External validation of prognostic models predicting pre-eclampsia : individual participant data meta-analysis

Abstract Background Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. Methods IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. Results Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model’s calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. Conclusions The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice. Trial registration PROSPERO ID: CRD42015029349

Lifestyle intervention in Danish obese pregnant women with early gestational diabetes mellitus according to WHO 2013 criteria does not change pregnancy outcomes: results from the LiP (Lifestyle in Pregnancy) study

To study effects of lifestyle intervention on metabolic and clinical outcomes in obese women fulfilling the World Health Organization (WHO) 2013 diagnostic criteria for gestational diabetes mellitus (GDM) in early gestation.Secondary analysis of data from the Lifestyle-in-Pregnancy (LiP) study, a lifestyle randomized controlled trial in 304 pregnant women with BMI ≥30 kg/m. Early GDM (week 12-15) was diagnosed according to modified WHO 2013 GDM criteria: fasting venous plasma glucose ≥5.1 mmol/L and/or 2-h capillary blood glucose (CBG) ≥8.5 mmol/L (75-g oral glucose tolerance test [OGTT]). Women with treated GDM fulfilling local Danish GDM criteria (2-h CBG ≥9.0 mmol/L) ( = 16) and women with normal OGTT ( = 198) were excluded.Of 90 women with early GDM, 36 received lifestyle intervention and 54 standard care. All were Caucasian, and median age was 29 years (interquartile range 27-33) and BMI 34.5 kg/m (32.3-38.1). All baseline characteristics were similar in the lifestyle intervention and standard care groups. At gestational week 28-30, the women in the lifestyle intervention group had significantly higher fasting total cholesterol and fasting LDL. All other metabolic parameters including measurements of glucose, insulin, and HOMA of insulin resistance were similar. There were more planned cesarean sections in the lifestyle intervention group (22.2 vs. 5.6%), but all other obstetric outcomes were similar.Lifestyle intervention in obese women fulfilling WHO 2013 GDM criteria in early pregnancy was not effective in improving obstetric or metabolic outcomes. Future studies should focus on interventions starting prepregnancy

Anthropometrics and body composition by dual energy X-ray in children of obese women:a follow-up of a randomized controlled trial (the Lifestyle in Pregnancy and Offspring [LiPO] study)

In obese women, 1) to assess whether lower gestational weight gain (GWG) during pregnancy in the lifestyle intervention group of a randomized controlled trial (RCT) resulted in differences in offspring anthropometrics and body composition, and 2) to compare offspring outcomes to a reference group of children born to women with a normal Body Mass Index (BMI).The LiPO (Lifestyle in Pregnancy and Offspring) study was an offspring follow-up of a RCT with 360 obese pregnant women with a lifestyle intervention during pregnancy including dietary advice, coaching and exercise. The trial was completed by 301 women who were eligible for follow-up. In addition, to the children from the RCT, a group of children born to women with a normal BMI were included as a reference group. At 2.8 (range 2.5-3.2) years, anthropometrics were measured in 157 children of the RCT mothers and in 97 reference group children with Body Mass Index (BMI) Z-score as a primary outcome. Body composition was estimated by Dual Energy X-ray (DEXA) in 123 successful scans out of 147 (84%).No differences between randomized groups were seen in mean (95% C.I.) BMI Z-score (intervention group 0.06 [-0.17; 0.29] vs. controls -0.18 [-0.43; 0.05]), in the percentage of overweight or obese children (10.9% vs. 6.7%), in other anthropometrics, or in body composition values by DEXA. Outcomes between children from the RCT and the reference group children were not significantly different.The RCT with lifestyle intervention in obese pregnant women did not result in any detectable effect on offspring anthropometrics or body composition by DEXA at 2.8 years of age. This may reflect the limited difference in GWG between intervention and control groups. Offspring of obese mothers from the RCT were comparable to offspring of mothers with a normal BMI

Simple and multiple regression analyses showing crude and adjusted difference in BMI Z-score in the three groups of term children at age 2.8 years.

<p>Legend: *Adjusted for gestational weight gain, parity, smoking during pregnancy, maternal age, educational level (school ≥12 years), breastfeeding (exclusive breastfeeding for at least 5 months), birth weight Z-score and excessive post natal growth (change in weight Z-score between 0 and 12 months). Only term children with available data on all variables were included in the adjusted analysis. Z-score; standard deviation score, LiP; Lifestyle in Pregnancy.</p

Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia : an individual participant data meta-analysis

Background: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management. Objective : To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia using individual participant data meta-analysis. We also estimated the prognostic value of individual markers. Design: This was an individual participant data meta-analysis of cohort studies. Setting: Source data from secondary and tertiary care. Predictors: We identified predictors from systematic reviews, and prioritised for importance in an international survey. Primary outcomes Early-onset (delivery at = 34 weeks' gestation) and any-onset pre-eclampsia. Analysis: 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 l(2) and tau(2). A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of individual predictors for pre-eclampsia as odds ratios with 95% confidence and prediction intervals. Result The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-eclampsia. 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-eclampsia, and lowest for the first-trimester clinical characteristics models to predict any pre-eclampsia. 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-eclampsia, 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-eclampsia. Limitations: 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 individual participant data. Conclusion: 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. Future work: 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.Peer reviewe

Impact of maternal education on response to lifestyle interventions to reduce gestational weight gain: individual participant data meta-analysis

OBJECTIVES: To identify if maternal educational attainment is a prognostic factor for gestational weight gain (GWG), and to determine the differential effects of lifestyle interventions (diet based, physical activity based or mixed approach) on GWG, stratified by educational attainment. DESIGN: Individual participant data meta-analysis using the previously established International Weight Management in Pregnancy (i-WIP) Collaborative Group database (https://iwipgroup.wixsite.com/collaboration). Preferred Reporting Items for Systematic reviews and Meta-Analysis of Individual Participant Data Statement guidelines were followed. DATA SOURCES: Major electronic databases, from inception to February 2017. ELIGIBILITY CRITERIA: Randomised controlled trials on diet and physical activity-based interventions in pregnancy. Maternal educational attainment was required for inclusion and was categorised as higher education (≥tertiary) or lower education (≤secondary). RISK OF BIAS: Cochrane risk of bias tool was used. DATA SYNTHESIS: Principle measures of effect were OR and regression coefficient. RESULTS: Of the 36 randomised controlled trials in the i-WIP database, 21 trials and 5183 pregnant women were included. Women with lower educational attainment had an increased risk of excessive (OR 1.182; 95% CI 1.008 to 1.385, p =0.039) and inadequate weight gain (OR 1.284; 95% CI 1.045 to 1.577, p =0.017). Among women with lower education, diet basedinterventions reduced risk of excessive weight gain (OR 0.515; 95% CI 0.339 to 0.785, p = 0.002) and inadequate weight gain (OR 0.504; 95% CI 0.288 to 0.884, p=0.017), and reduced kg/week gain (B -0.055; 95% CI -0.098 to -0.012, p=0.012). Mixed interventions reduced risk of excessive weight gain for women with lower education (OR 0.735; 95% CI 0.561 to 0.963, p=0.026). Among women with high education, diet based interventions reduced risk of excessive weight gain (OR 0.609; 95% CI 0.437 to 0.849, p=0.003), and mixed interventions reduced kg/week gain (B -0.053; 95% CI -0.069 to -0.037,p<0.001). Physical activity based interventions did not impact GWG when stratified by education. CONCLUSIONS: Pregnant women with lower education are at an increased risk of excessive and inadequate GWG. Diet based interventions seem the most appropriate choice for these women, and additional support through mixed interventions may also be beneficial.status: publishe