Comparison with results of previous studies
In a series of previous first and second trimester studies for the
prediction of stillbirth we highlighted that the causes of this adverse
event are heterogeneous and that the focus of research should be
placental dysfunction related stillbirths because they are relatively
common and to a great extent potentially
preventable17-22. However, a systematic review of 69
previous systematic reviews which aimed to identify variables that could
be relevant to the development of a clinical prediction model for
stillbirth treated this adverse event as a homogeneous
condition.23 The study reported that no marker had
useful screening performance, but maternal age, body mass index and
history of prior adverse pregnancy outcomes had a more convincing
association than the best performing tests, which were
pregnancy-associated plasma protein-A (PAPP-A), placental growth factor
(PlGF) and UtA-PI.23 Such types of publications that
do not recognize the fact that the causes of stillbirth are
heterogeneous could not possibly advance the development of strategies
for prediction and prevention of stillbirth.
The same group of authors attempted to externally validate previously
published prediction models for stillbirth using individual participant
data (IPD) meta-analysis from a heterogeneous group of 19 datasets24. A literature search identified 40 stillbirth
models, but they could only validate three of these models due to lack
of availability of the necessary predictors in their dataset or the
model equations in the previous publications; surprisingly for such a
study there was no attempt to contact the authors of the models to
request details on the equations. The authors reported that the three
models showed poor and uncertain predictive performance in their data,
they had limited clinical utility and that further research is needed to
identify stronger prognostic factors and develop more robust prediction
models 33. However, these conclusions are misleading
and can have a potential adverse impact on clinical practice and future
research, because first, two of the three models they evaluated were
based on maternal risk factors only and they overlooked many prediction
models based on a combination of maternal risk factors and first or
second trimester biomarkers, second, the heterogeneous datasets used for
their IPD meta-analysis were not derived from prospective screening for
stillbirth and were therefore inadequate for assessing models derived
from prospective examination of patients, and third, the authors
examined the value of the reported models for prediction of all
stillbirths and overlooked the fact that the original publications
highlighted that the models provided good prediction of placental
dysfunction related stillbirth, particularly those occurring preterm,
rather than prediction of all stillbirths.
In our study we have focussed on placental dysfunction related
stillbirth, prospectively recorded data from the maternal history and
biomarkers shown over the last few decades to be associated with the
birth of SGA neonates, developed and validated a model for prediction of
SGA and demonstrated that such model can effectively predict a high
proportion of stillbirths, especially those that occur preterm. We have
previously reported the increased risk for SGA fetuses / neonates is
provided by lower maternal weight and height, black, South and East
Asian racial origin, medical history of chronic hypertension, diabetes
mellitus and systemic lupus erythematosus or antiphospholipid syndrome,
conception by in vitro fertilization or ovulation induction and
smoking.4 For
parous women variables from the last pregnancy that increased the risk
for SGA were history of preeclampsia or stillbirth, decreasing birth
weight z-score and decreasing gestational age at delivery of the last
pregnancy and inter-pregnancy interval <0.5 years.4