title: Competing risks model in screening for preeclampsia by maternal factors and biomarkers at 11-13 weeks gestation.
abstract: BACKGROUND
  Preeclampsia affects approximately 3% of all pregnancies and is a major cause of maternal and perinatal morbidity and death. In the last decade, extensive research has been devoted to early screening for preeclampsia with the aim of reducing the prevalence of the disease through pharmacologic intervention in the high-risk group starting from the first trimester of pregnancy.
  
  
  OBJECTIVE
  The purpose of this study was to develop a model for preeclampsia based on maternal demographic characteristics and medical history (maternal factors) and biomarkers.
  
  
  METHODS
  The data for this study were derived from prospective screening for adverse obstetric outcomes in women who attended for their routine first hospital visit at 11-13 weeks gestation in 2 maternity hospitals in England. We screened 35,948 singleton pregnancies that included 1058 pregnancies (2.9%) that experienced preeclampsia. Bayes theorem was used to combine the a priori risk from maternal factors with various combinations of uterine artery pulsatility index, mean arterial pressure, serum pregnancy-associated plasma protein-A, and placental growth factor multiple of the median values. Five-fold cross validation was used to assess the performance of screening for preeclampsia that delivered at <37 weeks gestation (preterm-preeclampsia) and ≥37 weeks gestation (term-preeclampsia) by models that combined maternal factors with individual biomarkers and their combination with screening by maternal factors alone.
  
  
  RESULTS
  In pregnancies that experienced preeclampsia, the values of uterine artery pulsatility index and mean arterial pressure were increased, and the values of serum pregnancy-associated plasma protein-A and placental growth factor were decreased. For all biomarkers, the deviation from normal was greater for early than late preeclampsia; therefore, the performance of screening was related inversely to the gestational age at which delivery became necessary for maternal and/or fetal indications. Combined screening by maternal factors, uterine artery pulsatility index, mean arterial pressure, and placental growth factor predicted 75% (95% confidence interval, 70-80%) of preterm-preeclampsia and 47% (95% confidence interval, 44-51%) of term-preeclampsia, at a false-positive rate of 10%; inclusion of pregnancy-associated plasma protein-A did not improve the performance of screening. Such detection rates are superior to the respective values of 49% (95% confidence interval, 43-55%) and 38% (34-41%) that were achieved by screening with maternal factors alone.
  
  
  CONCLUSIONS
  Combination of maternal factors and biomarkers provides effective first-trimester screening for preterm-preeclampsia.
authors: Harris Birthright Research Centre for Fetal Medicine, King's College, London, UK.
authors: Neil
authors: N
authors: O'Gorman
authors: Institute of Health Research, University of Exeter, Exeter, UK.
authors: David
authors: D
authors: Wright
authors: Harris Birthright Research Centre for Fetal Medicine, King's College, London, UK.
authors: Argyro
authors: A
authors: Syngelaki
authors: Harris Birthright Research Centre for Fetal Medicine, King's College, London, UK; Department of Fetal Medicine, Medway Maritime Hospital, Gillingham, UK.
authors: Ranjit
authors: R
authors: Akolekar
authors: Institute of Health Research, University of Exeter, Exeter, UK.
authors: Alan
authors: A
authors: Wright
authors: Harris Birthright Research Centre for Fetal Medicine, King's College, London, UK.
authors: Leona C
authors: LC
authors: Poon
authors: Harris Birthright Research Centre for Fetal Medicine, King's College, London, UK. Electronic address: kypros@fetalmedicine.com.
authors: Kypros H
authors: KH
authors: Nicolaides
mesh_terms: D000328:Adult; D062186:Arterial Pressure; D001499:Bayes Theorem; D015415:Biomarkers / Q000097:blood; D036861:Delivery, Obstetric; D005189:False Positive Reactions; D005260:Female; D005865:Gestational Age; D006801:Humans; D015233:Models, Statistical; D010298:Parity; D000072483:Placenta Growth Factor; D011225:Pre-Eclampsia / Q000097:blood / Q000175:diagnosis* / Q000503:physiopathology*; D011237:Predictive Value of Tests; D011247:Pregnancy; D011257:Pregnancy Proteins / Q000097:blood; D011261:Pregnancy Trimester, First / Q000097:blood / Q000502:physiology*; D011266:Pregnancy-Associated Plasma Protein-A / Q000378:metabolism; D011446:Prospective Studies; D011673:Pulsatile Flow; D018570:Risk Assessment; D012307:Risk Factors; D014463:Ultrasonography; D055988:Uterine Artery / Q000000981:diagnostic imaging / Q000503:physiopathology
chemical_list: D015415:Biomarkers; C000608036:PGF protein, human; D011257:Pregnancy Proteins; D000072483:Placenta Growth Factor; D011266:Pregnancy-Associated Plasma Protein-A
keywords: Bayes theorem; first trimester screening; mean arterial pressure; placental growth factor; preeclampsia; pregnancy-associated plasma protein-A; uterine artery