Piya Chaemsaithong1, Ritsuko K Pooh2, Mingming Zheng3, Runmei Ma4, Noppadol Chaiyasit5, Mayumi Tokunaka6, Steven W Shaw7, Suresh Seshadri8, Mahesh Choolani9, Tuangsit Wataganara10, George S H Yeo11, Alan Wright12, Wing Cheong Leung13, Akihiko Sekizawa6, Yali Hu3, Katsuhiko Naruse14, Shigeru Saito15, Daljit Sahota1, Tak Yeung Leung1, Liona C Poon16. 1. Chinese University of Hong Kong, Hong Kong SAR, China. 2. CRIFM Clinical Research Institute of Fetal Medicine, Osaka, Japan. 3. Nanjing Drum Tower Hospital, Nanjing, China. 4. First Affiliated Hospital of Kunming Medical University, Kunming, China. 5. King Chulalongkorn Memorial Hospital, Bangkok, Thailand. 6. Showa University Hospital, Tokyo, Japan. 7. Taipei Chang Gung Memorial Hospital, Taipei, Taiwan. 8. Mediscan, Chennai, India. 9. National University Hospital, Singapore. 10. Faculty of Medicine, Siriraj Hospital, Bangkok, Thailand. 11. KK Women's and Children's Hospital, Singapore. 12. University of Exeter, Exeter, UK. 13. Kwong Wah Hospital, Hong Kong SAR, China. 14. St Barnabas' Hospital, Osaka, Japan. 15. University of Toyama University Hospital, Toyama, Japan. 16. Chinese University of Hong Kong, Hong Kong SAR, China. Electronic address: liona.poon@cuhk.edu.hk.
Abstract
BACKGROUND: The administration of aspirin <16 weeks gestation to women who are at high risk for preeclampsia has been shown to reduce the rate of preterm preeclampsia by 65%. The traditional approach to identify such women who are at risk is based on risk factors from maternal characteristics, obstetrics, and medical history as recommended by the American College of Obstetricians and Gynecologists and the National Institute for Health and Care Excellence. An alternative approach to screening for preeclampsia has been developed by the Fetal Medicine Foundation. This approach allows the estimation of patient-specific risks of preeclampsia that requires delivery before a specified gestational age with the use of Bayes theorem-based model. OBJECTIVE: The purpose of this study was to examine the diagnostic accuracy of the Fetal Medicine Foundation Bayes theorem-based model, the American College of Obstetricians and Gynecologists, and the National Institute for Health and Care Excellence recommendations for the prediction of preterm preeclampsia at 11-13+6 weeks gestation in a large Asian population STUDY DESIGN: This was a prospective, nonintervention, multicenter study in 10,935 singleton pregnancies at 11-13+6 weeks gestation in 11 recruiting centers across 7 regions in Asia between December 2016 and June 2018. Maternal characteristics and medical, obstetric, and drug history were recorded. Mean arterial pressure and uterine artery pulsatility indices were measured according to standardized protocols. Maternal serum placental growth factor concentrations were measured by automated analyzers. The measured values of mean arterial pressure, uterine artery pulsatility index, and placental growth factor were converted into multiples of the median. The Fetal Medicine Foundation Bayes theorem-based model was used for the calculation of patient-specific risk of preeclampsia at <37 weeks gestation (preterm preeclampsia) and at any gestation (all preeclampsia) in each participant. The performance of screening for preterm preeclampsia and all preeclampsia by a combination of maternal factors, mean arterial pressure, uterine artery pulsatility index, and placental growth factor (triple test) was evaluated with the adjustment of aspirin use. We examined the predictive performance of the model by the use of receiver operating characteristic curve and calibration by measurements of calibration slope and calibration in the large. The detection rate of screening by the Fetal Medicine Foundation Bayes theorem-based model was compared with the model that was derived from the application of American College of Obstetricians and Gynecologists and National Institute for Health and Care Excellence recommendations. RESULTS: There were 224 women (2.05%) who experienced preeclampsia, which included 73 cases (0.67%) of preterm preeclampsia. In pregnancies with preterm preeclampsia, the mean multiples of the median values of mean arterial pressure and uterine artery pulsatility index were significantly higher (mean arterial pressure, 1.099 vs 1.008 [P<.001]; uterine artery pulsatility index, 1.188 vs 1.063[P=.006]), and the mean placental growth factor multiples of the median was significantly lower (0.760 vs 1.100 [P<.001]) than in women without preeclampsia. The Fetal Medicine Foundation triple test achieved detection rates of 48.2%, 64.0%, 71.8%, and 75.8% at 5%, 10%, 15%, and 20% fixed false-positive rates, respectively, for the prediction of preterm preeclampsia. These were comparable with those of previously published data from the Fetal Medicine Foundation study. Screening that used the American College of Obstetricians and Gynecologists recommendations achieved detection rate of 54.6% at 20.4% false-positive rate. The detection rate with the use of National Institute for Health and Care Excellence guideline was 26.3% at 5.5% false-positive rate. CONCLUSION: Based on a large number of women, this study has demonstrated that the Fetal Medicine Foundation Bayes theorem-based model is effective in the prediction of preterm preeclampsia in an Asian population and that this method of screening is superior to the approach recommended by American College of Obstetricians and Gynecologists and the National Institute for Health and Care Excellence. We have also shown that the Fetal Medicine Foundation prediction model can be implemented as part of routine prenatal care through the use of the existing infrastructure of routine prenatal care.
