Individual participant data meta-analysis to examine interactions between treatment effect and participant-level covariates: Statistical recommendations for conduct and planning.

Precision medicine research often searches for treatment-covariate interactions, which refers to when a treatment effect (eg, measured as a mean difference, odds ratio, hazard ratio) changes across values of a participant-level covariate (eg, age, gender, biomarker). Single trials do not usually have sufficient power to detect genuine treatment-covariate interactions, which motivate the sharing of individual participant data (IPD) from multiple trials for meta-analysis. Here, we provide statistical recommendations for conducting and planning an IPD meta-analysis of randomized trials to examine treatment-covariate interactions. For conduct, two-stage and one-stage statistical models are described, and we recommend: (i) interactions should be estimated directly, and not by calculating differences in meta-analysis results for subgroups; (ii) interaction estimates should be based solely on within-study information; (iii) continuous covariates and outcomes should be analyzed on their continuous scale; (iv) nonlinear relationships should be examined for continuous covariates, using a multivariate meta-analysis of the trend (eg, using restricted cubic spline functions); and (v) translation of interactions into clinical practice is nontrivial, requiring individualized treatment effect prediction. For planning, we describe first why the decision to initiate an IPD meta-analysis project should not be based on between-study heterogeneity in the overall treatment effect; and second, how to calculate the power of a potential IPD meta-analysis project in advance of IPD collection, conditional on characteristics (eg, number of participants, standard deviation of covariates) of the trials (potentially) promising their IPD. Real IPD meta-analysis projects are used for illustration throughout.

Gestational weight gain outside the Institute of Medicine recommendations and adverse pregnancy outcomes: analysis using individual participant data from randomised trials.

BACKGROUND: High Body Mass Index (BMI) and gestational weight gain (GWG) affect an increasing number of pregnancies. The Institute of Medicine (IOM) has issued recommendations on the optimal GWG for women according to their pre-pregnancy BMI (healthy, overweight or obese). It has been shown that pregnant women rarely met the recommendations; however, it is unclear by how much. Previous studies also adjusted the analyses for various women's characteristics making their comparison challenging. METHODS: We analysed individual participant data (IPD) of healthy women with a singleton pregnancy and a BMI of 18.5 kg/m2 or more from the control arms of 36 randomised trials (16 countries). Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were used to describe the association between GWG outside (above or below) the IOM recommendations (2009) and risks of caesarean section, preterm birth, and large or small for gestational age (LGA or SGA) infants. The association was examined overall, within the BMI categories and by quartile of GWG departure from the IOM recommendations. We obtained aOR using mixed-effects logistic regression, accounting for the within-study clustering and a priori identified characteristics. RESULTS: Out of 4429 women (from 33 trials) meeting the inclusion criteria, two thirds gained weight outside the IOM recommendations (1646 above; 1291 below). The median GWG outside the IOM recommendations was 3.1 kg above and 2.7 kg below. In comparison to GWG within the IOM recommendations, GWG above was associated with increased odds of caesarean section (aOR 1.50; 95%CI 1.25, 1.80), LGA (2.00; 1.58, 2.54), and reduced odds of SGA (0.66; 0.50, 0.87); no significant effect on preterm birth was detected. The relationship between GWG below the IOM recommendation and caesarean section or LGA was inconclusive; however, the odds of preterm birth (1.94; 1.31, 2.28) and SGA (1.52; 1.18, 1.96) were increased. CONCLUSIONS: Consistently with previous findings, adherence to the IOM recommendations seem to help achieve better pregnancy outcomes. Nevertheless, even in the context of clinical trials, women find it difficult to adhere to them. Further research should focus on identifying ways of achieving a healthier GWG as defined by the IOM recommendations.

Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models.

