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Background Prostate MRI for the detection of clinically significant prostate cancer (csPCa) is standardized by the Prostate Imaging Reporting and Data System (PI-RADS), currently in version 2.1. A systematic review and meta-analysis infrastructure with a 12-month update cycle was established to evaluate the diagnostic performance of PI-RADS over time. Purpose To provide estimates of diagnostic accuracy and cancer detection rates (CDRs) of PI-RADS version 2.1 categories for prostate MRI, which is required for further evidence-based patient management. Materials and Methods A systematic search of PubMed, Embase, Cochrane Library, and multiple trial registers (English-language studies published from March 1, 2019, to August 30, 2022) was performed. Studies that reported data on diagnostic accuracy or CDRs of PI-RADS version 2.1 with csPCa as the primary outcome were included. For the meta-analysis, pooled estimates for sensitivity, specificity, and CDRs were derived from extracted data at the lesion level and patient level. Sensitivity and specificity for PI-RADS greater than or equal to 3 and PI-RADS greater than or equal to 4 considered as test positive were investigated. In addition to individual PI-RADS categories 1-5, subgroup analyses of subcategories (ie, 2+1, 3+0) were performed. Results A total of 70 studies (11 686 lesions, 13 330 patients) were included. At the patient level, with PI-RADS greater than or equal to 3 considered positive, meta-analysis found a 96% summary sensitivity (95% CI: 95, 98) and 43% specificity (95% CI: 33, 54), with an area under the summary receiver operating characteristic (SROC) curve of 0.86 (95% CI: 0.75, 0.93). For PI-RADS greater than or equal to 4, meta-analysis found an 89% sensitivity (95% CI: 85, 92) and 66% specificity (95% CI: 58, 74), with an area under the SROC curve of 0.89 (95% CI: 0.85, 0.92). CDRs were as follows: PI-RADS 1, 6%; PI-RADS 2, 5%; PI-RADS 3, 19%; PI-RADS 4, 54%; and PI-RADS 5, 84%. The CDR was 12% (95% CI: 7, 19) for transition zone 2+1 lesions and 19% (95% CI: 12, 29) for 3+0 lesions (P = .12). Conclusion Estimates of diagnostic accuracy and CDRs for PI-RADS version 2.1 categories are provided for quality benchmarking and to guide further evidence-based patient management. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Tammisetti and Jacobs in this issue.
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Benchmarking , Imageamento por Ressonância Magnética , Neoplasias da Próstata , Humanos , Neoplasias da Próstata/diagnóstico por imagem , Masculino , Imageamento por Ressonância Magnética/métodos , Sensibilidade e Especificidade , Próstata/diagnóstico por imagem , Próstata/patologiaRESUMO
Quantifying the contributions, or weights, of comparisons or single studies to the estimates in a network meta-analysis (NMA) is an active area of research. We extend this work to include the contributions of paths of evidence. We present a general framework, based on the path-design matrix, that describes the problem of finding path contributions as a linear equation. The resulting solutions may have negative coefficients. We show that two known approaches, called shortestpath and randomwalk, are special solutions of this equation, and both meet an optimization criterion, as they minimize the sum of absolute path contributions. In general, there is an infinite set of solutions, which can be identified using the generalized inverse (Moore-Penrose pseudoinverse). We consider two further special approaches. For large networks we find that shortestpath is superior with respect to run time and variability, compared to the other approaches, and is thus recommended in practice. The path-weights framework also has the potential to answer more general research questions in NMA.
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BACKGROUND: Although aggregate data (AD) from randomised clinical trials (RCTs) are used in the majority of network meta-analyses (NMAs), other study designs (e.g., cohort studies and other non-randomised studies, NRS) can be informative about relative treatment effects. The individual participant data (IPD) of the study, when available, are preferred to AD for adjusting for important participant characteristics and to better handle heterogeneity and inconsistency in the network. RESULTS: We developed the R package crossnma to perform cross-format (IPD and AD) and cross-design (RCT and NRS) NMA and network meta-regression (NMR). The models are implemented as Bayesian three-level hierarchical models using Just Another Gibbs Sampler (JAGS) software within the R environment. The R package crossnma includes functions to automatically create the JAGS model, reformat the data (based on user input), assess convergence and summarize the results. We demonstrate the workflow within crossnma by using a network of six trials comparing four treatments. CONCLUSIONS: The R package crossnma enables the user to perform NMA and NMR with different data types in a Bayesian framework and facilitates the inclusion of all types of evidence recognising differences in risk of bias.
