Mixed treatment comparison of repeated measurements of a continuous endpoint: an example using topical treatments for primary open-angle glaucoma and ocular hypertension

Bisphosphonate alternative regimens for the prevention of osteoporotic fragility fractures: BLAST-OFF, a mixed-methods study

Background

Bisphosphonates are a class of medication commonly used to treat osteoporosis. Alendronate is recommended as the first-line treatment; however, long-term adherence (both treatment compliance and persistence) is poor. Alternative bisphosphonates are available, which can be given intravenously and have been shown to improve long-term adherence. However, the most clinically effective and cost-effective alternative bisphosphonate regimen remains unclear. What is the most cost-effective bisphosphonate in clinical trials may not be the most cost-effective or acceptable to patients in everyday clinical practice.

Objectives

1. Explore patient, clinician and stakeholder views, experiences and preferences of alendronate compared to alternative bisphosphonates. 2. Update and refine the 2016 systematic review and cost-effectiveness analysis of bisphosphonates, and estimate the value of further research into their benefits. 3. Undertake stakeholder/consensus engagement to identify important research questions and further rank research priorities.

Methods

The study was conducted in two stages, stages 1A and 1B in parallel, followed by stage 2: • Stage 1A - we elicited patient and healthcare experiences to understand their preferences of bisphosphonates for the treatment of osteoporosis. This was undertaken by performing a systematic review and framework synthesis of qualitative studies, followed by semistructured qualitative interviews with participants. • Stage 1B - we updated and expanded the existing Health Technology Assessment systematic review and clinical and cost-effectiveness model, incorporating a more comprehensive review of treatment efficacy, safety, side effects, compliance and long-term persistence. • Stage 2 - we identified and ranked further research questions that need to be answered about the effectiveness and acceptability of bisphosphonates.

Results

Patients and healthcare professionals identified a number of challenges in adhering to bisphosphonate medication, balancing the potential for long-term risk reduction against the work involved in adhering to oral alendronate. Intravenous zoledronate treatment was generally more acceptable, with such regimens perceived to be more straightforward to engage in, although a portion of patients taking alendronate were satisfied with their current treatment. Intravenous zoledronate was found to be the most effective, with higher adherence rates compared to the other bisphosphonates, for reducing the risk of fragility fracture. However, oral bisphosphonates are more cost-effective than intravenous zoledronate due to the high cost of zoledronate administration in hospital. The importance of including patients and healthcare professionals when setting research priorities is recognised. Important areas for research were related to patient factors influencing treatment selection and effectiveness, how to optimise long-term care and the cost-effectiveness of delivering zoledronate in an alternative, non-hospital setting.

Conclusions

Intravenous zoledronate treatment was generally more acceptable to patients and found to be the most effective bisphosphonate and with greater adherence; however, the cost-effectiveness relative to oral alendronate is limited by its higher zoledronate hospital administration costs.

Future work

Further research is needed to support people to make decisions influencing treatment selection, effectiveness and optimal long-term care, together with the clinical and cost-effectiveness of intravenous zoledronate administered in a non-hospital (community) setting.

Limitations

Lack of clarity and limitations in the many studies included in the systematic review may have under-interpreted some of the findings relating to effects of bisphosphonates.

Trial registration

This trial is registered as ISRCTN10491361.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: NIHR127550) and is published in full in Health Technology Assessment; Vol. 28, No. 21. See the NIHR Funding and Awards website for further award information.

Network meta analysis to predict the efficacy of an approved treatment in a new indication

Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not widely used in practice. Instead, repurposing decisions are often based on subjective judgments from limited empirical evidence. In this article, we develop a novel Bayesian network meta-analysis (NMA) framework that can predict the efficacy of an approved treatment in a new indication and thereby identify candidate treatments for repurposing. We obtain predictions using two main steps: first, we use standard NMA modeling to estimate average relative effects from a network comprised of treatments studied in both indications in addition to one treatment studied in only one indication. Then, we model the correlation between relative effects using various strategies that differ in how they model treatments across indications and within the same drug class. We evaluate the predictive performance of each model using a simulation study and find that the model minimizing root mean squared error of the posterior median for the candidate treatment depends on the amount of available data, the level of correlation between indications, and whether treatment effects differ, on average, by drug class. We conclude by discussing an illustrative example in psoriasis and psoriatic arthritis and find that the candidate treatment has a high probability of success in a future trial.

Exercise therapy for tendinopathy: a mixed-methods evidence synthesis exploring feasibility, acceptability and effectiveness

Background

Tendinopathy is a common, painful and functionally limiting condition, primarily managed conservatively using exercise therapy.

Review questions

(i) What exercise interventions have been reported in the literature for which tendinopathies? (ii) What outcomes have been reported in studies investigating exercise interventions for tendinopathy? (iii) Which exercise interventions are most effective across all tendinopathies? (iv) Does type/location of tendinopathy or other specific covariates affect which are the most effective exercise therapies? (v) How feasible and acceptable are exercise interventions for tendinopathies?

Methods

A scoping review mapped exercise interventions for tendinopathies and outcomes reported to date (questions i and ii). Thereafter, two contingent systematic review workstreams were conducted. The first investigated a large number of studies and was split into three efficacy reviews that quantified and compared efficacy across different interventions (question iii), and investigated the influence of a range of potential moderators (question iv). The second was a convergent segregated mixed-method review (question v). Searches for studies published from 1998 were conducted in library databases (n = 9), trial registries (n = 6), grey literature databases (n = 5) and Google Scholar. Scoping review searches were completed on 28 April 2020 with efficacy and mixed-method search updates conducted on 19 January 2021 and 29 March 2021.