BACKGROUND: Unexpected clinical deterioration before 34 weeks gestation is an undesired course in early-onset pre-eclampsia. To safely prolong preterm gestation, accurate and timely prediction of complications is required. METHOD: Women with confirmed early onset pre-eclampsia were recruited from 53 maternity units in the UK to a large prospective cohort study (PREP-946) for development of prognostic models for the overall risk of experiencing a complication using logistic regression (PREP-L), and for predicting the time to adverse maternal outcome using a survival model (PREP-S). External validation of the models were carried out in a multinational cohort (PIERS-634) and another cohort from the Netherlands (PETRA-216). Main outcome measures were C-statistics to summarise discrimination of the models and calibration plots and calibration slopes. RESULTS: A total of 169 mothers (18%) in the PREP dataset had adverse outcomes by 48 hours, and 633 (67%) by discharge. The C-statistics of the models for predicting complications by 48 hours and by discharge were 0.84 (95% CI, 0.81-0.87; PREP-S) and 0.82 (0.80-0.84; PREP-L), respectively. The PREP-S model included maternal age, gestation, medical history, systolic blood pressure, deep tendon reflexes, urine protein creatinine ratio, platelets, serum alanine amino transaminase, urea, creatinine, oxygen saturation and treatment with antihypertensives or magnesium sulfate. The PREP-L model included the above except deep tendon reflexes, serum alanine amino transaminase and creatinine. On validation in the external PIERS dataset, the reduced PREP-S model showed reasonable calibration (slope 0.80) and discrimination (C-statistic 0.75) for predicting adverse outcome by 48 hours. Reduced PREP-L model showed excellent calibration (slope: 0.93 PIERS, 0.90 PETRA) and discrimination (0.81 PIERS, 0.75 PETRA) for predicting risk by discharge in the two external datasets. CONCLUSIONS: PREP models can be used to obtain predictions of adverse maternal outcome risk, including early preterm delivery, by 48 hours (PREP-S) and by discharge (PREP-L), in women with early onset pre-eclampsia in the context of current care. They have a potential role in triaging high-risk mothers who may need transfer to tertiary units for intensive maternal and neonatal care. TRIAL REGISTRATION: ISRCTN40384046 , retrospectively registered.

Variations in reporting of outcomes in randomized trials on diet and physical activity in pregnancy: A systematic review.

AIM: Trials on diet and physical activity in pregnancy report on various outcomes. We aimed to assess the variations in outcomes reported and their quality in trials on lifestyle interventions in pregnancy. METHODS: We searched major databases without language restrictions for randomized controlled trials on diet and physical activity-based interventions in pregnancy up to March 2015. Two independent reviewers undertook study selection and data extraction. We estimated the percentage of papers reporting 'critically important' and 'important' outcomes. We defined the quality of reporting as a proportion using a six-item questionnaire. Regression analysis was used to identify factors affecting this quality. RESULTS: Sixty-six randomized controlled trials were published in 78 papers (66 main, 12 secondary). Gestational diabetes (57.6%, 38/66), preterm birth (48.5%, 32/66) and cesarian section (60.6%, 40/66), were the commonly reported 'critically important' outcomes. Gestational weight gain (84.5%, 56/66) and birth weight (87.9%, 58/66) were reported in most papers, although not considered critically important. The median quality of reporting was 0.60 (interquartile range 0.25, 0.83) for a maximum score of one. Study and journal characteristics did not affect quality. CONCLUSION: Many studies on lifestyle interventions in pregnancy do not report critically important outcomes, highlighting the need for core outcome set development.

Meta-analysis using individual participant data from randomised trials: opportunities and limitations created by access to raw data.

Meta-analysis based on individual participant data (IPD), often described as the 'gold standard' for effectiveness evidence synthesis, is increasingly being deployed despite being more resource intensive than collating study-level results. Its professed virtues include the ability to incorporate unreported data and to standardise variables and their definitions across trials. In reality, the unreported data, although present in shared datasets, might still not be usable in the analysis. The characteristics of trial participants and their outcomes may be too diversely captured for harmonisation and too time and resource consuming to standardise. Embarking on an IPD meta-analysis can lead to unanticipated challenges which ought to be handled with pragmatism. The aim of this article is to discuss the opportunities created by access to IPD and the practical limitations placed on such meta-analyses, using an international IPD meta-analysis of trials on the effect of lifestyle interventions in pregnancy as an example. Despite the increasing uptake of IPD meta-analysis, they encounter old problems shared by other research methods. When embarking on IPD meta-analysis, it is essential to evaluate the trade-offs between the ambitions, and what is achievable due to constraints imposed by the condition of collected IPD. Furthermore, incorporation of aggregate data from trials where IPD was not available should be a mandatory sensitivity analysis that makes the evidence synthesis up-to-date.

Use of multiple covariates in assessing treatment-effect modifiers: A methodological review of individual participant data meta-analyses.