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Teorema de Bayes , Metanálise em Rede , Software , Humanos , Ensaios Clínicos Controlados Aleatórios como Assunto/métodos , Ensaios Clínicos Controlados Aleatórios como Assunto/estatística & dados numéricos , Projetos de Pesquisa , Algoritmos , Metanálise como AssuntoRESUMO
BACKGROUND: Network meta-analysis (NMA) allows estimating and ranking the effects of several interventions for a clinical condition. Component network meta-analysis (CNMA) is an extension of NMA which considers the individual components of multicomponent interventions. CNMA allows to "reconnect" a disconnected network with common components in subnetworks. An additive CNMA assumes that component effects are additive. This assumption can be relaxed by including interaction terms in the CNMA. METHODS: We evaluate a forward model selection strategy for component network meta-analysis to relax the additivity assumption that can be used in connected or disconnected networks. In addition, we describe a procedure to create disconnected networks in order to evaluate the properties of the model selection in connected and disconnected networks. We apply the methods to simulated data and a Cochrane review on interventions for postoperative nausea and vomiting in adults after general anaesthesia. Model performance is compared using average mean squared errors and coverage probabilities. RESULTS: CNMA models provide good performance for connected networks and can be an alternative to standard NMA if additivity holds. For disconnected networks, we recommend to use additive CNMA only if strong clinical arguments for additivity exist. CONCLUSIONS: CNMA methods are feasible for connected networks but questionable for disconnected networks.
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Registros , Adulto , Humanos , Metanálise em Rede , Simulação por Computador , ProbabilidadeRESUMO
BACKGROUND: This is the second update of the original Cochrane review published in 2013 (issue 6), which was updated in 2016 (issue 11). Pruritus occurs in patients with disparate underlying diseases and is caused by different pathologic mechanisms. In palliative care patients, pruritus is not the most prevalent but is a burdening symptom. It can cause considerable discomfort and negatively affect patients' quality of life. OBJECTIVES: To assess the effects of different pharmacological treatments compared with active control or placebo for preventing or treating pruritus in adult palliative care patients. SEARCH METHODS: For this update, we searched CENTRAL (the Cochrane Library), MEDLINE (OVID) and Embase (OVID) up to 6 July 2022. In addition, we searched trial registries and checked the reference lists of all relevant studies, key textbooks, reviews and websites, and we contacted investigators and specialists in pruritus and palliative care regarding unpublished data. SELECTION CRITERIA: We included randomised controlled trials (RCTs) assessing the effects of different pharmacological treatments, compared with a placebo, no treatment, or an alternative treatment, for preventing or treating pruritus in palliative care patients. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed the identified titles and abstracts, performed data extraction and assessed the risk of bias and methodological quality. We summarised the results descriptively and quantitatively (meta-analyses) according to the different pharmacological interventions and the diseases associated with pruritus. We assessed the evidence using GRADE and created 13 summary of findings tables. MAIN RESULTS: In total, we included 91 studies and 4652 participants in the review. We added 42 studies with 2839 participants for this update. Altogether, we included 51 different treatments for pruritus in four different patient groups. The overall risk of bias profile was heterogeneous and ranged from high to low risk. The main reason for giving a high risk of bias rating was a small sample size (fewer than 50 participants per treatment arm). Seventy-nine of 91 studies (87%) had fewer than 50 participants per treatment arm. Eight (9%) studies had low risk of bias in the specified key domains; the remaining studies had an unclear risk of bias (70 studies, 77%) or a high risk of bias (13 studies, 14%). Using GRADE criteria, we judged that the certainty of evidence for the primary outcome (i.e. pruritus) was high for kappa-opioid agonists compared to placebo and moderate for GABA-analogues compared to placebo. Certainty of evidence was low for naltrexone, fish-oil/omega-3 fatty acids, topical capsaicin, ondansetron and zinc sulphate compared to placebo and gabapentin compared to pregabalin, and very low for cromolyn sodium, paroxetine, montelukast, flumecinol, and rifampicin compared to placebo. We downgraded the certainty of the evidence mainly due to serious study limitations regarding risk of bias, imprecision, and inconsistency. For participants suffering from uraemic pruritus (UP; also known as chronic kidney disease (CKD)-associated pruritus (CKD-aP)), treatment with GABA-analogues compared to placebo likely resulted in a large reduction of pruritus (visual analogue scale (VAS) 0 to 10 cm): mean difference (MD) -5.10, 95% confidence interval (CI) -5.56 to -4.55; five RCTs, N = 297, certainty of evidence: moderate. Treatment with kappa-opioid receptor agonists (difelikefalin, nalbuphine, nalfurafine) compared to placebo reduced pruritus slightly (VAS 0 to 10 cm, MD -0.96, 95% CI -1.22 to -0.71; six RCTs, N = 1292, certainty of evidence: high); thus, this treatment was less effective than GABA-analogues. Treatment with montelukast compared to placebo may result in a reduction of pruritus, but the evidence is very uncertain (two studies, 87 participants): SMD -1.40, 95% CI -1.87 to -0.92; certainty of evidence: very low. Treatment with fish-oil/omega-3 fatty acids compared to placebo may result in a large reduction of pruritus (four studies, 160 observations): SMD -1.60, 95% CI -1.97 to -1.22; certainty of evidence: low. Treatment with cromolyn sodium compared to placebo may result in a reduction of pruritus, but the evidence is very uncertain (VAS 0 to 10 cm, MD -3.27, 95% CI -5.91 to -0.63; two RCTs, N = 100, certainty of evidence: very low). Treatment with topical capsaicin compared with placebo may result in a large reduction of pruritus (two studies; 112 participants): SMD -1.06, 95% CI -1.55 to -0.57; certainty of evidence: low. Ondansetron, zinc sulphate and several other treatments may not reduce pruritus in participants suffering from UP. In participants with cholestatic pruritus (CP), treatment with rifampicin compared to placebo may reduce pruritus, but the evidence is very uncertain (VAS: 0 to 100, MD -42.00, 95% CI -87.31 to 3.31; two RCTs, N = 42, certainty of evidence: very low). Treatment with flumecinol compared to placebo may reduce pruritus, but the evidence is very uncertain (RR > 1 favours treatment group; RR 2.32, 95% CI 0.54 to 10.1; two RCTs, N = 69, certainty of evidence: very low). Treatment with the opioid antagonist naltrexone compared to placebo may reduce pruritus (VAS: 0 to 10 cm, MD -2.42, 95% CI -3.90 to -0.94; two RCTs, N = 52, certainty of evidence: low). However, effects in participants with UP were inconclusive (percentage of difference -12.30%, 95% CI -25.82% to 1.22%, one RCT, N = 32). In palliative care participants with pruritus of a different nature, the treatment with the drug paroxetine (one study), a selective serotonin reuptake inhibitor, compared to placebo may reduce pruritus slightly by 0.78 (numerical analogue scale from 0 to 10 points; 95% CI -1.19 to -0.37; one RCT, N = 48, certainty of evidence: low). Most adverse events were mild or moderate. Two interventions showed multiple major adverse events (naltrexone and nalfurafine). AUTHORS CONCLUSIONS: Different interventions (GABA-analogues, kappa-opioid receptor agonists, cromolyn sodium, montelukast, fish-oil/omega-3 fatty acids and topical capsaicin compared to placebo) were effective for uraemic pruritus. GABA-analogues had the largest effect on pruritus. Rifampin, naltrexone and flumecinol tended to be effective for cholestatic pruritus. However, therapies for patients with malignancies are still lacking. Due to the small sample sizes in most meta-analyses and the heterogeneous methodological quality of the included trials, the results should be interpreted cautiously in terms of generalisability.
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Capsaicina , Cuidados Paliativos , Animais , Humanos , Cromolina Sódica , Ácido gama-Aminobutírico , Naltrexona , Ondansetron , Paroxetina , Receptores Opioides , Rifampina , Sulfato de ZincoRESUMO
Network meta-analysis can synthesize evidence from studies comparing multiple treatments for the same disease. Sometimes the treatments of a network are complex interventions, comprising several independent components in different combinations. A component network meta-analysis (CNMA) can be used to analyze such data and can in principle disentangle the individual effect of each component. However, components may interact with each other, either synergistically or antagonistically. Deciding which interactions, if any, to include in a CNMA model may be difficult, especially for large networks with many components. In this article, we present two Bayesian CNMA models that can be used to identify prominent interactions between components. Our models utilize Bayesian variable selection methods, namely the stochastic search variable selection and the Bayesian LASSO, and can benefit from the inclusion of prior information about important interactions. Moreover, we extend these models to combine data from studies providing aggregate information and studies providing individual patient data (IPD). We illustrate our models in practice using three real datasets, from studies in panic disorder, depression, and multiple myeloma. Finally, we describe methods for developing web-applications that can utilize results from an IPD-CNMA, to allow for personalized estimates of relative treatment effects given a patient's characteristics.
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Projetos de Pesquisa , Teorema de Bayes , Humanos , Metanálise em RedeRESUMO
BACKGROUND: Network meta-analysis estimates all relative effects between competing treatments and can produce a treatment hierarchy from the most to the least desirable option according to a health outcome. While about half of the published network meta-analyses present such a hierarchy, it is rarely the case that it is related to a clinically relevant decision question. METHODS: We first define treatment hierarchy and treatment ranking in a network meta-analysis and suggest a simulation method to estimate the probability of each possible hierarchy to occur. We then propose a stepwise approach to express clinically relevant decision questions as hierarchy questions and quantify the uncertainty of the criteria that constitute them. The steps of the approach are summarized as follows: a) a question of clinical relevance is defined, b) the hierarchies that satisfy the defined question are collected and c) the frequencies of the respective hierarchies are added; the resulted sum expresses the certainty of the defined set of criteria to hold. We then show how the frequencies of all possible hierarchies relate to common ranking metrics. RESULTS: We exemplify the method and its implementation using two networks. The first is a network of four treatments for chronic obstructive pulmonary disease where the most probable hierarchy has a frequency of 28%. The second is a network of 18 antidepressants, among which Vortioxetine, Bupropion and Escitalopram occupy the first three ranks with frequency 19%. CONCLUSIONS: The developed method offers a generalised approach of producing treatment hierarchies in network meta-analysis, which moves towards attaching treatment ranking to a clear decision question, relevant to all or a subset of competing treatments.