Results

Scoping review - 555 included studies identified a range of exercise interventions and outcomes across a range of tendinopathies, most commonly Achilles, patellar, lateral elbow and rotator cuff-related shoulder pain. Strengthening exercise was most common, with flexibility exercise used primarily in the upper limb. Disability was the most common outcome measured in Achilles, patellar and rotator cuff-related shoulder pain; physical function capacity was most common in lateral elbow tendinopathy. Efficacy reviews - 204 studies provided evidence that exercise therapy is safe and beneficial, and that patients are generally satisfied with treatment outcome and perceive the improvement to be substantial. In the context of generally low and very low-quality evidence, results identified that: (1) the shoulder may benefit more from flexibility (effect sizeResistance:Flexibility = 0.18 [95% CrI 0.07 to 0.29]) and proprioception (effect sizeResistance:Proprioception = 0.16 [95% CrI -1.8 to 0.32]); (2) when performing strengthening exercise it may be most beneficial to combine concentric and eccentric modes (effect sizeEccentricOnly:Concentric+Eccentric = 0.48 [95% CrI -0.13 to 1.1]; and (3) exercise may be most beneficial when combined with another conservative modality (e.g. injection or electro-therapy increasing effect size by ≈0.1 to 0.3). Mixed-method review - 94 studies (11 qualitative) provided evidence that exercise interventions for tendinopathy can largely be considered feasible and acceptable, and that several important factors should be considered when prescribing exercise for tendinopathy, including an awareness of potential barriers to and facilitators of engaging with exercise, patients' and providers' prior experience and beliefs, and the importance of patient education, self-management and the patient-healthcare professional relationship.

Limitations

Despite a large body of literature on exercise for tendinopathy, there are methodological and reporting limitations that influenced the recommendations that could be made.

Conclusion

The findings provide some support for the use of exercise combined with another conservative modality; flexibility and proprioception exercise for the shoulder; and a combination of eccentric and concentric strengthening exercise across tendinopathies. However, the findings must be interpreted within the context of the quality of the available evidence.

Future work

There is an urgent need for high-quality efficacy, effectiveness, cost-effectiveness and qualitative research that is adequately reported, using common terminology, definitions and outcomes.

Study registration

This project is registered as DOI: 10.11124/JBIES-20-00175 (scoping review); PROSPERO CRD 42020168187 (efficacy reviews); https://osf.io/preprints/sportrxiv/y7sk6/ (efficacy review 1); https://osf.io/preprints/sportrxiv/eyxgk/ (efficacy review 2); https://osf.io/preprints/sportrxiv/mx5pv/ (efficacy review 3); PROSPERO CRD42020164641 (mixed-method review).

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) HTA programme and will be published in full in HTA Journal; Vol. 27, No. 24. See the NIHR Journals Library website for further project information.

Assessing the Effectiveness of Bisphosphonates for the Prevention of Fragility Fractures: An Updated Systematic Review and Network Meta-Analyses

Bisphosphonates have been found to be effective in preventing fragility fractures. However, their comparative effectiveness in populations at risk has yet to be defined. In light of recent clinical trials, we aimed to compare four bisphosphonates (alendronate, ibandronate, risedronate, and zoledronate) and to identify which are the most effective for the prevention of fragility fractures. This is an update of a systematic review previously published as part of a NICE HTA report. We conducted a systematic review and network meta-analysis, updating the estimates regarding the comparative effectiveness of the aforementioned bisphosphonates. Studies identified from published and unpublished sources between 2014 and 2021 were added to the studies identified in the previous review. Screening, data extraction and risk of bias assessment were independently undertaken by two reviewers. Outcomes were fractures, femoral neck bone mineral density (BMD), mortality, and adverse events. We identified 25 additional trials, resulting in a total population of 47,007 participants. All treatments had beneficial effects on fractures versus placebo with zoledronate being the most effective treatment in preventing vertebral fractures (hazard ratio [HR] 0.38; 95% credibility interval [CrI], 0.28-0.49). Zoledronate (HR 0.71; 95% CrI, 0.61-0.81) and risedronate (HR 0.70; 95% CrI, 0.53-0.84) were found to be the most effective treatments in preventing nonvertebral fractures. All treatments were associated with increases in femoral neck BMD versus placebo with zoledronate being the most effective treatment mean difference (MD 4.02; 95% CrI, 3.2-4.84). There was a paucity of data regarding hip and wrist fractures. Depending on its cost-effectiveness, zoledronate could be considered a first-line option for people at increased risk of fragility fractures. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Challenges of modelling approaches for network meta-analysis of time-to-event outcomes in the presence of non-proportional hazards to aid decision making: Application to a melanoma network

BACKGROUND

Synthesis of clinical effectiveness from multiple trials is a well-established component of decision-making. Time-to-event outcomes are often synthesised using the Cox proportional hazards model assuming a constant hazard ratio over time. However, with an increasing proportion of trials reporting treatment effects where hazard ratios vary over time and with differing lengths of follow-up across trials, alternative synthesis methods are needed.

OBJECTIVES

To compare and contrast five modelling approaches for synthesis of time-to-event outcomes and provide guidance on key considerations for choosing between the modelling approaches.

METHODS

The Cox proportional hazards model and five other methods of estimating treatment effects from time-to-event outcomes, which relax the proportional hazards assumption, were applied to a network of melanoma trials reporting overall survival: restricted mean survival time, generalised gamma, piecewise exponential, fractional polynomial and Royston-Parmar models.

RESULTS

All models fitted the melanoma network acceptably well. However, there were important differences in extrapolations of the survival curve and interpretability of the modelling constraints demonstrating the potential for different conclusions from different modelling approaches.

CONCLUSION

The restricted mean survival time, generalised gamma, piecewise exponential, fractional polynomial and Royston-Parmar models can accommodate non-proportional hazards and differing lengths of trial follow-up within a network meta-analysis of time-to-event outcomes. We recommend that model choice is informed using available and relevant prior knowledge, model transparency, graphically comparing survival curves alongside observed data to aid consideration of the reliability of the survival estimates, and consideration of how the treatment effect estimates can be incorporated within a decision model.

Classifying information-sharing methods

BACKGROUND

Sparse relative effectiveness evidence is a frequent problem in Health Technology Assessment (HTA). Where evidence directly pertaining to the decision problem is sparse, it may be feasible to expand the evidence-base to include studies that relate to the decision problem only indirectly: for instance, when there is no evidence on a comparator, evidence on other treatments of the same molecular class could be used; similarly, a decision on children may borrow-strength from evidence on adults. Usually, in HTA, such indirect evidence is either included by ignoring any differences ('lumping') or not included at all ('splitting'). However, a range of more sophisticated methods exists, primarily in the biostatistics literature. The objective of this study is to identify and classify the breadth of the available information-sharing methods.

METHODS

Forwards and backwards citation-mining techniques were used on a set of seminal papers on the topic of information-sharing. Papers were included if they specified (network) meta-analytic methods for combining information from distinct populations, interventions, outcomes or study-designs.