Individual participant data (IPD) meta-analyses of randomised trials are considered a reliable way to assess participant-level treatment effect modifiers but may not make the best use of the available data. Traditionally, effect modifiers are explored one covariate at a time, which gives rise to the possibility that evidence of treatment-covariate interaction may be due to confounding from a different, related covariate. We aimed to evaluate current practice when estimating treatment-covariate interactions in IPD meta-analysis, specifically focusing on involvement of additional covariates in the models. We reviewed 100 IPD meta-analyses of randomised trials, published between 2015 and 2020, that assessed at least one treatment-covariate interaction. We identified four approaches to handling additional covariates: (1) Single interaction model (unadjusted): No additional covariates included (57/100 IPD meta-analyses); (2) Single interaction model (adjusted): Adjustment for the main effect of at least one additional covariate (35/100); (3) Multiple interactions model: Adjustment for at least one two-way interaction between treatment and an additional covariate (3/100); and (4) Three-way interaction model: Three-way interaction formed between treatment, the additional covariate and the potential effect modifier (5/100). IPD is not being utilised to its fullest extent. In an exemplar dataset, we demonstrate how these approaches lead to different conclusions. Researchers should adjust for additional covariates when estimating interactions in IPD meta-analysis providing they adjust their main effects, which is already widely recommended. Further, they should consider whether more complex approaches could provide better information on who might benefit most from treatments, improving patient choice and treatment policy and practice.

Nonlinear effects and effect modification at the participant-level in IPD meta-analysis part 2: methodological guidance is available.

OBJECTIVES: To review methodological guidance for nonlinear covariate-outcome associations (NL), and linear effect modification and nonlinear effect modification (LEM and NLEM) at the participant level in individual participant data meta-analyses (IPDMAs) and their power requirements. STUDY DESIGN AND SETTING: We searched Medline, Embase, Web of Science, Scopus, PsycINFO and the Cochrane Library to identify methodology publications on IPDMA of LEM, NL or NLEM (PROSPERO CRD42019126768). RESULTS: Through screening 6,466 records we identified 54 potential articles of which 23 full texts were relevant. Nine further relevant publications were published before or after the literature search and were added. Of these 32 references, 21 articles considered LEM, 6 articles NL or NLEM and 6 articles described sample size calculations. A book described all four. Sample size may be calculated through simulation or closed form. Assessments of LEM or NLEM at the participant level need to be based on within-trial information alone. Nonlinearity (NL or NLEM) can be modeled using polynomials or splines to avoid categorization. CONCLUSION: Detailed methodological guidance on IPDMA of effect modification at participant-level is available. However, methodology papers for sample size and nonlinearity are rarer and may not cover all scenarios. On these aspects, further guidance is needed.

Nonlinear effects and effect modification at the participant-level in IPD meta-analysis part 1: analysis methods are often substandard.

OBJECTIVES: To review analysis methods used for linear effect modification (LEM), nonlinear covariate-outcome associations (NL) and nonlinear effect modification (NLEM) at the participant-level in individual participant data meta-analysis (IPDMA). STUDY DESIGN AND SETTING: We searched Medline, Embase, Web of Science, Scopus, PsycINFO and the Cochrane Library to identify IPDMA of randomized controlled trials (PROSPERO CRD42019126768). We investigated if and how IPDMA examined LEM, NL and NLEM, including whether aggregation bias was addressed and if power was considered. RESULTS: We screened 6,466 records, randomly sampled 207 and identified 100 IPDMA of LEM, NL or NLEM. Power for LEM was calculated a priori in 3 IPDMA. Of 100 IPDMA, 94 analyzed LEM, 4 NLEM and 8 NL. One-stage models were favoured for all three (56%, 100%, 50%, respectively). Two-stage models were used in 15%, 0% and 25% of IPDMA with unclear descriptions in 30%, 0% and 25%, respectively. Only 12% of one-stage LEM and NLEM IPDMA provided sufficient detail to confirm they had addressed aggregation bias. CONCLUSION: Investigation of effect modification at the participant-level is common in IPDMA projects, but methods are often open to bias or lack detailed descriptions. Nonlinearity of continuous covariates and power of IPDMA are rarely assessed.

Development and Validation of Clinical Prediction Models for Surgical Success in Patients With Endometriosis: Protocol for a Mixed Methods Study.

