Danielle L. Burke

Percutaneous vesicoamniotic shunting versus conservative management for fetal lower urinary tract obstruction (PLUTO): a randomised trial.

Summary Background Fetal lower urinary tract obstruction (LUTO) is associated with high perinatal and long-term childhood mortality and morbidity. We aimed to assess the effectiveness of vesicoamniotic shunting for treatment of LUTO. Methods In a randomised trial in the UK, Ireland, and the Netherlands, women whose pregnancies with a male fetus were complicated by isolated LUTO were randomly assigned by a central telephone and web-based randomisation service to receive either the intervention (placement of vesicoamniotic shunt) or conservative management. Allocation could not be masked from clinicians or participants because of the invasive nature of the intervention. Diagnosis was by prenatal ultrasound. The primary outcome was survival of the baby to 28 days postnatally. All primary analyses were done on an intention-to-treat basis, but these results were compared with those of an as-treated analysis to investigate the effect of a fairly large proportion of crossovers. We used Bayesian methods to estimate the posterior probability distribution of the effectiveness of vesicoamniotic shunting at 28 days. The study is registered with the ISRCTN Register, number ISRCTN53328556. Findings 31 women with singleton pregnancies complicated by LUTO were included in the trial and main analysis, with 16 allocated to the vesicoamniotic shunt group and 15 to the conservative management group. The study closed early because of poor recruitment. There were 12 livebirths in each group. In the vesicoamniotic shunt group one intrauterine death occurred and three pregnancies were terminated. In the conservative management group one intrauterine death occurred and two pregnancies were terminated. Of the 16 pregnancies randomly assigned to vesicoamniotic shunting, eight neonates survived to 28 days, compared with four from the 15 pregnancies assigned to conservative management (intention-to-treat relative risk [RR] 1·88, 95% CI 0·71–4·96; p=0·27). Analysis based on treatment received showed a larger effect (3·20, 1·06–9·62; p=0·03). All 12 deaths were caused by pulmonary hypoplasia in the early neonatal period. Sensitivity analysis in which non-treatment-related terminations of pregnancy were excluded made some slight changes to point estimates only. Bayesian analysis in which the trial data were combined with elicited priors from experts suggested an 86% probability that vesicoamniotic shunting increased survival at 28 days and a 25% probability that it had a large, clinically important effect (defined as a relative increase of 55% or more in the proportion of neonates who survived). There was substantial short-term and long-term morbidity in both groups, including poor renal function—only two babies (both in the shunt group) survived to 2 years with normal renal function. Seven complications occurred in six fetuses from the shunt group, including spontaneous ruptured membranes, shunt blockage, and dislodgement. These complications resulted in four pregnancy losses. Interpretation Survival seemed to be higher in the fetuses receiving vesicoamniotic shunting, but the size and direction of the effect remained uncertain, such that benefit could not be conclusively proven. Our results suggest that the chance of newborn babies surviving with normal renal function is very low irrespective of whether or not vesicoamniotic shunting is done. Funding UK National Institute of Health Research, Wellbeing of Women, Hannah Eliza Guy Charity (Birmingham Childrens Hospital Charity).

Meta‐analysis using individual participant data: one‐stage and two‐stage approaches, and why they may differ

Meta‐analysis using individual participant data (IPD) obtains and synthesises the raw, participant‐level data from a set of relevant studies. The IPD approach is becoming an increasingly popular tool as an alternative to traditional aggregate data meta‐analysis, especially as it avoids reliance on published results and provides an opportunity to investigate individual‐level interactions, such as treatment‐effect modifiers. There are two statistical approaches for conducting an IPD meta‐analysis: one‐stage and two‐stage. The one‐stage approach analyses the IPD from all studies simultaneously, for example, in a hierarchical regression model with random effects. The two‐stage approach derives aggregate data (such as effect estimates) in each study separately and then combines these in a traditional meta‐analysis model. There have been numerous comparisons of the one‐stage and two‐stage approaches via theoretical consideration, simulation and empirical examples, yet there remains confusion regarding when each approach should be adopted, and indeed why they may differ. In this tutorial paper, we outline the key statistical methods for one‐stage and two‐stage IPD meta‐analyses, and provide 10 key reasons why they may produce different summary results. We explain that most differences arise because of different modelling assumptions, rather than the choice of one‐stage or two‐stage itself. We illustrate the concepts with recently published IPD meta‐analyses, summarise key statistical software and provide recommendations for future IPD meta‐analyses.