RESULTS

Overall, 89 papers were included. A plethora of evidence synthesis methods have been used for information-sharing. Most papers (n=79) described methods that shared information on relative treatment effects. Amongst these, there was a strong emphasis on methods for information-sharing across multiple outcomes (n=42) and treatments (n=25), with fewer papers focusing on study-designs (n=23) or populations (n=8). We categorise and discuss the methods under four 'core' relationships of information-sharing: functional, exchangeability-based, prior-based and multivariate relationships, and explain the assumptions made within each of these core approaches.

CONCLUSIONS

This study highlights the range of information-sharing methods available. These methods often impose more moderate assumptions than lumping or splitting. Hence, the degree of information-sharing that they impose could potentially be considered more appropriate. Our identification of four 'core' methods of information-sharing allows for an improved understanding of the assumptions underpinning the different methods. Further research is required to understand how the methods differ in terms of the strength of sharing they impose and the implications of this for health care decisions.

Joining the Dots: Linking Disconnected Networks of Evidence Using Dose-Response Model-Based Network Meta-Analysis

BACKGROUND

Network meta-analysis (NMA) synthesizes direct and indirect evidence on multiple treatments to estimate their relative effectiveness. However, comparisons between disconnected treatments are not possible without making strong assumptions. When studies including multiple doses of the same drug are available, model-based NMA (MBNMA) presents a novel solution to this problem by modeling a parametric dose-response relationship within an NMA framework. In this article, we illustrate several scenarios in which dose-response MBNMA can connect and strengthen evidence networks.

METHODS

We created illustrative data sets by removing studies or treatments from an NMA of triptans for migraine relief. We fitted MBNMA models with different dose-response relationships. For connected networks, we compared MBNMA estimates with NMA estimates. For disconnected networks, we compared MBNMA estimates with NMA estimates from an "augmented" network connected by adding studies or treatments back into the data set.

RESULTS

In connected networks, relative effect estimates from MBNMA were more precise than those from NMA models (ratio of posterior SDs NMA v. MBNMA: median = 1.13; range = 1.04-1.68). In disconnected networks, MBNMA provided estimates for all treatments where NMA could not and were consistent with NMA estimates from augmented networks for 15 of 18 data sets. In the remaining 3 of 18 data sets, a more complex dose-response relationship was required than could be fitted with the available evidence.

CONCLUSIONS

Where information on multiple doses is available, MBNMA can connect disconnected networks and increase precision while making less strong assumptions than alternative approaches. MBNMA relies on correct specification of the dose-response relationship, which requires sufficient data at different doses to allow reliable estimation. We recommend that systematic reviews for NMA search for and include evidence (including phase II trials) on multiple doses of agents where available.

Bayesian splines versus fractional polynomials in network meta-analysis

Background

Network meta-analysis (NMA) provides a powerful tool for the simultaneous evaluation of multiple treatments by combining evidence from different studies, allowing for direct and indirect comparisons between treatments. In recent years, NMA is becoming increasingly popular in the medical literature and underlying statistical methodologies are evolving both in the frequentist and Bayesian framework. Traditional NMA models are often based on the comparison of two treatment arms per study. These individual studies may measure outcomes at multiple time points that are not necessarily homogeneous across studies.

Methods

In this article we present a Bayesian model based on B-splines for the simultaneous analysis of outcomes across time points, that allows for indirect comparison of treatments across different longitudinal studies.

Results

We illustrate the proposed approach in simulations as well as on real data examples available in the literature and compare it with a model based on P-splines and one based on fractional polynomials, showing that our approach is flexible and overcomes the limitations of the latter.

Conclusions

The proposed approach is computationally efficient and able to accommodate a large class of temporal treatment effect patterns, allowing for direct and indirect comparisons of widely varying shapes of longitudinal profiles.

Performance of model-based network meta-analysis (MBNMA) of time-course relationships: A simulation study

Time-course model-based network meta-analysis (MBNMA) has been proposed as a framework to combine treatment comparisons from a network of randomized controlled trials reporting outcomes at multiple time-points. This can explain heterogeneity/inconsistency that arises by pooling studies with different follow-up times and allow inclusion of studies from earlier in drug development. The aim of this study is to explore using simulation: (a) how MBNMA model parameters are affected by the quantity/location of observed time-points across studies/comparisons, (b) how reliably an appropriate MBNMA model can be identified, (c) the robustness of model estimates and predictions under different dataset characteristics. Our results indicate that model parameters for a given treatment comparison are estimated with low mean bias even when no direct evidence was available, provided there was sufficient indirect evidence to estimate the time-course. A staged model selection strategy that selects time-course function, then heterogeneity, then covariance structure, identified the true model most reliably and efficiently. Predictions and parameter estimates from selected models had low mean bias even in the presence of high heterogeneity/correlation between time-points. However, failure to properly account for heterogeneity/correlation could lead to high error in precision of the estimates. Time-course MBNMA provides a statistically robust framework for synthesizing direct and indirect evidence to estimate relative effects and predicted mean responses whilst accounting for time-course and incorporating correlation and heterogeneity. This supports the use of MBNMA in evidence synthesis, particularly when additional studies are available with follow-up times that would otherwise prohibit their inclusion by conventional meta-analysis.

Uptake of methodological advances for synthesis of continuous and time-to-event outcomes would maximize use of the evidence base

Objective

The objective of the study is to establish how often continuous and time-to-event outcomes are synthesized in health technology assessment (HTA), the statistical methods and software used in their analysis and how often evidence synthesis informs decision models.

Study Design and Setting

This is a review of National Institute of Health Research HTA reports, National Institute for Health and Care Excellence (NICE) technology appraisals, and NICE guidelines reporting quantitative meta-analysis or network meta-analysis of at least one continuous or time-to-event outcome published from April 01, 2018 to March 31, 2019.

Results

We identified 47 eligible articles. At least one continuous or time-to-event outcome was synthesized in 51% and 55% of articles, respectively. Evidence synthesis results informed decision models in two-thirds of articles. The review and expert knowledge identified five areas where methodology is available for improving the synthesis of continuous and time-to-event outcomes: i) outcomes reported on multiple scales, ii) reporting of multiple related outcomes, iii) appropriateness of the additive scale, iv) reporting of multiple time points, and v) nonproportional hazards. We identified three anticipated barriers to the uptake and implementation of these methods: i) statistical expertise, ii) software, and iii) reporting of trials.

