title: Autocorrelation and cross-correlation between hCGβ and PAPP-A in repeated sampling during first trimester of pregnancy.
abstract: BACKGROUND
  Theoretically, repeated sampling of free β-human chorionic gonadotropin (hCGβ) and pregnancy associated plasma protein-A (PAPP-A) in the first trimester of pregnancy might improve performance of risk assessment of trisomy 21 (T21). To assess the performance of a screening test involving repeated measures of biochemical markers, correlations between markers must be estimated. The aims of this study were to calculate the autocorrelation and cross-correlation between hCGβ and PAPP-A in the first trimester of pregnancy and to investigate the possible impact of gestational age at the first sample and time between sampling on the correlation.
  
  
  METHODS
  A prospective study was conducted including 3891 unaffected singleton pregnancies. Two measurements of hCGβ and PAPP-A were obtained during the first trimester in each pregnancy. Correlations between the four parameters, hCGβ first, hCGβ second, PAPP-A first and PAPP-A second, were estimated and presented in terms of Pearson's r coefficients. Furthermore, the correlation between paired samples as a function of time between samples was investigated.
  
  
  RESULTS
  The study demonstrated high correlation between first and second samples of hCGβ and PAPP-A with a correlation coefficient of 0.80 and 0.79, respectively. By contrast, the correlations between hCGβ and PAPP-A were low. In addition, the study demonstrated that the correlation between paired samples of hCGβ and PAPP-A decreases with earlier gestational age at the first sample and with increasing time between samples.
  
  
  CONCLUSIONS
  We have developed a parameter set in terms of correlations between biochemical markers, which can be incorporated into a T21 screening algorithm based on repeated measures within the first trimester.
authors.forename: Pernille
authors.initials: P
authors.lastname: Nørgaard
authors.forename: Dave
authors.initials: D
authors.lastname: Wright
authors.forename: Susan
authors.initials: S
authors.lastname: Ball
authors.forename: Paul
authors.initials: P
authors.lastname: Newell
authors.forename: Ida
authors.initials: I
authors.lastname: Kirkegaard
authors.forename: Olav Bjørn
authors.initials: OB
authors.lastname: Petersen
authors.forename: Niels
authors.initials: N
authors.lastname: Uldbjerg
authors.forename: Niels
authors.initials: N
authors.lastname: Tørring
authors.forename: Finn Stener
authors.initials: FS
authors.lastname: Jørgensen
authors.forename: Lennart
authors.initials: L
authors.lastname: Friis-Hansen
authors.forename: Charlotte
authors.initials: C
authors.lastname: Ekelund
authors.forename: Ann
authors.initials: A
authors.lastname: Tabor
authors.forename: Steen
authors.initials: S
authors.lastname: Sørensen
mesh_terms: D000293:Adolescent; D000328:Adult; D015415:Biomarkers / Q000097:blood; D018997:Chorionic Gonadotropin, beta Subunit, Human / Q000097:blood*; D005260:Female; D006801:Humans; D008875:Middle Aged; D011247:Pregnancy; D011261:Pregnancy Trimester, First / Q000097:blood*; D011266:Pregnancy-Associated Plasma Protein-A / Q000032:analysis*; D011446:Prospective Studies; D018570:Risk Assessment; D055815:Young Adult
chemical_list: D015415:Biomarkers; D018997:Chorionic Gonadotropin, beta Subunit, Human; D011266:Pregnancy-Associated Plasma Protein-A