Performance of a risk score for predicting preterm
pre-eclampsia
Ulla Sovio
Cambridge University
The Rosie Hospital
Robinson Way
Cambridge
Email: us253@medschl.cam.ac.uk
Brunelli et al (BJOG 2020) evaluated a previously validated maternal
history -based risk score in a multicentric retrospective cohort from
Italy. The risk score discriminated poorly in this study (AUC=0.659
[95% CI 0.579-0.726]) but it discriminated well in the Pregnancy
Outcome Prediction (POP) study (AUC=0.846 [95% CI 0.787-0.906])
(Sovio et al, BJOG 2019;126:963-970), although the proportion of women
who developed preterm pre-eclampsia was similar in both studies (1.0%
and 0.7%, respectively). What could be the possible reasons for these
differences and what should be the next steps for evaluating such risk scores?
The prevalence of the maternal risk factors that constitute the risk
score was very low in this study. Chronic hypertension has a
major contribution, i.e. it strongly predicts (superimposed) preterm
pre-eclampsia. Only 0.5% of all the women in the study and 15% of the cases had
chronic hypertension, whereas in the POP study, the prevalences were 5%
and 35%, respectively (Sovio et al, Hypertension 2017;69(4):731-738).
An analysis of the SCOPE study (Myers, Pregnancy Hypertension
2019;17:S21) illustrated that the performance of the risk score was
similarly poor in a healthy nulliparous population which excluded all
women with chronic hypertension (AUC=0.661 [95% CI 0.596-0.725]).
This is not surprising.
In this study from Italy, it was not clear how representative the cohort was of the source population. In this regard,
comparisons between recruited women and eligible non-recruited women
would help in assessing selection bias, but these are not always possible due to limitations in data or ethical approvals. Misclassification may also
contribute to the poor performance of the risk score. In the POP study, pre-eclampsia was
ascertained through a careful review of case records and linkage to
electronic databases (Sovio et al, 2017). In the study from Italy, electronic
data were used as a basis of defining pre-eclampsia, and data quality issues should always be considered and discussed. Moreover, measurement error or misreporting of risk factors
or aspirin use could have increased random error or
bias in the risk score.
Future evaluations of the risk score should be performed
in datasets representative of the underlying population in terms of
prior maternal risk. Only the women undergoing interventions which may
alter the risk of preterm preeclampsia should be excluded. The risk
score has already been validated against the model for predicted
gestational age at preeclampsia (PGAPE) in nulliparous women (Sovio et
al, 2019; Myers, 2019). Brunelli et al (2020) did not attempt to
validate the risk score against PGAPE but instead compared it with the
full FMF algorithm, and the latter performed better. The need for
additional measurements to those included in the risk score was
expected, given the low prevalence of prior maternal risk factors
(Myers, 2019).
A suggested scoring for maternal risk has been published for parous
women (Sovio et al, 2019). Evaluation of the risk score and validation
against PGAPE in parous women is now needed since this could not be done
in the POP study or in the SCOPE study.
Disclosures: Dr. Sovio reports grants from NIHR Cambridge
Biomedical Research Centre, during the conduct of the study. In
addition, Dr. Sovio has a patent application for a novel predictive test
for fetal growth restriction (FGR) pending. A completed disclosure of
interest form is available to view online as supporting information.