Conclusion

Continuous and time-to-event outcomes are routinely reported in HTA. However, increased uptake of methodological advances could maximize the evidence base used to inform the decision making process.

The dark side of the force: Multiplicity issues in network meta-analysis and how to address them

Standard models for network meta-analysis simultaneously estimate multiple relative treatment effects. In practice, after estimation, these multiple estimates usually pass through a formal or informal selection procedure, eg, when researchers draw conclusions about the effects of the best performing treatment in the network. In this paper, we present theoretical arguments as well as results from simulations to illustrate how such practices might lead to exaggerated and overconfident statements regarding relative treatment effects. We discuss how the issue can be addressed via multilevel Bayesian modelling, where treatment effects are modelled exchangeably, and hence estimates are shrunk away from large values. We present a set of alternative models for network meta-analysis, and we show in simulations that in several scenarios, such models perform better than the usual network meta-analysis model.

Modelling time-course relationships with multiple treatments: Model-based network meta-analysis for continuous summary outcomes

BACKGROUND

Model-based meta-analysis (MBMA) is increasingly used to inform drug-development decisions by synthesising results from multiple studies to estimate treatment, dose-response, and time-course characteristics. Network meta-analysis (NMA) is used in Health Technology Appraisals for simultaneously comparing effects of multiple treatments, to inform reimbursement decisions. Recently, a framework for dose-response model-based network meta-analysis (MBNMA) has been proposed that combines, often nonlinear, MBMA modelling with the statistically robust properties of NMA. Here, we aim to extend this framework to time-course models.

METHODS

We propose a Bayesian time-course MBNMA modelling framework for continuous summary outcomes that allows for nonlinear modelling of multiparameter time-course functions, accounts for residual correlation between observations, preserves randomisation by modelling relative effects, and allows for testing of inconsistency between direct and indirect evidence on the time-course parameters. We demonstrate our modelling framework using an illustrative dataset of 23 trials investigating treatments for pain in osteoarthritis.

RESULTS

Of the time-course functions that we explored, the E_max model gave the best fit to the data and has biological plausibility. Some simplifying assumptions were needed to identify the ET₅₀ , due to few observations at early follow-up times. Treatment estimates were robust to the inclusion of correlations in the likelihood.

CONCLUSIONS

Time-course MBNMA provides a statistically robust framework for synthesising evidence on multiple treatments at multiple time points. The use of placebo-controlled studies in drug-development means there is limited potential for inconsistency. The methods can inform drug-development decisions and provide the rigour needed in the reimbursement decision-making process.

A comparative review of network meta-analysis models in longitudinal randomized controlled trial

Network meta-analysis (NMA) technique extends the standard meta-analysis methods, allowing pairwise comparison of all treatments in a network in the absence of head-to-head comparisons. Traditional NMA models consider a single endpoint for each trial. However, in many cases, trials in the network have different durations and/or report data at multiple time points. Moreover, these time points are often not the same for all trials. In this work, we review the most relevant methods that incorporate multiple time points and allow indirect comparisons of treatment effects across different longitudinal studies. In particular, we focus on the mixed treatment comparison developed by Dakin et al,[10] on the Bayesian evidence synthesis techniques-integrated two-component prediction developed by Ding et al,[11] and on the more recent method based on fractional polynomials by Jansen et al.[12] We highlight the main features of each model and illustrate them in simulations and in a real data application. Our study shows that methods based on fractional polynomials offer a flexible modeling strategy in most applications.

Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review

BACKGROUND

Rigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis.

METHODS

We undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios.

RESULTS

For missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally performed better than omitting trials. When estimating missing means, a formula using the median, lower quartile and upper quartile performed best in preserving the precision of the meta-analysis findings, although in some scenarios, omitting trials gave superior results.

CONCLUSIONS

Methods based on summary statistics (minimum, maximum, lower quartile, upper quartile, median) reported in the literature facilitate more comprehensive inclusion of randomised controlled trials with missing mean or variability summary statistics within meta-analyses.

A systematic review, evidence synthesis and meta-analysis of quantitative and qualitative studies evaluating the clinical effectiveness, the cost-effectiveness, safety and acceptability of interventions to prevent postnatal depression

BACKGROUND

Postnatal depression (PND) is a major depressive disorder in the year following childbirth, which impacts on women, their infants and their families. A range of interventions has been developed to prevent PND.

OBJECTIVES

To (1) evaluate the clinical effectiveness, cost-effectiveness, acceptability and safety of antenatal and postnatal interventions for pregnant and postnatal women to prevent PND; (2) apply rigorous methods of systematic reviewing of quantitative and qualitative studies, evidence synthesis and decision-analytic modelling to evaluate the preventive impact on women, their infants and their families; and (3) estimate cost-effectiveness.

DATA SOURCES

We searched MEDLINE, EMBASE, Science Citation Index and other databases (from inception to July 2013) in December 2012, and we were updated by electronic alerts until July 2013.

REVIEW METHODS

Two reviewers independently screened titles and abstracts with consensus agreement. We undertook quality assessment. All universal, selective and indicated preventive interventions for pregnant women and women in the first 6 postnatal weeks were included. All outcomes were included, focusing on the Edinburgh Postnatal Depression Scale (EPDS), diagnostic instruments and infant outcomes. The quantitative evidence was synthesised using network meta-analyses (NMAs). A mathematical model was constructed to explore the cost-effectiveness of interventions contained within the NMA for EPDS values.

RESULTS

From 3072 records identified, 122 papers (86 trials) were included in the quantitative review. From 2152 records, 56 papers (44 studies) were included in the qualitative review. The results were inconclusive. The most beneficial interventions appeared to be midwifery redesigned postnatal care [as shown by the mean 12-month EPDS score difference of -1.43 (95% credible interval -4.00 to 1.36)], person-centred approach (PCA)-based and cognitive-behavioural therapy (CBT)-based intervention (universal), interpersonal psychotherapy (IPT)-based intervention and education on preparing for parenting (selective), promoting parent-infant interaction, peer support, IPT-based intervention and PCA-based and CBT-based intervention (indicated). Women valued seeing the same health worker, the involvement of partners and access to several visits from a midwife or health visitor trained in person-centred or cognitive-behavioural approaches. The most cost-effective interventions were estimated to be midwifery redesigned postnatal care (universal), PCA-based intervention (indicated) and IPT-based intervention in the sensitivity analysis (indicated), although there was considerable uncertainty. Expected value of partial perfect information (EVPPI) for efficacy data was in excess of £150M for each population. Given the EVPPI values, future trials assessing the relative efficacies of promising interventions appears to represent value for money.