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Antidepressivos , Antidepressivos/uso terapêutico , Humanos , Metanálise em RedeRESUMO
In a quantitative synthesis of studies via meta-analysis, it is possible that some studies provide a markedly different relative treatment effect or have a large impact on the summary estimate and/or heterogeneity. Extreme study effects (outliers) can be detected visually with forest/funnel plots and by using statistical outlying detection methods. A forward search (FS) algorithm is a common outlying diagnostic tool recently extended to meta-analysis. FS starts by fitting the assumed model to a subset of the data which is gradually incremented by adding the remaining studies according to their closeness to the postulated data-generating model. At each step of the algorithm, parameter estimates, measures of fit (residuals, likelihood contributions), and test statistics are being monitored and their sharp changes are used as an indication for outliers. In this article, we extend the FS algorithm to network meta-analysis (NMA). In NMA, visualization of outliers is more challenging due to the multivariate nature of the data and the fact that studies contribute both directly and indirectly to the network estimates. Outliers are expected to contribute not only to heterogeneity but also to inconsistency, compromising the NMA results. The FS algorithm was applied to real and artificial networks of interventions that include outliers. We developed an R package (NMAoutlier) to allow replication and dissemination of the proposed method. We conclude that the FS algorithm is a visual diagnostic tool that helps to identify studies that are a potential source of heterogeneity and inconsistency.
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Algoritmos , Projetos de Pesquisa , Humanos , Metanálise em RedeRESUMO
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 characteristics. METHODS: We updated our collection of NMAs with articles published up to July 2018. We included networks with randomised clinical trials, at least four treatment nodes, at least one closed loop, a dichotomous primary outcome, and available arm-level data. We assessed consistency using the design-by-treatment interaction (DBT) model and testing all the inconsistency parameters globally through the Wald-type chi-squared test statistic. We estimated the prevalence of evidence of inconsistency and its association with different network characteristics (e.g., number of studies, interventions, intervention comparisons, loops). We evaluated the influence of the network characteristics on the DBT p-value via a multivariable regression analysis and the estimated Pearson correlation coefficients. We also evaluated heterogeneity in NMA (consistency) and DBT (inconsistency) random-effects models. RESULTS: We included 201 published NMAs. The p-value of the design-by-treatment interaction (DBT) model was lower than 0.05 in 14% of the networks and lower than 0.10 in 20% of the networks. Networks including many studies and comparing few interventions were more likely to have small DBT p-values (less than 0.10), which is probably because they yielded more precise estimates and power to detect differences between designs was higher. In the presence of inconsistency (DBT p-value lower than 0.10), the consistency model displayed higher heterogeneity than the DBT model. CONCLUSIONS: Our findings show that inconsistency was more frequent than what would be expected by chance, suggesting that researchers should devote more resources to exploring how to mitigate inconsistency. The results of this study highlight the need to develop strategies to detect inconsistency (because of the relatively high prevalence of evidence of inconsistency in published networks), and particularly in cases where the existing tests have low power.
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Reprodutibilidade dos Testes , Humanos , Metanálise em Rede , Prevalência , Análise de RegressãoRESUMO
PURPOSE: To evaluate the relationship between mortality or relapse of bloodstream infection (BSI) due to Enterococcus faecalis and infectious diseases specialist consultation (IDC) and other factors potentially associated with outcomes. METHODS: In a tertiary-care center, consecutive adult patients with E. faecalis BSI between January 1, 2016 and January 31, 2019, were prospectively followed. The management of E. faecalis BSI was evaluated in terms of adherence to evidence-based quality-of-care indicators (QCIs). IDC and other factors potentially associated with 90-day-mortality or relapse of E. faecalis BSI were analyzed by multivariate logistic regression. RESULTS: A total of 151 patients with a median age of 68 years were studied. IDC was performed in 38% of patients with E. faecalis BSI. 30 cases of endocarditis (20%) were diagnosed. All-cause in-hospital mortality was 23%, 90-day mortality was 37%, and 90-day relapsing E. faecalis BSI was 8%. IDC was significantly associated with better adherence to 5 QCIs. Factors significantly associated with 90-day mortality or relapsing EfB in multivariate analysis were severe sepsis or septic shock at onset (HR 4.32, CI 2.36e7.88) and deep-seated focus of infection (superficial focus HR 0.33, CI 0.14e0.76). CONCLUSION: Enterococcus faecalis bacteremia is associated with a high mortality. IDC contributed to improved diagnostic and therapeutic management.
