The relationship between body mass index and breast cancer recurrence/progression and breast cancer-specific death

The aim of this study was to describe the nonlinear association between body mass index (BMI) and breast cancer outcomes and to determine whether BMI improves prediction of outcomes. A cohort of906 breast cancer patients diagnosed at Henry Ford Health System, Detroit (1985-1990) were studied. The median follow-up was 10 years. Multivariate logistic regression was used to model breast cancer recurrence/progression and breast cancer-specific death. Restricted cubic splines were used to model nonlinear effects. Receiver operator characteristic areas under the curves (ROC AUC) were used to evaluate prediction. BMI was nonlinearly associated with recurrence/progression and death (p= 0.0230 and 0.0101). Probability of outcomes increased with increase or decrease ofBMI away from 25. BMI splines were suggestive of improved prediction of death. The ROC AUCs for nested models with and without BMI were 0.8424 and 0.8331 (p= 0.08). I f causally associated, modifying patients BMI towards 25 may improve outcomes.

Relationship between Socio-Demographic Factors and Familial and Partner Pressures to Conceive in HIV-Positive Women in Ontario

This study examined the relationship between socio-demographic factors and family and partner pressure to conceive in women living with HIV in Ontario, Canada. A total of 490 women, aged 18-52 years were included in the study. The HIV Pregnancy Planning Questionnaire was used to collect data on socio-demographic, medical, and pressure variables. Multivariate logistic regression analysis suggest that increased age, years lived in Canada, and living in Toronto were associated with lower odds, and being married and having 0-1 lifetime births were associated with higher odds of family pressure to conceive. Increased age was associated with lower odds, and being married and living in Toronto were associated with higher odds of partner pressure to conceive. Findings suggest that socio-demographic factors influence the fertility decision-making process. Health care providers should consider socio-demographic factors along with medical factors when assisting women living with HIV and their partners to make informed reproductive decisions.