A “preeclampsia screening” metric combining statistical methods plus certain biomarkers improved detection of preeclampsia compared with the standard of care in the United Kingdom, researchers found.
Combining certain maternal risk factors with biomarkers, such as mean arterial pressure, uterine artery pulsatility index, serum placental growth factor, and serum pregnancy-associated plasma protein-A, to be able to detect preeclampsia at any point during pregnancy better than current National Institute for Health and Care Excellence (NICE) guidelines in the U.K., reported M.Y. Tan, MD, of King’s College Hospital in London, and colleagues.
Writing in Ultrasound in Obstetrics and Gynecology, the authors said that an improved metric could potentially help to identify which women at risk of preeclampsia would most benefit from prophylactic use of aspirin.
But the researchers pointed out the weaknesses of the current NICE guidelines, which consider women at “high risk” of developing preeclampsia if they have one “major” factor (history of hypertensive disease in previous pregnancy, chronic kidney disease, autoimmune disease, diabetes mellitus, or chronic hypertension) or two “moderate” factors (first pregnancy at age 40 or over, an interpregnancy interval of more than 10 years, bond-mass index of over 35, or family history of preeclampsia).
The team therefore proposed an alternative: a Bayes’ theorem-based method that combined maternal risk factors with certain biomarkers. To test this hypothesis, the researchers performed a prospective multicenter cohort study in seven National Health Service (NHS) maternity hospitals in England.
Participants were women who were older than age 18 with a singleton pregnancy and a live fetus at the 11-13 week ultrasound. The women were tested using the NICE method compared with the “mini-combined test,” using the Bayes’ theorem-based method to combine maternal factors, mean arterial pressure, and serum pregnancy-associated protein-A.
Overall, data was available on a total of 16,747 participants. Of these, preeclampsia developed in 473 pregnancies, 142 of which had preterm preeclampsia.
The screen-positive rates for the NICE method were 10.3%, the authors said, while the detection rate for all preeclampsia was 30.4% (95% CI 26.3-34.6%). However, using the Bayes’ theorem-based method, the detection rate of all preeclampsia was 42.5%, (95% CI 38.0-46.8%).
A total of 256 patients took aspirin who were screen-positive by the NICE method and the mini-combined test, 144 patients who were screen-positive by the NICE method and screen negative by the mini-combined test, and 48 patients who were screen-negative for both tests.
After the researchers adjusted for the effect of aspirin, the detection rate of the NICE method was 31.5% (95% CI 27.3-35.7%) and the Bayes’ theorem-based method was 42.8% (95% CI 38.3-47.2%).
Secondary outcomes found similar results when comparing the two methods for detecting preterm preeclampsia, with screen-positive rates of 28.2% with the NICE method compared with 69.0% for the Bayes’ theorem mini-test. When the uterine pulsatility index, another biomarker, was added, the detection rate increased to 82.4%.
The authors noted that the combined test is available on the Fetal Medicine Foundation site as a risk calculator and an app.
One of the co-authors, Liona Poon, MD, also of King’s College, said in a statement that the results “provide definitive proof to support risk-based screening for preterm pre-eclampsia using various biomarkers. It is now time to revise the professional guidelines and to move away from using a checklist-based method for screening.”
This study was supported by grants from the U.K. government.
Reagents and equipment for the measurement of serum placental growth factor were provided free of charge by PerkinElmer Life and Analytical Sciences and Thermo Fisher Scientific.