The Percutaneous shunting in Lower Urinary Tract Obstruction (PLUTO) study and randomised controlled trial: evaluation of the effectiveness, cost-effectiveness and acceptability of percutaneous vesicoamniotic shunting for lower urinary tract obstruction.

BACKGROUND Congenital lower urinary tract obstruction (LUTO) is a disease associated with high perinatal mortality and childhood morbidity. Fetal vesicoamniotic shunting (VAS) bypasses the obstruction with the potential to improve outcome. OBJECTIVE To determine the effectiveness, cost-effectiveness and patient acceptability of VAS for fetal LUTO. DESIGN A multicentre, randomised controlled trial incorporating a prospective registry, decision-analytic health economic model and preplanned Bayesian analysis using elicited opinions. Patient acceptability was evaluated by interview in a qualitative study. SETTING Fetal medicine departments in the UK, Ireland and the Netherlands. PARTICIPANTS Pregnant women with a male singleton fetus with LUTO. INTERVENTIONS In utero percutaneous VAS compared with conservative care. MAIN OUTCOME MEASURES The primary outcome was survival to 28 days. Secondary outcome measures were survival and renal function at 1 year of age, cost of care and cost per additional life-year and per disability-free survival at the end of 1 year. RESULTS The trial stopped early with 31 women randomised because of difficulties in recruitment. Of those randomised to VAS and conservative management, 3/16 (19%) and 2/15 (13%), respectively, did not receive their allocated intervention. Based on intention-to-treat analysis, survival at 28 days was higher if allocated VAS (50%) than conservative management (27%) [relative risk (RR) 1.88, 95% confidence interval (CI) 0.71 to 4.96, p = 0.27]. At 12 months survival was 44% in the VAS arm and 20% in the conservative arm (RR 2.19, 95% CI 0.69 to 6.94, p = 0.25). Neither difference was statistically significant. Of survivors at 1 year, two in the VAS arm had no evidence of renal impairment and four in the VAS arm and two in the conservative arm required medical management. One baby in the conservative arm had end-stage renal failure at 1 year. VAS was more expensive because of additional surgery and intensive care. VAS cost £15,500 per survivor at 1 year and £43,900 per disability-free year. Elicited expert opinions showed uncertainty in the effect of VAS at 28 days. In a Bayesian analysis combining elicited opinion with the results, uncertainty of the benefit of VAS remained (RR 1.31, 95% credible interval 0.84 to 2.18). The acceptability study identified visualisation of the fetus during ultrasound scanning, perceiving a personal benefit, and altruism as positive influences on recruitment. Fear of the VAS procedure and the perceived severity of LUTO influenced non-participation. The need for more detailed information about the condition and its implications during pregnancy and following delivery was a further important finding of this research. Recruitment was hampered by logistical and regulatory difficulties, a lower incidence of LUTO and lower antenatal diagnosis rate [estimated to be 3.34 (95% CI 2.95 to 3.72) per 10,000 total births and 47%, respectively, in an associated epidemiological study] and high termination of pregnancy rates. In the registry women also demonstrated a clear preference for conservative management. CONCLUSIONS Survival to 28 days and 1 year appears to be higher with VAS than with conservative management, but it is not possible to prove benefit beyond reasonable doubt. Notably, prognosis in both arms for survival and renal function is poor. VAS was substantially more costly and unlikely to be regarded as cost-effective based on the 1-year data. Parents should be counselled about the risks of pregnancy loss with or without VAS insertion. The National Institute for Health and Care Excellence interventional procedures guidance (IPG 202) should be updated to reflect this new evidence. Babies in the PLUTO trial should be followed up long term for the different outcomes. TRIAL REGISTRATION ISRCTN53328556. FUNDING This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment ; Vol. 17, No. 59. See the NIHR Journals Library website for further project information.