BACKGROUND: Endometriosis is a chronic inflammatory condition affecting 6%-10% of women of reproductive age and is defined by the presence of endometrial-like tissue outside the uterus (lesions), commonly affecting the pelvis and ovaries. It is associated with debilitating pelvic pain, infertility, and fatigue and often has devastating effects on the quality of life (QoL). Although it is as common as back pain, it is poorly understood, and treatment and diagnosis are often delayed, leading to unnecessary suffering. Endometriosis has no cure. Surgery is one of several management options. Quantifying the probability of successful surgery is important for guiding clinical decisions and treatment strategies. Factors predicting success through pain reduction after endometriosis surgery have not yet been adequately identified. OBJECTIVE: This study aims to determine which women with confirmed endometriosis benefit from surgical improvement in pain and QoL and whether these women could be identified from clinical symptoms measured before laparoscopy. METHODS: First, we will carry out a systematic search and review and, if appropriate, meta-analysis of observational cohort and case-control studies reporting one or more risk factors for endometriosis and postsurgical treatment success. We will search PubMed, Embase, and Cochrane databases from inception without language restrictions and supplement the reference lists by manual searches. Second, we will develop separate clinical prediction models for women with confirmed and suspected diagnoses of endometriosis. A total of three suitable databases have been identified for development and external validation (the MEDAL [ISRCTN13028601] and LUNA [ISRCTN41196151] studies, and the BSGE database), and access has been guaranteed. The models will be developed using a linear regression approach that links candidate factors to outcomes. Third, we will hold 2 stakeholder co-design workshops involving eight clinicians and eight women with endometriosis separately and then bring all 16 participants together. Participants will discuss the implementation, delivery, usefulness, and sustainability of the prediction models. Clinicians will also focus on the ease of use and access to clinical prediction tools. RESULTS: This project was funded in March 2018 and approved by the Institutional Research Ethics Board in December 2019. At the time of writing, this study was in the data analysis phase, and the results are expected to be available in April 2021. CONCLUSIONS: This study is the first to aim to predict who will benefit most from laparoscopic surgery through the reduction of pain or increased QoL. The models will provide clinicians with robustly developed and externally validated support tools, improving decision making in the diagnosis and treatment of women. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/20986.

Impact of London's low emission zone on air quality and children's respiratory health: a sequential annual cross-sectional study.

BACKGROUND: Low emission zones (LEZ) are an increasingly common, but unevaluated, intervention aimed at improving urban air quality and public health. We investigated the impact of London's LEZ on air quality and children's respiratory health. METHODS: We did a sequential annual cross-sectional study of 2164 children aged 8-9 years attending primary schools between 2009-10 and 2013-14 in central London, UK, following the introduction of London's LEZ in February, 2008. We examined the association between modelled pollutant exposures of nitrogen oxides (including nitrogen dioxide [NO2]) and particulate matter with a diameter of less than 2·5 µm (PM2·5) and less than 10 µm (PM10) and lung function: postbronchodilator forced expiratory volume in 1 s (FEV1, primary outcome), forced vital capacity (FVC), and respiratory or allergic symptoms. We assigned annual exposures by each child's home and school address, as well as spatially resolved estimates for the 3 h (0600-0900 h), 24 h, and 7 days before each child's assessment, to isolate long-term from short-term effects. FINDINGS: The percentage of children living at addresses exceeding the EU limit value for annual NO2 (40 µg/m3) fell from 99% (444/450) in 2009 to 34% (150/441) in 2013. Over this period, we identified a reduction in NO2 at both roadside (median -1·35 µg/m3 per year; 95% CI -2·09 to -0·61; p=0·0004) and background locations (-0·97; -1·56 to -0·38; p=0·0013), but not for PM10. The effect on PM2·5 was equivocal. We found no association between postbronchodilator FEV1 and annual residential pollutant attributions. By contrast, FVC was inversely correlated with annual NO2 (-0·0023 L/µg per m3; -0·0044 to -0·0002; p=0·033) and PM10 (-0·0090 L/µg per m3; -0·0175 to -0·0005; p=0·038). INTERPRETATION: Within London's LEZ, a smaller lung volume in children was associated with higher annual air pollutant exposures. We found no evidence of a reduction in the proportion of children with small lungs over this period, despite small improvements in air quality in highly polluted urban areas during the implementation of London's LEZ. Interventions that deliver larger reductions in emissions might yield improvements in children's health. FUNDING: National Institute for Health Research Biomedical Research Centre at Guy's and St Thomas' National Health Service (NHS) Foundation Trust and King's College London, NHS Hackney, Lee Him donation, and Felicity Wilde Charitable Trust.

