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We aim to establish a prediction model for pregnancy outcomes through a combinatorial analysis of circulating biomarkers and maternal characteristics to effectively identify pregnant women with higher risks of preeclampsia in the first and third trimesters within the Asian population. A total of two hundred and twelve pregnant women were screened for preeclampsia through a multicenter study conducted in four recruiting centers in Taiwan from 2017 to 2020. In addition, serum levels of sFlt-1/PlGF ratio, miR-181a, miR-210 and miR-223 were measured and transformed into multiples of the median. We thus further developed statistically validated algorithmic models by designing combinations of different maternal characteristics and biomarker levels. Through the performance of the training cohort (0.848 AUC, 0.73–0.96 95% CI, 80% sensitivity, 85% specificity, p < 0.001) and the validation cohort (0.852 AUC, 0.74–0.98 95% CI, 75% sensitivity, 87% specificity, p < 0.001) from one hundred and fifty-two women with a combination of miR-210, miR-181a and BMI, we established a preeclampsia prediction model for the first trimester. We successfully identified pregnant women with higher risks of preeclampsia in the first and third trimesters in the Asian population using the established prediction models that utilized combinatorial analysis of circulating biomarkers and maternal characteristics. [ABSTRACT FROM AUTHOR]

Breast cancer is the most common cancer among women in China; however, a routine screening programme is currently not available. The aim of this study was to develop a novel model to estimate the effectiveness and cost-effectiveness of several screening strategies for women living in urban areas. We developed a state-transition natural history model of breast cancer and validated the model with multiple outcomes for Chinese women living in urban areas. A total of 23 screening scenarios were considered with different screening techniques, ages, and frequencies. We evaluated the reduction of breast cancer mortality for each screening scenario compared with no screening. By integrating population-specific cost and utility scores, we calculated the incremental cost-effectiveness ratio (ICER) in terms of the cost per quality-adjusted life-year gained. In the natural history model, the breast cancer incidence rate was estimated as 36·0 cases per 100 000 women and breast cancer mortality rate as 6·8 deaths per 100 000 women, which approximated reported rates from national cancer registries (incidence 34·9–36·5 cases per 100 000 women and 6·8–7·0 deaths per 100 000 women). Meanwhile, the modelled stage distribution and life expectancy were substantially similar to reported values. Compared with no screening, the breast cancer mortality of all screening scenarios decreased by 4·1–53·6%. The ICERs of 16 of the 23 scenarios was lower than the triple of the GDP per capita of China in 2018 (193 932 Chinese Yuan), indicating cost-effectiveness. At the national level, the biennial series-parallel strategy (ultrasound, followed by the mammography when suspected for women aged 40–44 years, and ultrasound combined with mammography for women aged 45–69 years) was the most cost-effective strategy, while the optimal screening interval differed with economic development at the provincial level. We developed a well calibrated natural history model of breast cancer for Chinese women living in urban areas. Generally, breast cancer screening is cost-effective in urban China. The biennial series-parallel strategy is recommended at the national level, but at the provincial level, the optimal strategy should be determined by balancing health gains and resources. National Natural Science Foundation of China (81773521 and 81402740) and National Health Commission of the People's Republic of China. [ABSTRACT FROM AUTHOR]