ORCID Profile
0000-0002-2358-5860
Current Organisations
Australian National University
,
Cairo University Faculty of Science
,
University of Aberdeen
,
University of Calcutta
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Publications
Chiral superfluid in a one-dimensional bipartite optical lattice
Publisher: American Physical Society (APS)
Date: 28-02-2022
Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis
Publisher: National Institute for Health and Care Research
Date: 12-2020
DOI: 10.3310/HTA24720
Abstract: Pre-ecl sia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management. To assess the performance of existing pre-ecl sia prediction models and to develop and validate models for pre-ecl sia using in idual participant data meta-analysis. We also estimated the prognostic value of in idual markers. This was an in idual participant data meta-analysis of cohort studies. Source data from secondary and tertiary care. We identified predictors from systematic reviews, and prioritised for importance in an international survey. Early-onset (delivery at 34 weeks’ gestation), late-onset (delivery at ≥ 34 weeks’ gestation) and any-onset pre-ecl sia. We externally validated existing prediction models in UK cohorts and reported their performance in terms of discrimination and calibration. We developed and validated 12 new models based on clinical characteristics, clinical characteristics and biochemical markers, and clinical characteristics and ultrasound markers in the first and second trimesters. We summarised the data set-specific performance of each model using a random-effects meta-analysis. Discrimination was considered promising for C -statistics of ≥ 0.7, and calibration was considered good if the slope was near 1 and calibration-in-the-large was near 0. Heterogeneity was quantified using I 2 and τ 2 . A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of in idual predictors for pre-ecl sia as odds ratios with 95% confidence and prediction intervals. The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-ecl sia. Twenty-four of the 131 published prediction models could be validated in 11 UK cohorts. Summary C -statistics were between 0.6 and 0.7 for most models, and calibration was generally poor owing to large between-study heterogeneity, suggesting model overfitting. The clinical utility of the models varied between showing net harm to showing minimal or no net benefit. The average discrimination for IPPIC models ranged between 0.68 and 0.83. This was highest for the second-trimester clinical characteristics and biochemical markers model to predict early-onset pre-ecl sia, and lowest for the first-trimester clinical characteristics models to predict any pre-ecl sia. Calibration performance was heterogeneous across studies. Net benefit was observed for International Prediction of Pregnancy Complications first and second-trimester clinical characteristics and clinical characteristics and biochemical markers models predicting any pre-ecl sia, when validated in singleton nulliparous women managed in the UK NHS. History of hypertension, parity, smoking, mode of conception, placental growth factor and uterine artery pulsatility index had the strongest unadjusted associations with pre-ecl sia. Variations in study population characteristics, type of predictors reported, too few events in some validation cohorts and the type of measurements contributed to heterogeneity in performance of the International Prediction of Pregnancy Complications models. Some published models were not validated because model predictors were unavailable in the in idual participant data. For models that could be validated, predictive performance was generally poor across data sets. Although the International Prediction of Pregnancy Complications models show good predictive performance on average, and in the singleton nulliparous population, heterogeneity in calibration performance is likely across settings. Recalibration of model parameters within populations may improve calibration performance. Additional strong predictors need to be identified to improve model performance and consistency. Validation, including examination of calibration heterogeneity, is required for the models we could not validate. This study is registered as PROSPERO CRD42015029349. This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment Vol. 24, No. 72. See the NIHR Journals Library website for further project information.
Related Organisations
Arab Academy For Science Technology And Maritime Transport - Cairo Campus
Location: Egypt
University Of Aberdeen
Location: United Kingdom of Great Britain and Northern Ireland
Related Funding Activities
No related grants have been discovered for Sohinee Bhattacharya.