Stepped-wedge randomised trial of laparoscopic ventral mesh rectopexy in adults with chronic constipation: study protocol for a randomized controlled trial.

BACKGROUND: Laparoscopic ventral mesh rectopexy (LVMR) is an established treatment for external full-thickness rectal prolapse. However, its clinical efficacy in patients with internal prolapse is uncertain due to the lack of high-quality evidence. METHODS: An individual level, stepped-wedge randomised trial has been designed to allow observer-blinded data comparisons between patients awaiting LVMR with those who have undergone surgery. Adults with symptomatic internal rectal prolapse, unresponsive to prior conservative management, will be eligible to participate. They will be randomised to three arms with different delays before surgery (0, 12 and 24 weeks). Efficacy outcome data will be collected at equally stepped time points (12, 24, 36 and 48 weeks). The primary objective is to determine clinical efficacy of LVMR compared to controls with reduction in the Patient Assessment of Constipation Quality of Life (PAC-QOL) at 24 weeks serving as the primary outcome. Secondary objectives are to determine: (1) the clinical effectiveness of LVMR to 48 weeks to a maximum of 72 weeks; (2) pre-operative determinants of outcome; (3) relevant health economics for LVMR; (4) qualitative evaluation of patient and health professional experience of LVMR and (5) 30-day morbidity and mortality rates. DISCUSSION: An individual-level, stepped-wedge, randomised trial serves the purpose of providing an untreated comparison for the active treatment group, while at the same time allowing the waiting-listed participants an opportunity to obtain the intervention at a later date. In keeping with the basic ethical tenets of this design, the average waiting time for LVMR (12 weeks) will be shorter than that for routine services (24 weeks). TRIAL REGISTRATION: ISRCTN registry, ISRCTN11747152 . Registered on 30 September 2015. The trial was prospectively registered (first patient enrolled on 21 March 2016).

AntiEpileptic drug Monitoring in PREgnancy (EMPiRE): a double-blind randomised trial on effectiveness and acceptability of monitoring strategies.

BACKGROUND: Pregnant women with epilepsy on antiepileptic drugs (AEDs) may experience a reduction in serum AED levels. This has the potential to worsen seizure control. OBJECTIVE: To determine if, in pregnant women with epilepsy on AEDs, additional therapeutic drug monitoring reduces seizure deterioration compared with clinical features monitoring after a reduction in serum AED levels. DESIGN: A double-blind, randomised trial nested within a cohort study was conducted and a qualitative study of acceptability of the two strategies was undertaken. Stratified block randomisation with a 1 : 1 allocation method was carried out. SETTING: Fifty obstetric and epilepsy clinics in secondary and tertiary care units in the UK. PARTICIPANTS: Pregnant women with epilepsy on one or more of the following AEDs: lamotrigine, carbamazepine, phenytoin or levetiracetam. Women with a ≥ 25% decrease in serum AED level from baseline were randomised to therapeutic drug monitoring or clinical features monitoring strategies. INTERVENTIONS: In the therapeutic drug monitoring group, clinicians had access to clinical findings and monthly serum AED levels to guide AED dosage adjustment for seizure control. In the clinical features monitoring group, AED dosage adjustment was based only on clinical features. MAIN OUTCOME MEASURES: Primary outcome - seizure deterioration, defined as time to first seizure and to all seizures after randomisation per woman until 6 weeks post partum. Secondary outcomes - pregnancy complications in mother and offspring, maternal quality of life, seizure rates in cohorts with stable serum AED level, AED dose exposure and adverse events related to AEDs. ANALYSIS: Analysis of time to first and to all seizures after randomisation was performed using a Cox proportional hazards model, and multivariate failure time analysis by the Andersen-Gill model. The effects were reported as hazard ratios (HRs) with 95% confidence intervals (CIs). Secondary outcomes were reported as mean differences (MDs) or odds ratios. RESULTS: A total of 130 women were randomised to the therapeutic drug monitoring group and 133 to the clinical features monitoring group; 294 women did not have a reduction in serum AED level. A total of 127 women in the therapeutic drug monitoring group and 130 women in the clinical features monitoring group (98% of complete data) were included in the primary analysis. There were no significant differences in the time to first seizure (HR 0.82, 95% CI 0.55 to 1.2) or timing of all seizures after randomisation (HR 1.3, 95% CI 0.7 to 2.5) between both trial groups. In comparison with the group with stable serum AED levels, there were no significant increases in seizures in the clinical features monitoring (odds ratio 0.93, 95% CI 0.56 to 1.5) or therapeutic drug monitoring group (odds ratio 0.93, 95% CI 0.56 to 1.5) associated with a reduction in serum AED levels. Maternal and neonatal outcomes were similar in both groups, except for higher cord blood levels of lamotrigine (MD 0.55 mg/l, 95% CI 0.11 to 1 mg/l) or levetiracetam (MD 7.8 mg/l, 95% CI 0.86 to 14.8 mg/l) in the therapeutic drug monitoring group than in the clinical features monitoring group. There were no differences between the groups on daily AED exposure or quality of life. An increase in exposure to lamotrigine, levetiracetam and carbamazepine significantly increased the cord blood levels of the AEDs, but not maternal or fetal complications. Women with epilepsy perceived the need for weighing up their increased vulnerability to seizures during pregnancy against the side effects of AEDs. LIMITATIONS: Fewer women than the original target were recruited. CONCLUSION: There is no evidence to suggest that regular monitoring of serum AED levels in pregnancy improves seizure control or affects maternal or fetal outcomes. FUTURE WORK RECOMMENDATIONS: Further evaluation of the risks of seizure deterioration for various threshold levels of reduction in AEDs and the long-term neurodevelopment of infants born to mothers in both randomised groups is needed. An individualised prediction model will help to identify those women who need close monitoring in pregnancy. TRIAL REGISTRATION: Current Controlled Trials ISRCTN01253916. FUNDING: 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. 22, No. 23. See the NIHR Journals Library website for further project information.

