Julian P T Higgins's research while affiliated with University of Bristol and other places

Publications (382)

Article
Full-text available
Background The use of Mendelian randomization (MR) in epidemiology has increased considerably in recent years, with a subsequent increase in systematic reviews of MR studies. We conducted a systematic review of tools designed for assessing risk of bias and/or quality of evidence in MR studies and a review of systematic reviews of MR studies. Metho...
Article
Full-text available
Background Evidence on the impact of the pandemic on healthcare presentations for self-harm has accumulated rapidly. However, existing reviews do not include studies published beyond 2020. Aims To systematically review evidence on presentations to health services following self-harm during the COVID-19 pandemic. Method A comprehensive search of d...
Article
Full-text available
There is widespread concern over the potential impact of the COVID-19 pandemic on suicide and self-harm globally, particularly in low- and middle-income countries (LMIC) where the burden of these behaviours is greatest. We synthesised the evidence from the published literature on the impact of the pandemic on suicide and self-harm in LMIC. This rev...
Article
Full-text available
Neurosurgeons today are inundated with rapidly amassing neurosurgical research publications. Systematic reviews and meta-analyses have consequently surged in popularity because, when executed properly, they constitute a high level of evidence and may save busy neurosurgeons many hours of combing and reviewing the literature for relevant articles. M...
Article
Full-text available
Background Previous research has suggested that statistical power is suboptimal in many biomedical disciplines, but it is unclear whether power is better in trials for particular interventions, disorders, or outcome types. We therefore performed a detailed examination of power in trials of psychotherapy, pharmacotherapy, and complementary and alter...
Article
Full-text available
Objective: The COVID-19 pandemic has had a complex impact on risks of suicide and non-fatal self-harm worldwide with some evidence of increased risk in specific populations including women, young people, and people from ethnic minority backgrounds. This review aims to systematically address whether SARS-CoV-2 infection and/or COVID-19 disease conf...
Article
Full-text available
Introduction Head and neck cancer squamous cell carcinoma (HNSCC) is the sixth most common cancer internationally. Established risk factors include smoking, alcohol and presence of human papillomavirus (HPV). The incidence rate of new disease continues to rise, despite falls in alcohol consumption and a reduction in smoking, the rising rates are un...
Chapter
Studies brought together in a meta‐analysis are likely to vary in terms of where, when, why, and how they were undertaken. This diversity across the studies often gives rise to heterogeneity: the statistical variability of results beyond what would be expected by chance alone. As a general principle, heterogeneity in meta‐analysis should be investi...
Chapter
Health care practitioners, decision‐makers, and consumers want to know which treatment is preferable among many competing options. Network meta‐analysis is an extension of meta‐analysis that allows the simultaneous comparison of multiple interventions. It combines the results of studies that compare two or more interventions for the same condition;...
Chapter
We begin with an introduction to systematic reviews and meta‐analysis, discuss terminology and scope, provide historical background, and examine the potential, promise, and limitations of systematic reviews and meta‐analysis. The statistical basis of meta‐analysis begins with Laplace in the late eighteenth century, while efforts to summarize resear...
Chapter
Stata is a commercial general‐purpose, programmable statistical package. A comprehensive set of commands are available for meta‐analysis of different types of studies and data. Meta‐analysis of studies comparing two treatments can be performed for binary (relative risk, odds ratio, risk difference) or continuous outcomes (difference in means, stand...
Article
Full-text available
Background Two-sample Mendelian randomization (2SMR) is an increasingly popular epidemiological method that uses genetic variants as instruments for making causal inferences. Clear reporting of methods employed in such studies is important for evaluating their underlying quality. However, the quality of methodological reporting of 2SMR studies is c...
Chapter
Here we describe the different effect measures that are typically used in meta‐analyses of randomized trials, many of which are also used in observational studies. For dichotomous data (e.g. dead or alive), the three main options are the odds ratio (OR), the risk ratio (RR) and the risk difference (RD). We describe how these are computed from resul...
