassification of these models, using data from questionnaires sent every 2 years to 76,922 participants in the Nurses' Health Study between 1980 and 2006, with 4,384 incident invasive breast cancers identified by 2008 (median follow-up, 24 years; range, 1-28 years). In a random one third sample of women, we also compared the performance of these models with predictions from the Rosner-Colditz model estimated from the remaining participants. Both the Gail and Tyrer-Cuzick models showed evidence of miscalibration (Hosmer-Lemeshow < 0.001 for each) with notable ( < 0.01) overprediction in higher-risk women (2-year risk above about 1%) and underprediction in lower-risk women (risk below about 0.25%). The Tyrer-Cuzick model had slightly higher C-statistics both overall ( < 0.001) and in age-specific comparisons than the Gail model (overall C, 0.63 for Tyrer-Cuzick vs. 0.61 for the Gail model). Evaluation of net reclassification did not favor either model. In the one third sample, the Rosner-Colditz model had better calibration and discrimination than the other two models. All models had C-statistics
ISSN:1055-9965
1538-7755
DOI:10.1158/1055-9965.EPI-18-1039