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Bacteriemia , Doenças Transmissíveis , Infecções por Bactérias Gram-Positivas , Sepse , Adulto , Idoso , Bacteriemia/epidemiologia , Enterococcus faecalis , Infecções por Bactérias Gram-Positivas/epidemiologia , Humanos , Encaminhamento e Consulta , Estudos Retrospectivos , Fatores de RiscoRESUMO
BACKGROUND: Mental burden due to the SARS-CoV-2 pandemic has been widely reported for the general public and specific risk groups like healthcare workers and different patient populations. We aimed to assess its impact on mental health during the early phase by comparing pandemic with prepandemic data and to identify potential risk and protective factors. METHODS: For this systematic review and meta-analyses, we systematically searched PubMed, PsycINFO, and Web of Science from January 1, 2019 to May 29, 2020, and screened reference lists of included studies. In addition, we searched PubMed and PsycINFO for prepandemic comparative data. Survey studies assessing mental burden by the SARS-CoV-2 pandemic in the general population, healthcare workers, or any patients (eg, COVID-19 patients), with a broad range of eligible mental health outcomes, and matching studies evaluating prepandemic comparative data in the same population (if available) were included. We used multilevel meta-analyses for main, subgroup, and sensitivity analyses, focusing on (perceived) stress, symptoms of anxiety and depression, and sleep-related symptoms as primary outcomes. RESULTS: Of 2429 records retrieved, 104 were included in the review (n = 208,261 participants), 43 in the meta-analysis (n = 71,613 participants). While symptoms of anxiety (standardized mean difference [SMD] 0.40; 95% CI 0.15-0.65) and depression (SMD 0.67; 95% CI 0.07-1.27) were increased in the general population during the early phase of the pandemic compared with prepandemic conditions, mental burden was not increased in patients as well as healthcare workers, irrespective of COVID-19 patient contact. Specific outcome measures (eg, Patient Health Questionnaire) and older comparative data (published ≥5 years ago) were associated with increased mental burden. Across the three population groups, existing mental disorders, female sex, and concerns about getting infected were repeatedly reported as risk factors, while older age, a good economic situation, and education were protective. CONCLUSIONS: This meta-analysis paints a more differentiated picture of the mental health consequences in pandemic situations than previous reviews. High-quality, representative surveys, high granular longitudinal studies, and more research on protective factors are required to better understand the psychological impacts of the SARS-CoV-2 pandemic and to help design effective preventive measures and interventions that are tailored to the needs of specific population groups.
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COVID-19/psicologia , Transtornos Mentais/etiologia , Saúde Mental , Pandemias , Adolescente , Adulto , Idoso , Ansiedade/epidemiologia , Ansiedade/etiologia , Depressão/epidemiologia , Depressão/etiologia , Feminino , Humanos , Masculino , Transtornos Mentais/epidemiologia , Pessoa de Meia-Idade , Fatores de Proteção , SARS-CoV-2 , Transtornos do Sono-Vigília/epidemiologia , Transtornos do Sono-Vigília/etiologia , Estresse Psicológico/epidemiologia , Estresse Psicológico/etiologiaRESUMO
Network meta-analysis is a method to combine evidence from randomized controlled trials (RCTs) that compare a number of different interventions for a given clinical condition. Usually, this requires a connected network. A possible approach to link a disconnected network is to add evidence from nonrandomized comparisons, using propensity score or matching-adjusted indirect comparisons methods. However, nonrandomized comparisons may be associated with an unclear risk of bias. Schmitz et al. used single-arm observational studies for bridging the gap between two disconnected networks of treatments for multiple myeloma. We present a reanalysis of these data using component network meta-analysis (CNMA) models entirely based on RCTs, utilizing the fact that many of the treatments consisted of common treatment components occurring in both networks. We discuss forward and backward strategies for selecting appropriate CNMA models and compare the results to those obtained by Schmitz et al. using their matching method. CNMA models provided a good fit to the data and led to treatment rankings that were similar, though not fully equal to that obtained by Schmitz et al. We conclude that researchers encountering a disconnected network with treatments in different subnets having common components should consider a CNMA model. Such models, exclusively based on evidence from RCTs, are a promising alternative to matching approaches that require additional evidence from observational studies. CNMA models are implemented in the R package netmeta.
