The Urban-Rural Heterogeneous Effect of Family SES on Achievement: The Mediating Role of Culture

Previous studies have fully discussed the relationship between family socioeconomic status (SES) and achievement, but few of them regarded urban-rural differences as the moderating factor, which is an essential issue in urban-rural educational equalization in terms of educational outcomes. This study discusses the urban-rural heterogeneous effect of family SES on achievement and manifests the mediating role of education-related cultural factors. Based on the China Education Panel Survey data of 18,672 junior high school students, this study found the following: (1) family SES had a weaker positive effect among rural children than among urban children; (2) the urban-rural heterogeneous effect could be mediated by education-related cultural factors, i.e., learning environments and beliefs; and (3) in this regard, contemporary China is experiencing cultural reproduction rather than a cultural mobility mode. In Conclusion, although the urban-rural achievement gap will be maintained or even expanded in China, improving rural children's learning environments and beliefs opens up the possibility of alleviating disadvantages in achievement resulting from family socioeconomic disadvantages. Therefore, narrowing down the urban-rural achievement gap from a cultural perspective provides policy implications for educational development in rural areas.

Adaptive Bayesian information borrowing methods for finding and optimizing subgroup-specific doses

In precision oncology, integrating multiple cancer patient subgroups into a single master protocol allows for the simultaneous assessment of treatment effects in these subgroups and promotes the sharing of information between them, ultimately reducing sample sizes and costs and enhancing scientific validity. However, the safety and efficacy of these therapies may vary across different subgroups, resulting in heterogeneous outcomes. Therefore, identifying subgroup-specific optimal doses in early-phase clinical trials is crucial for the development of future trials. In this article, we review various innovative Bayesian information-borrowing strategies that aim to determine and optimize subgroup-specific doses. Specifically, we discuss Bayesian hierarchical modeling, Bayesian clustering, Bayesian model averaging or selection, pairwise borrowing, and other relevant approaches. By employing these Bayesian information-borrowing methods, investigators can gain a better understanding of the intricate relationships between dose, toxicity, and efficacy in each subgroup. This increased understanding significantly improves the chances of identifying an optimal dose tailored to each specific subgroup. Furthermore, we present several practical recommendations to guide the design of future early-phase oncology trials involving multiple subgroups when using the Bayesian information-borrowing methods.

Heterogenous Effect of Risk Factors on Breast Cancer across the Breast Density Categories in a Korean Screening Population

We evaluated the heterogeneity of the effect of known risk factors on breast cancer development based on breast density by using the Breast Imaging-Reporting and Data System (BI-RADS). In total, 4,898,880 women, aged 40-74 years, who participated in the national breast cancer screening program in 2009-2010 were followed up to December 2018. Increased age showed a heterogeneous association with breast cancer (1-year hazard ratio (HR) = 0.92, 1.00 (reference), 1.03, and 1.03 in women with BI-RADS density category 1, 2, 3, and 4, respectively; P-heterogeneity < 0.001). More advanced age at menopause increased breast cancer risk in all BI-RADS categories. This was more prominent in women with BI-RADS density category 1 but less prominent in women in other BI-RADS categories (P-heterogeneity = 0.009). In postmenopausal women, a family history of breast cancer, body mass index ≥ 25 kg/m², and smoking showed a heterogeneous association with breast cancer across all BI-RADS categories. Other risk factors including age at menarche, menopause, hormone replacement therapy after menopause, oral contraceptive use, and alcohol consumption did not show a heterogeneous association with breast cancer across the BI-RADS categories. Several known risk factors of breast cancer had a heterogeneous effect on breast cancer development across breast density categories, especially in postmenopausal women.