Assessing risk of breast cancer in an ethnically South-East Asia population (results of a multiple ethnic groups study)

Abstract

BackgroundGail and others developed a model (GAIL) using age-at-menarche, age-at-birth of first live child, number of previous benign breast biopsy examinations, and number of first-degree-relatives with breast cancer as well as baseline age-specific breast cancer risks for predicting the 5-year risk of invasive breast cancer for Caucasian women. However, the validity of the model for projecting risk in South-East Asian women is uncertain. We evaluated GAIL and attempted to improve its performance for Singapore women of Chinese, Malay and Indian origins.MethodsData from the Singapore Breast Screening Programme (SBSP) are used. Motivated by lower breast cancer incidence in many Asian countries, we utilised race-specific invasive breast cancer and other cause mortality rates for Singapore women to produce GAIL-SBSP. By using risk factor information from a nested case-control study within SBSP, alternative models incorporating fewer then additional risk factors were determined. Their accuracy was assessed by comparing the expected cases (E) with the observed (O) by the ratio (E/O) and 95% confidence interval (CI) and the respective concordance statistics estimated.ResultsFrom 28,883 women, GAIL-SBSP predicted 241.83 cases during the 5-year follow-up while 241 were reported (E/O=1.00, CI=0.88 to 1.14). Except for women who had two or more first-degree-relatives with breast cancer, satisfactory prediction was present in almost all risk categories. This agreement was reflected in Chinese and Malay, but not in Indian women. We also found that a simplified model (S-GAIL-SBSP) including only age-at-menarche, age-at-birth of first live child and number of first-degree-relatives performed similarly with associated concordance statistics of 0.5997. Taking account of body mass index and parity did not improve the calibration of S-GAIL-SBSP.ConclusionsGAIL can be refined by using national race-specific invasive breast cancer rates and mortality rates for causes other than breast cancer. A revised model containing only three variables (S-GAIL-SBSP) provides a simpler approach for projecting absolute risk of invasive breast cancer in South-East Asia women. Nevertheless its role in counseling the individual women regarding their risk of breast cancer remains problematical and needs to be validated in independent data.

Differences in Incidence, Mortality and Survival of Breast Cancer by Regions and Countries in Asia and Contributing Factors

“…Mathematical models to estimate breast cancer risk specific to Asian women have been developed among Korean women and a multi-ethnic population in Singapore (Gao et al, 2012;Park et al, 2013). A Korean model was independently developed using the risk estimates extracted from a large Korean case-control study and was assessed in two Korean cohort studies, which showed AUCs of 0.61 and 0.89 (Park et al, 2013).…”

“…A Korean model was independently developed using the risk estimates extracted from a large Korean case-control study and was assessed in two Korean cohort studies, which showed AUCs of 0.61 and 0.89 (Park et al, 2013). The Singapore model, which was a modified Gail model, found that the inclusion of age at menarche, age at first birth, and the number of first degree relatives with breast cancer performed fairly well with associated concordance statistics of 0.60 (Gao et al, 2012). In addition to the known factors, 12 SNPs were included to a risk assessment model among Chinese women, with a c-statistic of 0.63 after adjustment for over-fitting .…”

Gail Model Underestimates Breast Cancer Risk in Thai Population

“…A study by Chay et al on Singaporean women with a 10-year follow up found that the number of expected invasive breast cancer cases based on the Gail model was 1.85 times higher than the actual number (Chay et al, 2012). The refined Gail model for a South East Asian population had a limited discrimination power of 0.6 (Gao et al, 2012). A validation study of the modified Gail model in a Korean population also found that the model did not perform well in an Asian population.…”

Validation of Electrical Impedance Tomography Qualitative and Quantitative Values and Comparison of the Numeric Pain Distress Score against Mammography

“…Table 2 described the comparison of EIT quantitative values between group 1 and group 2. The covariates and factors that taken into account in this study were based on Gail Model (Gao et al, 2012).…”