BACKGROUND: The administration of aspirin <16 weeks gestation to women who are at high risk for preeclampsia has been shown to reduce the rate of preterm preeclampsia by 65%. The traditional approach to identify such women who are at risk is based on risk factors from maternal characteristics, obstetrics, and medical history as recommended by the American College of Obstetricians and Gynecologists and the National Institute for Health and Care Excellence. An alternative approach to screening for preeclampsia has been developed by the Fetal Medicine Foundation. This approach allows the estimation of patient-specific risks of preeclampsia that requires delivery before a specified gestational age with the use of Bayes theorem-based model. OBJECTIVE: The purpose of this study was to examine the diagnostic accuracy of the Fetal Medicine Foundation Bayes theorem-based model, the American College of Obstetricians and Gynecologists, and the National Institute for Health and Care Excellence recommendations for the prediction of preterm preeclampsia at 11-13+6 weeks gestation in a large Asian population STUDY DESIGN: This was a prospective, nonintervention, multicenter study in 10,935 singleton pregnancies at 11-13+6 weeks gestation in 11 recruiting centers across 7 regions in Asia between December 2016 and June 2018. Maternal characteristics and medical, obstetric, and drug history were recorded. Mean arterial pressure and uterine artery pulsatility indices were measured according to standardized protocols. Maternal serum placental growth factor concentrations were measured by automated analyzers. The measured values of mean arterial pressure, uterine artery pulsatility index, and placental growth factor were converted into multiples of the median. The Fetal Medicine Foundation Bayes theorem-based model was used for the calculation of patient-specific risk of preeclampsia at <37 weeks gestation (preterm preeclampsia) and at any gestation (all preeclampsia) in each participant. The performance of screening for preterm preeclampsia and all preeclampsia by a combination of maternal factors, mean arterial pressure, uterine artery pulsatility index, and placental growth factor (triple test) was evaluated with the adjustment of aspirin use. We examined the predictive performance of the model by the use of receiver operating characteristic curve and calibration by measurements of calibration slope and calibration in the large. The detection rate of screening by the Fetal Medicine Foundation Bayes theorem-based model was compared with the model that was derived from the application of American College of Obstetricians and Gynecologists and National Institute for Health and Care Excellence recommendations. RESULTS: There were 224 women (2.05%) who experienced preeclampsia, which included 73 cases (0.67%) of preterm preeclampsia. In pregnancies with preterm preeclampsia, the mean multiples of the median values of mean arterial pressure and uterine artery pulsatility index were significantly higher (mean arterial pressure, 1.099 vs 1.008 [P<.001]; uterine artery pulsatility index, 1.188 vs 1.063[P=.006]), and the mean placental growth factor multiples of the median was significantly lower (0.760 vs 1.100 [P<.001]) than in women without preeclampsia. The Fetal Medicine Foundation triple test achieved detection rates of 48.2%, 64.0%, 71.8%, and 75.8% at 5%, 10%, 15%, and 20% fixed false-positive rates, respectively, for the prediction of preterm preeclampsia. These were comparable with those of previously published data from the Fetal Medicine Foundation study. Screening that used the American College of Obstetricians and Gynecologists recommendations achieved detection rate of 54.6% at 20.4% false-positive rate. The detection rate with the use of National Institute for Health and Care Excellence guideline was 26.3% at 5.5% false-positive rate. CONCLUSION: Based on a large number of women, this study has demonstrated that the Fetal Medicine Foundation Bayes theorem-based model is effective in the prediction of preterm preeclampsia in an Asian population and that this method of screening is superior to the approach recommended by American College of Obstetricians and Gynecologists and the National Institute for Health and Care Excellence. We have also shown that the Fetal Medicine Foundation prediction model can be implemented as part of routine prenatal care through the use of the existing infrastructure of routine prenatal care.
Keywords:
American College of Obstetricians and Gynecologists (ACOG); Asian population; Bayes theorem; Fetal Medicine Foundation (FMF); MAP; National Institute for Health and Care Excellence (NICE); UtA-PI; aspirin; biomarker; detection rate; false-positive rate; hypertension; multiples of the median (MoM); placental growth factor (PlGF); prediction model; preeclampsia; pulsatility index; screening; validation
Authors: Seung Mi Lee; Yonghyun Nam; Eun Saem Choi; Young Mi Jung; Vivek Sriram; Jacob S Leiby; Ja Nam Koo; Ig Hwan Oh; Byoung Jae Kim; Sun Min Kim; Sang Youn Kim; Gyoung Min Kim; Sae Kyung Joo; Sue Shin; Errol R Norwitz; Chan-Wook Park; Jong Kwan Jun; Won Kim; Dokyoon Kim; Joong Shin Park Journal: Sci Rep Date: 2022-09-22 Impact factor: 4.996
Authors: Max Mönckeberg; Valentina Arias; Rosario Fuenzalida; Santiago Álvarez; Victoria Toro; Andrés Calvo; Juan P Kusanovic; Lara J Monteiro; Manuel Schepeler; Jyh K Nien; Jaime Martinez; Sebastián E Illanes Journal: Diagnostics (Basel) Date: 2020-03-26