Development and validation of prediction models for risk of adverse outcomes in women with early-onset pre-eclampsia: protocol of the prospective cohort PREP study.

BACKGROUND: Early-onset pre-eclampsia with raised blood pressure and protein in the urine before 34 weeks' gestation is one of the leading causes of maternal deaths in the UK. The benefits to the child from prolonging the pregnancy need to be balanced against the risk of maternal deterioration. Accurate prediction models of risks are needed to plan management. METHODS: We aim to undertake a multicentre prospective cohort study (Prediction of Risks in Early onset Pre-eclampsia (PREP)) to develop clinical prediction models in women with early-onset pre-eclampsia, for risk of adverse maternal outcomes by 48 h and by discharge. We will externally validate the models in two independent cohorts with 634 and 216 women. In the secondary analyses, we will assess risk of adverse fetal and neonatal outcomes at birth and by discharge. DISCUSSION: The PREP study will quantify the risk of maternal complications at various time points and provide individualised estimates of overall risk in women with early-onset pre-eclampsia to plan the management. TRIAL REGISTRATION: ISRCTN registry, ISRCTN40384046.

Development and validation of Prediction models for Risks of complications in Early-onset Pre-eclampsia (PREP): a prospective cohort study.

BACKGROUND: The prognosis of early-onset pre-eclampsia (before 34 weeks' gestation) is variable. Accurate prediction of complications is required to plan appropriate management in high-risk women. OBJECTIVE: To develop and validate prediction models for outcomes in early-onset pre-eclampsia. DESIGN: Prospective cohort for model development, with validation in two external data sets. SETTING: Model development: 53 obstetric units in the UK. Model transportability: PIERS (Pre-eclampsia Integrated Estimate of RiSk for mothers) and PETRA (Pre-Eclampsia TRial Amsterdam) studies. PARTICIPANTS: Pregnant women with early-onset pre-eclampsia. SAMPLE SIZE: Nine hundred and forty-six women in the model development data set and 850 women (634 in PIERS, 216 in PETRA) in the transportability (external validation) data sets. PREDICTORS: The predictors were identified from systematic reviews of tests to predict complications in pre-eclampsia and were prioritised by Delphi survey. MAIN OUTCOME MEASURES: The primary outcome was the composite of adverse maternal outcomes established using Delphi surveys. The secondary outcome was the composite of fetal and neonatal complications. ANALYSIS: We developed two prediction models: a logistic regression model (PREP-L) to assess the overall risk of any maternal outcome until postnatal discharge and a survival analysis model (PREP-S) to obtain individual risk estimates at daily intervals from diagnosis until 34 weeks. Shrinkage was used to adjust for overoptimism of predictor effects. For internal validation (of the full models in the development data) and external validation (of the reduced models in the transportability data), we computed the ability of the models to discriminate between those with and without poor outcomes (c-statistic), and the agreement between predicted and observed risk (calibration slope). RESULTS: The PREP-L model included maternal age, gestational age at diagnosis, medical history, systolic blood pressure, urine protein-to-creatinine ratio, platelet count, serum urea concentration, oxygen saturation, baseline treatment with antihypertensive drugs and administration of magnesium sulphate. The PREP-S model additionally included exaggerated tendon reflexes and serum alanine aminotransaminase and creatinine concentration. Both models showed good discrimination for maternal complications, with anoptimism-adjusted c-statistic of 0.82 [95% confidence interval (CI) 0.80 to 0.84] for PREP-L and 0.75 (95% CI 0.73 to 0.78) for the PREP-S model in the internal validation. External validation of the reduced PREP-L model showed good performance with a c-statistic of 0.81 (95% CI 0.77 to 0.85) in PIERS and 0.75 (95% CI 0.64 to 0.86) in PETRA cohorts for maternal complications, and calibrated well with slopes of 0.93 (95% CI 0.72 to 1.10) and 0.90 (95% CI 0.48 to 1.32), respectively. In the PIERS data set, the reduced PREP-S model had a c-statistic of 0.71 (95% CI 0.67 to 0.75) and a calibration slope of 0.67 (95% CI 0.56 to 0.79). Low gestational age at