Literature DB >> 29536574

Comparison of diagnostic accuracy of early screening for pre-eclampsia by NICE guidelines and a method combining maternal factors and biomarkers: results of SPREE.

M Y Tan1,2, D Wright3, A Syngelaki1, R Akolekar1,4, S Cicero5, D Janga6, M Singh7, E Greco8, A Wright3, K Maclagan9, L C Poon1,10, K H Nicolaides1,2.   

Abstract

OBJECTIVE: To test the hypothesis that the performance of first-trimester screening for pre-eclampsia (PE) by a method that uses Bayes' theorem to combine maternal factors with biomarkers is superior to that defined by current National Institute for Health and Care Excellence (NICE) guidelines.
METHODS: This was a prospective multicenter study (screening program for pre-eclampsia (SPREE)) in seven National Health Service maternity hospitals in England, of women recruited between April and December 2016. Singleton pregnancies at 11-13 weeks' gestation had recording of maternal characteristics and medical history and measurements of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI), serum placental growth factor (PlGF) and serum pregnancy-associated plasma protein-A (PAPP-A). The performance of screening for PE by the Bayes' theorem-based method was compared with that of the NICE method. Primary comparison was detection rate (DR) using NICE method vs mini-combined test (maternal factors, MAP and PAPP-A) in the prediction of PE at any gestational age (all-PE) for the same screen-positive rate determined by the NICE method. Key secondary comparisons were DR of screening recommended by the NICE guidelines vs three Bayes' theorem-based methods (maternal factors, MAP and PAPP-A; maternal factors, MAP and PlGF; and maternal factors, MAP, UtA-PI and PlGF) in the prediction of preterm PE, defined as that requiring delivery < 37 weeks.
RESULTS: All-PE developed in 473 (2.8%) of the 16 747 pregnancies and preterm PE developed in 142 (0.8%). The screen-positive rate by the NICE method was 10.3% and the DR for all-PE was 30.4% and for preterm PE it was 40.8%. Compliance with the NICE recommendation that women at high risk for PE should be treated with aspirin from the first trimester to the end of pregnancy was only 23%. The DR of the mini-combined test for all-PE was 42.5%, which was superior to that of the NICE method by 12.1% (95% CI, 7.9-16.2%). In screening for preterm PE by a combination of maternal factors, MAP and PlGF, the DR was 69.0%, which was superior to that of the NICE method by 28.2% (95% CI, 19.4-37.0%) and with the addition of UtA-PI the DR was 82.4%, which was higher than that of the NICE method by 41.6% (95% CI, 33.2-49.9%).
CONCLUSIONS: The performance of screening for PE as currently recommended by NICE guidelines is poor and compliance with these guidelines is low. The performance of screening is substantially improved by a method combining maternal factors with biomarkers.
© 2018 Crown copyright. Ultrasound in Obstetrics & Gynecology © 2018 ISUOG. © 2018 Crown copyright. Ultrasound in Obstetrics & Gynecology © 2018 ISUOG.

Entities:  

Keywords:  Bayes' theorem; NICE guidelines; aspirin; diagnostic accuracy; first-trimester screening; pre-eclampsia

Mesh:

Substances:

Year:  2018        PMID: 29536574     DOI: 10.1002/uog.19039

Source DB:  PubMed          Journal:  Ultrasound Obstet Gynecol        ISSN: 0960-7692            Impact factor:   7.299


  31 in total

1.  The International Federation of Gynecology and Obstetrics (FIGO) initiative on pre-eclampsia: A pragmatic guide for first-trimester screening and prevention.

Authors:  Liona C Poon; Andrew Shennan; Jonathan A Hyett; Anil Kapur; Eran Hadar; Hema Divakar; Fionnuala McAuliffe; Fabricio da Silva Costa; Peter von Dadelszen; Harold David McIntyre; Anne B Kihara; Gian Carlo Di Renzo; Roberto Romero; Mary D'Alton; Vincenzo Berghella; Kypros H Nicolaides; Moshe Hod
Journal:  Int J Gynaecol Obstet       Date:  2019-05       Impact factor: 3.561

Review 2.  Comparative risks and predictors of preeclamptic pregnancy in the Eastern, Western and developing world.

Authors:  Ning Zhang; Jing Tan; HaiFeng Yang; Raouf A Khalil
Journal:  Biochem Pharmacol       Date:  2020-09-25       Impact factor: 5.858

3.  Prediction of preeclampsia throughout gestation with maternal characteristics and biophysical and biochemical markers: a longitudinal study.

Authors:  Adi L Tarca; Andreea Taran; Roberto Romero; Eunjung Jung; Carmen Paredes; Gaurav Bhatti; Corina Ghita; Tinnakorn Chaiworapongsa; Nandor Gabor Than; Chaur-Dong Hsu
Journal:  Am J Obstet Gynecol       Date:  2021-04-16       Impact factor: 8.661

4.  Placental growth factor testing to assess women with suspected pre-eclampsia: a multicentre, pragmatic, stepped-wedge cluster-randomised controlled trial.

Authors:  Kate E Duhig; Jenny Myers; Paul T Seed; Jenie Sparkes; Jessica Lowe; Rachael M Hunter; Andrew H Shennan; Lucy C Chappell
Journal:  Lancet       Date:  2019-04-01       Impact factor: 79.321

Review 5.  Evidence-Based Prevention of Preeclampsia: Commonly Asked Questions in Clinical Practice.

Authors:  Dagmar Wertaschnigg; Maya Reddy; Ben W J Mol; Fabricio da Silva Costa; Daniel L Rolnik
Journal:  J Pregnancy       Date:  2019-08-01

Review 6.  Prenatal screening for pre-eclampsia: Frequently asked questions.

Authors:  Dagmar Wertaschnigg; Maya Reddy; Ben W J Mol; Daniel L Rolnik; Fabricio da Silva Costa
Journal:  Aust N Z J Obstet Gynaecol       Date:  2019-05-22       Impact factor: 2.100

7.  Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study.

Authors:  Jing Zhang; Luhao Han; Wei Li; Qiaobin Chen; Jie Lei; Min Long; Weibin Yang; Wenya Li; Lizhen Zeng; Sifan Zeng
Journal:  BMC Pregnancy Childbirth       Date:  2019-08-19       Impact factor: 3.007

8.  Placental growth factor testing for suspected pre-eclampsia: a cost-effectiveness analysis.

Authors:  K E Duhig; P T Seed; J E Myers; R Bahl; G Bambridge; S Barnfield; J Ficquet; J C Girling; A Khalil; A H Shennan; L C Chappell; R M Hunter
Journal:  BJOG       Date:  2019-07-17       Impact factor: 6.531

9.  Prediction of Preeclampsia and Intrauterine Growth Restriction: Development of Machine Learning Models on a Prospective Cohort.

Authors:  Herdiantri Sufriyana; Yu-Wei Wu; Emily Chia-Yu Su
Journal:  JMIR Med Inform       Date:  2020-05-18

10.  Samrakshan: An Indian Radiological and Imaging Association program to reduce perinatal mortality in India.

Authors:  Rijo M Choorakuttil; Hemant Patel; Rajalingam Bavaharan; Palanisamy Devarajan; Saneej Kanhirat; Ramesh S Shenoy; Om P Tiwari; Rajendra K Sodani; Lalit K Sharma; Praveen K Nirmalan
Journal:  Indian J Radiol Imaging       Date:  2019-12-31
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