Literature DB >> 18373641

Gail model risk factors: impact of adding an extended family history for breast cancer.

Anna Crispo1, Giuseppe D'Aiuto, MariaRosaria De Marco, Massimo Rinaldo, Maria Grimaldi, Immacolata Capasso, Alfonso Amore, Cristina Bosetti, Carlo La Vecchia, Maurizio Montella.   

Abstract

An approach commonly used in estimating breast cancer risk is the Gail model. The objective of this study was to evaluate the feasibility and impact of adding extended family history as a new breast cancer risk factor into the Gail model. The data of the present study include cases with breast cancer and hospitalized controls recruited in the National Cancer Institute of Naples (southern Italy) between 1997 and 2000. We compared the first-degree relative (FDR) risk factor (standard Gail model) with the second-degree relative (SDR) information; and the FDR risk factor (standard Gail model) with the combination of FDR and SDR. We computed the c-statistic by comparing the risks found in our population to those in Gail-US population. The concordance for the model with FDR was 0.55 (95% CI 0.53-0.58), the model with SDR shows a modest but significant discriminatory accuracy (0.56, 95% CI 0.53-0.59), and the combination of FDR+SDR gave the concordance statistic of 0.57 (95% CI 0.54-0.60), indicating a good comparison between the two models. The results of our study show that extended family history information could be useful to improve the discriminatory power of the Gail model risk factors.

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Year:  2008        PMID: 18373641     DOI: 10.1111/j.1524-4741.2008.00566.x

Source DB:  PubMed          Journal:  Breast J        ISSN: 1075-122X            Impact factor:   2.431


  6 in total

1.  Gail model utilization in predicting breast cancer risk in Egyptian women: a cross-sectional study.

Authors:  Basem Saleh; Mohamed A Elhawary; Moataz E Mohamed; Islam N Ali; Menna S El Zayat; Hadeer Mohamed
Journal:  Breast Cancer Res Treat       Date:  2021-04-14       Impact factor: 4.872

2.  Assessment of performance of the Gail model for predicting breast cancer risk: a systematic review and meta-analysis with trial sequential analysis.

Authors:  Xin Wang; Yubei Huang; Lian Li; Hongji Dai; Fengju Song; Kexin Chen
Journal:  Breast Cancer Res       Date:  2018-03-13       Impact factor: 6.466

3.  Diagnostic and Prognostic Significance of Carboxypeptidase A4 (CPA4) in Breast Cancer.

Authors:  Suleyman Bademler; Muhammed Zubeyr Ucuncu; Ceren Tilgen Vatansever; Murat Serilmez; Hakan Ertin; Hasan Karanlık
Journal:  Biomolecules       Date:  2019-03-14

4.  Prospective validation of the NCI Breast Cancer Risk Assessment Tool (Gail Model) on 40,000 Australian women.

Authors:  Carolyn Nickson; Pietro Procopio; Louiza S Velentzis; Sarah Carr; Lisa Devereux; Gregory Bruce Mann; Paul James; Grant Lee; Cameron Wellard; Ian Campbell
Journal:  Breast Cancer Res       Date:  2018-12-20       Impact factor: 6.466

5.  Discovery of breast cancer risk genes and establishment of a prediction model based on estrogen metabolism regulation.

Authors:  Feng Zhao; Zhixiang Hao; Yanan Zhong; Yinxue Xu; Meng Guo; Bei Zhang; Xiaoxing Yin; Ying Li; Xueyan Zhou
Journal:  BMC Cancer       Date:  2021-02-25       Impact factor: 4.430

Review 6.  Assessment of the risk of developing breast cancer using the Gail model in Asian females: A systematic review.

Authors:  Solikhah Solikhah; Sitti Nurdjannah
Journal:  Heliyon       Date:  2020-04-22
  6 in total

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