Chapter
A p value, or the magnitude or direction of results, can influence decisions about whether, when, and how research findings are disseminated. Regardless of whether an entire study or a particular study result is unavailable because investigators considered the results to be unfavorable, reporting bias in a meta‐analysis may occur when available res...
Chapter
The principles and steps of systematic reviews are similar to any other research undertaking: formulation of the problem to be addressed, collection and analysis of the data, and interpretation of the results. A study protocol should be written, which states objectives and eligibility criteria, describes how studies will be identified and selected,...
Chapter
Meta‐analysis of controlled trials is usually a two‐stage process involving the calculation of an appropriate summary statistic of the intervention effect for each trial, followed by the combination of these statistics into a weighted average. Two models for meta‐analysis are in widespread use. A fixed‐effect meta‐analysis (also known as common‐eff...
Article
Full-text available
Codeletion of chromosomal arms 1p and 19q, in conjunction with a mutation in the isocitrate dehydrogenase 1 or 2 gene, is the molecular diagnostic criterion for oligodendroglioma, IDH-mutant and 1p/19q-codeleted. 1p/19q codeletion is a diagnostic marker and allows prognostication and prediction of the best drug response within IDH-mutant tumours. W...
Article
Full-text available
Background Selective outcome reporting and publication bias threaten the validity of systematic reviews and meta-analyses and can affect clinical decision-making. A rigorous method to evaluate the impact of this bias on the results of network meta-analyses of interventions is lacking. We present a tool to assess the Risk Of Bias due to Missing Evid...
Article
Full-text available
Background Evidence from previous studies is often used relatively informally in the design of clinical trials: for example, a systematic review to indicate whether a gap in the current evidence base justifies a new trial. External evidence can be used more formally in both trial design and analysis, by explicitly incorporating a synthesis of it in...
Article
Full-text available
Background : The COVID-19 pandemic has had an impact on the mental health of healthcare and social care workers, and its potential effect on suicidal thoughts and behaviour is of particular concern. Methods : This systematic review identified and appraised the published literature that has reported on the impact of COVID-19 on suicidal thoughts an...
Article
Full-text available
Background Detailed prevalence estimates of BRAFV600 mutations and BRAF inhibitor (BRAFi) treatment responses in V600-mutant glioma will inform trial development. Methods Our systematic review analysed overall prevalence of BRAFV600 mutations in glioma and BRAFi treatment response. Results Based on 13,682 patients in 182 publications, the prevale...
Article
Importance Mendelian randomization (MR) studies use genetic variation associated with modifiable exposures to assess their possible causal relationship with outcomes and aim to reduce potential bias from confounding and reverse causation. Objective To develop the STROBE-MR Statement as a stand-alone extension to the STROBE (Strengthening the Repor...
Article
Full-text available
Mendelian randomisation (MR) studies allow a better understanding of the causal effects of modifiable exposures on health outcomes, but the published evidence is often hampered by inadequate reporting. Reporting guidelines help authors effectively communicate all critical information about what was done and what was found. STROBE-MR (strengthening...
Article
Full-text available
Background Network meta-analysis (NMA) has attracted growing interest in evidence-based medicine. Consistency between different sources of evidence is fundamental to the reliability of the NMA results. The purpose of the present study was to estimate the prevalence of evidence of inconsistency and describe its association with different NMA charact...
Article
Full-text available
Excess body weight is thought to increase the risk of aggressive prostate cancer (PCa), although the biological mechanism is currently unclear. Body fatness is positively associated with a diminished cellular response to insulin and biomarkers of insulin signalling have been positively associated with PCa risk. We carried out a two-pronged systemat...
Preprint
Full-text available
Background: Two-sample Mendelian randomization (2SMR) is an increasingly popular epidemiological method that uses genetic variants as instruments for making causal inferences. Clear reporting of methods employed in such studies is important for evaluating their underlying quality. However, the quality of methodological reporting of 2SMR studies is...
Preprint
Full-text available
Background: Previous research has suggested that statistical power is suboptimal in many biomedical disciplines, but it is unclear whether power is better in trials for particular interventions, disorders, or outcome types. We therefore performed a detailed examination of power in trials of psychotherapy, pharmacotherapy, and complementary and alte...