LIMITATIONS

In the NMAs, some trials were omitted because they could not be connected to the main network of evidence or did not provide EPDS scores. This may have introduced reporting or selection bias. No adjustment was made for the lack of quality of some trials. Although we appraised a very large number of studies, much of the evidence was inconclusive.

CONCLUSIONS

Interventions warrant replication within randomised controlled trials (RCTs). Several interventions appear to be cost-effective relative to usual care, but this is subject to considerable uncertainty.

FUTURE WORK RECOMMENDATIONS

Several interventions appear to be cost-effective relative to usual care, but this is subject to considerable uncertainty. Future research conducting RCTs to establish which interventions are most clinically effective and cost-effective should be considered.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42012003273.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Network meta-analysis: application and practice using Stata

This review aimed to arrange the concepts of a network meta-analysis (NMA) and to demonstrate the analytical process of NMA using Stata software under frequentist framework. The NMA tries to synthesize evidences for a decision making by evaluating the comparative effectiveness of more than two alternative interventions for the same condition. Before conducting a NMA, 3 major assumptions—similarity, transitivity, and consistency—should be checked. The statistical analysis consists of 5 steps. The first step is to draw a network geometry to provide an overview of the network relationship. The second step checks the assumption of consistency. The third step is to make the network forest plot or interval plot in order to illustrate the summary size of comparative effectiveness among various interventions. The fourth step calculates cumulative rankings for identifying superiority among interventions. The last step evaluates publication bias or effect modifiers for a valid inference from results. The synthesized evidences through five steps would be very useful to evidence-based decision-making in healthcare. Thus, NMA should be activated in order to guarantee the quality of healthcare system.

The Clinical Effectiveness of Ranibizumab Treat and Extend Regimen in nAMD: Systematic Review and Network Meta-Analysis

Introduction

Neovascular age-related macular degeneration (nAMD) is a chronic eye condition that causes severe deterioration of vision and ultimately blindness. Two vascular endothelial growth factor inhibitors are approved for nAMD treatment in Europe: ranibizumab and aflibercept. The European license for ranibizumab was updated with an individualized “treat and extend” (T&E) regimen, which involves more proactive treatment based on changes in best corrected visual acuity (BCVA) and/or anatomical outcomes. The aim of this publication is to compare the efficacy of the ranibizumab T&E regimen with other approved dosing regimens for nAMD on the basis of outcomes identified from a systematic review and subsequent NMA.

Methods

Following a systematic search of publications, to identify relevant studies, a repeated-measures network meta-analysis (NMA) was performed to estimate the relative effectiveness of ranibizumab T&E versus approved dosing regimens of ranibizumab and aflibercept. The analysis focused on licensed treatment regimens for nAMD. We examined mean change from baseline in BCVA on the Early Treatment Diabetic Retinopathy Study (ETDRS) chart.

Results

The systematic literature review identified 22,949 records, of which 23 studies were included in the NMA. At 12 months, the ranibizumab T&E dosing regimen vs ranibizumab pro re nata (PRN) was associated with small differences in change in BCVA, between 1.86 letter gain at 12 months and 2.35 letter gain at 24 months. A similar difference was observed in the aflibercept dosing regimen versus ranibizumab T&E ; 1.94 letter gain at 12 months and 3.31 letter gain at 24 months. All doses of ranibizumab and aflibercept showed similar effectiveness, and the differences between treatment options were not significant.

Conclusion

This study used novel repeated-measures NMA to synthesize efficacy results when treatment effects were reported at multiple follow-up times. This repeated-measures NMA suggests that treating patients with the ranibizumab T&E regimen yields similar effectiveness compared to other approved ranibizumab and aflibercept dosing regimens for nAMD treatment.

Funding: Novartis Pharmaceuticals UK Ltd, Surrey, UK.

Electronic supplementary material

The online version of this article (doi:10.1007/s12325-017-0484-0) contains supplementary material, which is available to authorized users.

Acupuncture for chronic pain and depression in primary care: a programme of research

Background

There has been an increase in the utilisation of acupuncture in recent years, yet the evidence base is insufficiently well established to be certain about its clinical effectiveness and cost-effectiveness. Addressing the questions related to the evidence base will reduce uncertainty and help policy- and decision-makers with regard to whether or not wider access is appropriate and provides value for money.

Aim

Our aim was to establish the most reliable evidence on the clinical effectiveness and cost-effectiveness of acupuncture for chronic pain by drawing on relevant evidence, including recent high-quality trials, and to develop fresh evidence on acupuncture for depression. To extend the evidence base we synthesised the results of published trials using robust systematic review methodology and conducted a randomised controlled trial (RCT) of acupuncture for depression.

Methods and results

We synthesised the evidence from high-quality trials of acupuncture for chronic pain, consisting of musculoskeletal pain related to the neck and low back, osteoarthritis of the knee, and headache and migraine, involving nearly 18,000 patients. In an individual patient data (IPD) pairwise meta-analysis, acupuncture was significantly better than both sham acupuncture (p < 0.001) and usual care (p < 0.001) for all conditions. Using network meta-analyses, we compared acupuncture with other physical therapies for osteoarthritis of the knee. In both an analysis of all available evidence and an analysis of a subset of better-quality trials, using aggregate-level data, we found acupuncture to be one of the more effective therapies. We developed new Bayesian methods for analysing multiple individual patient-level data sets to evaluate heterogeneous continuous outcomes. An accompanying cost-effectiveness analysis found transcutaneous electrical nerve stimulation (TENS) to be cost-effective for osteoarthritis at a threshold of £20,000 per quality-adjusted life-year when all trials were synthesised. When the analysis was restricted to trials of higher quality with adequate allocation concealment, acupuncture was cost-effective. In a RCT of acupuncture or counselling compared with usual care for depression, in which half the patients were also experiencing comorbid pain, we found acupuncture and counselling to be clinically effective and acupuncture to be cost-effective. For patients in whom acupuncture is inappropriate or unavailable, counselling is cost-effective.