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Projetos de Pesquisa , Viés , Metanálise em RedeRESUMO
BACKGROUND: In pairwise meta-analysis, the contribution of each study to the pooled estimate is given by its weight, which is based on the inverse variance of the estimate from that study. For network meta-analysis (NMA), the contribution of direct (and indirect) evidence is easily obtained from the diagonal elements of a hat matrix. It is, however, not fully clear how to generalize this to the percentage contribution of each study to a NMA estimate. METHODS: We define the importance of each study for a NMA estimate by the reduction of the estimate's variance when adding the given study to the others. An equivalent interpretation is the relative loss in precision when the study is left out. Importances are values between 0 and 1. An importance of 1 means that the study is an essential link of the pathway in the network connecting one of the treatments with another. RESULTS: Importances can be defined for two-stage and one-stage NMA. These numbers in general do not add to one and thus cannot be interpreted as 'percentage contributions'. After briefly discussing other available approaches, we question whether it is possible to obtain unique percentage contributions for NMA. CONCLUSIONS: Importances generalize the concept of weights in pairwise meta-analysis in a natural way. Moreover, they are uniquely defined, easily calculated, and have an intuitive interpretation. We give some real examples for illustration.
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Metanálise em Rede , HumanosRESUMO
In network meta-analysis (NMA), treatments can be complex interventions, for example, some treatments may be combinations of others or of common components. In standard NMA, all existing (single or combined) treatments are different nodes in the network. However, sometimes an alternative model is of interest that utilizes the information that some treatments are combinations of common components, called component network meta-analysis (CNMA) model. The additive CNMA model assumes that the effect of a treatment combined of two components A and B is the sum of the effects of A and B, which is easily extended to treatments composed of more than two components. This implies that in comparisons equal components cancel out. Interaction CNMA models also allow interactions between the components. Bayesian analyses have been suggested. We report an implementation of CNMA models in the frequentist R package netmeta. All parameters are estimated using weighted least squares regression. We illustrate the application of CNMA models using an NMA of treatments for depression in primary care. Moreover, we show that these models can even be applied to disconnected networks, if the composite treatments in the subnetworks contain common components.
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Biometria/métodos , Depressão/terapia , Humanos , Modelos Estatísticos , Atenção Primária à SaúdeRESUMO
OBJECTIVE: The aim of this paper was to provide a systematic review and update on the pharmacotherapy of social anxiety disorder (SAD), including the efficacy and tolerability of these agents, the ranking of interventions, and the grading of results by quality of evidence. METHODS: The Common Mental Disorder Controlled Trial Register and two trial registries were searched for randomised controlled trials (RCTs) comparing any pharmacological intervention or placebo in the treatment of SAD. We performed a standard pairwise meta-analysis using a random effects model and carried out a network meta-analysis (NMA) using the statistical package, R. Quality of evidence was also assessed. RESULTS: We included 67 RCTs in the review and 21 to 45 interventions in the NMA. Paroxetine was most effective in the reduction of symptom severity as compared to placebo. Superior response to treatment was also observed for paroxetine, brofaromine, bromazepam, clonazepam, escitalopram, fluvoxamine, phenelzine, and sertraline. Higher dropout rates were found for fluvoxamine. Brofaromine, escitalopram, fluvoxamine, paroxetine, pregabalin, sertraline, and venlafaxine performed worse in comparison to placebo for the outcome of dropouts due to adverse events. Olanzapine yielded a relatively high rank for treatment efficacy and buspirone the worse rank for dropouts due to any cause. CONCLUSION: The differences between drugs and placebo were small, apart from a significant reduction in symptom severity and response for paroxetine. We suggest paroxetine as a first-line treatment of SAD, with the consideration of future research on the drug olanzapine as well as brofaromine, bromazepam, clonazepam, escitalopram, fluvoxamine, phenelzine, and sertraline because we observed a response to treatment.
