Meta-analysis of individual patient data from randomised trials: a review of methods used in practice

Background: Meta-analyses based on individual patient data (IPD) are regarded as the gold standard for systematic reviews. However, the methods used for analysing and presenting results from IPD meta-analyses have received little discussion. Methods We review 44 IPD meta-analyses published during the years 1999–2001. We summarize whether they obtained all the data they sought, what types of approaches were used in the analysis, including assumptions of common or random effects, and how they examined the effects of covariates. Results: Twenty-four out of 44 analyses focused on time-to-event outcomes, and most analyses (28) estimated treatment effects within each trial and then combined the results assuming a common treatment effect across trials. Three analyses failed to stratify by trial, analysing the data is if they came from a single mega-trial. Only nine analyses used random effects methods. Covariate-treatment interactions were generally investigated by subgrouping patients. Seven of the meta-analyses included data from less than 80% of the randomized patients sought, but did not address the resulting potential biases. Conclusions: Although IPD meta-analyses have many advantages in assessing the effects of health care, there are several aspects that could be further developed to make fuller use of the potential of these time-consuming projects. In particular, IPD could be used to more fully investigate the influence of covariates on heterogeneity of treatment effects, both within and between trials. The impact of heterogeneity, or use of random effects, are seldom discussed. There is thus considerable scope for enhancing the methods of analysis and presentation of IPD meta-analysis.

Variance estimation for systematic sampling from deliberately ordered populations

The systematic sampling (SYS) design (Madow and Madow, 1944) is widely used by statistical offices due to its simplicity and efficiency (e.g., Iachan, 1982). But it suffers from a serious defect, namely, that it is impossible to unbiasedly estimate the sampling variance (Iachan, 1982) and usual variance estimators (Yates and Grundy, 1953) are inadequate and can overestimate the variance significantly (Särndal et al., 1992). We propose a novel variance estimator which is less biased and that can be implemented with any given population order. We will justify this estimator theoretically and with a Monte Carlo simulation study.

Efficient and accurate experimental design for enzyme kinetics: Bayesian studies reveal a systematic approach

In areas such as drug development, clinical diagnosis and biotechnology research, acquiring details about the kinetic parameters of enzymes is crucial. The correct design of an experiment is critical to collecting data suitable for analysis, modelling and deriving the correct information. As classical design methods are not targeted to the more complex kinetics being frequently studied, attention is needed to estimate parameters of such models with low variance. We demonstrate that a Bayesian approach (the use of prior knowledge) can produce major gains quantifiable in terms of information, productivity and accuracy of each experiment. Developing the use of Bayesian Utility functions, we have used a systematic method to identify the optimum experimental designs for a number of kinetic model data sets. This has enabled the identification of trends between kinetic model types, sets of design rules and the key conclusion that such designs should be based on some prior knowledge of K-M and/or the kinetic model. We suggest an optimal and iterative method for selecting features of the design such as the substrate range, number of measurements and choice of intermediate points. The final design collects data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. (C) 2003 Elsevier Science B.V. All rights reserved.

Evidence of systematic approaches to innovation in facilities management

Purpose – This paper seeks to examine the nature of “service innovation” in the facilities management (FM) context. It reviews recent thinking on “service innovation” as distinct from “product innovation”. Applying these contemporary perspectives it describes UK case studies of 11 innovations in different FM organisations. These include both in-house client-based innovations and third-party innovations. Design/methodology/approach – The study described in the paper encompasses 11 different innovations that constitute a mix of process, product and practice innovations. All of the innovations stem from UK-based organisations that were subject to in-depth interviews regarding the identification, screening, commitment of resources and implementation of the selected innovations. Findings – The research suggested that service innovation is highly active in the UK FM sector. However, the process of innovation rarely followed a common formalized path. Generally, the innovations were one-shot commitments at the early stage. None of the innovations studied failed to proceed to full adoption stage. This was either due to the reluctance of participating organisations to volunteer “tested but unsuccessful” innovations or the absence of any trial methods that might have exposed an innovations shortcomings. Research limitations/implications – The selection of innovations was restricted to the UK context. Moreover, the choice of innovations was partly determined by the innovating organisation. This selection process appeared to emphasise “one-shot” high profile technological innovations, typically associated with software. This may have been at the expense of less resource intensive, bottom-up innovations. Practical implications – This paper suggests that there is a role for “research and innovation” teams within larger FM organisations, whether they are client-based or third-party. Central to this philosophy is an approach that is open to the possibility of failure. The innovations studied were risk averse with a firm commitment to proceed at the early stage. Originality/value – This paper introduces new thinking on the subject of “service innovation” to the context of FM. It presents research and development as a planned solution to innovation. This approach will enable service organisations to fully test and exploit service innovations.

