Interpretation
Our finding and conclusions are in
agreement with a recent study by Maser Zumaeta and colleagues, which has
concluded that PAPP-A is the preferred marker for trisomy 21 screening,
and that replacing PAPP-A with PlGF increases the false positive and
screen positive rates.11Mazer Zumaeta A, Wright A, Syngelaki A,
Maritsa VA, Bardani E, et al. Screening for trisomies at 11-13 weeks’
gestation: use of PAPP-A, PlGF or both. Ultrasound Obstet Gynecol 2020
doi: 10.1002/uog.22140 In a parallel study the same authors have
reported that PlGF is the preferred biochemical marker for preeclampsia
screening at 11-13 weeks of gestation, and that using PAPP-A instead of
PlGF reduces preeclampsia screening sensitivity.22Mazer Zumaeta
A, Wright A, Syngelaki A, Maritsa VA, Da Silva AB et al. Screening for
pre-eclampsia at 11-13 weeks’ gestation: use of pregnancy-associated
plasma protein-A, placental growth factor or both. Ultrasound Obstet
Gynecol 2020 doi: 10.1002/uog.22093. Our data and analysis indicate
that previous studies reporting increased or similar levels of PlGF
relative to unaffected pregnancies, as opposed to reduced levels of PlGF
in trisomy 21, were probably due to the impact of case-selection,
potential sample degradation or underlying differences between earlier
PlGF assays and current assays. Our earlier study indicated that PlGF in
stored samples remained stable for at least 3 years 33Law LW,
Sahota DS, Chan LW, Chen M, Lau TK, et al. Effect of long-term storage
on placental growth factor and fms-like tyrosine kinase 1 measurements
in samples from pregnant women.J Matern Fetal Neonatal Med
2010;23:1475-80, however its stability when serum samples were stored
for longer periods remained unknown. It has been shown that duration of
storage time accounts for up to 35% of plasma protein concentration
variation in frozen biobank samples of healthy women. 44Enroth
S, Hallmans G, Grankvist K, Gyllensten U. Effects of Long-Term Storage
Time and Original Sampling Month on Biobank Plasma Protein
Concentrations. EBioMedicine 2016;12:309-14 Sensitivity of reported
PlGF concentrations to specific PlGF isoforms has also been reported7, 55Nucci
M, Poon LC, Demirdjian G, Darbouret B, Nicolaides KH. Maternal serum
placental growth factor (PlGF) isoforms 1 and 2 at 11-13 weeks’
gestation in normal and pathological pregnancies. Fetal Diagn Ther.
2014;36:106-16 Nucci et al. reported that the PlGF-2 isoform of PlGF
is more abundant than the PlGF-1 isoform throughout pregnancy,24 whilst Cheng et al. reported that current assays
had cross reactivity to PlGF-2 ranging from 10 to 21%, whilst PlGF-1
isomer recovery ranged from 38 to 60%.7
In the vast majority of cases adding PlGF or replacing PAPP-A with PlGF
would not have changed whether women were screened high risk (≥1:250) or
low risk (<1:250) for trisomy 21. Women whose status did
change, particularly when PlGF was added to the combined test, were
those in whom PAPP-A and PlGF MoMs were discordant and with an atypical
screening marker pattern for trisomy 21, either PAPP-A MoM was reduced
(<1 MoM) and PlGF MoM was increased (>1 MoM) or
PlGF MoM was reduced and PAPP-A MoM was increased. Of the 29 women
having a trisomy 21 affected pregnancy, 24 were screened as high risk by
the combined test, the combined test plus PlGF and after replacing
PAPP-A by PlGF. Each test identified 2 of the 5 remaining trisomy 21
affected pregnancies, and hence there was effectively a zero sum gain.
One alternative would be to use non-probability based pattern
recognition such as machine learning based on multi-layer neural
networks to see if such an approach would allow increased flexibility
and recognition of atypical trisomy 21 screening marker patterns.
66Koivu A, Korpimäki T, Kivelä P, Pahikkala T, Sairanen M.
Evaluation of machine learning algorithms for improved risk assessment
for Down’s syndrome. Comput Biol Med 2018;98:1-7
The current screening model for trisomy 21 is based on probability based
pattern recognition, namely that trisomy 21 is associated with
increasing maternal age, increased fetal NT and free β-hCG MoMs, reduced
levels of PAPP-A and PlGF MoMs relative to unaffected fetuses. Our
current and earlier study, as well as studies reporting reduced levels
of PlGF in trisomy 21 affected pregnancies all indicated significant and
strong correlations between PlGF and PAPP-MoMs. This is in contrast to
other screening markers used to estimate risk for trisomy 21 as the
inter-marker correlations are negligible, indicating that each marker is
providing additional as opposed to effectively the same information when
used to estimate risks. Inclusion of an additional biomarker which is
significantly correlated with an existing marker is thus, as our study
has demonstrated, unlikely to provide additional screening benefit.
Replacing PAPP-A with PlGF or adding PlGF would only increase costs as
the cost of the PlGF assay is higher than that of the PAPP-A assay.
Our study highlights also the difference in determining screening
performance based on modelling versus that observed empirically when the
test is used on a day to day basis. The former presumes collected data
is in full agreement with the risk estimation model assumptions. Our
earlier case-control study indicated that adding PlGF to the combined
test would be expected to achieve a detection rate of 96% for the same
5% false positive rate based on modelling even though the population in
our earlier study was 2 years younger than in our current study.17 Modelling, whilst useful remains only as a guide,
and as our data indicate, models reporting expected detection rates in
future should incorporate a random percentage of cases having
measurement discordance between included screening markers.