Prospective validation of the NCI Breast Cancer Risk Assessment Tool (Gail Model) on 40,000 Australian women.
Background: There is a growing interest in delivering more personalised, risk-based breast cancer screening protocols. This requires population-level validation of practical models that can stratify women into breast cancer risk groups. Few studies have evaluated the Gail model (NCI Breast Cancer Ri...
| Publicado en: | Breast Cancer Research Vol. 20; no. 1 |
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| Autores principales: | , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
BioMed Central
12/20/2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=133663802&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 133663802 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14655411 8UYJ jtl: Breast Cancer Research issn: 14655411 maglogo: N pubinfo: dt: 12/20/2018 vid: 20 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 133663802 133663802 NLM30572910 133663802 10.1186/s13058-018-1084-x NLM30572910 133663802 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Prospective validation of the NCI Breast Cancer Risk Assessment Tool (Gail Model) on 40,000 Australian women. aug: au: Nickson, Carolyn Procopio, Pietro Velentzis, Louiza S. Carr, Sarah Devereux, Lisa Mann, Gregory Bruce James, Paul Lee, Grant Wellard, Cameron Campbell, Ian affil: Melbourne School of Population and Global Health, University of Melbourne, 3010, Carlton, Victoria, Australia sug: subj: Early Detection of Cancer Methods Models, Statistical Breast Neoplasms Diagnosis Health Screening Methods Risk Factors Female United States Breast Neoplasms Prevention and Control Prognosis Patient Selection Aged Australia National Cancer Institute (U.S.) Middle Age Human Pharmacokinetics Prospective Studies Breast Neoplasms Epidemiology Risk Assessment Methods Validation Studies Comparative Studies Evaluation Research Multicenter Studies Aged: 65+ years Middle Aged: 45-64 years Female ab: Background: There is a growing interest in delivering more personalised, risk-based breast cancer screening protocols. This requires population-level validation of practical models that can stratify women into breast cancer risk groups. Few studies have evaluated the Gail model (NCI Breast Cancer Risk Assessment Tool) in a population screening setting; we validated this tool in a large, screened population.Methods: We used data from 40,158 women aged 50-69 years (via the lifepool cohort) participating in Australia's BreastScreen programme. We investigated the association between Gail scores and future invasive breast cancer, comparing observed and expected outcomes by Gail score ranked groups. We also used machine learning to rank Gail model input variables by importance and then assessed the incremental benefit in risk prediction obtained by adding variables in order of diminishing importance.Results: Over a median of 4.3 years, the Gail model predicted 612 invasive breast cancers compared with 564 observed cancers (expected/observed (E/O) = 1.09, 95% confidence interval (CI) 1.00-1.18). There was good agreement across decile groups of Gail scores (χ2 = 7.1, p = 0.6) although there was some overestimation of cancer risk in the top decile of our study group (E/O = 1.65, 95% CI 1.33-2.07). Women in the highest quintile (Q5) of Gail scores had a 2.28-fold increased risk of breast cancer (95% CI 1.73-3.02, p < 0.0001) compared with the lowest quintile (Q1). Compared with the median quintile, women in Q5 had a 34% increased risk (95% CI 1.06-1.70, p = 0.014) and those in Q1 had a 41% reduced risk (95% CI 0.44-0.79, p < 0.0001). Similar patterns were observed separately for women aged 50-59 and 60-69 years. The model's overall discrimination was modest (area under the curve (AUC) 0.59, 95% CI 0.56-0.61). A reduced Gail model excluding information on ethnicity and hyperplasia was comparable to the full Gail model in terms of correctly stratifying women into risk groups.Conclusions: This study confirms that the Gail model (or a reduced model excluding information on hyperplasia and ethnicity) can effectively stratify a screened population aged 50-69 years according to the risk of future invasive breast cancer. This information has the potential to enable more personalised, risk-based screening strategies that aim to improve the balance of the benefits and harms of screening. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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