Conclusion

We have provided the most robust evidence from high-quality trials on acupuncture for chronic pain. The synthesis of high-quality IPD found that acupuncture was more effective than both usual care and sham acupuncture. Acupuncture is one of the more clinically effective physical therapies for osteoarthritis and is also cost-effective if only high-quality trials are analysed. When all trials are analysed, TENS is cost-effective. Promising clinical and economic evidence on acupuncture for depression needs to be extended to other contexts and settings. For the conditions we have investigated, the drawing together of evidence on acupuncture from this programme of research has substantially reduced levels of uncertainty. We have identified directions for further research. Our research also provides a valuable basis for considering the potential role of acupuncture as a referral option in health care and enabling providers and policy-makers to make decisions based on robust sources of evidence.

Trial registration

Current Controlled Trials ISRCTN63787732.

Funding

The National Institute for Health Research Programme Grants for Applied Research programme.

The Cost-Effectiveness of Ranibizumab Treat and Extend Regimen Versus Aflibercept in the UK

INTRODUCTION

Wet age-related macular degeneration (AMD) is a chronic eye condition that causes severe deterioration of vision and even blindness. Current wet AMD treatment in the UK involves the vascular endothelial growth factor inhibitors ranibizumab and aflibercept. Patients with wet AMD require frequent and long-term monitoring for treatment to be effective, contributing to a substantial resource burden at wet AMD centers. The European license for ranibizumab was recently updated with an individualized 'treat and extend' (T&E) regimen, comprising a structured monitoring and treatment protocol. This study evaluated the cost-effectiveness of ranibizumab T&E versus aflibercept within a UK setting.

METHODS

An individual patient-level simulation model was developed utilizing treatment effects from a network meta-analysis of randomized controlled trials. The model was conducted from a UK National Health Service (NHS) perspective over a lifetime horizon and the base case utilized probabilistic sensitivity analysis to assess uncertainty in the model. Additional scenario analyses were conducted to assess the impact of changes to the model inputs.

RESULTS

Ranibizumab T&E was found to be more effective and less costly than aflibercept, providing, on average, an additional 1.058 quality-adjusted life years (QALYs) and a cost-saving of £19,604 over a lifetime horizon. At list price, ranibizumab T&E was found to be cost-effective versus aflibercept in 100% of simulations at a willingness-to-pay threshold of £20,000 per QALY. The robustness of the results was tested in several scenario analyses; ranibizumab T&E was found to be more effective, and less costly, than aflibercept in the vast majority of cases.

CONCLUSION

This evaluation suggests that treating patients with ranibizumab according to the T&E regimen could be a better use of NHS resources than aflibercept, and could, therefore, be considered as a first-line regimen for patients with wet AMD in the UK.

FUNDING

Novartis Pharmaceuticals UK Limited.

GetReal in network meta-analysis: a review of the methodology

Pairwise meta-analysis is an established statistical tool for synthesizing evidence from multiple trials, but it is informative only about the relative efficacy of two specific interventions. The usefulness of pairwise meta-analysis is thus limited in real-life medical practice, where many competing interventions may be available for a certain condition and studies informing some of the pairwise comparisons may be lacking. This commonly encountered scenario has led to the development of network meta-analysis (NMA). In the last decade, several applications, methodological developments, and empirical studies in NMA have been published, and the area is thriving as its relevance to public health is increasingly recognized. This article presents a review of the relevant literature on NMA methodology aiming to pinpoint the developments that have appeared in the field. Copyright © 2016 John Wiley & Sons, Ltd.

Accounting for correlation in network meta-analysis with multi-arm trials

Multi-arm trials (trials with more than two arms) are particularly valuable forms of evidence for network meta-analysis (NMA). Trial results are available either as arm-level summaries, where effect measures are reported for each arm, or as contrast-level summaries, where the differences in effect between arms compare with the control arm chosen for the trial. We show that likelihood-based inference in both contrast-level and arm-level formats is identical if there are only two-arm trials, but that if there are multi-arm trials, results from the contrast-level format will be incorrect unless correlations are accounted for in the likelihood. We review Bayesian and frequentist software for NMA with multi-arm trials that can account for this correlation and give an illustrative example of the difference in estimates that can be introduced if the correlations are not incorporated. We discuss methods of imputing correlations when they cannot be derived from the reported results and urge trialists to report the standard error for the control arm even if only contrast-level summaries are reported. Copyright © 2012 John Wiley & Sons, Ltd.

Network meta-analysis of longitudinal data using fractional polynomials

Network meta-analysis of randomized controlled trials (RCTs) are often based on one treatment effect measure per study. However, many studies report data at multiple time points. Furthermore, not all studies measure the outcomes at the same time points. As an alternative to a network meta-analysis based on a synthesis of the results at one time point, a network meta-analysis method is presented that allows for the simultaneous analysis of outcomes at multiple time points. The development of outcomes over time of interventions compared in an RCT is modeled with fractional polynomials, and the differences between the parameters of these polynomials within a trial are synthesized across studies with a Bayesian network meta-analysis. The proposed models are illustrated with an analysis of RCTs evaluating interventions for osteoarthritis of the knee. Fixed and random effects second order fractional polynomials were applied to the case study. Network meta-analysis with models that represent the treatment effects in terms of several parameters using fractional polynomials can be considered a useful addition to models for network meta-analysis of repeated measures previously proposed. When RCTs report treatment effects at multiple follow-up times, these models can be used to synthesize the results even if reporting times differ across the studies.

Network meta-analysis: development of a three-level hierarchical modeling approach incorporating dose-related constraints

BACKGROUND

Network meta-analysis (NMA) is commonly used in evidence synthesis; however, in situations in which there are a large number of treatment options, which may be subdivided into classes, and relatively few trials, NMAs produce considerable uncertainty in the estimated treatment effects, and consequently, identification of the most beneficial intervention remains inconclusive.

OBJECTIVE

To develop and demonstrate the use of evidence synthesis methods to evaluate extensive treatment networks with a limited number of trials, making use of classes.

METHODS

Using Bayesian Markov chain Monte Carlo methods, we build on the existing work of a random effects NMA to develop a three-level hierarchical NMA model that accounts for the exchangeability between treatments within the same class as well as for the residual between-study heterogeneity. We demonstrate the application of these methods to a continuous and binary outcome, using a motivating example of overactive bladder. We illustrate methods for incorporating ordering constraints in increasing doses, model selection, and assessing inconsistency between the direct and indirect evidence.

