Predicting breast cancer risk and its association to biopsychosocial factors among Taiwanese women with a family history of breast cancer: an investigation based on the Gail model.

BACKGROUND

First-degree relatives with breast cancer have a two-fold higher risk than women without a family history. The Gail model approach has been employed in numerous studies to investigate the risk of breast cancer among women in a variety of countries. Nevertheless, the studies investigating the correlation between the level of breast cancer risk and biopsychosocial factors among Taiwanese women with a family history of breast cancer (FHBC) are limited. By using the Gail model, we explored the breast cancer risk score and its relationship to biopsychosocial factors among Taiwanese women with FHBC.

METHODS

The present study was a cross-sectional study from secondary data of the Taiwan Biobank from 2008 to 2018. Self-reports were conducted to determine biopsychosocial factors. A total of 3,060 women aged 35-70 years with and without FHBC were considered eligible for enrollment. The Gail model, which utilizes six questions, was used to estimate individual five-year absolute breast cancer risk. Women with scores at least 1.66% and above were categorized as high risk. In addition, we performed bivariate and multivariate logistic regression analysis using SPSS version 27 to predict the associations between biopsychosocial factors and the risk of breast cancer based on the Gail model. All analyses were stratified by age.

RESULTS

Among the 3,060 Taiwanese women, there was a statistically significant difference in breast cancer risk score between the groups with and without FHBC (p = < 0.001), stratified by age, of which 574 in FHBC group (34.2%) were identified as having a high breast cancer risk based on the Gail model. Furthermore, six out of 15 biopsychosocial factors were significantly associated with breast cancer risk in women under 50 years of age, while seven factors showed significant associations in women aged 50 years and older. Logistic regression analysis identified five biopsychosocial factors as consistent and significant predictors of breast cancer risk in women aged 50 years and older, highlighting this group as particularly vulnerable.

CONCLUSIONS

This study concludes that the Gail model identifies Taiwanese women who have a higher estimated risk of breast cancer based on cross-sectional data. Various biopsychosocial factors are associated with higher risk estimates in this population particularly in older women. Professionals can assist women in recognizing risk factors beyond the inevitable risk by encouraging regular screenings, positive behavior, and health promotion.