diagnosis, high urine protein-to-creatinine ratio, increased serum urea concentration, treatment with antihypertensive drugs, magnesium sulphate, abnormal uterine artery Doppler scan findings and estimated fetal weight below the 10th centile were associated with fetal complications. CONCLUSIONS: The PREP-L model provided individualised risk estimates in early-onset pre-eclampsia to plan management of high- or low-risk individuals. The PREP-S model has the potential to be used as a triage tool for risk assessment. The impacts of the model use on outcomes need further evaluation. TRIAL REGISTRATION: Current Controlled Trials ISRCTN40384046. FUNDING: The National Institute for Health Research Health Technology Assessment programme.

Effects of antenatal diet and physical activity on maternal and fetal outcomes: individual patient data meta-analysis and health economic evaluation.

BACKGROUND: Diet- and physical activity-based interventions in pregnancy have the potential to alter maternal and child outcomes. OBJECTIVES: To assess whether or not the effects of diet and lifestyle interventions vary in subgroups of women, based on maternal body mass index (BMI), age, parity, Caucasian ethnicity and underlying medical condition(s), by undertaking an individual patient data (IPD) meta-analysis. We also evaluated the association of gestational weight gain (GWG) with adverse pregnancy outcomes and assessed the cost-effectiveness of the interventions. DATA SOURCES: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects and Health Technology Assessment database were searched from October 2013 to March 2015 (to update a previous search). REVIEW METHODS: Researchers from the International Weight Management in Pregnancy Collaborative Network shared the primary data. For each intervention type and outcome, we performed a two-step IPD random-effects meta-analysis, for all women (except underweight) combined and for each subgroup of interest, to obtain summary estimates of effects and 95% confidence intervals (CIs), and synthesised the differences in effects between subgroups. In the first stage, we fitted a linear regression adjusted for baseline (for continuous outcomes) or a logistic regression model (for binary outcomes) in each study separately; estimates were combined across studies using random-effects meta-analysis models. We quantified the relationship between weight gain and complications, and undertook a decision-analytic model-based economic evaluation to assess the cost-effectiveness of the interventions. RESULTS: Diet and lifestyle interventions reduced GWG by an average of 0.70 kg (95% CI -0.92 to -0.48 kg; 33 studies, 9320 women). The effects on composite maternal outcome [summary odds ratio (OR) 0.90, 95% CI 0.79 to 1.03; 24 studies, 8852 women] and composite fetal/neonatal outcome (summary OR 0.94, 95% CI 0.83 to 1.08; 18 studies, 7981 women) were not significant. The effect did not vary with baseline BMI, age, ethnicity, parity or underlying medical conditions for GWG, and composite maternal and fetal outcomes. Lifestyle interventions reduce Caesarean sections (OR 0.91, 95% CI 0.83 to 0.99), but not other individual maternal outcomes such as gestational diabetes mellitus (OR 0.89, 95% CI 0.72 to 1.10), pre-eclampsia or pregnancy-induced hypertension (OR 0.95, 95% CI 0.78 to 1.16) and preterm birth (OR 0.94, 95% CI 0.78 to 1.13). There was no significant effect on fetal outcomes. The interventions were not cost-effective. GWG, including adherence to the Institute of Medicine-recommended targets, was not associated with a reduction in complications. Predictors of GWG were maternal age (summary estimate -0.10 kg, 95% CI -0.14 to -0.06 kg) and multiparity (summary estimate -0.73 kg, 95% CI -1.24 to -0.23 kg). LIMITATIONS: The findings were limited by the lack of standardisation in the components of intervention, residual heterogeneity in effects across studies for most analyses and the unavailability of IPD in some studies. CONCLUSION: Diet and lifestyle interventions in pregnancy are clinically effective in reducing GWG irrespective of risk factors, with no effects on composite maternal and fetal outcomes. FUTURE WORK: The differential effects of lifestyle interventions on individual pregnancy outcomes need evaluation. STUDY REGISTRATION: This study is registered as PROSPERO CRD42013003804. FUNDING: The National Institute for Health Research Health Technology Assessment programme.