RESULTS

The methods were applied to a data set obtained from a systematic literature review of trials for overactive bladder, evaluating the mean reduction in incontinence episodes from baseline and the number of patients reporting one or more adverse events. The data set involved 72 trials comparing 34 interventions that were categorized into nine classes of interventions, including placebo.

CONCLUSIONS

Bayesian three-level hierarchical NMAs have the potential to increase the precision in the effect estimates while maintaining the interpretability of the individual interventions for decision making.

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes

Background

Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes.

Methods

The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations.

Results

Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis.

Conclusions

Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately.

The effectiveness and risks of bariatric surgery: an updated systematic review and meta-analysis, 2003-2012

IMPORTANCE

The prevalence of obesity and outcomes of bariatric surgery are well established. However, analyses of the surgery impact have not been updated and comprehensively investigated since 2003.

OBJECTIVE

To examine the effectiveness and risks of bariatric surgery using up-to-date, comprehensive data and appropriate meta-analytic techniques.

DATA SOURCES

Literature searches of Medline, Embase, Scopus, Current Contents, Cochrane Library, and Clinicaltrials.gov between 2003 and 2012 were performed.

STUDY SELECTION

Exclusion criteria included publication of abstracts only, case reports, letters, comments, or reviews; animal studies; languages other than English; duplicate studies; no surgical intervention; and no population of interest. Inclusion criteria were a report of surgical procedure performed and at least 1 outcome of interest resulting from the studied surgery was reported: comorbidities, mortality, complications, reoperations, or weight loss. Of the 25,060 initially identified articles, 24,023 studies met the exclusion criteria, and 259 met the inclusion criteria.

DATA EXTRACTION AND SYNTHESIS

A review protocol was followed throughout. Three reviewers independently reviewed studies, abstracted data, and resolved disagreements by consensus. Studies were evaluated for quality.

MAIN OUTCOMES AND MEASURES

Mortality, complications, reoperations, weight loss, and remission of obesity-related diseases.

RESULTS

A total of 164 studies were included (37 randomized clinical trials and 127 observational studies). Analyses included 161,756 patients with a mean age of 44.56 years and body mass index of 45.62. We conducted random-effects and fixed-effect meta-analyses and meta-regression. In randomized clinical trials, the mortality rate within 30 days was 0.08% (95% CI, 0.01%-0.24%); the mortality rate after 30 days was 0.31% (95% CI, 0.01%-0.75%). Body mass index loss at 5 years postsurgery was 12 to 17. The complication rate was 17% (95% CI, 11%-23%), and the reoperation rate was 7% (95% CI, 3%-12%). Gastric bypass was more effective in weight loss but associated with more complications. Adjustable gastric banding had lower mortality and complication rates; yet, the reoperation rate was higher and weight loss was less substantial than gastric bypass. Sleeve gastrectomy appeared to be more effective in weight loss than adjustable gastric banding and comparable with gastric bypass.

CONCLUSIONS AND RELEVANCE

Bariatric surgery provides substantial and sustained effects on weight loss and ameliorates obesity-attributable comorbidities in the majority of bariatric patients, although risks of complication, reoperation, and death exist. Death rates were lower than those reported in previous meta-analyses.

The effectiveness and risks of bariatric surgery: an updated systematic review and meta-analysis, 2003-2012

IMPORTANCE

The prevalence of obesity and outcomes of bariatric surgery are well established. However, analyses of the surgery impact have not been updated and comprehensively investigated since 2003.

OBJECTIVE

To examine the effectiveness and risks of bariatric surgery using up-to-date, comprehensive data and appropriate meta-analytic techniques.

DATA SOURCES

Literature searches of Medline, Embase, Scopus, Current Contents, Cochrane Library, and Clinicaltrials.gov between 2003 and 2012 were performed.

STUDY SELECTION

Exclusion criteria included publication of abstracts only, case reports, letters, comments, or reviews; animal studies; languages other than English; duplicate studies; no surgical intervention; and no population of interest. Inclusion criteria were a report of surgical procedure performed and at least 1 outcome of interest resulting from the studied surgery was reported: comorbidities, mortality, complications, reoperations, or weight loss. Of the 25,060 initially identified articles, 24,023 studies met the exclusion criteria, and 259 met the inclusion criteria.

DATA EXTRACTION AND SYNTHESIS

A review protocol was followed throughout. Three reviewers independently reviewed studies, abstracted data, and resolved disagreements by consensus. Studies were evaluated for quality.

MAIN OUTCOMES AND MEASURES

Mortality, complications, reoperations, weight loss, and remission of obesity-related diseases.

RESULTS

A total of 164 studies were included (37 randomized clinical trials and 127 observational studies). Analyses included 161,756 patients with a mean age of 44.56 years and body mass index of 45.62. We conducted random-effects and fixed-effect meta-analyses and meta-regression. In randomized clinical trials, the mortality rate within 30 days was 0.08% (95% CI, 0.01%-0.24%); the mortality rate after 30 days was 0.31% (95% CI, 0.01%-0.75%). Body mass index loss at 5 years postsurgery was 12 to 17. The complication rate was 17% (95% CI, 11%-23%), and the reoperation rate was 7% (95% CI, 3%-12%). Gastric bypass was more effective in weight loss but associated with more complications. Adjustable gastric banding had lower mortality and complication rates; yet, the reoperation rate was higher and weight loss was less substantial than gastric bypass. Sleeve gastrectomy appeared to be more effective in weight loss than adjustable gastric banding and comparable with gastric bypass.

CONCLUSIONS AND RELEVANCE

Bariatric surgery provides substantial and sustained effects on weight loss and ameliorates obesity-attributable comorbidities in the majority of bariatric patients, although risks of complication, reoperation, and death exist. Death rates were lower than those reported in previous meta-analyses.

Review of mixed treatment comparisons in published systematic reviews shows marked increase since 2009

OBJECTIVES

To identify and summarize published systematic reviews that report results of meta-analyses that combined direct and indirect comparisons.

STUDY DESIGN AND SETTING

Narrative review of mixed treatment comparisons (MTCs) reported in systematic reviews of health interventions. MEDLINE, MEDLINE In-Process, Embase, CINAHL, DARE, the Cochrane Database of Systematic Reviews, and SIGLE were searched for reviews published up to June 2012 in which a meta-analysis had been conducted that combined direct and indirect comparisons among more than two interventions.