Article
Full-text available
Aims Glioma is a fatal disease that causes significant years of life lost to an individual. Mutations in the driver gene BRAF, such as the V600 alteration, may contribute to gliomagenesis in adults and children through abnormal signaling causing uncontrolled cell proliferation. The use of BRAF-inhibitor drugs including Vemurafenib and Dabrafenib ha...
Article
Full-text available
Importance Clinical trials assessing the efficacy of IL-6 antagonists in patients hospitalized for COVID-19 have variously reported benefit, no effect, and harm. Objective To estimate the association between administration of IL-6 antagonists compared with usual care or placebo and 28-day all-cause mortality and other outcomes. Data Sources Trial...
Article
Standard meta-analysis methods are vulnerable to bias from incomplete reporting of results (both publication and outcome reporting bias) and poor study quality. Several alternative methods have been proposed as being less vulnerable to such biases. To evaluate these claims independently we simulated study results under a broad range of conditions f...
Article
Full-text available
Background: The COVID-19 pandemic has caused considerable morbidity, mortality and disruption to people’s lives around the world. There are concerns that rates of suicide and suicidal behaviour may rise during and in its aftermath. Our living systematic review synthesises findings from emerging literature on incidence and prevalence of suicidal beh...
Article
Full-text available
Background: The reliable and usable (semi)automation of data extraction can support the field of systematic review by reducing the workload required to gather information about the conduct and results of the included studies. This living systematic review examines published approaches for data extraction from reports of clinical studies. Methods: W...
Article
The basic idea of meta‐analysis is to compute an effect size from each of several studies, and to calculate a weighted average of these effect size estimates. This chapter provides some examples of situations in which requirements for meta‐analysis are met and where meta‐analysis can therefore be used to combine findings across studies. It aims to...
Article
This chapter provides information on various websites, professional societies, and journals on meta‐analysis, as well as special issues dedicated to meta‐analysis and books on systematic review methods and meta‐analysis. The Human Genome Epidemiology Network is a global collaboration committed to the assessment of the impact of human genome variati...
Article
In this chapter, the authors show how they can use a prediction interval to describe the distribution of true effect sizes. They review how the prediction interval is used in primary studies, and also show how the same mechanism can be used for meta‐analysis. The summary line in a forest plot uses a diamond to depict the mean effect size and its co...
Article
This chapter introduces the fixed‐effect model. It discusses the assumptions of this model and shows how these are reflected in the formulas used to compute a summary effect, and in the meaning of the summary effect. All factors that could influence the effect size are the same in all the studies, and therefore the true effect size is the same (hen...
Article
For studies that report a correlation between two continuous variables, the correlation coefficient itself can serve as the effect size index. The correlation is an intuitive measure that has been standardized to take account of different metrics in the original scales. Most meta‐analysts do not perform syntheses on the correlation coefficient itse...
Article
A meta‐analysis of effect sizes addresses the magnitude of the effect. Vote counting is the process of counting the number of studies that are statistically significant and the number that are not, and then choosing the winner. A meta‐analysis of p‐values tells us only that the effect is probably not zero. This chapter describes two methods for per...
Article
For data from a prospective study, such as a randomized trial, that was originally reported as the number of events and non‐events in two groups (the classic 2 × 2 table), researchers typically compute a risk ratio, an odds ratio, and/or a risk difference. For risk ratios, computations are carried out on a log scale. The log risk ratio and the stan...
Article
Vote counting is the process of counting the number of studies that are statistically significant and comparing this with the number that are not statistically significant. In any event, the idea of vote counting is fundamentally flawed and the variants on this process are equally flawed. This chapter aims to explain why this is so, and to provide...
Article
In meta‐analysis, the confidence interval for the mean is traditionally based on the Z distribution, which yields a relatively narrow interval. When researchers use the random effects model, it would be better to use the Knapp–Hartung adjustment, which yields a wider confidence interval. The adjustment includes two components. First, it modifies th...
