TY - JOUR
T1 - External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis
T2 - the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol
AU - IPPIC Collaborative Network
AU - Allotey, John
AU - Snell, Kym I E
AU - Chan, Claire
AU - Hooper, Richard
AU - Dodds, Julie
AU - Rogozinska, Ewelina
AU - Khan, Khalid S
AU - Poston, Lucilla
AU - Kenny, Louise
AU - Myers, Jenny
AU - Thilaganathan, Basky
AU - Chappell, Lucy
AU - Mol, Ben W
AU - Von Dadelszen, Peter
AU - Ahmed, Asif
AU - Green, Marcus
AU - Poon, Liona
AU - Khalil, Asma
AU - Moons, Karel G M
AU - Riley, Richard D
AU - Thangaratinam, Shakila
PY - 2017
Y1 - 2017
N2 - Background: Pre-eclampsia, a condition with raised blood pressure and proteinuria is associated with an increased risk of maternal and offspring mortality and morbidity. Early identification of mothers at risk is needed to target management.Methods/design: We aim to systematically review the existing literature to identify prediction models for pre-eclampsia. We have established the International Prediction of Pregnancy Complication Network (IPPIC), made up of 72 researchers from 21 countries who have carried out relevant primary studies or have access to existing registry databases, and collectively possess data from more than two million patients. We will use the individual participant data (IPD) from these studies to externally validate these existing prediction models and summarise model performance across studies using random-effects meta-analysis for any, late (after 34 weeks) and early (before 34 weeks) onset pre-eclampsia. If none of the models perform well, we will recalibrate (update), or develop and validate new prediction models using the IPD. We will assess the differential accuracy of the models in various settings and subgroups according to the risk status. We will also validate or develop prediction models based on clinical characteristics only; clinical and biochemical markers; clinical and ultrasound parameters; and clinical, biochemical and ultrasound tests.Discussion: Numerous systematic reviews with aggregate data meta-analysis have evaluated various risk factors separately or in combination for predicting pre-eclampsia, but these are affected by many limitations. Our large-scale collaborative IPD approach encourages consensus towards well developed, and validated prognostic models, rather than a number of competing non-validated ones. The large sample size from our IPD will also allow development and validation of multivariable prediction model for the relatively rare outcome of early onset pre-eclampsia.Trial registration: The project was registered on Prospero on the 27 November 2015 with ID: CRD42015029349.
AB - Background: Pre-eclampsia, a condition with raised blood pressure and proteinuria is associated with an increased risk of maternal and offspring mortality and morbidity. Early identification of mothers at risk is needed to target management.Methods/design: We aim to systematically review the existing literature to identify prediction models for pre-eclampsia. We have established the International Prediction of Pregnancy Complication Network (IPPIC), made up of 72 researchers from 21 countries who have carried out relevant primary studies or have access to existing registry databases, and collectively possess data from more than two million patients. We will use the individual participant data (IPD) from these studies to externally validate these existing prediction models and summarise model performance across studies using random-effects meta-analysis for any, late (after 34 weeks) and early (before 34 weeks) onset pre-eclampsia. If none of the models perform well, we will recalibrate (update), or develop and validate new prediction models using the IPD. We will assess the differential accuracy of the models in various settings and subgroups according to the risk status. We will also validate or develop prediction models based on clinical characteristics only; clinical and biochemical markers; clinical and ultrasound parameters; and clinical, biochemical and ultrasound tests.Discussion: Numerous systematic reviews with aggregate data meta-analysis have evaluated various risk factors separately or in combination for predicting pre-eclampsia, but these are affected by many limitations. Our large-scale collaborative IPD approach encourages consensus towards well developed, and validated prognostic models, rather than a number of competing non-validated ones. The large sample size from our IPD will also allow development and validation of multivariable prediction model for the relatively rare outcome of early onset pre-eclampsia.Trial registration: The project was registered on Prospero on the 27 November 2015 with ID: CRD42015029349.
U2 - 10.1186/s41512-017-0016-z
DO - 10.1186/s41512-017-0016-z
M3 - Article
C2 - 31093545
SN - 2397-7523
VL - 1
SP - 16
JO - Diagnostic and Prognostic Research
JF - Diagnostic and Prognostic Research
ER -