RESULTS

Reviews reporting MTCs are difficult to identify when searching major databases. These databases offer no way to identify MTCs, and authors use various names when reporting them. Of the 201 eligible reviews identified, more than three-quarters had been published in full. MTC methods have been used to study a wide range of clinical topics. The reported use of these methods has increased rapidly since 2009, and results from MTCs are commonly used in health policy decisions, through the evidence considered in health technology assessments.

CONCLUSION

In view of the increasing use of MTCs, indexing of this study type in databases and a consensus on terminology and standards for conduct and reporting would be timely.

Assessing key assumptions of network meta-analysis: a review of methods

BACKGROUND

Homogeneity and consistency assumptions underlie network meta-analysis (NMA). Methods exist to assess the assumptions but they are rarely and poorly applied. We review and illustrate methods to assess homogeneity and consistency.

METHODS

Eligible articles focussed on indirect comparison or NMA methodology. Articles were sought by hand-searching and scanning references (March 2013). Assumption assessment methods described in the articles were reviewed, and applied to compare anti-malarial drugs.

RESULTS

116 articles were included. Methods to assess homogeneity were: comparing characteristics across trials; comparing trial-specific treatment effects; using hypothesis tests or statistical measures; applying fixed-effect and random-effects pair-wise meta-analysis; and investigating treatment effect-modifiers. Methods to assess consistency were: comparing characteristics; investigating treatment effect-modifiers; comparing outcome measurements in the referent group; node-splitting; inconsistency modelling; hypothesis tests; back transformation; multidimensional scaling; a two-stage approach; and a graph-theoretical method. For the malaria example, heterogeneity existed for some comparisons that was unexplained by investigating treatment effect-modifiers. Inconsistency was detected using node-splitting and inconsistency modelling. It was unclear whether the covariates explained the inconsistency.

CONCLUSIONS

Presently, we advocate applying existing assessment methods collectively to gain the best understanding possible regarding whether assumptions are reasonable. In our example, consistency was questionable; therefore the NMA results may be unreliable.

Tocolytic therapy for preterm delivery: systematic review and network meta-analysis

OBJECTIVE

To determine the most effective tocolytic agent at delaying delivery.

DESIGN

Systematic review and network meta-analysis.

DATA SOURCES

Cochrane Central Register of Controlled Trials, Medline, Medline In-Process, Embase, and CINAHL up to 17 February 2012.

STUDY SELECTION

Randomised controlled trials of tocolytic therapy in women at risk of preterm delivery.

DATA EXTRACTION

At least two reviewers extracted data on study design, characteristics, number of participants, and outcomes reported (neonatal and maternal). A network meta-analysis was done using a random effects model with drug class effect. Two sensitivity analyses were carried out for the primary outcome; restricted to studies at low risk of bias and restricted to studies excluding women at high risk of preterm delivery (those with multiple gestation and ruptured membranes).

RESULTS

Of the 3263 titles initially identified, 95 randomized controlled trials of tocolytic therapy were reviewed. Compared with placebo, the probability of delivery being delayed by 48 hours was highest with prostaglandin inhibitors (odds ratio 5.39, 95% credible interval 2.14 to 12.34) followed by magnesium sulfate (2.76, 1.58 to 4.94), calcium channel blockers (2.71, 1.17 to 5.91), beta mimetics (2.41, 1.27 to 4.55), and the oxytocin receptor blocker atosiban (2.02, 1.10 to 3.80). No class of tocolytic was significantly superior to placebo in reducing neonatal respiratory distress syndrome. Compared with placebo, side effects requiring a change of medication were significantly higher for beta mimetics (22.68, 7.51 to 73.67), magnesium sulfate (8.15, 2.47 to 27.70), and calcium channel blockers (3.80, 1.02 to 16.92). Prostaglandin inhibitors and calcium channel blockers were the tocolytics with the best probability of being ranked in the top three medication classes for the outcomes of 48 hour delay in delivery, respiratory distress syndrome, neonatal mortality, and maternal side effects (all cause).

CONCLUSIONS

Prostaglandin inhibitors and calcium channel blockers had the highest probability of delaying delivery and improving neonatal and maternal outcomes.

Multiple treatment comparisons in a series of anti-malarial trials with an ordinal primary outcome and repeated treatment evaluations

BACKGROUND

Artemisinin-based combination therapies (ACT) are widely used in African countries, including Cameroon. Between 2005 and 2007, five randomized studies comparing different treatment arms among artesunate-amodiaquine and other ACT were conducted in Cameroonian children aged two to 60 months who had uncomplicated Plasmodium falciparum malaria. In these studies, the categorical criterion proposed by the World Health Organization (WHO) to assess the relative effectiveness of anti-malarial drugs was repeatedly evaluated on Days 14, 21 and 28 after treatment initiation. The aim of the present study was to compare the effects of different treatments on this repeated ordinal outcome, hence using the fully available information.

METHODS

The quantitative synthesis was based on individual patient data. Due to the incomplete block design concerning treatment arms between different trials, a mixed treatment comparison (MTC) meta-analysis approach was adopted. The repeated ordinal outcome was modelled through a latent variable, as a proportional odds mixed model with trial, period and treatment arms as covariates. The model was further complexified to account for the variance heterogeneity, and the individual log-residual variance was modelled as a linear mixed model, as well. The effects of individual covariates at inclusion, such as parasitaemia, fever, gender and weight, were also tested. Model parameters were estimated using a Bayesian approach via the WinBUGS software. After selecting the best model using Deviance Information Criterion (DIC), mixed treatment comparisons were based on the estimated treatment effects.

RESULTS

Modeling the residual variance improved the model ability to adjust the data. The results showed that, compared to artesunate-amodiaquine (ASAQ), dihydroartemisinin-piperaquine (DHPP) was significantly more efficacious. Artesunate-chlorproguanil-dapsone (ASCD) was less efficacious than artesunate-sulphadoxine-pyrimethamine (ASSP), artemether-lumefantrine (AMLM) and DHPP, the difference with the latter being significant. No difference in efficacy was found between ASAQ and AMLM.

CONCLUSIONS

Bayesian mixed treatment comparisons of a network of connected randomized trials with repeated measurements of the primary categorical outcome allowed to take into account both the individual- and between- studies sources of heterogeneity. The results of the present study complete the previous quantitative review based on a binary outcome at a fixed time point, suggesting that DHPP represents an alternative for the treatment of uncomplicated P. falciparum malaria in Cameroonian children.