Randomised controlled trial of GP-led in-hospital management of homeless people ('Pathway').

Homeless people have complex problems. GP enhanced care (Pathway) has shown benefits. We performed a randomised, -parallel arm trial at two large inner city hospitals. Inpatient homeless adults were randomly allocated to either standard care (all management by the hospital-based clinical team) or enhanced care with input from a homeless care team. The hospital data system provided healthcare usage information, and we used questionnaires to assess quality of life. 206 patients were allocated to enhanced care and 204 to usual care. Length of stay (up to 90 days after admission) did not differ between groups (standard care 14.0 days, enhanced care 13.3 days). Average reattendance at the emergency department within a year was 5.8 visits in the standard care group and 4.8 visits with enhanced care, but this decrease was not significant. -Quality of life scores after discharge (in 108 patients) improved with enhanced care (EQ-5D-5L score increased by 0.12 [95% CI 0.032 to 0.22] compared wtih 0.03 [-0.1 to 0.15; p=0.076] with standard care). The proportion of people sleeping on the streets after discharge was 14.6% in the standard care arm and 3.8% in the enhanced care arm (p=0.034). The quality-of-life cost per quality-adjusted life-year was £26,000. The Pathway approach doesn't alter length of stay but improves quality of life and reduces street -homelessness.

Air pollution, ethnicity and telomere length in east London schoolchildren: An observational study.

BACKGROUND: Short telomeres are associated with chronic disease and early mortality. Recent studies in adults suggest an association between telomere length and exposure to particulate matter, and that ethnicity may modify the relationship. However associations in children are unknown. OBJECTIVES: We examined associations between air pollution and telomere length in an ethnically diverse group of children exposed to high levels of traffic derived pollutants, particularly diesel exhaust, and to environmental tobacco smoke. METHODS: Oral DNA from 333 children (8-9years) participating in a study on air quality and respiratory health in 23 inner city London schools was analysed for relative telomere length using monochrome multiplex qPCR. Annual, weekly and daily exposures to nitrogen oxides and particulate matter were obtained from urban dispersion models (2008-10) and tobacco smoke by urinary cotinine. Ethnicity was assessed by self-report and continental ancestry by analysis of 28 random genomic markers. We used linear mixed effects models to examine associations with telomere length. RESULTS: Telomere length increased with increasing annual exposure to NOx (model coefficient 0.003, [0.001, 0.005], p<0.001), NO2 (0.009 [0.004, 0.015], p<0.001), PM2.5 (0.041, [0.020, 0.063], p<0.001) and PM10 (0.096, [0.044, 0.149], p<0.001). There was no association with environmental tobacco smoke. Telomere length was increased in children reporting black ethnicity (22% [95% CI 10%, 36%], p<0.001) CONCLUSIONS: Pollution exposure is associated with longer telomeres in children and genetic ancestry is an important determinant of telomere length. Further studies should investigate both short and long-term associations between pollutant exposure and telomeres in childhood and assess underlying mechanisms.