Assessing quality standards of biomarker measurement in first‐trimester combined screening for preeclampsia in the Chinese population: A multicenter study

Introduction The first‐trimester combined screening test for preterm preeclampsia (preterm‐PE) has been implemented in Mainland China. This study aims, first, to evaluate the applicability of multiple of the median (MoM) models based on biomarkers developed and utilized in a European population for prospective preterm‐PE screening in Mainland China; second, to assess the criteria for biomarker adjustment; and third, to establish criteria for continuous quality assurance in the screening process. Material and Methods In this prospective multicenter cross‐sectional study, 22 066 singleton pregnancies undergoing preterm‐PE screening at 11 + 0 –13 + 6 weeks were recruited from six tertiary hospitals in Mainland China. Mean arterial pressure (MAP) and placental growth factor (PlGF) were measured and converted to their equivalent MoM values using Fetal Medicine Foundation MoMing models incorporated in commercial software. PlGF levels were also determined using immunoassays developed in China. MoM and log 10 MoM distributions in the initial screened subjects were assessed for (1) central tendency and dispersion and (2) whether biomarker MoM distributions needed to be recentered. Biomarker central tendency and temporal stability both before and after recentering were assessed using Cumulative Sum plots. Distribution central tendency was considered good if its median MoM was between 0.95 and 1.05 and acceptable if between 1.05 and 1.10. Results After excluding the initial 400 pregnancies from each center, all PlGF, but not all MAP MoM distributions, required recentering. Post‐recentering, the overall distribution median (95% confidence interval) MoM values for MAP and PlGF were 1.003 (1.001, 1.004) and 1.004 (0.996, 1.013), respectively. Conclusions Chinese centers performing combined PE screening should assess biomarker MoM distributions in their initial cases to ensure that they conform to the expected central tendencies assumed in the risk estimation models.