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Ansiolíticos/uso terapêutico , Fobia Social/tratamento farmacológico , Adulto , Ansiolíticos/efeitos adversos , Humanos , Metanálise em Rede , Fobia Social/diagnóstico , Fobia Social/psicologia , Ensaios Clínicos Controlados Aleatórios como Assunto , Resultado do TratamentoRESUMO
BACKGROUND: Herpes simplex virus type 1 (HSV-1) epidemiology in Asia was characterized by assessing seroprevalence levels and extent to which HSV-1 is isolated from clinically diagnosed genital ulcer disease (GUD) and genital herpes. METHODS: HSV-1 reports in Asia were systematically reviewed and synthesized, following PRISMA guidelines. Random-effects meta-analyses estimated pooled mean seroprevalence and proportion of HSV-1 detection in GUD and genital herpes. Random-effects meta-regressions identified predictors of seroprevalence and sources of between-study heterogeneity. RESULTS: Forty-nine relevant publications were identified. Fifty-four overall seroprevalence measures (182 stratified measures), and 8 and 24 proportions of HSV-1 detection in GUD and in genital herpes, respectively, were extracted. The pooled mean seroprevalence was 50.0% (n = 26; 95% confidence interval [CI], 41.3%-58.7%) for children and 76.5% (n = 151; 73.3%-79.6%) for adults. By age group, the pooled mean was lowest at 55.5% (n = 37; 95% CI, 47.5%-63.4%) in individuals aged <20 years, followed by 67.9% (n = 48; 62.4%-73.3%) in those aged 20-39 and 87.5% (n = 44; 83.4%-91.1%) in those aged ≥40 years. In meta-regression, age was the major predictor of seroprevalence. The mean proportion of HSV-1 detection was 5.6% (n = 8; 95% CI, 0.8%-13.6%) in GUD and 18.8% (n = 24; 12.0%-26.7%) in genital herpes. CONCLUSIONS: HSV-1 epidemiology is transitioning in Asia. HSV-1 is probably playing a significant role as a sexually transmitted infection, explaining one-fifth of genital herpes cases. There is a need for expanded seroprevalence monitoring and GUD/genital herpes etiological surveillance.
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Herpes Simples/epidemiologia , Herpesvirus Humano 1 , Anticorpos Antivirais/sangue , Ásia/epidemiologia , Herpes Simples/virologia , Humanos , Estudos SoroepidemiológicosRESUMO
The Mantel-Haenszel (MH) method has been used for decades to synthesize data obtained from studies that compare two interventions with respect to a binary outcome. It has been shown to perform better than the inverse-variance method or Peto's odds ratio when data is sparse. Network meta-analysis (NMA) is increasingly used to compare the safety of medical interventions, synthesizing, eg, data on mortality or serious adverse events. In this setting, sparse data occur often and yet there is to-date, no extension of the MH method for the case of NMA. In this paper, we fill this gap by presenting a MH-NMA method for odds ratios. Similarly to the pairwise MH method, we assume common treatment effects. We implement our approach in R, and we provide freely available easy-to-use routines. We illustrate our approach using data from two previously published networks. We compare our results to those obtained from three other approaches to NMA, namely, NMA with noncentral hypergeometric likelihood, an inverse-variance NMA, and a Bayesian NMA with a binomial likelihood. We also perform simulations to assess the performance of our method and compare it with alternative methods. We conclude that our MH-NMA method offers a reliable approach to the NMA of binary outcomes, especially in the case or sparse data, and when the assumption of methodological and clinical homogeneity is justifiable.
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Metanálise em Rede , Razão de Chances , Simulação por Computador , HumanosRESUMO
BACKGROUND: Abstracts of presentations at scientific meetings are usually available only in conference proceedings. If subsequent full publication of results reported in these abstracts is based on the magnitude or direction of the results, publication bias may result. Publication bias creates problems for those conducting systematic reviews or relying on the published literature for evidence about health and social care. OBJECTIVES: To systematically review reports of studies that have examined the proportion of meeting abstracts and other summaries that are subsequently published in full, the time between meeting presentation and full publication, and factors associated with full publication. SEARCH METHODS: We searched MEDLINE, Embase, the Cochrane Library, Science Citation Index, reference lists, and author files. The most recent search was done in February 2016 for this substantial update to our earlier Cochrane Methodology Review (published in 2007). SELECTION CRITERIA: We included reports of methodology research that examined the proportion of biomedical results initially presented as abstracts or in summary form that were subsequently published. Searches for full publications had to be at least two years after meeting presentation. DATA COLLECTION AND ANALYSIS: Two review authors extracted data and assessed risk of bias. We calculated the proportion of abstracts published in full using a random-effects model. Dichotomous variables were analyzed using risk ratio (RR), with multivariable models taking into account various characteristics of the reports. We assessed time to publication using Kaplan-Meier survival analyses. MAIN RESULTS: Combining data from 425 reports (307,028 abstracts) resulted in an overall full publication proportion of 37.3% (95% confidence interval (CI), 35.3% to 39.3%) with varying lengths of follow-up. This is significantly lower than that found in our 2007 review (44.5%. 