Abstract PR02: Validation of breast cancer risk prediction model using Nurses Health and Nurse Health II Studies

Conclusions: These results confirm that breast cancer risk prediction models can discriminate between high-risk and low-risk women, but they also highlight that the accuracy of absolute risk estimates can vary across populations. Findings from this study can add insights into model improvement and model application. Moreover, the method of using IPW weights to approximate a full cohort analysis provides a potential solution for utilizing nested case-control studies in future validation analyses.This abstract is also being presented as Poster A05.Citation Format: Chi Gao, Parichoy Pal Choudhury, Paige Maas, Rulla Tamimi, Heather Eliassen, Nilanjan Chatterjee, Montserrat Garcia-Closas, Peter Kraft. Validation of breast cancer risk prediction model using Nurses Health and Nurse Health II Studies. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR02.

Source: Cancer Epidemiology Biomarkers and Prevention - April 30, 2017 Category: Cancer & Oncology Authors: Gao, C., Choudhury, P. P., Maas, P., Tamimi, R., Eliassen, H., Chatterjee, N., Garcia-Closas, M., Kraft, P. Tags: Improving Cancer Risk Prediction for Prevention and Early Detection: Oral Presentations - Proffered Abstracts Source Type: research