Which drugs cause preventable admissions to hospital? A systematic review

Aim: Previous systematic reviews have found that drug-related morbidity accounts for 4.3% of preventable hospital admissions. None, however, has identified the drugs most commonly responsible for preventable hospital admissions. The aims of this study were to estimate the percentage of preventable drug-related hospital admissions, the most common drug causes of preventable hospital admissions and the most common underlying causes of preventable drug-related admissions. Methods: Bibliographic databases and reference lists from eligible articles and study authors were the sources for data. Seventeen prospective observational studies reporting the proportion of preventable drug-related hospital admissions, causative drugs and/or the underlying causes of hospital admissions were selected. Included studies used multiple reviewers and/or explicit criteria to assess causality and preventability of hospital admissions. Two investigators abstracted data from all included studies using a purpose-made data extraction form. Results: From 13 papers the median percentage of preventable drug-related admissions to hospital was 3.7% (range 1.4-15.4). From nine papers the majority (51%) of preventable drug-related admissions involved either antiplatelets (16%), diuretics (16%), nonsteroidal anti-inflammatory drugs (11%) or anticoagulants (8%). From five studies the median proportion of preventable drug-related admissions associated with prescribing problems was 30.6% (range 11.1-41.8), with adherence problems 33.3% (range 20.9-41.7) and with monitoring problems 22.2% (range 0-31.3). Conclusions: Four groups of drugs account for more than 50% of the drug groups associated with preventable drug-related hospital admissions. Concentrating interventions on these drug groups could reduce appreciably the number of preventable drug-related admissions to hospital from primary care.

Childhood obesity: should primary school children be routinely screened? A systematic review and discussion of the evidence

Background: Population monitoring has been introduced in UK primary schools in an effort to track the growing obesity epidemic. It has been argued that parents should be informed of their child's results, but is there evidence that moving from monitoring to screening would be effective? We describe what is known about the effectiveness of monitoring and screening for overweight and obesity in primary school children and highlight areas where evidence is lacking and research should be prioritised. Design: Systematic review with discussion of evidence gaps and future research. Data sources: Published and unpublished studies ( any language) from electronic databases ( inception to July 2005), clinical experts, Primary Care Trusts and Strategic Health Authorities, and reference lists of retrieved studies. Review methods: We included any study that evaluated measures of overweight and obesity as part of a population-level assessment and excluded studies whose primary outcome measure was prevalence. Results: There were no trials assessing the effectiveness of monitoring or screening for overweight and obesity. Studies focussed on the diagnostic accuracy of measurements. Information on the attitudes of children, parents and health professionals to monitoring was extremely sparse. Conclusions: Our review found a lack of data on the potential impact of population monitoring or screening for obesity and more research is indicated. Identification of effective weight reduction strategies for children and clarification of the role of preventative measures are priorities. It is difficult to see how screening to identify individual children can be justified without effective interventions.

A systematic review of the routine monitoring of growth in children of primary school age to identify growth-related conditions

Objectives: To clarify the role of growth monitoring in primary school children, including obesity, and to examine issues that might impact on the effectiveness and cost-effectiveness of such programmes. Data sources: Electronic databases were searched up to July 2005. Experts in the field were also consulted. Review methods: Data extraction and quality assessment were performed on studies meeting the review's inclusion criteria. The performance of growth monitoring to detect disorders of stature and obesity was evaluated against National Screening Committee (NSC) criteria. Results: In the 31 studies that were included in the review, there were no controlled trials of the impact of growth monitoring and no studies of the diagnostic accuracy of different methods for growth monitoring. Analysis of the studies that presented a 'diagnostic yield' of growth monitoring suggested that one-off screening might identify between 1: 545 and 1: 1793 new cases of potentially treatable conditions. Economic modelling suggested that growth monitoring is associated with health improvements [ incremental cost per quality-adjusted life-year (QALY) of pound 9500] and indicated that monitoring was cost-effective 100% of the time over the given probability distributions for a willingness to pay threshold of pound 30,000 per QALY. Studies of obesity focused on the performance of body mass index against measures of body fat. A number of issues relating to human resources required for growth monitoring were identified, but data on attitudes to growth monitoring were extremely sparse. Preliminary findings from economic modelling suggested that primary prevention may be the most cost-effective approach to obesity management, but the model incorporated a great deal of uncertainty. Conclusions: This review has indicated the potential utility and cost-effectiveness of growth monitoring in terms of increased detection of stature-related disorders. It has also pointed strongly to the need for further research. Growth monitoring does not currently meet all NSC criteria. However, it is questionable whether some of these criteria can be meaningfully applied to growth monitoring given that short stature is not a disease in itself, but is used as a marker for a range of pathologies and as an indicator of general health status. Identification of effective interventions for the treatment of obesity is likely to be considered a prerequisite to any move from monitoring to a screening programme designed to identify individual overweight and obese children. Similarly, further long-term studies of the predictors of obesity-related co-morbidities in adulthood are warranted. A cluster randomised trial comparing growth monitoring strategies with no growth monitoring in the general population would most reliably determine the clinical effectiveness of growth monitoring. Studies of diagnostic accuracy, alongside evidence of effective treatment strategies, could provide an alternative approach. In this context, careful consideration would need to be given to target conditions and intervention thresholds. Diagnostic accuracy studies would require long-term follow-up of both short and normal children to determine sensitivity and specificity of growth monitoring.