Article
Most of the issues that one would address when reporting the results of a meta‐analysis are similar to those for reporting the results of a primary study. There are some unique issues as well, and this chapter addresses those issues. A common mistake is to use the fixed‐effect model on the basis that there is no evidence of heterogeneity. The fores...
Article
When the studies report means and standard deviations, the preferred effect size is usually the raw mean difference, the standardized mean difference, or the response ratio. These effect sizes are discussed in this chapter. When the outcome is reported on a meaningful scale and all studies in the analysis use the same scale, the meta‐analysis can b...
Article
This chapter provides practical advice about how to think about heterogeneity. It highlights the prediction interval, the statistic that reports the range of true effects. This statistic provides the information that we need, and that many think is being provided by the other statistics. The forest plot of a meta‐analysis typically includes a line...
Article
This chapter is adapted from the text Common Mistakes in Meta‐Analysis and How to Avoid Them. When the analysis is based on studies pulled from the literature, the random‐effects model is almost invariably the model that should be used. The random‐effects model works well if the following assumptions are met: the studies that were performed are a r...
Article
This chapter presents worked examples for exploring how to compute the measures of heterogeneity. It shows how to compute the effect size (the log odds ratio) and variance for each study. Further, the chapter also shows how to compute the effect size (the Fisher’s z transformation of the correlation coefficient) and variance for each study. It incl...
Article
The first case of a complex data structure is the case where studies report data from two or more independent subgroups. The stage‐1 and stage‐2 patients represent two independent subgroups since each patient is included in one group or the other, but not both. This chapter aims to compute a summary effect for the impact of the intervention for sta...
Chapter
This chapter provides examples of how one might explain the results of a simple meta‐analysis, for example to a colleague. There is one example based on each of several effect sizes. The chapter introduces the analysis by providing some basic information such as the number of studies and the effect‐size index. It also provides the rationale for usi...
Chapter
The effect size, a value which reflects the magnitude of the treatment effect or the strength of a relationship between two variables, is the unit of currency in a meta‐analysis. In this chapter, the effect size for each study is computed, and then the effect sizes is discussed to assess the consistency of the effect across studies and to compute a...
Chapter
This chapter begins with an example to show how meta‐analysis and narrative review would approach the same question, and then uses this example to highlight the key differences between the two. The meta‐analysis allows us to combine the effects and evaluate the statistical significance of the summary effect. The meta‐analytic approaches allow us to...
Chapter
In this chapter, the authors show how meta‐analysis can be used to compare the mean effect for different subgroups of studies. They present three computational models. These are fixed‐effect, random‐effects using separate estimates of 𝜏2, and random‐effects using a pooled estimate of 𝜏2. In a primary study, the t‐test can be used to compare the mea...
Chapter
This chapter shows how the multiple regression used in primary studies can be applied to meta‐regression. It begins with the fixed‐effect model, which is simpler, and then moves on to the random‐effects model, which is generally more appropriate. Since the meaning of a summary effect size is different for fixed versus random effects, the null hypot...
Chapter
This chapter focuses on two themes related to statistical power. The first theme is conceptual. The chapter discusses the factors that determine power and explores how the value of these factors may change as we move from a primary study to a meta‐analysis. The second theme is practical. The chapter briefly reviews the process of power analysis for...
Chapter
Studies that used independent groups and studies that used matched groups were both used to yield estimates of the standardized mean difference. There is no problem in combining these estimates in a meta‐analysis since the effect size has the same meaning in all studies. The question of whether or not it is appropriate to combine effect sizes from...
Chapter
A central theme in this volume is the fact that we usually prefer to work with effect sizes, rather than p‐values. The reason reflects a fundamental issue that applies both to primary studies and to meta‐analysis, and is the subject of this chapter. Since narrative reviews typically work with p‐values while meta‐analyses typically work with effect...
Chapter
This chapter discusses the reasons for publication bias and the evidence that it exists. It also outlines a series of methods that have been developed to assess the likely impact of bias in any given meta‐analysis. The chapter introduces the idea of a small‐study effect, and how this is often conflated with publication bias. In particular, it expla...