One‐stage individual participant data meta‐analysis models: estimation of treatment‐covariate interactions must avoid ecological bias by separating out within‐trial and across‐trial information

Stratified medicine utilizes individual‐level covariates that are associated with a differential treatment effect, also known as treatment‐covariate interactions. When multiple trials are available, meta‐analysis is used to help detect true treatment‐covariate interactions by combining their data. Meta‐regression of trial‐level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta‐analyses are preferable to examine interactions utilizing individual‐level information. However, one‐stage IPD models are often wrongly specified, such that interactions are based on amalgamating within‐ and across‐trial information. We compare, through simulations and an applied example, fixed‐effect and random‐effects models for a one‐stage IPD meta‐analysis of time‐to‐event data where the goal is to estimate a treatment‐covariate interaction. We show that it is crucial to centre patient‐level covariates by their mean value in each trial, in order to separate out within‐trial and across‐trial information. Otherwise, bias and coverage of interaction estimates may be adversely affected, leading to potentially erroneous conclusions driven by ecological bias. We revisit an IPD meta‐analysis of five epilepsy trials and examine age as a treatment effect modifier. The interaction is −0.011 (95% CI: −0.019 to −0.003; p = 0.004), and thus highly significant, when amalgamating within‐trial and across‐trial information. However, when separating within‐trial from across‐trial information, the interaction is −0.007 (95% CI: −0.019 to 0.005; p = 0.22), and thus its magnitude and statistical significance are greatly reduced. We recommend that meta‐analysts should only use within‐trial information to examine individual predictors of treatment effect and that one‐stage IPD models should separate within‐trial from across‐trial information to avoid ecological bias.

Multivariate and network meta-analysis of multiple outcomes and multiple treatments: rationale, concepts, and examples

Organisations such as the National Institute for Health and Care Excellence require the synthesis of evidence from existing studies to inform their decisions—for example, about the best available treatments with respect to multiple efficacy and safety outcomes. However, relevant studies may not provide direct evidence about all the treatments or outcomes of interest. Multivariate and network meta-analysis methods provide a framework to address this, using correlated or indirect evidence from such studies alongside any direct evidence. In this article, the authors describe the key concepts and assumptions of these methods, outline how correlated and indirect evidence arises, and illustrate the contribution of such evidence in real clinical examples involving multiple outcomes and multiple treatments

Bayesian bivariate meta-analysis of correlated effects: Impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences

Multivariate random-effects meta-analysis allows the joint synthesis of correlated results from multiple studies, for example, for multiple outcomes or multiple treatment groups. In a Bayesian univariate meta-analysis of one endpoint, the importance of specifying a sensible prior distribution for the between-study variance is well understood. However, in multivariate meta-analysis, there is little guidance about the choice of prior distributions for the variances or, crucially, the between-study correlation, ρB; for the latter, researchers often use a Uniform(−1,1) distribution assuming it is vague. In this paper, an extensive simulation study and a real illustrative example is used to examine the impact of various (realistically) vague prior distributions for ρB and the between-study variances within a Bayesian bivariate random-effects meta-analysis of two correlated treatment effects. A range of diverse scenarios are considered, including complete and missing data, to examine the impact of the prior distributions on posterior results (for treatment effect and between-study correlation), amount of borrowing of strength, and joint predictive distributions of treatment effectiveness in new studies. Two key recommendations are identified to improve the robustness of multivariate meta-analysis results. First, the routine use of a Uniform(−1,1) prior distribution for ρB should be avoided, if possible, as it is not necessarily vague. Instead, researchers should identify a sensible prior distribution, for example, by restricting values to be positive or negative as indicated by prior knowledge. Second, it remains critical to use sensible (e.g. empirically based) prior distributions for the between-study variances, as an inappropriate choice can adversely impact the posterior distribution for ρB, which may then adversely affect inferences such as joint predictive probabilities. These recommendations are especially important with a small number of studies and missing data.