Estimation of systematic error in an equatorial ocean model using data assimilation

Assimilation of temperature observations into an ocean model near the equator often results in a dynamically unbalanced state with unrealistic overturning circulations. The way in which these circulations arise from systematic errors in the model or its forcing is discussed. A scheme is proposed, based on the theory of state augmentation, which uses the departures of the model state from the observations to update slowly evolving bias fields. Results are summarized from an experiment applying this bias correction scheme to an ocean general circulation model. They show that the method produces more balanced analyses and a better fit to the temperature observations.

Adjoint methods in data assimilation for estimating model error

Data assimilation aims to incorporate measured observations into a dynamical system model in order to produce accurate estimates of all the current (and future) state variables of the system. The optimal estimates minimize a variational principle and can be found using adjoint methods. The model equations are treated as strong constraints on the problem. In reality, the model does not represent the system behaviour exactly and errors arise due to lack of resolution and inaccuracies in physical parameters, boundary conditions and forcing terms. A technique for estimating systematic and time-correlated errors as part of the variational assimilation procedure is described here. The modified method determines a correction term that compensates for model error and leads to improved predictions of the system states. The technique is illustrated in two test cases. Applications to the 1-D nonlinear shallow water equations demonstrate the effectiveness of the new procedure.

Evolutionary developmental biology: impact on systematic theory and practice, and the contribution of systematics

Evolutionary developmental genetics brings together systematists, morphologists and developmental geneticists; it will therefore impact on each of these component disciplines. The goals and methods of phylogenetic analysis are reviewed here, and the contribution of evolutionary developmental genetics to morphological systematics, in terms of character conceptualisation and primary homology assessment, is discussed. Evolutionary developmental genetics, like its component disciplines phylogenetic systematics and comparative morphology, is concerned with homology concepts. Phylogenetic concepts of homology and their limitations are considered here, and the need for independent homology statements at different levels of biological organisation is evaluated. The role of systematics in evolutionary developmental genetics is outlined. Phylogenetic systematics and comparative morphology will suggest effective sampling strategies to developmental geneticists. Phylogenetic systematics provides hypotheses of character evolution (including parallel evolution and convergence), stimulating investigations into the evolutionary gains and losses of morphologies. Comparative morphology identifies those structures that are not easily amenable to typological categorisation, and that may be of particular interest in terms of developmental genetics. The concepts of latent homology and genetic recall may also prove useful in the evolutionary interpretation of developmental genetic data.

Use of nutritional complete supplements in older adults with dementia: systematic review and meta-analysis of clinical outcomes

Background & Aims: Malnutrition is prevalent in people diagnosed with dementia however ensuring adequate oral intake within this group is often problematic. It is important to determine whether providing nutritionally complete oral nutritional supplements (ONS) drinks is an effective way of improving clinical outcomes for older people with dementia. This paper systematically reviewed clinical, wellbeing and nutritional outcomes in people with long-term cognitive impairment. Methods: The CINAHL, Medline and EMBASE databases were searched from their inception until January 2012. Reference lists of the included papers, foreign language papers and review articles obtained were manually searched. Results: Twelve articles were included in the review containing 1076 people in the supplement groups (intervention) and 748 people in the control groups. Meta-analysis shows there was a significant improvement in weight (p=<0.0001), Body Mass Index (BMI) (p=<0.0001) and cognition at 6.5+/-3.9 month follow up (p=0.002) when supplements were given compared to the control group. Conclusions: Providing ONS drinks has a positive effect on weight gain and cognition at follow up in older people with dementia. Additional research is required in both comparing nutritional supplements to vitamin/mineral tablets and high protein/calorie shots and clinical outcomes relevant to hospitalised people with dementia.