Chapter
This chapter provides an overview of software Comprehensive Meta‐Analysis (CMA) and shows how to use it to implement the ideas. The same approach could be used with any other program as well. The chapter also provides a sense for the look‐and‐feel of the program. CMA features a spreadsheet view and a menu‐driven interface. As such, it allows a rese...
Chapter
The report of a meta‐analysis will focus on the mean effect size, and then address heterogeneity as a separate matter, if at all. Castells et al. conducted a meta‐analysis of studies that assessed the impact of methylphenidate vs. placebo on the cognitive functioning of adults with attention deficit hyperactivity disorder. Katout et al. looked at t...
Chapter
The goal of a meta‐analysis is only rarely to synthesize data from a set of identical studies. Almost invariably, the goal is to broaden the base of studies in some way, expand the question, and study the pattern of answers. The question of whether it makes sense to perform a meta‐analysis, and the question of what kinds of studies to include, must...
Chapter
This chapter presents two methods, the Mantel–Haenszel method and the one‐step method (also known as the Peto method) for performing a meta‐analysis on odds ratios. For both methods we assume the data from each study are presented in the form of a 2 × 2 table. The Mantel–Haenszel method is based on the fixed‐effect model, where the weight assigned...
Chapter
This chapter addresses how to proceed when we want to incorporate treatment groups in the same analysis. Specifically, it aims to compute a summary effect for the active intervention versus control and aims to investigate the difference in effect size for interventions. the chapter describes the difference between multiple outcomes and multiple com...
Chapter
This chapter highlights the conceptual and practical differences between fixed‐effect and random‐effects models. Under the random‐effects model the goal is not to estimate one true effect, but to estimate the mean of a distribution of effects. Under the fixed‐effect model there is a wide range of weights whereas under the random‐effects model the w...
Chapter
To compute the summary effect in a meta‐analysis the researchers compute an effect size for each study and then combine these effect sizes, rather than pooling the data directly. Van Howe published a review article in the International Journal of STD and AIDS that looked at the relationship between circumcision and HIV infection in Africa. The arti...
Chapter
This chapter presents an overview of the key concepts discussed in part 7 of this book. The part discusses three cases where studies provide more than one unit of data for the analysis. These are the case of multiple independent subgroups within a study, multiple outcomes or time‐points based on the same subjects, and two or more treatment groups t...
Chapter
This chapter provides information on software used for meta‐analysis. The software Comprehensive Meta‐Analysis (CMA) was initially released in 2000 and has been updated on a regular basis since then. The next version is scheduled for release in 2021. For researchers who would prefer to use R to perform meta‐analysis, Wolfgang Viechtbauer has publis...
Chapter
This chapter provides some context for the variance for specific effect sizes such as the standardized mean difference or a log risk ratio. The term precision is used as a general term to encompass three formal statistics, the variance, standard error, and confidence interval. The chapter outlines the relationship between the indices of precision....
Chapter
Researchers have developed the practice of classifying heterogeneity as being low, moderate, or high based on the value of I2. This chapter argues that the idea of classifying heterogeneity based on I2 should be strongly discouraged. In the transfusion analysis, the I2 statistic was 29%. In the off‐hours analysis, the I2 statistic was 75%. On that...
Chapter
In this chapter, the authors address a number of issues that are relevant to both subgroup analyses and to meta‐regression. The researcher must always choose between a fixed‐effect model and a random‐effects model. Researchers often ask about the practical implications of using a random‐effects model rather than a fixed‐effect model. Since the mean...
Chapter
This chapter introduces the random‐effects model. It discusses the assumptions of this model, and show how these are reflected in the formulas used to compute a summary effect, and in the meaning of the summary effect. The fixed‐effect model starts with the assumption that the true effect size is the same in all studies. In a random‐effects meta‐an...
Chapter
A cumulative meta‐analysis is a meta‐analysis that is performed first with one study, then with two studies, and so on, until all relevant studies have been included in the analysis. Lau et al. used the streptokinase analysis to show the potential impact of meta‐analysis as part of the research process. They argued that if meta‐analysis had been av...