Meta-analysis of randomized phase II trials to inform subsequent phase III decisions

BackgroundIf multiple Phase II randomized trials exist then meta-analysis is favorable to increase statistical power and summarize the existing evidence about an interventions effect in order to help inform Phase III decisions. We consider some statistical issues for meta-analysis of Phase II trials for this purpose, as motivated by a real example involving nine Phase II trials of bolus thrombolytic therapy in acute myocardial infarction with binary outcomes.MethodsWe propose that a Bayesian random effects logistic regression model is most suitable as it models the binomial distribution of the data, helps avoid continuity corrections, accounts for between-trial heterogeneity, and incorporates parameter uncertainty when making inferences. The model also allows predictions that inform Phase III decisions, and we show how to derive: (i) the probability that the intervention will be truly beneficial in a new trial, and (ii) the probability that, in a new trial with a given sample size, the 95% credible interval for the odds ratio will be entirely in favor of the intervention. As Phase II trials are potentially optimistic due to bias in design and reporting, we also discuss how skeptical prior distributions can reduce this optimism to make more realistic predictions.ResultsIn the example, the model identifies heterogeneity in intervention effect missed by an I-squared of 0%. Prediction intervals accounting for this heterogeneity are shown to support subsequent Phase III trials. The probability of success in Phase III trials increases as the sample size increases, up to 0.82 for intracranial hemorrhage and 0.79 for reinfarction outcomes.ConclusionsThe choice of meta-analysis methods can influence the decision about whether a trial should proceed to Phase III and thus need to be clearly documented and investigated whenever a Phase II meta-analysis is performed.

Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models:

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher’s information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis).

Subgrouping and TargetEd Exercise pRogrammes for knee and hip OsteoArthritis (STEER OA): : a systematic review update and individual participant data meta-analysis protocol

Introduction Knee and hip osteoarthritis (OA) is a leading cause of disability worldwide. Therapeutic exercise is a recommended core treatment for people with knee and hip OA, however, the observed effect sizes for reducing pain and improving physical function are small to moderate. This may be due to insufficient targeting of exercise to subgroups of people who are most likely to respond and/or suboptimal content of exercise programmes. This study aims to identify: (1) subgroups of people with knee and hip OA that do/do not respond to therapeutic exercise and to different types of exercise and (2) mediators of the effect of therapeutic exercise for reducing pain and improving physical function. This will enable optimal targeting and refining the content of future exercise interventions. Methods and analysis Systematic review and individual participant data meta-analyses. A previous comprehensive systematic review will be updated to identify randomised controlled trials that compare the effects of therapeutic exercise for people with knee and hip OA on pain and physical function to a non-exercise control. Lead authors of eligible trials will be invited to share individual participant data. Trial-level and participant-level characteristics (for baseline variables and outcomes) of included studies will be summarised. Meta-analyses will use a two-stage approach, where effect estimates are obtained for each trial and then synthesised using a random effects model (to account for heterogeneity). All analyses will be on an intention-to-treat principle and all summary meta-analysis estimates will be reported as standardised mean differences with 95% CI. Ethics and dissemination Research ethical or governance approval is exempt as no new data are being collected and no identifiable participant information will be shared. Findings will be disseminated via national and international conferences, publication in peer-reviewed journals and summaries posted on websites accessed by the public and clinicians. PROSPERO registration number CRD42017054049.

Association of maternal serum PAPP‐A levels, nuchal translucency and crown–rump length in first trimester with adverse pregnancy outcomes: retrospective cohort study

Are first trimester serum pregnancy‐associated plasma protein‐A (PAPP‐A), nuchal translucency (NT) and crown–rump length (CRL) prognostic factors for adverse pregnancy outcomes?