95% CI, 43.9% to 45.1%). Using a survival analyses to estimate the proportion of abstracts that would be published in full by 10 years produced proportions of 46.4% for all studies; 68.7% for randomized and controlled trials and 44.9% for other studies. Three hundred and fifty-three reports were at high risk of bias on one or more items, but only 32 reports were considered at high risk of bias overall.Forty-five reports (15,783 abstracts) with 'positive' results (defined as any 'significant' result) showed an association with full publication (RR = 1.31; 95% CI 1.23 to 1.40), as did 'positive' results defined as a result favoring the experimental treatment (RR =1.17; 95% CI 1.07 to 1.28) in 34 reports (8794 abstracts). Results emanating from randomized or controlled trials showed the same pattern for both definitions (RR = 1.21; 95% CI 1.10 to 1.32 (15 reports and 2616 abstracts) and RR = 1.17; 95% CI, 1.04 to 1.32 (13 reports and 2307 abstracts), respectively.Other factors associated with full publication include oral presentation (RR = 1.46; 95% CI 1.40 to 1.52; studied in 143 reports with 115,910 abstracts); acceptance for meeting presentation (RR = 1.65; 95% CI 1.48 to 1.85; 22 reports with 22,319 abstracts); randomized trial design (RR = 1.51; 95% CI 1.36 to 1.67; 47 reports with 28,928 abstracts); and basic research (RR = 0.78; 95% CI 0.74 to 0.82; 92 reports with 97,372 abstracts). Abstracts originating at an academic setting were associated with full publication (RR = 1.60; 95% CI 1.34 to 1.92; 34 reports with 16,913 abstracts), as were those considered to be of higher quality (RR = 1.46; 95% CI 1.23 to 1.73; 12 reports with 3364 abstracts), or having high impact (RR = 1.60; 95% CI 1.41 to 1.82; 11 reports with 6982 abstracts). Sensitivity analyses excluding reports that were abstracts themselves or classified as having a high risk of bias did not change these findings in any important way.In considering the reports of the methodology research that we included in this review, we found that reports published in English or from a native English-speaking country found significantly higher proportions of studies published in full, but that there was no association with year of report publication. The findings correspond to a proportion of abstracts published in full of 31.9% for all reports, 40.5% for reports in English, 42.9% for reports from native English-speaking countries, and 52.2% for both these covariates combined. AUTHORS' CONCLUSIONS: More than half of results from abstracts, and almost a third of randomized trial results initially presented as abstracts fail to be published in full and this problem does not appear to be decreasing over time. Publication bias is present in that 'positive' results were more frequently published than 'not positive' results. Reports of methodology research written in English showed that a higher proportion of abstracts had been published in full, as did those from native English-speaking countries, suggesting that studies from non-native English-speaking countries may be underrepresented in the scientific literature. After the considerable work involved in adding in the more than 300 additional studies found by the February 2016 searches, we chose not to update the search again because additional searches are unlikely to change these overall conclusions in any important way.
Assuntos
Indexação e Redação de Resumos/estatística & dados numéricos , Congressos como Assunto , Editoração/estatística & dados numéricos , Ensaios Clínicos Controlados como Assunto/estatística & dados numéricos , Viés de Publicação , Ensaios Clínicos Controlados Aleatórios como Assunto/estatística & dados numéricos , Fatores de TempoRESUMO
The modified method for random-effects meta-analysis, usually attributed to Hartung and Knapp and also proposed by Sidik and Jonkman, is easy to implement and is becoming advocated for general use. Here, we examine a range of potential concerns about the widespread adoption of this method. Motivated by these issues, a variety of different conventions can be adopted when using the modified method in practice. We describe and investigate the use of a variety of these conventions using a new taxonomy of meta-analysis datasets. We conclude that the Hartung and Knapp modification may be a suitable replacement for the standard method. Despite this, analysts who advocate the modified method should be ready to defend its use against the possible objections to it that we present. We further recommend that the results from more conventional approaches should be used as sensitivity analyses when using the modified method. It has previously been suggested that a common-effect analysis should be used for this purpose but we suggest amending this recommendation and argue that a standard random-effects analysis should be used instead.
Assuntos
Metanálise como Assunto , Modelos Estatísticos , Classificação , Intervalos de Confiança , HumanosRESUMO
A widely used method in classic random-effects meta-analysis is the DerSimonian-Laird method. An alternative meta-analytical approach is the Hartung-Knapp method. This article reports results of an empirical comparison and a simulation study of these two methods and presents corresponding analytical results. For the empirical evaluation, we took 157 meta-analyses with binary outcomes, analysed each one using both methods and performed a comparison of the results based on treatment estimates, standard errors and associated P-values. In several simulation scenarios, we systematically evaluated coverage probabilities and confidence interval lengths. Generally, results are more conservative with the Hartung-Knapp method, giving wider confidence intervals and larger P-values for the overall treatment effect. However, in some meta-analyses with very homogeneous individual treatment results, the Hartung-Knapp method yields narrower confidence intervals and smaller P-values than the classic random-effects method, which in this situation, actually reduces to a fixed-effect meta-analysis. Therefore, it is recommended to conduct a sensitivity analysis based on the fixed-effect model instead of solely relying on the result of the Hartung-Knapp random-effects meta-analysis. Copyright © 2016 John Wiley & Sons, Ltd.