Evidence map›Paper›PMID 33708742›Full record

ArticleIranian journal of public health2020

Discriminatory Accuracy of the Gail Model for Breast Cancer Risk Assessment among Iranian Women.

Sahar Rostami, Ali Rafei, Maryam Damghanian, Zohreh Khakbazan, Farzad Maleki, Kazem Zendehdel

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Article in Iranian journal of public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 citing papers in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Sahar RostamiDepartment of Reproductive Health and Midwifery, School of Nursing and Midwifery, Tehran University of Medical Sciences, Tehran, Iran.
Ali RafeiCancer Research Center, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Iran.
Maryam DamghanianNursing and Midwifery Care Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Zohreh KhakbazanNursing and Midwifery Care Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Farzad MalekiCancer Research Center, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Iran.
Kazem ZendehdelCancer Research Center, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Gail model is the most well-known tool for breast cancer risk assessment worldwide. Although it was validated in various Western populations, inconsistent results were reported from Asian populations. We used data from a large case-control study and evaluated the discriminatory accuracy of the Gail model for breast cancer risk assessment among the Iranian female population.

methodsWe used data from 942 breast cancer patients and 975 healthy controls at the Cancer Institute of Iran, Tehran, Iran, in 2016. We refitted the Gail model to our case-control data (the IR-Gail model). We compared the discriminatory power of the IR-Gail with the original Gail model, using ROC curve analyses and estimation of the area under the ROC curve (AUC).

resultsExcept for the history of biopsies that showed an extremely high relative risk (OR=9.1), the observed ORs were similar to the estimates observed in Gail's study. Incidence rates of breast cancer were extremely lower in Iran than in the USA, leading to a lower average absolute risk among the Iranian population (2.78, ±SD 2.45). The AUC was significantly improved after refitting the model, but it remained modest (0.636 vs. 0.627, ΔAUC = 0.009, bootstrapped

conclusionAlthough the coefficients from the local study improved the discriminatory accuracy of the model, it remained modest. Cohort studies are warranted to evaluate the validity of the model for Iranian women.

Indexed as

Breast neoplasmsLogistic modelsModels, StatisticalRisk assessment

Identifiers

PMID33708742
PMCPMC7917489

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