Intercomparison of methods of coupling between convection and large-scale circulation: 1. Comparison over uniform surface conditions

As part of an international intercomparison project, a set of single column models (SCMs) and cloud-resolving models (CRMs) are run under the weak temperature gradient (WTG) method and the damped gravity wave (DGW) method. For each model, the implementation of the WTG or DGW method involves a simulated column which is coupled to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. The simulated column has the same surface conditions as the reference state and is initialized with profiles from the reference state. We performed systematic comparison of the behavior of different models under a consistent implementation of the WTG method and the DGW method and systematic comparison of the WTG and DGW methods in models with different physics and numerics. CRMs and SCMs produce a variety of behaviors under both WTG and DGW methods. Some of the models reproduce the reference state while others sustain a large-scale circulation which results in either substantially lower or higher precipitation compared to the value of the reference state. CRMs show a fairly linear relationship between precipitation and circulation strength. SCMs display a wider range of behaviors than CRMs. Some SCMs under the WTG method produce zero precipitation. Within an individual SCM, a DGW simulation and a corresponding WTG simulation can produce different signed circulation. When initialized with a dry troposphere, DGW simulations always result in a precipitating equilibrium state. The greatest sensitivities to the initial moisture conditions occur for multiple stable equilibria in some WTG simulations, corresponding to either a dry equilibrium state when initialized as dry or a precipitating equilibrium state when initialized as moist. Multiple equilibria are seen in more WTG simulations for higher SST. In some models, the existence of multiple equilibria is sensitive to some parameters in the WTG calculations.

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.

An investigation of the shortcomings of the CONSORT 2010 statement for the reporting of group sequential randomised controlled trials: a methodological systematic review

Background It can be argued that adaptive designs are underused in clinical research. We have explored concerns related to inadequate reporting of such trials, which may influence their uptake. Through a careful examination of the literature, we evaluated the standards of reporting of group sequential (GS) randomised controlled trials, one form of a confirmatory adaptive design. Methods We undertook a systematic review, by searching Ovid MEDLINE from the 1st January 2001 to 23rd September 2014, supplemented with trials from an audit study. We included parallel group, confirmatory, GS trials that were prospectively designed using a Frequentist approach. Eligible trials were examined for compliance in their reporting against the CONSORT 2010 checklist. In addition, as part of our evaluation, we developed a supplementary checklist to explicitly capture group sequential specific reporting aspects, and investigated how these are currently being reported. Results Of the 284 screened trials, 68(24%) were eligible. Most trials were published in “high impact” peer-reviewed journals. Examination of trials established that 46(68%) were stopped early, predominantly either for futility or efficacy. Suboptimal reporting compliance was found in general items relating to: access to full trials protocols; methods to generate randomisation list(s); details of randomisation concealment, and its implementation. Benchmarking against the supplementary checklist, GS aspects were largely inadequately reported. Only 3(7%) trials which stopped early reported use of statistical bias correction. Moreover, 52(76%) trials failed to disclose methods used to minimise the risk of operational bias, due to the knowledge or leakage of interim results. Occurrence of changes to trial methods and outcomes could not be determined in most trials, due to inaccessible protocols and amendments. Discussion and Conclusions There are issues with the reporting of GS trials, particularly those specific to the conduct of interim analyses. Suboptimal reporting of bias correction methods could potentially imply most GS trials stopping early are giving biased results of treatment effects. As a result, research consumers may question credibility of findings to change practice when trials are stopped early. These issues could be alleviated through a CONSORT extension. Assurance of scientific rigour through transparent adequate reporting is paramount to the credibility of findings from adaptive trials. Our systematic literature search was restricted to one database due to resource constraints.

Parents' verbal communication and childhood anxiety: a systematic review

Parents’ verbal communication to their child, particularly the expression of fear-relevant information (e.g., attributions of threat to the environment), is considered to play a key role in children’s fears and anxiety. This review considers the extent to which parental verbal communication is associated with child anxiety by examining research that has employed objective observational methods. Using a systematic search strategy, we identified 15 studies that addressed this question. These studies provided some evidence that particular fear-relevant features of parental verbal communication are associated with child anxiety under certain conditions. However, the scope for drawing reliable, general conclusions was limited by extensive methodological variation between studies, particularly in terms of the features of parental verbal communication examined and the context in which communication took place, how child anxiety was measured, and inconsistent consideration of factors that may moderate the verbal communication–child anxiety relationship. We discuss ways in which future research can contribute to this developing evidence base and reduce further methodological inconsistency so as to inform interventions for children with anxiety problems.